JP6476287B2 - Railway vehicle state monitoring device, state monitoring system, and train formation - Google Patents

Description

  The present invention relates to a state monitoring device, a state monitoring system, and a train knitting vehicle, and is suitable for being applied to a state monitoring device and a state monitoring system for monitoring the state of a railway vehicle, and a knitted vehicle having the state monitoring system. .

  Conventionally, when a railway vehicle is traveling (vehicle operation), it has been important to quickly detect abnormalities such as derailment, component abnormality, and snake behavior in order to ensure traveling safety. For example, when a driver or a crew member who is in the vehicle feels abnormal vibration, the vehicle travels emergency stop and the vehicle state is checked to see if derailment or the like has occurred.

  Patent Document 1 discloses a derailment detection device that detects derailment of a railway vehicle traveling on a track. In the derailment detection device disclosed in Patent Document 1, an acceleration detection unit is installed in each vehicle body of a plurality of vehicles constituting a formation vehicle, and a signal in a specific frequency band is extracted from an output signal (acceleration information) of the acceleration detection unit. Integrate a signal in a specific frequency band repeatedly every predetermined time to calculate an integrated value, and determine vehicle derailment based on the difference between the current integrated value and the integrated value before the predetermined time (threshold determination processing) . According to such an escape detection device, derailment is determined by performing threshold determination processing based on acceleration information obtained for each vehicle, and therefore, derailment detection is delayed in a vehicle such as an intermediate vehicle in which no crew is on board. To solve the problem and enable rapid and appropriate derailment detection.

JP 2002-211400 A

  However, in the derailment detection device disclosed in Patent Document 1, in the threshold determination process for individual acceleration information detected by each vehicle, the threshold determination process based on the absolute value of acceleration is performed. When traveling at a low speed, which is relatively low, there is a high possibility that an abnormal state cannot be detected.

  In general, the infrastructure state (specifically, for example, the track state, the ground, the climate, etc.) in which the vehicle travels is not uniform, and the traveling speed of the vehicle during vehicle operation varies depending on the vehicle operating conditions. In the escape detection device disclosed in Document 1, if threshold determination processing is performed in view of such conditions, it is necessary to set threshold conditions that are subdivided according to the infrastructure state, traveling speed, and the like, and the system becomes complicated. There was a problem that it would end up. Another problem is that it takes time to collect acceleration information used for the threshold condition.

  The present invention has been made in view of the above points. A state monitoring device and a state monitoring system capable of monitoring an abnormal state of a vehicle and improving driving safety during vehicle operation, and the state monitoring system. An attempt is made to propose an organized vehicle having

In order to solve such a problem, in the present invention, sensors (vibration acceleration sensors 17A to 17N) are respectively mounted on a plurality of vehicles (for example, vehicles 11A to 11N described later) constituting the formation vehicle, and each of the sensors Is a state monitoring device that monitors the state of a vehicle based on sensor signals (same as above, sensor signals 171A to 171N), and a signal detection processing unit (same as above) that detects sensor signals of a plurality of vehicles on which the sensors are mounted. , Vibration acceleration detection processing unit 101), data extraction unit (filter processing unit 102) for extracting vehicle data corresponding to the sensor signal from each sensor signal detected by the signal detection processing unit, One reference value is extracted based on the data of each vehicle extracted by the data extraction unit, and the data of each vehicle with respect to the reference value is extracted. An amplitude ratio calculation processing unit (amplitude ratio calculation processing unit 103) that calculates a rate, and a threshold determination processing unit that determines the presence or absence of an abnormal state of each vehicle based on the result of the calculation by the amplitude ratio calculation processing unit ( The railway vehicle state monitoring device (state monitoring device 100) is provided. In the railway vehicle state monitoring apparatus, the data extraction unit applies a band-pass filter that limits a frequency band to be extracted to each sensor signal detected by the signal detection processing unit. Then, vehicle data corresponding to each of the sensor signals is extracted by performing a second filter process that applies a window filter that limits the data length to be extracted. In the second filter processing, the time width during which the window filter is applied is based on the vehicle speed of the trained vehicle so that the amount of data necessary for the calculation by the amplitude ratio calculation processing unit can be extracted without excess or deficiency. And the phase to which the window filter is applied is based on the vehicle speed of the trained vehicle so that the detection positions of the data of each vehicle extracted by the application of the window filter match in all vehicles. Is displaced every time.

Further, in order to solve such a problem, in the present invention, a sensor mounted on each of a plurality of vehicles constituting a formation vehicle, and a vehicle connected to the sensor so as to be communicable and based on a sensor signal from each sensor. A state monitoring device that monitors the state of the signal, and the state monitoring device detects a sensor signal of a plurality of vehicles on which the sensor is mounted, and each detected by the signal detection processing unit A data extraction unit for extracting vehicle data corresponding to the sensor signal from the sensor signal, and extracting one reference value based on the data of each vehicle extracted by the data extraction unit, and each vehicle corresponding to the reference value Based on the result of the calculation by the amplitude ratio calculation processing unit and the amplitude ratio calculation processing unit, the presence or absence of an abnormal state of each vehicle is calculated. Condition monitoring system (e.g., condition monitoring system 1 described later) of the rail vehicle, characterized in that it comprises a threshold determination processing unit for a constant, is provided. In this railway vehicle state monitoring system, the data extraction unit of the state monitoring device applies a bandpass filter that limits a frequency band to be extracted to each sensor signal detected by the signal detection processing unit. By performing a first filter process and a second filter process that applies a window filter that limits the length of data to be extracted, vehicle data corresponding to each of the sensor signals is extracted. In the second filter processing, the time width during which the window filter is applied is based on the vehicle speed of the trained vehicle so that the amount of data necessary for the calculation by the amplitude ratio calculation processing unit can be extracted without excess or deficiency. And the phase to which the window filter is applied is based on the vehicle speed of the trained vehicle so that the detection positions of the data of each vehicle extracted by the application of the window filter match in all vehicles. Is displaced every time.

Further, in order to solve such a problem, in the present invention, a knitted vehicle configured by connecting a plurality of vehicles, each of the sensors mounted on the plurality of vehicles constituting the knitted vehicle, and communication with the sensors. And a state monitoring device that monitors the state of the vehicle based on sensor signals from the sensors, and the state monitoring device detects sensor signals of a plurality of vehicles on which the sensors are mounted. A signal detection processing unit, a data extraction unit for extracting vehicle data corresponding to the sensor signal from each sensor signal detected by the signal detection processing unit, and data of each vehicle extracted by the data extraction unit An amplitude ratio calculation processing unit that extracts one reference value based on the above and calculates a ratio of each vehicle data to the reference value, and the amplitude ratio calculation processing unit And a threshold value determination processing unit that determines the presence or absence of an abnormal state of each vehicle based on the result of the calculation, and sharing the determination result of the abnormal state by the threshold value determination processing unit among the vehicles of the trained vehicle. A featured knitted vehicle (for example, a knitted vehicle in a third embodiment described later) is provided. In this knitted vehicle, the data extraction unit of the state monitoring device applies a bandpass filter that limits a frequency band to be extracted to each sensor signal detected by the signal detection processing unit. The vehicle data corresponding to each of the sensor signals is extracted by performing a process and a second filter process that applies a window filter that limits the data length to be extracted. In the second filter processing, the time width during which the window filter is applied is based on the vehicle speed of the trained vehicle so that the amount of data necessary for the calculation by the amplitude ratio calculation processing unit can be extracted without excess or deficiency. And the phase to which the window filter is applied is based on the vehicle speed of the trained vehicle so that the detection positions of the data of each vehicle extracted by the application of the window filter match in all vehicles. Is displaced every time.

  According to the present invention, it is possible to monitor an abnormal state even for a vehicle on which a driver or a crew member is not on board, and improve traveling safety during vehicle operation.

1 is a block diagram illustrating an example of the overall configuration of a railway vehicle state monitoring system according to a first embodiment. It is a block diagram which shows the hardware structural example of the state monitoring apparatus shown in FIG. It is a flowchart which shows the example of a procedure of the abnormality detection process in 1st Embodiment. It is a figure for demonstrating the process image of the abnormality detection process in 1st Embodiment. It is a block diagram which shows the example of whole structure of the state monitoring system of the rail vehicle which concerns on 2nd Embodiment. It is a block diagram which shows the hardware structural example of the state monitoring apparatus shown in FIG. It is a flowchart which shows the example of a procedure of the abnormality detection process in 2nd Embodiment. It is FIG. (1) for demonstrating an example of the amplitude ratio calculation process in 2nd Embodiment. It is FIG. (2) for demonstrating an example of the amplitude ratio calculation process in 2nd Embodiment. It is a flowchart which shows the example of a procedure of the abnormality detection process by the state monitoring system of the rail vehicle which concerns on 3rd Embodiment. It is a figure for demonstrating an example of the reference value production | generation process in 3rd Embodiment.

