JP7532291B2 - Train information management device - Google Patents

Description

An embodiment of the present invention relates to a train information management device.

Data collected from trains and the processed data (hereafter referred to as vehicle data) are used to monitor train operation status and analyze the causes of equipment failures. Various types of vehicle data, such as operational information for the control devices and vehicle equipment, as well as sensor measurements, can be obtained from various sensors installed in the train's control devices and vehicle equipment. In recent years, IoT (Internet of Things) technology has become more common, and vehicle data is transmitted from the train to a server or other location on the ground. Using the vast amount of data stored on the server, it is possible to visualize long-term data fluctuations and analyze them by comparing them with other formations.

However, whether train vehicle data is being collected normally depends on the operating status of the collection system. For example, if the operation of the collection system stops, there is a possibility that the data will become partially discontinuous. In other words, there is a possibility that the data collection time interval will become large. This is because there will be a gap in the collection time from when the collection system stops to when it starts operating again. When such a gap in collection time occurs, it is difficult to determine from the collected vehicle data whether data collection stopped under normal operating conditions of the collection system or whether data loss occurred due to data collection stopping under abnormal operating conditions. As a result, there is a possibility that the lack of data will not be addressed adequately. For example, when collecting data is aggregated for visualization or analysis, there is a problem that if data is missing, it will be impossible to calculate the correct value.

International Publication No. 2019/225181 JP 2016-46692 A

The aim is to provide a train information management device that can deal with missing data more appropriately.

The train information management device according to this embodiment includes a collection date and time acquisition unit, an accumulated information acquisition unit, and a missing data determination unit. The collection date and time acquisition unit acquires the collection date and time of a data collection device that collects vehicle data including at least first accumulated information of first predetermined data related to vehicles in operation. The accumulated information acquisition unit acquires the first accumulated information. The missing data determination unit determines whether or not there is a data missing due to an abnormality in the data collection device between the two vehicle data based on the amount of change in the first accumulated information between two vehicle data whose collection dates and times are adjacent.

1 is a block diagram showing an example of an overall configuration of a train information system including a train information management device according to a first embodiment. FIG. 4 is a diagram showing an example of vehicle data according to the first embodiment. FIG. 2 is a block diagram showing an example of the configuration of a running missing information calculation unit according to the first embodiment. FIG. 2 is a flow chart showing an example of an operation of the train information management device according to the first embodiment. FIG. 4 is a flow chart showing an example of an operation of a running missing information calculation unit according to the first embodiment. 4 is a diagram showing an example of data included in vehicle data and traveling missing information according to the first embodiment; 4 is a diagram showing the relationship between the operating state of the vehicle, the operating state of the data collection device, and the speed accumulation value according to the first embodiment; FIG. FIG. 8 is a diagram showing an example of the relationship between the data collection interval and the collected data corresponding to FIG. 7 . FIG. 4 is a flow chart showing an example of the operation of the train information display device according to the first embodiment. FIG. 2 is a diagram showing an example of a display of the train display device according to the first embodiment. FIG. 11 is a block diagram showing an example of an overall configuration of a train information system including a train information management device according to a second embodiment. FIG. 13 is a block diagram showing an example of the configuration of an air conditioning deficiency information calculation unit according to the second embodiment. FIG. 11 is a flowchart showing an example of an operation of an air conditioning deficiency information calculation unit according to the second embodiment. 13A and 13B are diagrams showing an example of data included in vehicle data and air conditioning missing information according to the second embodiment. FIG. 11 is a diagram showing the relationship between the operating state of a vehicle, the operating state of a data collection device, and the cumulative value of the air-conditioning CP operation count according to the second embodiment. FIG. 13 is a diagram showing an example of a display of a train display device according to the second embodiment. FIG. 13 is a block diagram showing an example of an overall configuration of a train information system including a train information management device according to a third embodiment. FIG. 13 is a block diagram showing an example of an overall configuration of a train information system including a train information management device according to a fourth embodiment.

Below, an embodiment of the present invention will be described with reference to the drawings. The present invention is not limited to this embodiment. The drawings are schematic or conceptual, and the ratio of each part is not necessarily the same as the actual one. In the specification and drawings, elements similar to those described above with respect to the previous drawings are given the same reference numerals, and detailed explanations are omitted as appropriate.

(First embodiment)
Fig. 1 is a block diagram showing an example of the overall configuration of a train information system 1 including a train information management device 300 according to the first embodiment. The train information system 1 shown in Fig. 1 accumulates, in a ground server or the like, information to which a pre-processing has been applied and analysis data to which missing information during traveling has been added from vehicle data including equipment information and accumulated speed information of a vehicle 100 in operation, and outputs a summary result of the traveling distance to a train information display device 400.

The train information system 1 includes a vehicle 100, a train information storage device 200, a train information management device 300, and a train information display device 400.

The train information storage device 200 stores vehicle data transmitted from the vehicle 100, creates analysis data based on the vehicle data, and transmits the analysis data to other devices.

The train information management device 300 analyzes missing information in the vehicle data. In the first embodiment, the train information management device 300 is placed on the ground side. Note that the train information management device 300 shown in FIG. 1 is placed inside the train information storage device 200, but it may also be placed outside the train information storage device 200.

The train information display device 400 displays visualization data calculated according to the purpose based on the analysis data calculated by the train information management device 300.

