JP7543092B2 - Information processing device, article manufacturing method, information processing method, program, and recording medium - Google Patents

Description

The present invention relates to a technology for measuring the state of a mechanical device using a sensor attached to the mechanical device.

In recent years, predictive maintenance has been practiced, in which sensors are used to measure the condition of machinery and equipment incorporated in production facilities, and parts of the machinery are replaced, repaired, or updated depending on the deterioration state of the machinery. Predictive maintenance can reduce unnecessary part replacement and labor costs. In addition, when measuring the condition of machinery and equipment incorporated in production facilities, sensors are installed on the machinery and measurement data is collected, making it possible to detect failures or abnormalities in the machinery at an early stage and diagnose the machinery in detail.

From the viewpoint of energy conservation, it is preferable to start supplying power to the sensor when measurement is required and stop supplying power to the sensor when the measurement is completed. However, immediately after supplying power to the sensor, the sensing data obtained by the sensor sensing fluctuates transiently and is not stable. The sensing data during this transient period lacks accuracy as measurement data. In response to this, Patent Document 1 describes providing a delay time from the start of sensor detection until the output of a signal.

JP 2012-181197 A

Patent Document 1 describes that the delay time can be set by the user by selecting from multiple values that are preset in stages. However, setting the delay time longer than necessary increases the time it takes for power to be supplied to the sensor, leading to increased power consumption in the sensor. The appropriate delay time differs depending on the measurement target, or the type or individual differences of the sensor. With conventional methods, users, designers, workers, and other personnel had to accurately predict the delay time depending on the sensor, which was a heavy workload.

Therefore, the present invention aims to reduce the workload.

A first aspect of the present disclosure is an information processing device that can acquire data from a sensor after a first time has elapsed since executing a process to acquire data from the sensor , and is characterized in that it acquires a second time based on the data from the sensor, and if the first time acquired based on the acquired second time is outside a predetermined range, notifies a user, and if the first time acquired based on the acquired second time is within a predetermined range, automatically sets the first time as information to be used when acquiring data from the sensor .
A second aspect of the present disclosure is an information processing device that can acquire data from a sensor after a first time has elapsed since executing a process to acquire data from the sensor, and is characterized in that the information processing device acquires a second time at which data from the sensor satisfies a convergence condition, acquires a first time that is longer than the second time, and automatically sets the first time as information to be used when acquiring data from the sensor.
A third aspect of the present disclosure is an information processing device capable of acquiring data from a sensor after a first time has elapsed since executing a process to acquire data from the sensor, wherein the first time is automatically set as information to be used when acquiring data from the sensor, and the information processing device is capable of executing a setting mode for setting the first time and a measurement mode for acquiring measurement data for acquiring the state of a mechanical device that is the target of measurement by the sensor based on the data from the sensor, and wherein, in the measurement mode, the information processing device starts supplying power to the sensor at a timing earlier than the scheduled measurement time by the first time set in the setting mode.
A fourth aspect of the present disclosure is an information processing device that can acquire data from a sensor after a first time has elapsed since executing a process to acquire data from the sensor, wherein the first time is automatically set as information to be used when acquiring data from the sensor, the sensor is one of a plurality of sensors, each of the plurality of sensors is included in one of a plurality of groups, and if any of the plurality of groups includes two or more sensors, the first time is set to be the same for the two or more sensors.

A fifth aspect of the present disclosure is an information processing method of an information processing device that can acquire data from a sensor after a first time has elapsed since executing a process to acquire data from the sensor, the information processing method acquiring a second time based on the data from the sensor, notifying a user if the first time acquired based on the acquired second time is outside a predetermined range, and automatically setting the first time as information to be used when acquiring data from the sensor if the first time acquired based on the acquired second time is within a predetermined range .
A sixth aspect of the present disclosure is an information processing method of an information processing device that can acquire data from a sensor after a first time has elapsed since executing a process to acquire data from the sensor, the information processing method comprising: acquiring a second time at which data from the sensor satisfies a convergence condition; acquiring a first time that is longer than the second time; and automatically setting the first time as information to be used when acquiring data from the sensor.
A seventh aspect of the present disclosure is an information processing method of an information processing device that can acquire data from a sensor after a first time has elapsed since executing a process to acquire data from the sensor, wherein the first time is automatically set as information to be used when acquiring data from the sensor, and the information processing method is capable of executing a setting mode for setting the first time and a measurement mode for acquiring measurement data when acquiring the state of a mechanical device that is the target of measurement by the sensor based on the data from the sensor.
An eighth aspect of the present disclosure is an information processing method of an information processing device that can acquire data from a sensor after a first time has elapsed since executing a process to acquire data from the sensor, wherein the first time is automatically set as information to be used when acquiring data from the sensor, the sensor is one of a plurality of sensors, each of the plurality of sensors is included in one of a plurality of groups, and if any of the plurality of groups includes two or more sensors, the first time is set to be the same for the two or more sensors.