  Embodiments according to the present invention will be described below with reference to the drawings. In each figure, the same number is given to the component which has a common function, and the duplicate explanation is omitted.

(1) First Embodiment (1-1) Configuration of State Monitoring System FIG. 1 shows an example of the overall configuration of a railway vehicle state monitoring system (state monitoring system 1) according to a first embodiment of the present invention. It is a block diagram.

  In FIG. 1, the formation vehicle 10 includes a plurality of connected vehicles 11 (11A to 11N). The plurality of vehicles 11 can be divided into a leading vehicle 11A on which a driver 90 gets on and performs a driving operation, and intermediate vehicles 11B to 11N connected behind the leading vehicle 11A. Although not shown, the trained vehicle 10 may include a tail vehicle at the end opposite to the leading vehicle 11A. At this time, the intermediate vehicles 11B to 11N are connected (knitted) between the leading vehicle 11A and the trailing vehicle. Further, the rear vehicle may be regarded as being included in the intermediate vehicles 11B to 11N (that is, one of the intermediate vehicles 11B to 11N).

  The configuration of the vehicle 11 will be described by taking the leading vehicle 11A as an example. According to FIG. 1, the leading vehicle 11 </ b> A includes a vehicle body 12 and a carriage 13, and the vehicle body 12 and the carriage 13 are supported by a suspension such as an air spring 14. The carriage 13 includes a carriage frame 15 corresponding to the framework of the carriage 13 and two rotatable wheel shafts 16, and the leading vehicle 11 </ b> A moves as the wheel shafts 16 travel on the track. In FIG. 1, the wheel shaft 16 of the vehicle 11 </ b> B is described as being on a broken line that is off the track (solid line in the horizontal direction), but this is because the vehicle 11 </ b> B of the trained vehicle 10 is in a derailed state. The other vehicles 11A, 11N, etc. described so that the wheel shaft 16 is on the track are not derailed.

  In the present specification, when a configuration common to each of the vehicles 11A to 11N is limited to a specific vehicle, the same subscript (uppercase letter) as that of the target vehicles 11A to 11N may be added. is there. Specifically, for example, the vehicle body 12 of the leading vehicle 11A can be expressed as a vehicle body 12A, and the vehicle body 12 of the intermediate vehicle 11B can be expressed as a vehicle body 12B. The same applies to other configurations, and a description thereof will be omitted.

  A cab 18 for driving the formation vehicle 10 is provided on the vehicle body 12A of the leading vehicle 11A. The trained vehicle 10 travels when the driver 90 gets on the leading vehicle 11A and operates the cab 18. A state in which the trained vehicle 10 is being driven by the driver 90 is referred to as vehicle operation time. The intermediate vehicles 11B to 11N have substantially the same configuration as the leading vehicle 11A except that the cab 18 is not provided.

  Further, the vehicle body 12A is provided with a vibration acceleration sensor 17A for detecting vibration acceleration of the vehicle body 12A in the up / down, left / right or front / rear direction with respect to the traveling direction of the knitted vehicle 10, and the detection result by the vibration acceleration sensor 17A is a sensor The signal is output to the state monitoring apparatus 100 as a signal 171A. FIG. 1 shows that similar vibration acceleration sensors 17A to 17N are installed on the floor surfaces of the vehicle bodies 12A to 12N in the vehicles 11A to 11N constituting the formation vehicle 10. The detection results by the vibration acceleration sensors 17A to 17N are output to the state monitoring apparatus 100 as sensor signals 171 (individually 171A to 171N).

  In FIG. 1, it is shown that the vibration acceleration sensors 17A to 17N are installed on the floor surfaces of the vehicle bodies 12A to 12N in each of the vehicles 11A to 11N constituting the formation vehicle 10, but the state monitoring of the present invention is performed. The installation configuration of the vibration acceleration sensor 17 in the system is not limited to this, and one or more vibration acceleration sensors 17 may be installed in each of at least two or more vehicles 11. Further, the installation position of the vibration acceleration sensor 17 is not limited to the vehicle body 12. For example, the vibration acceleration sensor 17 may be installed on the bogie frame 15 or the wheel shaft 16 of the bogie 13 or mounted on each vehicle 11. It may be installed in an electrical component, an equipment component, or the like. In addition, it is preferably installed in a place where a passenger does not enter (for example, a driver's cab, a crew cabin, or under the floor).

  In FIG. 1, the number of installed vibration acceleration sensors 17 is shown as one for each vehicle. However, the present invention is not limited to this, and a plurality of vibration acceleration sensors are installed in one vehicle 11. 17 may be installed. However, in such a case, if a plurality of sensor signals are output from the same vehicle to the state monitoring device 100, it is expected that the processing load of abnormality detection processing (details will be described later) in the state monitoring device 100 increases. Therefore, in the vehicle 11 or the state monitoring device 100, it is preferable to perform processing such as combining a plurality of sensor signals output in the same vehicle into one sensor signal.

  A configuration of the state monitoring apparatus 100 will be described. The state monitoring device 100 is included in the state monitoring system 1 and is installed, for example, in the equipment room or under the floor of a specific vehicle such as the leading vehicle 11A. Note that the state monitoring device 100 does not necessarily have to be installed in the trained vehicle 10, and may be installed in a control room or the like that can communicate with the trained vehicle 10, for example. The state monitoring apparatus 100 includes a vibration acceleration detection processing unit 101, a filter processing unit 102, an amplitude ratio calculation processing unit 103, a threshold determination processing unit 104, an alarm generation processing unit 105, and a data recording processing unit 106.

  Detailed processing contents in each processing unit constituting the state monitoring apparatus 100 will be described later with reference to FIGS. 3 and 4. The outline of signal input / output in the state monitoring apparatus 100 is as follows.

  The vibration acceleration detection processing unit 101 filters the vibration acceleration signal 172 (individually 172A to 172N) based on the sensor signal 171 (individually 171A to 171N) input from the vibration acceleration sensors 11A to 11N. Output to. Based on the signal input from the vibration acceleration detection processing unit 101, the filter processing unit 102 outputs the vibration acceleration signal 173 after filtering (173 A to 173 N individually) to the amplitude ratio calculation processing unit 103. The amplitude ratio calculation processing unit 103 outputs an amplitude ratio signal 174 (individually 174B to 174N) to the threshold determination processing unit 104 based on the signal input from the filter processing unit 102. The threshold determination processing unit 104 outputs a determination processing result signal 175 (individually, 175B to 175N) to the alarm generation processing unit 105 based on the signal input from the amplitude ratio calculation processing unit 103. The alarm generation processing unit 105 outputs an alarm signal 176 to the data recording processing unit 106 and the cab 18 based on the signal input from the threshold determination processing unit 104. The data recording processing unit 106 records data based on the signal input from the alarm generation processing unit, and the cab 18 warns as necessary based on the signal input from the alarm generation processing unit. Etc. are output.

  FIG. 2 is a block diagram illustrating a hardware configuration example of the state monitoring apparatus illustrated in FIG. As shown in FIG. 2, the state monitoring apparatus 100 includes a processor 110. The processor 110 is a computer, and includes a CPU (Central Processing Unit) 111, a RAM (Random Access Memory) 112, an interface 113, a ROM (Read Only Memory) 114, and a card connector 115. Processing by each processing unit (101 to 106) of the state monitoring device 100 is realized by the processor 110 (mainly the CPU 111).

  The CPU 111 is a central processing unit that controls the inside of the processor 110 by a program, and is connected to the interface 113, RAM 112, ROM 114, and card connector 115 via the bus 116. The RAM 112 and the ROM 114 are storage devices that can store data. The interface 113 is connected to the vibration acceleration sensor 17 (17A to 17N) installed in the vehicle 11 (11A to 11N), and is also connected to the cab 18.

  A memory card 117 as a storage medium can be attached to the card connector 115, and the processor 110 (particularly the CPU 111) can cause the memory card 117 attached to the card connector 115 to store or read data. it can. Note that the card connector 115 may be provided at a position where the driver or the like can directly take out the attached memory card 117, for example, on the surface of the state monitoring device 100. Further, in the configuration example of the state monitoring apparatus 100, the card connector 115 and the memory card 117 are merely examples, and it is only necessary to have a configuration capable of connecting a storage medium capable of storing data.