Next, the internal configuration of the vehicle 100 will be described.

The vehicle 100 includes a vehicle data acquisition unit 101 and a vehicle data transmission unit 102.

The vehicle data acquisition unit 101 is located on the vehicle and functions as a data collection device that sequentially collects vehicle data. The vehicle data acquisition unit 101 also acquires, for example, running information such as train speed and distance between stations, control information, equipment operation information, and sensor measurement values of the equipment.

The vehicle data transmission unit 102 transmits vehicle data to a ground server.

Figure 2 shows an example of vehicle data according to the first embodiment.

The collection date and time in the first column is the date and time information (timestamp) when the vehicle data was collected, and shows that it has been collected at approximately 1 second intervals since 14:30 on June 1, 2020. In the example shown in Figure 2, the collection date and time includes the year, month, date, and time, and the collection date and time is shown to the millisecond. The second column and subsequent columns are vehicle information corresponding to each collection date and time. The accumulated speed value in the fifth column is accumulated speed information calculated based on the train speed, and is information equivalent to the mileage calculated and stored on board the vehicle. Here, the train speed rounded up to the nearest integer is added to the accumulated speed value.

That is, the vehicle data includes at least first cumulative information of the first predetermined data regarding the vehicle 100 in operation. The first predetermined data is, for example, the speed of the vehicle 100. The first cumulative information is the cumulative value of the train speed of the vehicle 100 or the travel distance of the vehicle 100.

Next, we will explain the internal configuration of the train information storage device 200 shown in Figure 1.

The train information storage device 200 includes a vehicle data storage unit 201, an additional data calculation unit 202, an analysis data creation unit 203, an analysis data storage unit 204, and a train information management device 300.

The vehicle data storage unit 201 stores vehicle data transmitted from the vehicle.

The additional data calculation unit 202 calculates additional data that has been calculated or converted based on the accumulated vehicle data. Examples of additional data include data that has been converted based on specific rules or specifications, such as acceleration step (notch) information equivalent to a railway accelerator. This notch information can be calculated from a combination of signals related to notches in the vehicle data based on conditions defined in the train control specifications, to calculate any notch information. The purpose of the additional data is to make data easier to handle and more efficient in data utilization by pre-calculating processes that are frequently performed when visualizing and analyzing accumulated vehicle data.

The analysis data creation unit 203 combines the vehicle data output by the additional data calculation unit 202 and the train information management device 300 to create analysis data.

The additional data calculation unit 202 and the analysis data creation unit 203 may also pre-process the raw data stored in the vehicle data storage unit and delete unnecessary information such as outliers.

The analysis data storage unit 204 stores the analysis data created by the analysis data creation unit 203. The analysis data storage unit 204 also functions as an analysis data transmission unit that transmits the stored analysis data to the train information management device 300. The vehicle data storage unit 201 and the analysis data storage unit 204 hold the transmitted vehicle data and analysis data in any format. In this embodiment, the data format is a file such as CSV (Comma Separated Values) data, but it may also be binary data or data managed in a database, etc.

Next, we will explain the internal configuration of the train information management device 300.

The train information management device 300 includes a collection date and time acquisition unit 301, a speed accumulation information acquisition unit 302, and a running loss information calculation unit 303.

The collection date and time acquisition unit 301 acquires information regarding the collection date and time of the vehicle data. That is, the collection date and time acquisition unit 301 acquires the collection date and time when the data collection device (vehicle data acquisition unit 101) collected the vehicle data.

The speed accumulation information acquisition unit 302 acquires the first accumulation information. That is, the speed accumulation information acquisition unit 302 acquires information that accumulates information on the train speed measured from the rotation of the vehicle's axle. This speed accumulation information is information equivalent to the travel distance calculated from the speed, and may be absolute travel distance data as long as it is a value that accumulates without being initialized.

The missing driving information calculation unit 303 analyzes missing vehicle data information from the collection date and time and cumulative speed information.

Figure 3 is a block diagram showing an example of the configuration of the travel missing information calculation unit 303 according to the first embodiment.

The driving missing information calculation unit 303 includes a collection interval calculation unit 304, a collection interval determination unit 305, a missing change amount calculation unit 306, a missing change amount determination unit 315, a driving missing information addition unit 307, and a vehicle data output unit 308.

The collection interval calculation unit 304 uses the input collection date and time to calculate the data collection interval based on the difference between the current time and the time one time ago. In other words, the collection interval calculation unit 304 calculates the collection interval by calculating the difference in timestamps between two vehicle data sets with adjacent collection dates and times.

The collection interval determination unit 305 determines whether there is a gap in the collection date and time in the time series data. A "gap in the collection date and time" occurs when the data collection device is not operating, regardless of the state (normal or abnormal) of the data collection device. The collection interval determination unit 305 determines whether the collection interval calculated by the collection interval calculation unit 304 exceeds a threshold (predetermined time interval). This threshold is a time width that can be set arbitrarily, and is a value for determining whether the collection interval is normal. The simplest example is a method in which the collection interval of data defined in the system is used as the threshold. For example, in the case of a system that collects vehicle data every second, if the collection interval is within one second, it can be determined that there is no gap in the collection date and time, and therefore no abnormality such as missing data has occurred. On the other hand, if it exceeds one second, it can be determined that the collection interval has become longer due to some influence. The actual data collection interval often varies due to the operating state of the data collection device and the influence of synchronization, and is not necessarily a constant value. Therefore, by setting the threshold value to a value that allows a certain margin from the specified collection interval, it is possible to reduce erroneous determination that the collection interval has become longer due to some influence.