The present invention can reduce the workload.

FIG. 1 is a schematic diagram of a production facility according to a first embodiment. FIG. 2 is a block diagram of a monitoring node device according to the first embodiment. 5A and 5B are explanatory diagrams showing an example of a setting table according to the first embodiment. 3 is a flowchart of an information processing method according to the first embodiment. 10A and 10B are diagrams illustrating a convergence determination process in the first embodiment, and FIG. 10C is a diagram illustrating a measurement routine process in the first embodiment. 13 is a flowchart of an information processing method according to a second embodiment. FIG. 13 is an explanatory diagram showing an example of a setting table according to the third embodiment. FIG. 13 is an explanatory diagram of a measurement routine process according to the fourth embodiment. FIG. 13 is an explanatory diagram of a measurement routine process according to the fifth embodiment. 13 is a flowchart of an information processing method according to a sixth embodiment.

The following describes in detail the embodiment of the present invention with reference to the drawings.

[First embodiment]
FIG. 1 is a schematic diagram of a production facility 1000 according to a first embodiment. The production facility 1000 is a facility used to manufacture an item W, and is arranged in a factory or the like. The production facility 1000 includes a machine 101 to be monitored, and a monitoring system 100, which is an example of a system, for monitoring the monitored item. The machine 101 is, for example, a pump. The production facility 1000 including the machine 101 manufactures the item W by a predetermined manufacturing method while monitoring the machine 101 by measuring the state of the machine 101 with the monitoring system 100. The item W may be a finished product or an intermediate product in the middle of production.

The monitoring system 100 is used for preventive maintenance of the machine 101. By monitoring the machine 101 with the monitoring system 100, it is possible to detect failures or abnormalities in the machine 101 at an early stage and perform a detailed diagnosis of the machine 101.

The monitoring system 100 includes at least one sensor used to monitor the machine device 101. In this embodiment, the at least one sensor is a plurality of sensors, for example, two sensors 102 and 103. The monitoring system 100 is also an example of a monitoring device, and includes a monitoring node device 104, which is an example of a node device, a monitoring gateway device 106, which is an example of a gateway device, a database 108, and a terminal 109.

Each of the sensors 102, 103 is a sensor for measuring the state of the mechanical device 101, and is provided on the mechanical device 101. Each of the sensors 102, 103 is a sensor capable of outputting an analog sensing signal that quantifies the state of the mechanical device 101 as a physical quantity, such as a vibration sensor, acceleration sensor, pressure sensor, light sensor, torque sensor, or temperature sensor. For example, a vibration sensor outputs the strength of vibration as a voltage, which is a physical quantity.

The monitoring node device 104 has a terminal unit 105 to which a sensor can be connected. The terminal unit 105 includes multiple, for example, eight channel terminals ch1 to ch8 to which multiple sensors can be connected. In this embodiment, of the multiple channel terminals 1ch to 8ch of the terminal unit 105, a sensor 102 is connected to channel terminal 1ch, and a sensor 103 is connected to another channel terminal 2ch. In the example of FIG. 1, of the multiple channel terminals 1ch to 8ch, no sensors are connected to channel terminals ch3 to ch8 other than channel terminals 1ch and 2ch.

The sensor 102 and the channel terminal 1ch are connected by a cable 121 including, for example, a power line, a ground line, and a signal line. The sensor 103 and the channel terminal 2ch are connected by a cable 122 including, for example, a power line, a ground line, and a signal line.