  In addition, the state monitoring device 100 may be provided with a display device such as an LED (Light Emitting Diode) on the surface in order to display the operating state of the state monitoring device 100 and the detection result of the abnormal state in the trained vehicle 10. Good. In addition, a switch for resetting the state of the state monitoring device 100 may be provided on the surface of the state monitoring device 100, and may be applied in processing of each processing unit (see FIG. 1) in the state device 100. A connector for connecting a cable or the like for setting various parameters may be provided.

(1-2) Abnormal State Detection Processing FIG. 3 is a flowchart illustrating a procedure example of the abnormality detection processing according to the first embodiment. The abnormality detection process shown in FIG. 3 is executed by the processor 110 (mainly the CPU 111) of the state monitoring apparatus 100 in order to detect an abnormal state of the railway vehicle (the train set 10 in FIG. 1). Hereinafter, the abnormality detection process will be described in detail with reference to FIG.

  First, in step S100, a sensor signal 171 (individually 171A to 171N) is input to the vibration acceleration detection processing unit 101 from the vibration acceleration sensor 17 (17A to 17N) installed in each vehicle 11 (11A to 11N). The

  In step S101, the vibration acceleration detection processing unit 101 applies a filter (band-pass filter) that passes only a predetermined frequency bandwidth set in advance to each of the input sensor signals 171A to 171N. Thus, a vibration acceleration signal 172 (individually 172A to 172N) configured only with a predetermined frequency bandwidth is extracted, and the signal is output to the filter processing unit 102.

  In step S102, the filter processing unit 102 extracts a filter (window filter) that extracts a vibration acceleration signal with a preset fixed data length (time width) for each of the input vibration acceleration signals 172A to 172N. By applying this, the vibration acceleration signal 173 after filtering (173 A to 173 N individually) is extracted, and the signal is output to the amplitude ratio calculation processing unit 103. In order to avoid confusion with the vibration acceleration signal 172, hereinafter, the vibration acceleration signal 173 after filtering is referred to as a window filtering signal 173.

  In steps S103 and S104, the amplitude ratio calculation processing unit 103 performs an amplitude ratio calculation process. First, in step S103, the amplitude ratio calculation processing unit 103 applies a vibration acceleration RMS value (RMS: Root Mean Square) value for each of the input window filtering signals 173A to 173N (for each vehicle). (Vibration acceleration RMS value) is calculated. As a detailed calculation method example of the vibration acceleration RMS value, for example, a plurality of calculation points are set in the time width of the fixed data length extracted by the window filter, and the RMS value is calculated for the vibration acceleration at the plurality of calculation points. May be calculated (specifically, for example, corresponding to the RMS values 185A to 185N shown in FIG. 4 later).

  In step S104, the amplitude ratio calculation processing unit 103 calculates an amplitude ratio (RMS value amplitude ratio) for each vehicle using the vibration acceleration RMS value for each vehicle calculated in step S103. Specifically, for example, the amplitude ratio calculation processing unit 103 calculates the ratio of the respective vibration acceleration RMS values in the other vehicles (intermediate vehicles 11B to 11N) with reference to the vibration acceleration RMS value of the leading vehicle 11A. Based on the calculation result, the amplitude ratio calculation processing unit 103 outputs an amplitude ratio signal 174 (individually, 174B to 174N) based on the RMS value amplitude ratio of the intermediate vehicles 11B to 11N to the threshold determination processing unit 104. Note that when the total number of vehicles is N and the vibration acceleration RMS value of the leading vehicle 11A is used as a reference, the RMS value amplitude ratio of the vehicle 11A is always “1” even if it is not calculated. There is no need to output to. Therefore, as a result of the calculation process in step S104, N−1 amplitude ratio signals 174B to 174N are output to the threshold determination processing unit 104.

  As another example of the calculation process in step S104, the absolute value of the difference between the vibration acceleration RMS values of the other vehicles (intermediate vehicles 11B to 11N) is calculated using the vibration acceleration RMS value of the leading vehicle 11A as a reference value. A signal based on the calculation result may be output to the threshold determination processing unit 104.

  In the above-described steps S103 and S104, the calculation processing example using the vibration acceleration RMS value has been described. However, calculation processing using a value other than the RMS value may be performed. Specifically, for example, from the filter processing unit 102 Based on the input window filtering signal 173, an average value, maximum value, median value, integrated value (area) of power spectrum density (PSD) is calculated, and the reference vehicle (for example, the head) The amplitude ratio between the calculated value of the vehicle 11A) and the calculated values of the other vehicles (intermediate vehicles 11B to 11N) may be calculated.

  In step S <b> 105, the threshold determination processing unit 104 executes threshold determination processing based on a preset threshold for the amplitude ratio signal 174 (174 </ b> B to 174 </ b> N) input from the amplitude ratio calculation processing unit 103. To do. As specific threshold determination processing, for example, the amplitude ratio is divided into levels, and a predetermined level is used as a threshold, and it is determined whether or not the threshold level is exceeded. Also, for example, it is determined whether or not the time that exceeds the threshold level (threshold excess time) exceeds a predetermined time. Then, the threshold determination processing unit 104 outputs a determination processing result signal 175 (individually, 175B to 175N) based on the determination result for each amplitude ratio signal 174 to the alarm generation processing unit 105.

  In step S <b> 106, the alarm generation processing unit 105 executes alarm generation processing for generating a warning (alarm) based on the determination processing result signal 175 (175 </ b> B to 175 </ b> N) input from the threshold determination processing unit 104. When an alarm is generated in the alarm generation processing, the alarm generation processing unit 105 outputs an alarm signal 176 to the data recording processing unit 106 and the cab 18.

  The alarm signal 176 may be any notification that can identify at least the vehicle in which the abnormal state is detected, but it is preferable that more alarm information is included. Specifically, for example, information that can specify the alarm target intermediate vehicle 11 (that is, the intermediate vehicle 11 corresponding to the amplitude ratio signal 174 determined to have exceeded the threshold value in the threshold determination processing in step S105), or the alarm target It is assumed that the vibration acceleration detected by the intermediate vehicle 11 is alarm information.

  When the alarm signal 176 is input to the cab 18, a warning display (alarm display) is performed to notify the driver and the crew that an abnormal state has occurred. When the alarm signal 176 includes the above alarm information, the alarm information is preferably displayed on the cab 18.

  On the other hand, the data recording processing unit 106 records the alarm signal 176 (or alarm information included in the signal) input from the alarm generation processing unit 105 in a storage medium (for example, a memory card 117) in the state monitoring device 100. (Step S107). Further, the data recording processing unit 106 can record various types of vehicle information (for example, images of the in-vehicle camera in the alarm target intermediate vehicle 11 and the state of various devices) together with the alarm signal 176 in the storage medium. preferable.

  As described above, by performing the processing shown in steps S100 to S106 of FIG. 3, the state monitoring apparatus 100 determines the specific vehicle (for example, the leading vehicle 11A) with respect to the plurality of vehicles 11A to 11N constituting the formation vehicle 10. ) Based on the relative value of vibration acceleration (for example, RMS value amplitude ratio), the state of each vehicle 11 can be determined and an abnormal state can be detected.

  FIG. 4 is a diagram for explaining a processing image of the abnormality detection processing in the first embodiment. 4A to 4C show processing images of “vibration acceleration A” based on the sensor signal 171A output from the vibration acceleration sensor 17A of the leading vehicle 11A. FIGS. The processing image of “vibration acceleration B” based on the sensor signal 171B output from the vibration acceleration sensor 17B of the intermediate vehicle 11B is shown, and FIGS. 4G to 4I are output from the vibration acceleration sensor 17N of the intermediate vehicle 11N. The processing image of “vibration acceleration N” based on the sensor signal 171N. FIG. 4J shows a processing image of the amplitude ratio (RMS value amplitude ratio) of the intermediate vehicles 11B and 11N when the leading vehicle 11A is used as a reference. In the following, FIGS. 4 (a) to (c) and (j) will be described in detail, and descriptions of FIGS. 4 (d) to (f) and (g) to (i) where similar processing is performed will be omitted. .

  FIG. 4A is a processing image corresponding to step S100 in FIG. 3, and the head indicated by the sensor signal 171A that is input from the vibration acceleration sensor 17A to the vibration acceleration detection processing unit 101 of the state monitoring device 100 every moment. The vibration acceleration A of the vehicle 11A is shown. The vibration acceleration A (181A) shown in FIG. 4A is a so-called “raw waveform” before each processing described later is performed, and includes vibration accelerations of various frequencies.

  FIG. 4B is a processing image corresponding to step S101 of FIG. 3, and a predetermined frequency bandwidth set in advance for the vibration acceleration 181A of the raw waveform shown in FIG. 4A. It is shown that a band pass filter 182 that passes only the filter is applied.