When the collection interval determination unit 305 determines that the collection interval has increased, the missing change amount calculation unit (change amount calculation unit) 306 calculates the difference in the speed cumulative information (corresponding to the distance traveled) and calculates the amount of change in that value. That is, the missing change amount calculation unit 306 calculates the amount of change in the first cumulative information between two vehicle data items corresponding to a collection interval that is greater than a predetermined time interval. This amount of change will be nearly zero if the data collection device is normal. However, if a problem occurs in the data collection device due to some influence while driving and data is lost, the speed cumulative information after the data loss will have a value that greatly exceeds the speed cumulative information before the data loss. Therefore, the amount of change will be a large value.

The missing change amount determination unit (missing change determination unit) 315 determines whether or not there is missing data due to an abnormality in the data collection device between two vehicle data sets whose collection dates and times are adjacent, based on the amount of change in the first cumulative information between the two vehicle data sets whose collection dates and times are adjacent. "Missing (missing data)" means that vehicle data that should have been collected cannot be collected due to an abnormality in the data collection device. More specifically, the missing change amount determination unit 315 determines whether or not there is missing data based on the collection interval between the collection dates and times between two vehicle data sets whose collection dates and times are adjacent, and the amount of change in the first cumulative information. The missing change amount determination unit 315 also determines whether or not there is missing data based on a comparison between the amount of change in the first cumulative information calculated by the missing change amount calculation unit 306 and a predetermined value. Details of the determination by the missing change amount determination unit 315 will be described later with reference to FIG. 5.

The driving missing information addition unit (information addition unit) 307 adds the information (missing information) calculated by the collection interval determination unit 305 and the missing change amount calculation unit 306 to the input vehicle data to create new vehicle data.

The vehicle data output unit 308 outputs the result of the determination by the missing change amount determination unit 315, as well as the missing information including the amount of change in the first cumulative information between the two vehicle data determined to have missing data, and at least one of the collection intervals of the collection dates and times, so as to display the missing information together with the vehicle data on the train information display device 400. More specifically, the vehicle data output unit 308 outputs the vehicle data to which the missing information has been added.

Next, we will explain the internal configuration of the train information display device 400 shown in Figure 1.

The train information display device 400 includes an analysis data acquisition unit 401, a visualization data calculation unit 402, and a visualization data display unit 403.

The analysis data acquisition unit 401 acquires the necessary analysis data based on the parameters for visualization (period, composition, vehicles, equipment, visualization method, etc.).

The visualization data calculation unit 402 calculates statistics, etc. from the acquired analysis data according to the visualization method.

The visualization data display unit 403 outputs the calculated visualization data to the screen as graphs, etc.

Next, we will explain the processing flow of the train information management device 300.

Figure 4 is a flow diagram showing an example of the operation of the train information management device 300 according to the first embodiment.

First, the collection date and time acquisition unit 301 and the speed accumulation information acquisition unit 302 of the train information management device 300 acquire the collection date and time and the speed accumulation information, respectively, from the vehicle data stored in the vehicle data storage unit 201 (S10, S11). Next, the running missing information calculation unit 303 calculates the running missing information based on the acquired collection date and time and the speed accumulation information (S12). Next, the running missing information calculation unit 303 outputs analysis data in which the running missing information has been added to the vehicle data (S13).

Figure 5 is a flow diagram showing an example of the operation of the running missing information calculation unit 303 according to the first embodiment.

First, the collection interval calculation unit 304 and the missing change amount calculation unit 306 acquire the collection date and time and the speed accumulation information, respectively (S20, S21). Next, the collection interval calculation unit 304 calculates the data collection interval using the collection date and time information (S22). Next, the missing change amount determination unit 315 initializes the missing determination value and the missing change amount to zero (S23, S24).

Next, the collection interval determination unit 305 determines whether the collection interval is greater than a threshold value (S25). Here, the threshold value is set to 10 seconds, but it is not limited to this value and may be set to any value. If the collection interval exceeds the threshold value (Yes in step S25), the missing change amount calculation unit 306 calculates the missing change amount (S26). This missing change amount can be calculated from the difference between the accumulated speed value when the threshold is exceeded and the accumulated speed value one time before. The value of this difference is information equivalent to the traveled distance.

Next, the missing change amount determination unit 315 determines whether the missing change amount calculated in step S26 is greater than a predetermined value (S27). The predetermined value is, for example, zero. If the missing change amount is greater than zero (Yes in step S27), the missing change amount determination unit 315 determines that there is missing data, and sets the missing data determination value to 1 (S28).

If the collection interval is equal to or less than the threshold value (No in step S25), or if the amount of missing data change is equal to or less than zero (No in step S27), the missing data change amount determination unit 315 determines that no data missing has occurred during driving. Then, step S29 is executed. Next, the driving missing data addition unit 307 adds the driving missing data to the vehicle data (S29). The driving missing data includes, for example, the collection interval calculated in step S22, and the missing data determination value and the missing data change amount calculated in steps S23 to S28.

Figure 6 shows an example of the data included in the vehicle data and missing travel information according to the first embodiment.