One or more monitoring node devices 104 are installed in the monitoring system 100 as necessary. In this embodiment, the monitoring system 100 is described as having one monitoring node device 104, but multiple monitoring node devices may be included. For example, the monitoring system 100 may have the same number of monitoring node devices as the number of objects to be monitored. Each monitoring node device 104 is assigned an individual node number.

The monitoring node device 104 has a communication unit 110, and the monitoring gateway device 106 has a communication unit 111. These communication units 110, 111 enable the monitoring node device 104 and the monitoring gateway device 106 to communicate with each other. The monitoring node device 104 is capable of outputting, i.e. transmitting, measurement data to the monitoring gateway device 106 via wireless communication or wired communication. The monitoring gateway device 106 can collect information from the monitoring node device 104.

The communication method of the communication units 110 and 111 may be wireless communication such as LPWA (Low Power Wide Area) or wireless LAN, or may be wired communication such as Ethernet (registered trademark) or field network. The communication units 110 and 111 may have both wireless communication and wired communication functions and selectively execute either of the wireless communication and wired communication methods. In the first embodiment, the communication units 110 and 111 have both wireless communication and wired communication functions and are configured to selectively execute either of the wireless communication and wired communication methods.

The monitoring gateway device 106 is set within a range where it can communicate with the monitoring node device 104. Measurement data generated by the monitoring node device 104 is collected in the monitoring gateway device 106 by the communication units 110 and 111.

The monitoring gateway device 106, database 108, and terminal 109 are connected to a network 107. The network 107 may be a dedicated network within a factory or a wide area network such as the Internet. The measurement data collected by the monitoring gateway device 106 is stored in the database 108, which is an example of a data storage device, via the network 107. The terminal 109 is a computer equipped with a display. The terminal 109 may also be equipped with a speaker, if necessary.

The monitoring gateway device 106 may be implemented in the database 108 or the terminal 109 as software processing in the database 108 or the terminal 109. The database 108 may be either a storage device or a storage medium. The terminal 109 may be configured to allow the results stored in the database 108 to be checked by a user's operation. The terminal 109 may be configured to notify the user, if necessary, by a notification means such as an alert or email transmission, when an abnormality occurs in the mechanical device 101.

Figure 2 is a block diagram of the monitoring node device 104 according to the first embodiment. In the first embodiment, the monitoring node device 104 is an information processing device, i.e., a computer. The monitoring node device 104 includes a terminal unit 105, a trigger generating unit 202, a power supply unit 204, a signal input unit 205 which is an example of an AD conversion unit, a signal processing unit 206 which is an example of a processing unit, an output unit 207, and a memory unit 210. These are connected by a bus 220. The memory unit 210 is, for example, a storage device such as an HDD or SSD.

A battery 203 is connected to the power supply unit 204. The power supply unit 204 controls the supply of power from the battery 203 to each unit of the monitoring node device 104 and the sensors 102, 103. The battery 203 may be built into the monitoring node device 104 or may be detachable from the monitoring node device 104. The battery 203 may also be external to the monitoring node device 104. The power supply unit 204 supplies power to each sensor 102, 103 at any timing determined by a program. When power is supplied to each sensor 102, 103, it becomes possible to perform sensing, and outputs an analog signal, such as a voltage, which is a sensing signal obtained by sensing.

The signal input unit 205 is configured to receive an analog signal, for example an output voltage, from each sensor 102, 103, and perform analog-to-digital conversion processing, i.e., AD conversion processing, to convert the analog signal into a digital signal. The signal input unit 205 may be built into each sensor 102, 103. As the AD conversion processing, the analog signal acquired from a specified channel terminal is sampled at a specified sampling frequency and a specified number of samples, and sensing data, which is a digital signal, is generated.

The signal processing unit 206 also serves as a control unit that comprehensively controls the trigger generating unit 202, the power supply unit 204, the signal input unit 205, the output unit 207, and the memory unit 210. The signal processing unit 206 is composed of, for example, a CPU, and can execute various processes by executing a control program 230 stored in the memory unit 210.

The signal processing unit 206 can measure the state of the mechanical device 101 using each sensor 102, 103 by executing a measurement task. The measurement task includes an AD conversion processing task that causes the signal input unit 205 to perform AD conversion, a signal processing task that processes the digital signal generated by the signal input unit 205 to generate measurement data, and an output processing task that causes the output unit 207 to output the measurement data. The signal processing that processes digital signals is data processing that processes sensing data.