  FIG. 4C is a processing image corresponding to steps S102 to S103 in FIG. First, a fixed data length (time width) set in advance with respect to the vibration acceleration A (183A) after filtering, which is extracted by applying the bandpass filter 182 to the vibration acceleration 181A of the raw waveform. A window filter 184 is applied (step S102). Then, for the vibration acceleration 183A extracted by application of the window filter 184, the RMS value 185A of the vibration acceleration A is calculated based on the vibration acceleration at a plurality of calculation points (step S103). In FIG. 4C, “p” is illustrated as a specific value of the RMS value 185A of the vibration acceleration A.

  As in FIGS. 4A to 4C, in FIGS. 4D to 4F, the RMS value 185B (specifically, the vibration acceleration B detected by the intermediate vehicle 11B (vibration acceleration 181B in FIG. 4D)) is specified. 4 (g) to (i), the RMS value 185N (specific value “r”) for the vibration acceleration N detected by the intermediate vehicle 11N (vibration acceleration 181N in FIG. 4 (g)) is calculated. ) Is calculated. Although not shown, RMS values are similarly calculated for the other intermediate vehicles 11 as well. Using the RMS value of the vibration acceleration calculated for each vehicle 11, in FIG. 4 (j), the RMS value amplitude ratio for each vehicle is calculated (step S104).

  FIG. 4J shows a processing image corresponding to steps S104 to S105 in FIG. In FIG. 4 (j), the vertical axis represents the RMS value amplitude ratio, and the horizontal axis represents the passage of time. FIG. 4J also shows a threshold value 187 (specific value “k”) used in the threshold determination process. In FIG. 4J, the RMS value amplitude ratio 186B is the amplitude ratio of the RMS value 185B of the vibration acceleration B with reference to the RMS value 185A of the vibration acceleration A, and is “q / p” as a specific value. Similarly, the RMS value amplitude ratio 186N is the amplitude ratio of the RMS value 185N of the vibration acceleration N with reference to the RMS value 185A of the vibration acceleration A, and is “r / p” as a specific value. As described above, the RMS value amplitude ratio related to the vibration acceleration A is “p / p”, that is, “1”.

  Here, in the example shown in FIG. 4, the RMS value 185B of the vibration acceleration B is relatively larger than the RMS value 185A of the vibration acceleration A (FIG. 4 (f)), and the vibration acceleration N The RMS value 185N is almost the same value (FIG. 4 (i)). Therefore, in FIG. 4J, the RMS value amplitude ratio 186B “q / p” for the vibration acceleration B is larger than the RMS value amplitude ratio 186N for the vibration acceleration N (“r / p” at time Xt). It has become. Then, the threshold value “k” shown in FIG. 4J is compared with the respective RMS value amplitude ratios 186 (individually, 186B to 186N) to execute threshold value determination processing based on the threshold value (step S105). ).

  In the case of FIG. 4J, the RMS value amplitude ratio 186B (“q / p”) related to the vibration acceleration B at time Xt exceeds the threshold value 187 (“k”), and thus is determined to be abnormal. That is, it can be detected that an abnormality has occurred in the intermediate vehicle 11B on which the vibration acceleration sensor 17B that is the detection source of the vibration acceleration B is mounted (it is in an abnormal state).

  In the threshold value determination process according to the present invention, the installation location of the vibration acceleration sensors 17A to 17N, the detection direction of vibration acceleration (for example, up / down, left / right, front / rear direction with respect to the traveling direction), and each in the state monitoring apparatus 100 The content of the abnormality can be selected according to the setting parameter in the processing unit or the level of the RMS value amplitude ratio 186 determined to be an abnormal state.

(1-3) Effects of First Embodiment As described above, according to the state monitoring system 1 (or the state monitoring device 100) of the first embodiment, the multiple vehicles 11 ( 11A to 11N) using the vibration acceleration sensor 17 (17A to 17N), the driver 90 gets on the basis of the vibration acceleration sensor signal 171A in the vehicle on which the driver 90 rides (leading vehicle 11A). The relative acceleration of vibration acceleration in other vehicles (intermediate vehicles 11B to 11N, etc.) that have not been detected causes abnormal states (for example, not only vehicle derailment but also vehicle or infrastructure conditions) to occur in the other vehicles. , And snake behavior).

  Here, the state monitoring system 1 (or the state monitoring device 100) of the first embodiment uses a relative value of vibration acceleration in the knitted vehicle when determining an abnormal state in the abnormality detection processing of FIG. It is said.

  If the determination based on the absolute value of the vibration acceleration is performed (for example, Patent Document 1), the vehicle vibration tends to decrease during low-speed traveling, so that the detected vibration acceleration also decreases, resulting in a low speed. There was a problem that it was difficult to detect an abnormal state such as derailment. Further, when the infrastructure state during vehicle running is not good, relatively large vehicle vibrations are generated in the entire trained vehicle, and there is a possibility that the state abnormality is detected although it is not a vehicle abnormality. In order to solve such a problem, if various settings (for example, changing the threshold setting) are performed in accordance with the traveling speed and the infrastructure state, more complicated processing is required, leading to a processing burden on the processor. End up. In addition, since it is necessary to collect data comprehensively for setting the threshold value, the practicality is significantly reduced.

  On the other hand, the state monitoring system 1 (or the state monitoring device 100) of the first embodiment, as shown in the processing image in FIG. 4, determines the specific vehicle (leading vehicle 21) on which the driver 90 is riding. Since abnormality detection processing is performed using the relative value of vibration acceleration of each vehicle as a reference (RMS value amplitude ratio 186), for example, even during low-speed driving, or even if the infrastructure condition is not good If there is a difference in vibration acceleration between vehicles, it can be detected. That is, according to the state monitoring system 1 (or the state monitoring device 100) of the first embodiment, the influence on the entire vehicle due to the vehicle speed and the infrastructure state can be excluded, so the above problem can be solved with high accuracy. An abnormal state can be detected, and driving safety during vehicle operation can be improved.

  In addition, the state monitoring system 1 (or the state monitoring apparatus 100) according to the first embodiment notifies the driver 90 or the like of an alarm when an abnormal state is detected, thereby causing a serious accident that may be caused from the abnormal state. Can be expected to prevent. That is, the state monitoring system 1 (or the state monitoring device 100) according to the present embodiment enables monitoring of an abnormal state even for a vehicle on which a driver or a crew member is not on board, and improves traveling safety during vehicle operation. Can be made.

  Further, according to the state monitoring system 1 (or the state monitoring device 100) of the present embodiment, the formation vehicle 10 travels by enabling detection of an abnormal state in the vehicle 11 constituting the formation vehicle 10 as described above. It is possible to detect a malfunction of the infrastructure state to be performed. In addition, if the failure of the infrastructure state can be detected at an early stage, the infrastructure can be easily maintained, so that the reliability of the infrastructure is improved.

(2) Second Embodiment (2-1) Configuration of State Monitoring System FIG. 5 is a block diagram showing an example of the overall configuration of a railway vehicle state monitoring system (state monitoring system 2) according to the second embodiment. is there.

  Hereinafter, the configuration of the state monitoring system 2 will be described with reference to FIG. 5, focusing on differences from the state monitoring system 1 shown in FIG. In addition, in the railway vehicle state monitoring system 2 according to the second embodiment, configurations having the same numbers as those in the railway vehicle state monitoring system 1 according to the first embodiment are common to the state monitoring system 1. The configuration is shown, and detailed description thereof is omitted.

  In FIG. 5, the formation vehicle 20 is composed of a plurality of vehicles 21. Specifically, the leading vehicle 21 </ b> A and intermediate vehicles 21 </ b> B to 21 </ b> N (the rear vehicle is also included in the intermediate vehicle as in the first embodiment). And. In FIG. 5, the wheel shaft 16 of the vehicle 21 </ b> B is described as being on a broken line that deviates from the track (solid line in the horizontal direction). This indicates that the vehicle 21 </ b> B of the trained vehicle 20 is in a derailed state. The other vehicles 21A, 21C, 21N, etc. described so that the wheel shaft 16 is on the track are not derailed.

  A vehicle information control device 29A is mounted on the leading vehicle 21A. The vehicle information control device 29 </ b> A relates to all the vehicles 21 </ b> A to 21 </ b> N of the formation vehicle 20, such as basic information on vehicle operation such as travel speed, travel distance, travel position (GPS information: Global Positioning System), and station information during vehicle operation. In addition, a device that constantly manages and controls the state of equipment such as a motor, a brake, a door, and an air conditioner mounted on the formation vehicle 20 is controlled by, for example, execution of a program.