The data from the collection date and time in the first column to the overhead line voltage in the sixth column represents the original vehicle data, and the data from the collection interval (s) in the seventh column to the missing data determination value in the ninth column represents the missing data information. The collection interval (s) can be measured at about 1 second from the beginning of the data, but an interval of about 47,355 seconds (13 hours) occurs in the middle, and the missing data change amount at the same time is 12,488, and the missing data determination value is 1. Focusing on the collection times on June 2 and June 3, the collection end time on June 2 is 19:27, and the collection start time on June 3 is 8:36, and since the train speed is 0 (m/s) in both cases, it can be seen that the train stopped before and after the interval. At first glance, it appears that the data collection stopped under normal operating conditions, but the change in the accumulated speed value shows that the train ran for more than 12 km during this collection interval. From this, it can be determined that the data during the run that should have been collected was not collected normally, and the data collection device stopped under abnormal operating conditions. This makes it possible to determine whether data is missing while driving and to calculate the distance traveled during the missing period.

The collection interval also becomes larger when the data collection device stops and restarts data collection under normal operating conditions, for example when the vehicle 100 ends operation on one business day and restarts operation on the next business day. However, the distance traveled between the stop and restart of data collection is small, so the amount of missing data change is small. Therefore, it is determined that there is no missing data, and the missing data determination value is zero.

Next, the vehicle data output unit 308 outputs the vehicle data to which the missing driving information has been added (S30). This completes the process flow for calculating missing information. The vehicle data output in step S30 of FIG. 5 is output as analysis data (step S13 of FIG. 4).

Next, the relationship between cumulative information and missing data will be explained with reference to Figures 7 and 8.

Figure 7 is a diagram showing the relationship between the operating state of the vehicle 100 according to the first embodiment, the operating state of the data collection device, and the cumulative speed value. The horizontal axis of the multiple graphs in Figure 7 represents time, and shows the range from June 1st to June 4th.

The graph G1 in the upper part shows the vehicle's power ON and OFF states in time series. The periods T1 to T3 are periods during which the vehicle 100 is in operation, and show continuous data of the collection target under normal conditions. The graph G2 in the middle part shows the data collection device's ON and OFF states in time series. The periods T11 to T13 show periods during which data collection was possible. Here, the data collection device abnormally stopped midway through June 2nd, and then recovered, so some intermediate data is missing. At this time, the time of emergency stop is t _a , and the time of recovery is t _b . The graph G3 in the lower part shows the time series change in the speed accumulation value. The time series change in the accumulation value during the missing period, which is from the abnormal stop of the data collection device to the time of recovery, cannot be measured. However, the accumulated value immediately after recovery is measured on the vehicle side, so it is the speed accumulation value including the running during the missing period.

FIG. 8 is a diagram showing an example of the relationship between the data collection interval and the collected data corresponding to FIG. 7. The horizontal axis of the graph is time information in which the collected data is arranged in chronological order. The upper graph G4 shows the data collection interval, and indicates that data can be collected in a concentrated manner at a certain value (here, 1 second) under normal conditions. On the other hand, the time interval between collected data becomes large at the timing of turning the vehicle power supply OFF and ON and at the timing of emergency stop and recovery of the data collection device, and therefore, the data collection interval becomes a large value exceeding the threshold value at the timing of switching data in the period T11 to T13 including data loss. In this case, by taking the difference between the speed accumulation value at the time t _a of the abnormal stop and the speed accumulation value at the time t _b of recovery, it is possible to calculate the travel distance during the occurrence of the loss and to determine whether the loss occurred during travel.

Next, we will explain the processing flow of the train information display device 400.

Figure 9 is a flow diagram showing an example of the operation of the train information display device 400 according to the first embodiment.

First, the analysis data acquisition unit 401 acquires analysis data from the analysis data storage unit 204 (S40). Next, the visualization data calculation unit 402 calculates visualization data using the acquired analysis data (S41). This visualization data corresponds to, for example, an aggregated value of the distance traveled each day. Next, the visualization data display unit 403 displays the visualization results in a table, graph, or the like based on the information calculated by the visualization data calculation unit 402 (S42).

Figure 10 is a diagram showing an example of the display of the train information display device 400 according to the first embodiment. Figure 10 shows an example of the display of the visualization result of calculating the daily running distance. Figure 10 also shows the daily aggregation result of the missing change amount (missing running distance) and missing determination value in Figure 6.

The visualization result is a table that aggregates the mileage of A-set from June 1 to June 3, 2020, and a bar graph of the aggregated value for each day. In the visualization result (table), the missing judgment is 1 for the mileage of 143 km on June 2, 2020, and the missing mileage is displayed as 47.36 km. It can be seen that the mileage aggregated based on the vehicle data showed a data missing on June 2. For this reason, by linking the missing travel information calculated by the train information management device 300 in the visualization of the vehicle data, it can be treated as one of the indices for measuring the reliability of the display results. For example, the larger the missing judgment and missing mileage values, the lower the reliability. This makes it possible to check the presence or absence of missing data against the aggregated value, for example, when the system automatically calculates the mileage aggregate.