Signal processing, i.e., data processing, includes multiple processing operations. Specific examples of multiple processing operations are described below, but are not limited to the following processing operations. In addition, the signal processing unit 206 may have all the functions of the multiple processing operations shown below, or may have only the necessary functions.

Signal processing includes, for example, relay processing, delay timer calculation processing, FFT processing, partial overall processing, envelope processing, frequency filter processing, differentiation processing, integration processing, wavelet processing, average value processing, standard deviation processing, maximum value processing, and minimum value processing. Signal processing also includes, for example, peak-to-peak processing, peak hold processing, effective value processing, crest factor processing, waveform factor processing, impulse coefficient processing, margin coefficient processing, and machine learning model inference processing. The signal processing unit 206 executes a processing content selected from these multiple processing contents. When two or more processing contents are selected, the signal processing unit 206 executes the two or more selected processing contents in a specified order.

The content of each process is explained below. Relay processing is a process of passing the input digital signal to the output unit 207 as it is. Delay timer calculation processing is a process of judging the convergence of sensing data, calculating the convergence time, and multiplying it by a safety factor to calculate a delay timer value. FFT processing is a process of decomposing the input digital signal into frequency components. Partial overall processing is a process of limiting the frequency range of the FFT-processed frequency components to obtain a product sum. Envelope processing is a process of performing envelope processing on the input digital signal. Frequency filter processing is a process of removing unnecessary signal components by setting a frequency for the input digital signal and passing it through a low-pass filter, a high-pass filter, or a band-pass filter. Differentiation processing is a process of differentiating the input digital signal. Integration processing is a process of integrating the input digital signal. Wavelet processing is a process of decomposing the input digital signal into frequency components and time components. Average value processing is a process of obtaining an average value for the input digital signal. The standard deviation processing is a process for obtaining a standard deviation of an input digital signal. The maximum value processing is a process for obtaining a maximum value for an input digital signal. The minimum value processing is a process for obtaining a minimum value for an input digital signal. The peak-to-peak processing is a process for obtaining a difference between a maximum value and a minimum value for an input digital signal. The peak hold processing is a process for obtaining a maximum value from an input digital signal within a predetermined period. The effective value processing is a process for obtaining an effective value for an input digital signal. The crest factor processing is a process for obtaining a crest factor by dividing the maximum value of an input digital signal by the effective value. The form factor processing is a process for obtaining a form factor by dividing the effective value of an input digital signal by its average value. The impulse coefficient processing is a process for obtaining an impulse coefficient by dividing the maximum value of an input digital signal by the average value of the absolute values of the digital signal. The margin coefficient processing is a process for obtaining a margin coefficient by dividing the maximum value of an input digital signal by the square of the average value of the square root of the digital signal. The machine learning model inference process is a process that determines an output based on an input digital signal and a machine learning model. The machine learning model is generated by loading learning data into a computer, having the computer analyze the data, and defining rules for classification and identification. The generated machine learning model is incorporated in advance into the monitoring node device 104.

As described above, the signal processing unit 206 can perform signal processing of the selected processing content on the digital signal to generate measurement data.

The output unit 207 is a device capable of performing output processing to output the measurement data generated by the signal processing unit 206. That is, the output unit 207 is capable of outputting the measurement data by executing output processing. The output unit 207 includes a communication unit 110 and a general-purpose input/output unit 212. The communication unit 110 includes a communication module 208 that performs wireless communication and a communication module 209 that performs wired communication. The communication module 208 can output the measurement data wirelessly. In this case, the monitoring gateway device 106 will acquire the measurement data from the monitoring node device 104 as radio waves. The communication module 209 can output the measurement data to the network 107. In this case, the monitoring gateway device 106 will acquire the measurement data from the monitoring node device 104 via the network 107.

The output unit 207 is configured to be capable of inputting and outputting signals, but it is sufficient that it is configured to be capable of at least outputting measurement data. In addition, depending on the communication method adopted by the monitoring system 100, either the communication module 208 or the communication module 209 may be omitted in the output unit 207.