  Further, vehicle information control devices 29B to 29N are mounted on the intermediate vehicles 21B to 21N. The vehicle information control devices 29B to 29N can collect at least basic information on the vehicle operation, equipment states, and the like for the vehicles 21B to 21N on which the vehicles are mounted. The vehicle information control devices 29B to 29N are connected so as to be communicable with the vehicle information control device 29A. The vehicle information control device 29A is a master unit, and the vehicle information control devices 29B to 29N are respectively slave units. Note that the vehicle information control device 29A and the vehicle information control devices 29B to 29N may be devices having equivalent functions, and the vehicle information control device 29A that is a parent device has basic information and device status on vehicle operation. In order to constantly manage and control etc., a device having more functions than the slave unit may be used.

  As a method for connecting the vehicle information control devices 29A to 29N, for example, as shown in FIG. 5, the vehicle information control devices 29A to 29N are connected to each other so that they can communicate with each other by wire (or wireless). By allowing the vehicle information to be shared, the vehicle information control device 29A can grasp the vehicle information regarding all the vehicles 21A to 21N. Alternatively, for example, the vehicle information control device 29A is connected to each of the vehicle information control devices 29B to 29N so as to be directly communicable by radio or the like, so that the vehicle information control device 29A grasps vehicle information regarding all the vehicles 21A to 21N. You may be able to do it.

  Next, input / output of signals with the state monitoring apparatus 200 in the state monitoring system 2 will be described.

  In the state monitoring system 2 shown in FIG. 5, the vibration acceleration sensors 17 </ b> A to 17 </ b> N are installed in the vehicles 21 </ b> A to 21 </ b> N, similarly to the state monitoring system 1 (see FIG. 1) of the first embodiment. However, in the second embodiment, the sensor signals 171B to 171N based on the vibration acceleration detection results by the vibration acceleration sensors 17B to 17N are not directly output to the state monitoring device 100 as in the first embodiment. After being transmitted to the vehicle information control device 29A mounted on the leading vehicle 21A via the vehicle information control devices 29B to 29N mounted on the host vehicle, the state monitoring device is used as the sensor signal 271 from the vehicle information control device 29A. 200 is output.

  For example, the sensor signal 171B based on the vibration acceleration detection result by the vibration acceleration sensor 17B of the intermediate vehicle 21B is transmitted to the vehicle information control device 29B and exchanged between the vehicle information control device 29B and the vehicle information control device 29A. It is included in the vehicle information signal 270B and transmitted to the vehicle information control device 29A. As described above, since the vehicle information control devices 29A to 29N can share information between adjacent vehicles, the vehicle information control device 29B is used in all the intermediate vehicles 21C to 21N in the direction opposite to the leading vehicle 21A. Sensor signals 171C to 171N can also be acquired and transmitted to the vehicle information control device 29A. Then, the vehicle information control device 29A detects vibration acceleration information detected by the intermediate vehicles 21B to 21N based on the transmitted vehicle information signal 270B (indirectly including the vehicle information signals 270C to 270N). The signal 271 is input to the vibration acceleration detection processing unit 201 of the state monitoring device 200.

  On the other hand, the vibration acceleration detection result by the vibration acceleration sensor 17A of the leading vehicle 21A is directly input to the vibration acceleration detection processing unit 201 of the state monitoring device 200, as in the first embodiment. In the state monitoring system 2 of the second embodiment, as another example, the detection result by the vibration acceleration sensor 17A of the leading vehicle 21A is also transmitted to the vehicle information control device 29A, and the sensor signal 271 is transmitted to the vibration acceleration detection processing unit 201. You may make it input.

  Further, the vehicle information control device 29A of the leading vehicle 21A inputs the vehicle information signal 273 to the state monitoring device 200 in addition to the sensor signal 271. The vehicle information signal 273 includes vehicle information shared by the vehicle information control device 29A (for example, vehicle speed information, installation position information of the vibration acceleration sensor, etc.). By inputting the sensor signal 271 and the vehicle information signal 273, the state monitoring apparatus 200 can grasp the installation position of the vibration acceleration sensor in each vehicle, the vehicle speed when the vibration acceleration is detected, and the like. In the example of FIG. 5, the vehicle information signal 273 is shown to be input to the amplitude ratio calculation processing unit 203 of the state monitoring device 200. However, in the state monitoring system 2 of the present embodiment, It may be input to another processing unit.

  As shown in FIG. 5, the state monitoring device 200 is included in the state monitoring system 2 and is installed, for example, in the equipment room or under the floor of a specific vehicle such as the leading vehicle 21A. It should be noted that the state monitoring device 200 does not necessarily have to be installed in the formation vehicle 20, and may be installed in a control room or the like that can communicate with the leading vehicle 21A, for example. The state monitoring apparatus 200 includes a vibration acceleration detection processing unit 201, a filter processing unit 202, an amplitude ratio calculation processing unit 203, a threshold determination processing unit 204, an alarm generation processing unit 205, and a data recording processing unit 206. Details of processing by each processing unit will be described later with reference to FIG.

  The state monitoring device 200 performs an abnormal state detection process based on the sensor signal 171A input from the acceleration sensor 17A, the sensor signal 271 and the vehicle information signal 273 input from the vehicle information control device 29A, and detects an abnormal state. Is detected, an alarm signal 276 is output to the vehicle information control device 29A. The vehicle information control device 29A to which the alarm signal 276 is input inputs an alarm display signal 277 to the cab 18 and displays an alarm.

  FIG. 6 is a block diagram illustrating a hardware configuration example of the state monitoring apparatus illustrated in FIG. The processor 210 of the state monitoring apparatus 200 shown in FIG. 6 is different from the processor 110 of the state monitoring apparatus 100 shown in FIG. 2 in that the vehicle information control device 29A is connected to the interface 213. That is, if the state monitoring device 200 is mounted on the leading vehicle 21A, the state monitoring device 200 outputs sensor signals from the vibration acceleration sensors 17B to 17N in the intermediate vehicles 21B to 21N where the state monitoring device 200 is not mounted. The signal is input to the processor 210 via the vehicle information control device 29A of the mounted leading vehicle 21A.

  As described above, the state monitoring system 2 of the second embodiment is configured such that only the leading vehicle 21A inputs and outputs signals to and from the state monitoring device 200. A state abnormality can be detected without being influenced by the configuration other than 21A. Further, a system configuration in which the vehicle information control device 29A includes the state monitoring device 200 may be adopted. In such a case, the vehicle information control device 29A and the state monitoring device 200 are integrated. Thus, it is possible to design a more compact device, and it is easy to mount in a vehicle where the loading space is limited.

(2-2) Abnormal State Detection Process FIG. 7 is a flowchart illustrating an example of a procedure of an abnormality detection process in the second embodiment. The abnormality detection process shown in FIG. 7 is executed by the processor 210 (mainly the CPU 110) of the state monitoring apparatus 200. In the following, the abnormality detection process shown in FIG. 5 will be described focusing on the difference from the abnormality detection process (see FIG. 3) described in the first embodiment.

  First, in step S200, sensor signals 171A and 271 detected by the vibration acceleration sensor 27 (27A to 27N) installed in each vehicle 21 (21A to 21N) are input to the vibration acceleration detection processing unit 201. As described above, the sensor signal 171A detected by the vibration acceleration sensor 17A is directly input from the vibration acceleration sensor 17A, but the sensor signals 171B to 171N detected by the vibration acceleration sensors 17B to 17N are the vehicle information control device 29A. Is input as a sensor signal 271.

  Then, the vibration acceleration detection processing unit 201 extracts sensor signals 171B to 171N from the sensor signal 271, and outputs sensor signals 171 (individually 171A to 171N) indicating the vibration acceleration detected in the respective vehicles 21A to 21N. Output to the vibration acceleration detection processing unit 201.

  Next, in step S201, the vibration acceleration detection processing unit 201 performs band-pass filter processing on each of the input sensor signals 171A to 171N, and filters vibration acceleration signals 172 (individually 172A to 172N). To the unit 202. The bandpass filter process in step S201 is the same as the process in step S101 in FIG.

  In step S202, the filter processing unit 102 performs, for each of the input vibration acceleration signals 172A to 172N, extraction processing of the vibration acceleration signal having a variation data length (time width) by a window filter based on the vehicle information, The filtered window filtering signal 173 (individually 173A to 173N) is output to the amplitude ratio calculation processing unit 203. The process of step S202 is different from the process of step S102 of FIG. 3 in which a window filter having a fixed data length is applied in that a window filter based on vehicle information is applied.