As described above, according to the first embodiment of the train information management device 300, by using the data collection interval calculated from the data collection date and time information and the amount of change in the speed accumulation information corresponding to the traveling distance calculated and stored on board the vehicle, it is possible to calculate the traveling missing information from the vehicle data on the ground side and determine whether the data collection device stopped under an abnormal operating condition or under a normal operating condition. In addition to the determination, it is possible to calculate the traveling distance under an abnormal operating condition. Furthermore, in visualizing the vehicle data, by linking the traveling missing information, it is possible to check the traveling distance summary value together with an index corresponding to the reliability of the presence or absence of missing data. As a result, it is possible to deal with missing data more appropriately.

Whether train vehicle data is collected normally depends on the operating state of the data collection device, and if the operation of the data collection device stops, the data may become partially discontinuous. In other words, the data collection time interval may become exceptionally large. It was difficult to determine from the collected vehicle data whether the cause of the loss of continuity was that data collection stopped under normal operating conditions of the system, or that data loss occurred due to data collection stopping under abnormal operating conditions. If the train information management device 300 was not provided, for example, maintenance personnel had to record data and plan maintenance inspections, relying on the mileage value displayed on the train information display device 400. In addition, when collecting data for visualization or analysis, if data is missing, there was a problem that the calculated value could not be calculated correctly.

In contrast, in the first embodiment, data loss due to an abnormality in the data collection device can be detected and an indicator of data reliability can be presented. For example, when data loss is determined and reliability is low, a maintenance worker can manually check the vehicle data to obtain more accurate calculations of mileage, etc. In addition, the train information management device 300 calculates running loss information from the vehicle data collected by the data collection device. Therefore, there is no need to acquire and analyze new data, and it is relatively easy to determine whether data is missing.

In the first embodiment, the cumulative information used to determine whether data is missing is the cumulative value of train speed (travel distance). However, this is not limited to this, and other data that changes cumulatively among the data collected by the data collection device may be used to determine whether vehicle data is missing.

Second Embodiment
11 is a block diagram showing an example of the overall configuration of a train information system 1 including a train information management device 300 according to a second embodiment. The second embodiment differs from the first embodiment in that cumulative information on air conditioning operation is used to determine whether vehicle data is missing, instead of cumulative information on speed.

The vehicle data acquisition unit 101 according to the second embodiment acquires vehicle data including first cumulative information. The vehicle data acquisition unit 101 also collects vehicle data that further includes second cumulative information of second specified data different from the first specified data. The first cumulative information is used to determine data loss, whereas the second cumulative information is not used to determine data loss, but is visualized and used to determine maintenance, etc. The first cumulative information is, for example, cumulative air conditioning power supply status information of an air conditioning device mounted on the vehicle 100. The air conditioning power supply status cumulative information is, for example, a cumulative value of the operating time of the air conditioning device. The second cumulative information is, for example, a cumulative value of the number of times the compressor of the air conditioning device operates.

The train information management device 300 according to the second embodiment includes an air conditioning power supply status cumulative information acquisition unit 309, an air conditioning CP (compressor) operation count cumulative information acquisition unit 310, and an air conditioning missing information calculation unit 311.

The air conditioning power status cumulative information acquisition unit 309 acquires information indicating the power status of the air conditioners installed on the train (air conditioning power status cumulative information). Here, the target air conditioner is described as one unit, but it is also possible to calculate air conditioning missing information for two or more units. The data acquired for the air conditioning power status is set to 0 for power OFF and 1 for power ON.

The air conditioning CP operation count cumulative information acquisition unit 310 acquires the cumulative value of the number of times the air conditioning compressor has operated.

The air conditioning failure information calculation unit 311 uses the accumulated air conditioning power status information to determine whether a failure occurred when the air conditioner was turned on.

Figure 12 is a block diagram showing an example of the configuration of the air conditioning deficit information calculation unit 311 according to the second embodiment.

Compared to the driving missing information calculation unit 303 according to the first embodiment shown in FIG. 3, the air conditioning missing information calculation unit 311 includes an air conditioning missing information addition unit 312 instead of the driving missing information addition unit 307.

The air conditioning missing information calculation unit 311 acquires air conditioning power state cumulative information, which is the cumulative power state of the air conditioning, and information related to the cumulative value of the number of times the air conditioning CP has operated, from the vehicle data storage unit 201. The air conditioning power state cumulative information and the cumulative number of times the CP has operated are information that is calculated and stored on the vehicle or vehicle equipment side, similar to the speed cumulative value. The air conditioning missing information calculation unit 311 adds information related to missing air conditioning data calculated by the missing change amount calculation unit 306 to the vehicle data and outputs it.

The vehicle data output unit 308 outputs the amount of change in the cumulative air conditioning power supply state information and the amount of change in the cumulative number of CP operations calculated by the missing data change amount calculation unit 306 as missing data. In other words, the vehicle data output unit 308 outputs the missing data, including the amount of change in the second cumulative information between two vehicle data sets determined to have missing data, to be displayed on the train information display device 400 together with the vehicle data.

Next, we will explain the processing flow of the air conditioning loss information calculation unit 311.

Figure 13 is a flow diagram showing an example of the operation of the air conditioning deficit information calculation unit 311 according to the second embodiment.

First, the collection interval calculation unit 304 acquires the collection time, and the missing change amount calculation unit 306 acquires the air conditioning power supply status cumulative information and the air conditioning CP operation count cumulative information (S50, S51, S52). Next, the collection interval calculation unit 304 calculates the data collection interval using the collection date and time information (S53). Next, the missing change amount determination unit 315 initializes the missing determination value and missing change amount to zero (S54, S55).