The output unit 207 can also output the measurement data to the storage unit 210. The output unit 207 can also output the measurement data to an external device (e.g., external storage) connected to the general-purpose input/output unit 212. As an output process, the output unit 207 outputs node number information for identifying an individual monitoring node device 104 and task number information of a measurement task executed by the signal processing unit 206 together with the measurement data. For example, the output unit 207 outputs the node number information, task number information, and measurement data to the monitoring gateway device 106 in this order by wireless communication or wired communication.

When an event occurs, the trigger generating unit 202 causes the signal processing unit 206 to generate a trigger signal. That is, when an event occurs, the trigger generating unit 202 outputs a trigger signal corresponding to the event that has occurred. The trigger signal includes task number information.

Here, "an event occurs" means that a condition for starting measurement is satisfied. Hereinafter, this condition is referred to as an event condition. In this embodiment, the condition for starting measurement, i.e., the event condition, is set in the trigger generating unit 202 by the signal processing unit 206. Also, the event condition set by the signal processing unit 206 may be only one or may be multiple. When multiple event conditions are set in the trigger generating unit 202 by the signal processing unit 206, the trigger generating unit 202 outputs trigger signals corresponding to the event conditions that have been satisfied among the multiple event conditions to the signal processing unit 206 in the order in which they were satisfied.

Event conditions that can be set by the signal processing unit 206 include time conditions such as a measurement time interval or a measurement start time. In this embodiment, the event conditions that can be set by the signal processing unit 206 also include conditions other than time conditions. Examples of conditions other than time conditions include an external trigger input signal, a state change of the monitoring node device, a call from another task in the monitoring node, a call from a monitoring gateway device, and a call from another monitoring node device.

If the event condition is a measurement time interval, an event occurs at a predetermined fixed time interval. If the event condition is a measurement time, an event occurs at a predetermined time, and if a day of the week is also specified, an event occurs at the predetermined day of the week. If the event condition is an external trigger input signal, an event occurs when a signal change occurs in the general-purpose input/output unit 212. If the event condition is a change in the state of the monitoring node device, an event occurs when there is a change in the remaining battery level of the monitoring node device or a change in the temperature sensor in the monitoring node device. If the event condition is a call from another task in the monitoring node, an event occurs when the device is called from the output condition of another task other than the measurement task in the same monitoring node device. If the event condition is a call from a monitoring gateway device, an event occurs when a task execution command is received from the monitoring gateway device. If the event condition is a call from another monitoring node device, an event occurs when the device is called by the output process of the other monitoring node device.

The process contents of the AD conversion process of the signal input unit 205, the signal process of the signal processing unit 206, and the output process of the output unit 207, which are associated with each of the multiple event conditions, are recorded as measurement tasks in the task table 240. The task table 240 is stored in, for example, the storage unit 210. The signal processing unit 206 refers to the task table 240 and performs measurements using sensors specified in the measurement tasks defined in the task table 240. The storage location of the task table 240 is preferably the storage unit 210 inside the monitoring node device 104, but is not limited to this. For example, the task table 240 may be stored in an external storage device outside the monitoring node device 104. The information in the task table 240 is set by a person such as an operator or user.

The signal processing unit 206 has a timer 216 as an example of a timekeeping unit. The signal processing unit 206 can measure time using the timer 216. Note that although the description has been given of a case in which the timer 216 is provided within the signal processing unit 206, this is not limiting. The timer 216 may be provided anywhere within the monitoring node device 104.

The storage unit 210 also stores a setting table 250 that is used when the signal processing unit 206 executes a measurement task. In the first embodiment, the signal processing unit 206 can alternatively execute a measurement mode in which measurement data is generated according to a measurement task, and a setting mode in which a setting process is executed in which information is set in the setting table 250. The storage location of the setting table 250 is preferably the storage unit 210 inside the monitoring node device 104, but is not limited to this. For example, the setting table 250 may be stored in an external storage device outside the monitoring node device 104.

An external device can be connected to the general-purpose input/output unit 212. As an example of an external device, a recording medium 214 on which a control program 230 is recorded can be connected to the general-purpose input/output unit 212. The recording medium 214 is a computer-readable non-transitory recording medium on which the control program 230 is recorded. The control program 230 recorded on the recording medium 214 can be stored in the storage unit 210 via the general-purpose input/output unit 212. The recording medium 214 may be a recording disk such as a magnetic disk or optical disk (e.g., a CD-ROM or a DVD-ROM), or may be a storage device such as a flash memory (e.g., an SD card).