  Here, the window filter processing in step S202 will be described in detail. The filter processing unit 202 is a window for vibration acceleration signals 172A to 172N based on vehicle information (for example, vehicle speed information and installation information of vibration acceleration sensors) input from the vehicle information control device 29A to the state monitoring device 200. Change the application position and range of the filter.

  First, the application position of the window filter will be described. The vibration acceleration generated when the trained vehicle 20 travels has different travel positions in the leading vehicle 21A and the intermediate vehicles 21B to 21N. That is, for example, assuming that the vibration acceleration of each of the vehicles 21A to 21N is detected at the same timing, the absolute position of each vehicle at the time of detection (more precisely, the installation position of the vibration acceleration sensors 17A to 17N) is the length of the vehicle. It depends on the vehicle speed. Such a shift between vehicles (between vibration acceleration sensors) can be specified based on vehicle speed information and installation position information of the vibration acceleration sensor.

  Therefore, the filter processing unit 202 calculates the timing at which the vibration acceleration sensors 17A to 17N of the vehicles 21A to 21N pass a predetermined point based on the vehicle speed information and the installation position information of the vibration acceleration sensor, and each vehicle 21A. With respect to the vibration acceleration signals 172A to 172N detected at ˜21N, the application position (phase) of the window filter is changed for each vehicle. As a result, with respect to the window filtering signals 173 (173A to 173N) for all the vehicles of the trained vehicle 20, the vibration acceleration detection positions (generation positions) of all the vehicles can be made to coincide with each other (for example, FIG. 8A). (Refer to the position of the window filter 281 in (c)).

  As described above, by matching the detection positions (occurrence positions) of the vibration accelerations of all the vehicles at the predetermined points, the state monitoring apparatus 200 according to the present embodiment is affected by the infrastructure state (starting state, ground, etc.) at the predetermined points. Therefore, the abnormal state can be detected based on the difference in vibration acceleration between the vehicles.

  Next, the application range of the window filter will be described. The filter processing unit 202 adjusts the amount of data obtained by applying the window filter (the amount of data of the window filtering signal 173) by changing the window filter application range (time width to be extracted) according to the vehicle speed. can do.

  For example, when the vehicle speed is high, vibration acceleration data of an amount necessary for appropriately calculating the calculated value in the subsequent calculation of the vibration acceleration RMS value (step S203) is obtained in a relatively short time. be able to. Therefore, when the vehicle speed is high, the application range by the window filter is narrower than usual (the extraction time width is shortened), so that it is possible to suppress the accumulation of more data than necessary, and the vibration in step S203 The calculation amount of the acceleration RMS value can be reduced to reduce the processing load on the processor 210 (see, for example, the time width of the window filter 283 in FIGS. 9A to 9C).

  For example, when the vehicle speed is low, it takes a relatively long time to obtain the amount of vibration acceleration data necessary to appropriately calculate the vibration acceleration RMS value. Therefore, when the vehicle speed is slow, the range of application by the window filter is made wider than usual (the extraction time width is made longer), so that the vibration acceleration RMS value with low reliability is calculated due to insufficient collection of data amount. (See, for example, the time width of the window filter 281 in FIGS. 8A to 8C).

  After the processing in step S202, in steps S203 and S204, the amplitude calculation processing unit 203 performs amplitude ratio calculation processing. First, in step S203, the vibration acceleration RMS value of each vibration acceleration (for each vehicle) is calculated for each of the input window filtering signals 173 (173A to 173N). In step S204, the RMS value amplitude ratio for each vehicle is calculated based on the vibration acceleration RMS value for each vehicle calculated in step S203, and the amplitude ratio signal 174 based on the RMS value amplitude ratio of the intermediate vehicles 11B to 11N. (Individually, 174B to 174N) are output to the threshold determination processing unit 204.

  In step S205, the threshold determination processing unit 204 executes threshold determination processing based on a threshold set in advance for the amplitude ratio signal 174 (174B to 174N) input from the amplitude ratio calculation processing unit 203. To do.

  Next, in step S206, the alarm generation processing unit 206 generates an alarm for generating a warning (alarm) related to detection of an abnormal state based on the determination processing result signal 175 (175B to 175N) input from the threshold determination processing unit 204. Execute the process. When generating an alarm in the alarm generation process, the alarm generation processing unit 205 outputs an alarm signal 276 to the data recording processing unit 206 and the vehicle information control device 29A. The vehicle information control device 29A to which the alarm signal 276 is input inputs an alarm display signal 277 to the cab 18 and displays an alarm. In the alarm display, specifically, for example, the identification of the vehicle in which the abnormal state is detected, the type of the detected abnormal state, the data (vibration acceleration) that is the determination target of the abnormal state, and the like are displayed. The vehicle information control device 29A also transfers the alarm signal 276 input from the alarm generation processing unit 206 to the vehicle information control devices 29B to 29N mounted on the other vehicles 21B to 21N, so that the trained vehicle 20 Among the vehicles constituting the vehicle, the determination result of the abnormality detection process can be shared among all the vehicles 21A to 21N in which the vehicle information control device 29 is mounted.

  Finally, in step S207, the data recording processing unit 206 uses the alarm signal 276 (or alarm information included in the signal) input from the alarm generation processing unit 205 as a storage medium (for example, a memory) To card 117). Further, the data recording processing unit 206 can record various types of vehicle information (for example, video images of in-vehicle cameras and various device states in the intermediate vehicle 11 to be alarmed) together with the alarm signal 176 in the storage medium. preferable.

  Since the processing of steps S203 to S205 and S207 is the same as the processing of steps S103 to 105 shown in FIG. 3, detailed description thereof is omitted. Also, the alarm information included in the alarm signal 276 output in step S206 is the same as the alarm signal 176 in FIG.

  As described above, by performing the processing shown in steps S200 to S206 of FIG. 7, the state monitoring device 200 is mounted with the vehicle information control device 29A on the plurality of vehicles 21A to 21N constituting the formation vehicle 20. The state of each vehicle 21 can be determined and an abnormal state can be detected based on the relative value (for example, RMS value amplitude ratio) of vibration acceleration with the specified vehicle (leading vehicle 21A) as a reference.

  8 and 9 are diagrams (No. 1 and No. 2) for explaining an example of the amplitude ratio calculation process in the second embodiment. FIG. 8 is a processing image of the amplitude ratio calculation process when the vehicle speed is low, and FIG. 9 is a processing image of the amplitude ratio calculation process when the vehicle speed is high.

  FIG. 8A is a processing image for “vibration acceleration A” based on the sensor signal 171A output from the vibration acceleration sensor 17A of the leading vehicle 21A, and is shown in FIG. 4C shown in the first embodiment. Equivalent to. FIG. 8B is a processing image for “vibration acceleration B” based on the sensor signal 171B output from the vibration acceleration sensor 17B of the intermediate vehicle 21B. FIG. 8B shows the processing image for FIG. 4F shown in the first embodiment. Equivalent to. FIG. 8C is a processing image for “vibration acceleration N” based on the sensor signal 171N output from the vibration acceleration sensor 17N of the intermediate vehicle 21N, and is the same as FIG. 4I shown in the first embodiment. Equivalent to. Note that FIGS. 9A to 9C are the same, and the description thereof is omitted.

  In FIGS. 8A to 8C, since the vehicle speed is low, a window filter 281 having an application range (time width) wider than usual is used. Further, the application position (phase) of the window filter 281 is set to a position earlier in time in FIG. 8B corresponding to the rear intermediate vehicle 21B than in FIG. 8A corresponding to the leading vehicle 21A. Further, in FIG. 8C corresponding to the rear intermediate vehicle 21N, the position is earlier in time. By doing in this way, the detection position (generation position) of the vibration acceleration in all the vehicles 21A-21N is made to correspond.

  8A to 8C, by applying such a window filter 281, the vibration acceleration RMS value 282 in each vehicle based on the vibration acceleration 183 (183A to 183N) extracted with a long data length. (282A to 282N) can be calculated, and the amount of data to be calculated can be adjusted. Then, the amplitude ratio calculation processing unit 203 calculates the RMS value amplitude ratio using such vibration acceleration RMS values 282A to 282N, and the threshold determination processing unit 204 performs a threshold determination process based on the RMS value amplitude ratio. be able to.

  In FIGS. 9A to 9C, since the vehicle speed is high, a window filter 283 whose application range (time width) is narrower than usual is used. In addition, the application position (phase) of the window filter 283 is set to a position earlier in time in FIG. 9B corresponding to the rear intermediate vehicle 21B than in FIG. 9A corresponding to the leading vehicle 21A. Further, in FIG. 9C corresponding to the intermediate vehicle 21N at the rear, the vehicle is positioned earlier in time. By doing in this way, the detection position (generation position) of the vibration acceleration in all the vehicles 21A-21N is made to correspond.