Next, the collection interval determination unit 305 determines whether the collection interval is greater than the threshold (S56). If the collection interval is greater than the threshold (Yes in step S56), the missing change amount calculation unit 306 calculates the cumulative change amount of the air conditioning power supply state (S57). Next, the missing change amount determination unit 315 determines whether the change amount of the air conditioning power supply state is a predetermined value (for example, 1) or more (S58). Since the air conditioning power supply state is 0 when the power is OFF and 1 when the power is ON, if data missing occurs even though the power of the air conditioner is ON, the cumulative change amount of this air conditioning power supply state will be 1 or more. Therefore, if the cumulative change amount of the air conditioning power supply state is 1 or more (Yes in step S58), the missing change amount calculation unit 306 calculates the operating time of the air conditioner calculated from the cumulative change amount of the air conditioning power supply state and the data collection interval, and the number of operations of the air conditioning CP during the missing period (S59). Next, the missing change amount determination unit 315 sets the missing judgment value to 1 (S60). This makes it possible to calculate the operating time of the air conditioner during the interruption period and the number of times the air conditioner CP operates.

If the collection interval is less than or equal to the threshold value (No in step S56), or if the cumulative change in the air conditioning power state is less than 1 (No in step S58), the missing change amount determination unit 315 determines that no data missing has occurred during driving. Then, step S61 is executed. Next, the driving missing information addition unit 307 adds the air conditioning judgment value and the amount of change calculated in the above process to the vehicle data as air conditioning missing information (S61). Next, the vehicle data output unit 308 outputs the vehicle data (S62).

Figure 14 shows an example of the data included in the vehicle data and air conditioning missing information according to the second embodiment.

The data from the collection date and time in the first column to the cumulative number of air conditioning CP operations in the sixth column represents the original vehicle data, and the data from the collection interval (s) in the seventh column to the missingness determination value in the ninth column represents the air conditioning missingness information. The collection interval (s) can be measured at about 1 second from the beginning of the data, but an interval of about 47,355 seconds (13 hours) occurs in the middle, and it can be seen that the missingness change amount at the same time is 6 and the missingness determination value is 1. Focusing on the collection times on June 2nd and June 3rd, as in the example of running missing information in the first embodiment, the train speed is 0 (m/s) and the data collection seems to have stopped under normal operating conditions at first glance, but when looking at the air conditioning power supply status cumulative information, a difference of 16200 (6663425-6647225) occurs during this collection interval, and it can be seen that the air conditioning CP has operated six times. From this, it can be determined that the data when the air conditioning power supply is ON, which should have been collected, was not collected normally, and the data collection device stopped under abnormal operating conditions. This makes it possible to determine whether data loss occurred when the air conditioning power was turned on, and to calculate the number of times the air conditioning CP operated during the period when data loss occurred.

Figure 15 is a diagram showing the relationship between the operating state of the vehicle 100 according to the second embodiment, the operating state of the data collection device, and the cumulative number of air conditioning CP operations. The horizontal axis of the diagram is time, and shows the range from June 1 to June 4.

The top graph G6 and the middle graph G7 are the same as the example shown in Figure 7. The bottom graph G8 shows the time series change in the accumulated value of the number of air conditioning CP operations. Note that unlike the accumulated mileage value shown in Figure 7, the accumulated value of the number of air conditioning CP operations is counted at the timing when the compressor operates in response to air conditioning control. The accumulated values shown in graph G7 during the abnormal stop and recovery of the data collection device are missing, so the time series change in the accumulated value during the missing period cannot be measured, but because the accumulated value immediately after recovery is measured on the vehicle side, it is possible to calculate the number of air conditioning CP operations during the missing period when the air conditioning power is ON from the amount of change in the accumulated value.

Figure 16 is a diagram showing an example of the display of the train information display device 400 according to the second embodiment. Figure 16 shows an example of the display of the visualization result of tallying up the number of air conditioning CP operations per day. Figure 16 also shows the daily tallying up of the power supply status cumulative change amount, the missing change amount (accumulated air conditioning power supply status information and number of air conditioning CP operations) and the missingness determination value in Figure 14.

The visualization result is a table that tally up the number of air conditioning CP operations for formation A from June 1 to June 3, 2020, and a bar graph of the tally for each day. In the visualization result (table) of the tally up result, it is displayed that there was one missing judgment and five missing air conditioning CP operations for the 26 air conditioning CP operations on June 2, 2020, and it can be confirmed that the number of air conditioning CP operations tallied based on the vehicle data was missing data on June 2. Therefore, by linking the air conditioning missing information calculated by the train information management device 300 in the visualization of the vehicle data, it can be treated as one of the indicators for measuring the reliability of the display results. This makes it possible to check the presence or absence of missing data by checking the tallied value, for example, when the system automatically calculates the number of air conditioning CP operations.

As described above, according to the train information management device 300 of the second embodiment, it is possible to calculate air conditioning omission information by using the data collection interval calculated from the data collection date and time information, the cumulative air conditioning power supply status information calculated and stored on board, and the cumulative number of air conditioning CP operations, and to determine whether the data collection device stopped under abnormal operating conditions or normal operating conditions. In addition to the determination, it is possible to calculate the number of air conditioning CP operations during the period when there was a omission under abnormal operating conditions. Furthermore, by linking the air conditioning omission information in the visualization of vehicle data, it is possible to check the operating time of the air conditioning device during the omission period and the aggregated number of compressor (CP) operations together with an index corresponding to the reliability of the presence or absence of a omission.