In the measurement mode, the monitoring node device 104 stops supplying power to the sensor 102 or 103 until an event occurs. When an event occurs, the monitoring node device 104 starts supplying power to the corresponding sensor out of the sensors 102 and 103, and performs measurement. For example, if the sensor for which the event condition is met is sensor 102, the monitoring node device 104 starts supplying power to sensor 102 and performs measurement using sensor 102. In this way, it is possible to suppress a decrease in capacity of the battery 203. The same applies to the sensor 103.

When power supply to the sensor 102 is started, the sensing data obtained by the sensing of the sensor 102 is not stable immediately after power supply to the sensor 102 because it fluctuates transiently. Measurement data using the sensing data during this transient period lacks accuracy. Therefore, in this embodiment, the signal processing unit 206 is configured to be able to generate measurement data using sensing data obtained after power supply to the sensor 102 is started, that is, sensing data obtained after a predetermined time T1 has elapsed since power supply to the sensor 102 is started.

Time T1 is the first time. This time T1 is also called a delay time or a standby time. That is, in the first embodiment, power supply to the sensor 102 is started when the event condition is met, and measurement using the sensor 102 is started when the output voltage of the sensor 102 is stabilized. Time T1 can also be called a delay time because the measurement start time is delayed from the time when the event condition is met. Time T1 can also be called a standby time because measurement is waited from the time when the event condition is met until the output voltage of the sensor 102 is stabilized. Information on this time T1 is registered in the setting table 250.

In the first embodiment, in the measurement mode, the signal input unit 205 does not perform AD conversion processing during time T1 even if an analog signal is input from the sensor 102. Therefore, the signal processing unit 206 does not perform signal processing during time T1. Then, the signal processing unit 206 converts the analog signal into a digital signal, i.e., sensing data, from the point in time T1. The signal processing unit 206 performs signal processing of the selected processing content on the sensing data acquired from the signal input unit 205 to generate measurement data. Note that when the processing content of the signal processing is relay processing, the sensing data after time T1 is output to the output unit 207 as is, and is therefore the same as the measurement data. In other words, even if there is no change in content between the sensing data and the measurement data, the relay processing is included in the processing for generating the measurement data.

In consideration of the processing load on the signal input unit 205, it is preferable that the signal input unit 205 does not perform processing during the count period of time T1 in the measurement mode, but this is not limited to this. In other words, the signal input unit 205 may generate sensing data even during the count period of time T1 that is not used as measurement data.

Here, the time T1 to be set differs depending on the type of sensor and the object being measured by the sensor. For this reason, it is difficult for a person to set an appropriate time T1. If the time T1 is set too short, the measurement data will be unstable. Also, if the time T1 is set too long, delays in the timing of starting measurement and unnecessary power consumption will occur.

In the first embodiment, the signal processing unit 206 is configured to be able to execute a setting process to automatically set the time T1. That is, in the setting mode, the signal processing unit 206 executes a setting process to automatically set the time T1. In this embodiment, since at least one sensor is a plurality of sensors 102, 103, the signal processing unit 206 automatically sets the time T1 individually for each of the plurality of sensors 102, 103.

FIGS. 3(a) and 3(b) are explanatory diagrams showing an example of a setting table 250 stored in the storage unit 210 according to the first embodiment. FIG. 3(a) illustrates the setting table 250 before the information on time T1 is set (registered). FIG. 3(b) illustrates the setting table 250 after the information on time T1 is set (registered).

The setting table 250 includes an item 302 in which the channel number assigned to each channel terminal in the terminal unit 105 is set, and an item 303 in which information on the operating voltage applied to each sensor is set. The setting table 250 also includes an item 304 in which a coefficient for calculating each time T1 is set, and an item 305 in which a threshold value used to determine the convergence of the output voltage of each sensor is set. The setting table 250 also includes an item 306 in which information on each time T1 obtained by the signal processing unit 206 is set. In the setting table 250 shown in FIG. 3(a), before the information on time T1 is set, the item 303 in which the information on time T1 is set is blank. In addition, the items 302 to 306 are also blank for channels to which no sensor is connected. The information in the items 302 to 305 is set manually. Here, in the example shown in Figures 3(a) and 3(b), channel number 1 corresponds to channel terminal ch1, i.e., sensor 102, and channel number 2 corresponds to channel terminal ch2, i.e., sensor 103.