  9A to 9C, by applying such a window filter 283, based on the vibration acceleration 183 (183A to 183N) extracted with a short data length, the vibration acceleration RMS value 284 in each vehicle. (284A to 284N) can be calculated, and the amount of data to be calculated can be adjusted. Then, the amplitude ratio calculation processing unit 203 calculates the RMS value amplitude ratio using such vibration acceleration RMS values 284A to 284N, and the threshold determination processing unit 204 performs the threshold determination processing based on the RMS value amplitude ratio. be able to.

(2-3) Effects of the Second Embodiment As described above, according to the state monitoring system 2 (or the state monitoring device 200) of the second embodiment, the multiple vehicles 21 ( 21A to 21N) using the vibration acceleration sensor 17 (17A to 17N) mounted on the specific vehicle (the leading vehicle 21A on which the vehicle information control device 29A is mounted) on the basis of the vibration acceleration sensor signal 171A. By relatively determining the vibration acceleration in the vehicle (the intermediate vehicles 11B to 11N), an abnormal state (for example, derailment of the vehicle, malfunction of the vehicle or infrastructure, snake behavior, etc.) occurring in the other vehicle is detected. can do.

  In particular, in the state monitoring system 2 (or the state monitoring device 200) according to the second embodiment, a calculation criterion for calculating the relative value (RMS value amplitude ratio) of the vibration acceleration for each vehicle in the abnormality detection process of FIG. For the window filtering signals 173A to 173N to be obtained, vibration acceleration at the same point can be extracted based on vehicle information such as the vehicle speed and the installation position of the vibration acceleration sensor (see also FIGS. 8 and 9). The influence of the infrastructure state (starting state, ground, etc.) at the point is eliminated, and the abnormal state can be detected based on the difference in vibration acceleration between the vehicles. By making it possible to detect an abnormal state in consideration of vehicle information in this way, the state monitoring system 2 (or the state monitoring device 200) of the second embodiment can perform state monitoring with high accuracy and during vehicle operation. The driving safety can be further improved.

  Further, the state monitoring system 2 (or the state monitoring device 200) of the second embodiment is the same as that of the first embodiment when the vehicle information control device 29A is mounted on the leading vehicle 21A on which the driver 90 gets. Similar to the state monitoring system 1 (or the state monitoring device 100), “relative to vibration acceleration in other vehicles on which the driver 90 is not on board, based on the sensor signal 171A of vibration acceleration on the vehicle on which the driver 90 rides. Therefore, the effect of the first embodiment can also be realized.

(3) Third Embodiment A railway vehicle state monitoring system according to a third embodiment of the present invention will be described. The railway vehicle state monitoring system according to the third embodiment can utilize the same configuration as the railway vehicle state monitoring system according to the first or second embodiment, and an abnormality detection process performed by the state monitoring device. Only some of the processing is different. Therefore, for the sake of brevity, description of parts common to the first or second embodiment is omitted. However, in the third embodiment, it is assumed that the vibration acceleration sensor is installed in each of at least three vehicles among a plurality of vehicles constituting the formation vehicle.

  FIG. 10 is a flowchart illustrating an example of a procedure of an abnormality detection process performed by the railway vehicle state monitoring system according to the third embodiment.

  In the abnormality detection process shown in FIG. 10, the vibration acceleration RMS value of the leading vehicle is not used as a reference value as in the abnormality detection process in the first or second embodiment, but new based on all vibration acceleration RMS values. A reference value generation process for determining a reference value is performed (step S304). Then, the RMS value amplitude ratio of each vehicle is calculated using the newly determined reference value (step S305).

  The processing in steps S300 to S303 in FIG. 10 is the same as the processing in steps S100 to S103 in FIG. 3 (or steps S200 to S203 in FIG. 7). The processing in steps S306 to S308 in FIG. Since it is the same as the process of S105-S107 (or step S205-S207 of FIG. 7), these description is abbreviate | omitted and only step S304, S305 is demonstrated.

  In step S304, the amplitude ratio calculation processing unit determines a reference value of the amplitude ratio based on the vibration acceleration RMS value of each vehicle calculated in step S303 (reference value generation process). In the reference value generation process, the reference value is determined by a predetermined calculation method (average value, median value, minimum value, etc.) from the vibration acceleration set data detected by the vibration acceleration sensor of each vehicle.

  FIG. 11 is a diagram for describing an example of a reference value generation process according to the third embodiment. In FIG. 11, vibration acceleration RMS values 371A to 371N corresponding to the vehicles (for example, the vehicles 11A to 11N) constituting the formation vehicle are shown, and the average value is determined as the reference value 381.

  In step S305, the vibration acceleration RMS value (for example, vibration acceleration RMS value 371A to 371N in FIG. 11) of each vehicle is set with reference to the reference value (for example, the reference value 381 in FIG. 11) determined in the reference value generation process. ) To calculate the RMS value amplitude ratio of each vehicle, and based on the calculation result, the amplitude ratio signal 174 (174A to 174N individually) of each vehicle 11A to 11N is a threshold value determination processing unit. Is output.

  Thus, by performing the processing shown in steps S300 to S308 of FIG. 10, the state monitoring apparatus of the third embodiment performs vibration acceleration in the entire knitted vehicle with respect to a plurality of vehicles constituting the knitted vehicle. Since the abnormal state is detected using a relative value based on the above, the abnormal state of all individual vehicles (for example, vehicle derailment, vehicle or infrastructure state) Malfunction, snake behavior, etc.) can be detected.

  Further, according to the state monitoring system (or state monitoring device) of the third embodiment, the abnormal state is detected based on the relative value of the vibration acceleration between the vehicles, so that it is also described in the first or second embodiment. As described above, it is possible to detect an abnormal state with high accuracy by excluding the influence on the entire vehicle due to the vehicle speed and the infrastructure state, and to improve the traveling safety during the vehicle operation.

  Moreover, according to the state monitoring system (or the state monitoring device) of the third embodiment, an abnormal state can be detected generically for the individual vehicles constituting the formation vehicle, so that the infrastructure state in which the formation vehicle travels can be detected. If the failure can be detected and the failure of the infrastructure state can be detected at an early stage, the infrastructure can be easily maintained, and the reliability of the infrastructure is improved.

(4) Other Embodiments The present invention is not limited to the above-described embodiments, and includes various modifications. For example, the above-described embodiment has been described in detail for easy understanding of the present invention, and is not necessarily limited to one having all the configurations described. Further, a part of the configuration of an embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of an embodiment. In addition, it is possible to add, delete, and replace other configurations for a part of the configuration of each embodiment.

  For example, in the above-described embodiment, a vibration acceleration sensor that detects vibration acceleration is installed as a sensor for detecting a vehicle state during vehicle operation, and an abnormal state is detected based on the sensor signal (vibration acceleration sensor signal). However, the present invention is not limited to this. As another example of the sensor, a sound sensor (for example, a microphone) that detects sound, a strain gauge that measures strain, a thermocouple that measures a physical quantity of heat, or a pressure sensor that detects pressure applied to a vehicle or the like is installed. be able to. In such a case, the sensor signal output from the sensor is a sound sensor signal, a strain sensor signal, a thermal sensor signal, or a pressure sensor signal, respectively, and the present invention detects an abnormal state based on these sensor signals. You may make it do. In this way, by making it possible to use various types of sensors, the present invention can use an appropriate sensor according to the type of abnormal state to be detected. Can do.

  In the case where a microphone is used as the sensor, the detection sound by the microphone may be discriminated from the in-vehicle sound generated inside the mounted vehicle or the outside sound generated outside the mounted vehicle. If the abnormality detection process is performed using the sound sensor signals of each vehicle based on the in-vehicle sound, the process excluding the sound caused by the infrastructure state (mainly the outside sound) becomes possible. The detection accuracy of the abnormal state caused by the inside can be improved. Also, if the abnormality detection process is performed using the sound sensor signals of each vehicle based on the sound outside the vehicle, the process based on the sound caused by the infrastructure state becomes possible. The state detection accuracy can be increased.

  Each of the above-described configurations, functions, processing units, processing means, and the like may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Each of the above-described configurations, functions, and the like may be realized by software by interpreting and executing a program that realizes each function by the processor. Information such as programs, tables, and files that realize each function can be stored in a storage device such as a memory, a hard disk, or an SSD (Solid State Drive), or a storage medium such as an IC card, an SD card, or a DVD.