The cumulative number of compressor operations is used, for example, to create an inspection plan for the air conditioning device. However, the cumulative number of compressor operations may also be used to determine data loss. That is, the first cumulative information is, for example, the cumulative air conditioning power supply state information of the air conditioning device mounted on the vehicle 100, or the cumulative value of the number of operations of the compressor of the air conditioning device. By using the cumulative number of compressor operations, it is possible to prevent the loss of operation information during the data loss period even if data loss occurs. Note that the compressor operates according to the air conditioning control and the in-vehicle conditions (in-vehicle temperature, in-vehicle humidity, occupancy rate, etc.), so it may not operate for a certain period of time. For this reason, for example, when the data collection interval is large and the cumulative number of compressor operations is zero, it is difficult to determine whether data loss has occurred. Therefore, in order to prevent the compressor operation count from being lost and to determine the occurrence of data loss, it is more preferable to use the amount of change in the cumulative air conditioning power supply state information.

Other configurations of the train information management device 300 according to the second embodiment are similar to the corresponding configurations of the train information management device 300 according to the first embodiment, so detailed descriptions thereof will be omitted. The train information management device 300 according to the second embodiment can obtain the same effects as the first embodiment.

Third Embodiment
17 is a block diagram showing an example of an overall configuration of a train information system 1 including a train information management device 300 according to the third embodiment. The third embodiment is different from the first embodiment in the arrangement of the train information management device 300.

The train information management device 300 is arranged inside the vehicle 100. The train information management device 300 according to the first embodiment calculates the missing running information on the ground side of the train information storage device 200, whereas the train information management device 300 according to the third embodiment calculates the missing running information on the train side.

The train information management device 300 calculates the running missing information on the train in the same manner as in the first embodiment. The train information management device 300 in this embodiment calculates the running missing information on the train in the same manner as in the first embodiment. The train information management device 300 and the data collection device (vehicle data acquisition unit 101) are arranged in the vehicle 100, and the train information management device 300 can directly acquire vehicle data. Therefore, the train information management device 300 acquires the data (collection date and time and accumulated speed value) required by the running missing information calculation unit 303 using the collection date and time acquisition unit 301 and the speed accumulation information acquisition unit 302, and calculates the running missing information. The running missing information is added to the original vehicle data and sent to the vehicle data accumulation unit 201 of the train information accumulation device 200 such as a ground server via the vehicle data transmission unit 102. Therefore, the vehicle data of the vehicle data accumulation unit 201 in this embodiment is data including the running missing information calculated on the train.

In the third embodiment, similarly to the first embodiment, the running distance during the period when the loss occurred can be calculated on-board almost at the same time as determining whether a loss occurred during running. This allows running loss information to be calculated independently on-board in units of the data size sent from the vehicle 100 to the train information storage device 200, without referring to vehicle data stored in a ground-side server or the like. For this reason, in this embodiment, the processing time required for creating analysis data, which was required in the first embodiment, is reduced, and the occurrence of a loss can be detected in a shorter time from the timing when the data loss actually occurred. In addition, the status of the stable operation of the data collection device can be grasped in more real time.

Other configurations of the train information management device 300 according to the third embodiment are similar to the corresponding configurations of the train information management device 300 according to the first embodiment, so detailed descriptions thereof will be omitted. The train information management device 300 according to the third embodiment can obtain the same effects as the first embodiment.

Fourth Embodiment
18 is a block diagram showing an example of an overall configuration of a train information system 1 including a train information management device 300 according to the fourth embodiment. The fourth embodiment differs from the second embodiment in the arrangement of the train information management device 300.

The train information management device 300 is disposed inside the vehicle 100. The train information management device 300 according to the second embodiment calculates the air conditioning deficiency information on the ground side of the train information storage device 200, whereas the train information management device 300 according to the third embodiment calculates the air conditioning deficiency information on the train side.

The train information management device 300 calculates the air conditioning deficiency information on the train in the same manner as in the second embodiment. The train information management device 300 in this embodiment calculates the air conditioning deficiency information on the train in the same manner as in the second embodiment. The train information management device 300 and the data collection device (vehicle data acquisition unit 101) are arranged in the vehicle 100, and the train information management device 300 can directly acquire vehicle data. For this reason, the train information management device 300 acquires the data required by the air conditioning deficiency information calculation unit 311 (collection date and time, air conditioning power supply state cumulative information, and air conditioning CP operation count cumulative information) using the collection date and time acquisition unit 301, the air conditioning power supply state cumulative information acquisition unit 309, and the air conditioning CP operation count cumulative information acquisition unit 310, and calculates the air conditioning deficiency information. The air conditioning deficiency information is added to the original vehicle data and sent to the vehicle data storage unit 201 of the train information storage device 200, such as a ground server, via the vehicle data transmission unit 102. Therefore, in this embodiment, the vehicle data in the vehicle data storage unit 201 is data that includes air conditioning loss information calculated on-board the vehicle.