  Further, the control lines and information lines indicate what is considered necessary for the explanation, and not all the control lines and information lines on the product are necessarily shown. In practice, it may be considered that almost all components are connected to each other.

  The present invention is suitable for application to a state monitoring device and a state monitoring system for monitoring the state of a railway vehicle, and a knitted vehicle having the state monitoring system, but is not limited thereto. For example, the present invention can be applied to a mobile body system that monitors a state of a mobile body (for example, an elevator, an escalator, a mining dump truck, etc.) that travels on a specific track.

DESCRIPTION OF SYMBOLS 1 Condition monitoring system 10,20 Formation vehicle 11,21 Vehicle 11A, 21A Lead vehicle 11B-11N, 21B-21N Intermediate vehicle 12 Car body 13 Bogie 14 Air spring 15 Bogie frame 16 Wheel shaft 17 (17A-17N) Vibration acceleration sensor 18 Driving Table 29 (29A to 29N) Vehicle information control device 90 Driver 100, 200 State monitoring device 101, 201 Vibration acceleration detection processing unit 102, 202 Filter processing unit 103, 203 Amplitude ratio calculation processing unit 104, 204 Threshold determination processing unit 105 205 Alarm generation processing unit 106, 206 Data recording processing unit 110, 210 Processor 111 CPU
112 RAM
113,213 interface 114 ROM
115 Card connector 116 Bus 117 Memory card 171 (171A to 171N), 271 Sensor signal 172 Vibration acceleration signal 173 Vibration acceleration signal (window filtering signal)
174 Amplitude ratio signal 175 Determination processing result signal 176 Alarm signal 270 (270B to 270N), 273 Vehicle information signal

Claims (11)

A state monitoring device in which sensors are mounted on each of a plurality of vehicles constituting the trained vehicle, and the state of the vehicle is monitored based on sensor signals from the sensors.
A signal detection processing unit for detecting sensor signals of a plurality of vehicles equipped with the sensors;
A data extraction unit for extracting vehicle data corresponding to the sensor signal from each sensor signal detected by the signal detection processing unit;
An amplitude ratio calculation processing unit that extracts one reference value based on the data of each vehicle extracted by the data extraction unit and calculates the ratio of the data of each vehicle with respect to the reference value;
Based on the calculation result by the amplitude ratio calculation processing unit, a threshold determination processing unit that determines the presence or absence of an abnormal state of each vehicle;
Equipped with a,
The data extraction unit limits the data length to be extracted and the first filter processing that applies a band pass filter that limits the frequency band to be extracted to each sensor signal detected by the signal detection processing unit. By performing the second filter processing that applies the window filter, the vehicle data corresponding to each of the sensor signals is extracted,
In the second filter processing, the time width for applying the window filter varies based on the vehicle speed of the trained vehicle so that the amount of data necessary for the calculation by the amplitude ratio calculation processing unit can be extracted without excess or deficiency. And the phase to which the window filter is applied is determined for each vehicle based on the vehicle speed of the trained vehicle so that the detection positions of the data of each vehicle extracted by application of the window filter match in all vehicles. A state monitoring device for a railway vehicle, which is displaced . The state monitoring apparatus according to claim 1, further comprising an alarm generation processing unit that warns of the abnormal state of the vehicle for which the determination is made when the threshold determination processing unit determines that there is an abnormal state. Among the plurality of vehicles constituting the formation vehicle, the sensor is mounted on a specific vehicle and a general vehicle other than the specific vehicle,
The amplitude ratio calculation processing unit extracts one reference value based on the data of the specific vehicle from the data of each vehicle extracted by the data extraction unit, and the ratio of the data of the general vehicle to the reference value And
The state monitoring apparatus according to claim 1, wherein the threshold determination processing unit determines whether or not there is an abnormal state of the general vehicle based on a result of the calculation by the amplitude ratio calculation processing unit. The amplitude ratio calculation processing unit extracts a reference value from a set of data of each vehicle extracted by the data extraction unit, and calculates a ratio of the data of each vehicle with respect to the reference value. The state monitoring device described. A sensor mounted on each of a plurality of vehicles constituting the formation vehicle;
A state monitoring device that is communicably connected to the sensors and that monitors the state of the vehicle based on sensor signals from the sensors;
With
The state monitoring device
A signal detection processing unit for detecting sensor signals of a plurality of vehicles equipped with the sensors;
A data extraction unit for extracting vehicle data corresponding to the sensor signal from each sensor signal detected by the signal detection processing unit;
An amplitude ratio calculation processing unit that extracts one reference value based on the data of each vehicle extracted by the data extraction unit and calculates the ratio of the data of each vehicle with respect to the reference value;
A threshold determination processing unit that determines the presence or absence of an abnormal state of each vehicle based on the result of the calculation by the amplitude ratio calculation processing unit ,
The data extraction unit limits the data length to be extracted and the first filter processing that applies a band pass filter that limits the frequency band to be extracted to each sensor signal detected by the signal detection processing unit. By performing the second filter processing that applies the window filter, the vehicle data corresponding to each of the sensor signals is extracted,
In the second filter processing, the time width for applying the window filter varies based on the vehicle speed of the trained vehicle so that the amount of data necessary for the calculation by the amplitude ratio calculation processing unit can be extracted without excess or deficiency. And the phase to which the window filter is applied is determined for each vehicle based on the vehicle speed of the trained vehicle so that the detection positions of the data of each vehicle extracted by application of the window filter match in all vehicles. A railway vehicle state monitoring system characterized by being displaced . The sensor is mounted on a specific vehicle on which a driver or a crew member rides and a general vehicle other than the specific vehicle among a plurality of vehicles constituting the formation vehicle,
In the state monitoring device,
The amplitude ratio calculation processing unit extracts one reference value based on the data of the specific vehicle from the data of each vehicle extracted by the data extraction unit, and the ratio of the data of the general vehicle to the reference value And
The state monitoring system according to claim 5, wherein the threshold determination processing unit determines the presence or absence of an abnormal state of the general vehicle based on a result of the calculation by the amplitude ratio calculation processing unit. A vehicle information control device that manages vehicle information related to each vehicle that is mounted on the specific vehicle that can communicate with the state monitoring device and constitutes a formation vehicle;
The state monitoring system according to claim 6 , wherein a sensor signal from the sensor mounted on the general vehicle is input to the state monitoring device via the vehicle information control device. The state monitoring system according to claim 5 , wherein the sensor is installed on a vehicle body or a carriage of the vehicle. The sensor is at least one of a vibration acceleration sensor that detects vibration acceleration, a sound sensor that detects sound, a strain gauge that measures strain, a thermocouple that measures a physical quantity of heat, or a pressure sensor that detects pressure. The state monitoring system according to claim 5 . When the sound sensors are mounted on the plurality of vehicles,
Among the sounds detected by the sound sensor of each vehicle, the state monitoring device is configured to detect sensor signals based on outside sound generated outside the vehicle or sensor signals based on in-vehicle sound generated inside the vehicle. The state monitoring system according to claim 9 , wherein state monitoring of the vehicle is performed based on the state monitoring. A knitted vehicle configured by connecting a plurality of vehicles,
A sensor mounted on each of a plurality of vehicles constituting the formation vehicle;
A state monitoring device that is communicably connected to the sensors and that monitors the state of the vehicle based on sensor signals from the sensors;
With
The state monitoring device
A signal detection processing unit for detecting sensor signals of a plurality of vehicles equipped with the sensors;
A data extraction unit for extracting vehicle data corresponding to the sensor signal from each sensor signal detected by the signal detection processing unit;
An amplitude ratio calculation processing unit that extracts one reference value based on the data of each vehicle extracted by the data extraction unit and calculates the ratio of the data of each vehicle with respect to the reference value;
A threshold determination processing unit that determines the presence or absence of an abnormal state of each vehicle based on the result of the calculation by the amplitude ratio calculation processing unit,
The data extraction unit limits the data length to be extracted and the first filter processing that applies a band pass filter that limits the frequency band to be extracted to each sensor signal detected by the signal detection processing unit. By performing the second filter processing that applies the window filter, the vehicle data corresponding to each of the sensor signals is extracted,
In the second filter processing, the time width for applying the window filter varies based on the vehicle speed of the trained vehicle so that the amount of data necessary for the calculation by the amplitude ratio calculation processing unit can be extracted without excess or deficiency. And the phase to which the window filter is applied is determined for each vehicle based on the vehicle speed of the trained vehicle so that the detection positions of the data of each vehicle extracted by application of the window filter match in all vehicles. Displaced,
The knitted vehicle characterized in that the state monitoring device shares the determination result of the abnormal state by the threshold value determination processing unit among the vehicles of the knitted vehicle.

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