In the fourth embodiment, similarly to the second embodiment, the number of times the air conditioning CP was operated during the period when the loss occurred can be calculated on-board at almost the same time as determining whether a loss of the air conditioning power ON state has occurred. This allows the air conditioning loss information to be calculated independently on-board in units of the data size sent from the vehicle 100 to the train information storage device 200, without referring to vehicle data stored in a ground-side server or the like. For this reason, in this embodiment, the processing time required for creating the analysis data, which was required in the second embodiment, is reduced, and it is possible to detect the occurrence of a loss of data in a shorter time from the time when the loss actually occurs. In addition, it is possible to grasp the status of the stable operation of data collection in a more real-time manner.

Other configurations of the train information management device 300 according to the fourth embodiment are similar to the corresponding configurations of the train information management device 300 according to the second embodiment, so detailed descriptions thereof will be omitted. The train information management device 300 according to the fourth embodiment can obtain the same effects as the second embodiment.

At least a part of the train information management device 300 according to this embodiment may be configured with hardware or software. When configured with software, a program that realizes at least a part of the functions of the train information management device 300 may be stored in a recording medium such as a flexible disk or CD-ROM, and may be read and executed by a computer. The recording medium is not limited to removable ones such as magnetic disks or optical disks, but may be fixed recording media such as hard disk drives or memories. In addition, a program that realizes at least a part of the functions of the train information management device 300 may be distributed via a communication line (including wireless communication) such as the Internet. Furthermore, the program may be encrypted, modulated, or compressed and distributed via a wired line or wireless line such as the Internet, or stored in a recording medium.

Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are within the scope of the invention and its equivalents as set forth in the claims, as well as the scope and gist of the invention.

100 Vehicle, 101 Vehicle data acquisition unit, 200 Train information storage device, 300 Train information management device, 301 Collection date and time acquisition unit, 302 Accumulated speed information acquisition unit, 303 Running missing information calculation unit, 305 Collection interval determination unit, 306 Missing change amount calculation unit, 307 Running missing information addition unit, 308 Vehicle data output unit, 309 Air conditioning power supply state cumulative information acquisition unit, 310 Air conditioning CP operation count cumulative information acquisition unit, 311 Air conditioning missing information calculation unit, 315 Missing change amount determination unit, 400 Train information display device

Claims (14)

a collection date and time acquisition unit that acquires a collection date and time of a data collection device that collects vehicle data including at least first cumulative information of first predetermined data related to a vehicle in operation;
an accumulated information acquiring unit for acquiring the first accumulated information;
a loss determination unit that determines whether or not there is data loss due to an abnormality in the data collection device between the two vehicle data based on an amount of change in the first cumulative information between the two vehicle data whose collection dates and times are adjacent. The train information management device according to claim 1, wherein the missing data determination unit determines whether or not there is missing data based on the collection interval between the collection dates and times of the two pieces of vehicle data whose collection dates and times are adjacent, and the amount of change in the first cumulative information. a collection interval determination unit that determines whether the collection interval is greater than a predetermined time interval;
a change amount calculation unit that calculates a change amount of the first cumulative information between two of the vehicle data corresponding to the collection interval that is greater than the predetermined time interval,
The train information management device according to claim 2 , wherein the loss determination unit determines whether or not the data is lost based on a comparison between the amount of change in the first cumulative information calculated by the amount of change calculation unit and a predetermined value. The train information management device according to claim 2 or 3, wherein the loss determination unit determines that there is no data loss if the collection interval is equal to or less than a predetermined time interval. The train information management device according to claim 2 or 3, wherein the loss determination unit determines that there is no data loss when the collection interval is greater than a predetermined time interval and the amount of change in the first cumulative information is equal to or less than a predetermined value. The train information management device according to claim 2 or 3, wherein the missing data determination unit determines that there is a data missing data when the collection interval is greater than a predetermined time interval and the amount of change in the first cumulative information is greater than a predetermined value. The train information management device according to any one of claims 1 to 6, further comprising an information adding unit that adds missing information to the vehicle data, the missing information including at least one of the result of the determination by the missing data determining unit, the amount of change in the first cumulative information between the two vehicle data determined to have the missing data, and the collection interval of the collection date and time. The train information management device according to any one of claims 1 to 7, further comprising an output unit that outputs the result of the determination by the missing data determination unit, and missing data including at least one of the amount of change in the first cumulative information between the two vehicle data determined to have missing data, and the collection interval of the collection date and time, so as to display the missing data together with the vehicle data on a display unit. the data collection device collects the vehicle data including second cumulative information of second predetermined data different from the first predetermined data;
The train information management device according to claim 8, wherein the output unit outputs the missing information including the amount of change in the second cumulative information between the two vehicle data determined to have the data missing, so as to display the missing information on a display unit together with the vehicle data. The first cumulative information is cumulative information of an air conditioning power supply state of an air conditioning device mounted in the vehicle,
The train information management device according to claim 9 , wherein the second cumulative information is a cumulative value of the number of operations of a compressor of the air conditioner. The train information management device according to any one of claims 1 to 9, wherein the first cumulative information is a cumulative value of the speed of the vehicle or a travel distance of the vehicle. The train information management device according to any one of claims 1 to 9, wherein the first cumulative information is cumulative information on the air conditioning power supply state of an air conditioning device mounted on the vehicle, or a cumulative value of the number of times a compressor of the air conditioning device operates. The data collection device is disposed in the vehicle;
The train information control device according to claim 1 , wherein the train information control device is arranged on a ground side. The train information management device according to any one of claims 1 to 12, wherein the data collection device and the train information management device are arranged in the vehicle.

Images