In the following, an example will be described in which the sensor for which the event condition is met in the measurement mode is sensor 102. In the measurement mode, the signal processing unit 206 uses the setting table 250 in which the time T1 shown in FIG. 3B has already been set. The sensor 102 is connected to channel terminal 1ch. In the measurement mode, the signal processing unit 206 refers to the setting table 250, and controls the power supply unit 204 and the signal input unit 205 using information corresponding to the sensor 102 for which the event condition is met. For example, the signal processing unit 206 refers to the setting table 250 and supplies a sensor voltage of 3.3V to the channel terminal 1ch to which the sensor 102 is connected.

The signal processing unit 206 starts timing using the timer 216 when power supply to the sensor 102 starts. When the time measured by the timer 216 reaches time T1, i.e., 150 msec, the signal processing unit 206 commands the signal input unit 205 to set the sampling frequency and the number of samples, etc. The measurement time is determined by the sampling frequency and the number of samples. The signal processing unit 206 acquires the sensing data sampled by the signal input unit 205 from the signal input unit 205. In this way, the signal processing unit 206 waits until time T1 has elapsed since starting power supply to the sensor 102, and then starts measurement.

On the other hand, in the setting mode, the signal processing unit 206 instructs the signal input unit 205 on the sampling frequency and the number of samples from the timing when power supply to the sensor 102 is started, and acquires sensing data from the signal input unit 205. The signal processing unit 206 derives time T1 from the acquired sensing data using the coefficient set in item 304 and the threshold value set in item 305, and sets the information on time T1 in item 306 of the setting table 250 in FIG. 3(a).

The following describes in detail the setting process in which the signal processing unit 206 sets information on the time T1 for the sensor 102. The setting process for the time T1 for the sensor 103 is similar to the setting process for the time T1 for the sensor 102, and therefore the description is omitted. Note that if both setting processes for the sensors 102 and 103 can be executed simultaneously, they may be executed simultaneously, or the setting process for one sensor may be executed first, followed by the setting process for the other sensor in sequence.

Figure 4 is a flowchart of the information processing method according to the first embodiment. That is, Figure 4 is a flowchart of the processing after the monitoring node device 104 is started. Here, "starting up" refers to the start of supplying power from the battery 203 to each part of the monitoring node device 104. For example, "starting up" refers to the case where a power switch (not shown) of the monitoring node device 104 is turned on. Also, "starting up" refers to the case where, if the monitoring node device 104 has a reset switch (not shown), the reset switch (not shown) is turned on. In other words, starting up includes restarting.

First, in step S1, the power switch is turned on and the monitoring node device 104 is started. In step S2, the signal processing unit 206 executes a predetermined node startup process. For example, the information stored in the memory unit 210 is expanded in a RAM (not shown). After that, the signal processing unit 206 executes a setting process 401 in the setting mode. In this setting process 401, the signal processing unit 206 calculates the time T1 using sensing data after power supply to the sensor 102 starts. The sensing data used in the setting process 401 of the first embodiment is not data for calculating measurement data, but data for deriving the time T1.

The setting process 401 is executed in a state where there is no change in the measurement environment of the sensor 102 in the mechanical device 101, or where it can be assumed that there is no change. For example, if the sensor 102 is a temperature sensor, the setting process 401 is executed in a state where there is no change in temperature, or where it can be assumed that there is no change in temperature. This is because if the sensing data changes depending on the environment, it becomes difficult to determine convergence.

The setting process 401 will be described in detail below. In step S3, the signal processing unit 206 starts supplying power to the sensor 102 connected to the channel terminal ch1. In step S4, the signal processing unit 206 instructs the signal input unit 205 of the sampling frequency and the number of samples to perform AD conversion processing. The start timing of the process of step S4 is simultaneous with the process of step S3, i.e., the same timing as when power supply to the sensor 102 is started. In step S4, the signal processing unit 206 sequentially acquires sensing data of the specified number of samples from the signal input unit 205 after starting power supply to the sensor 102.

Next, in step S5, the signal processing unit 206 uses these sensing data to calculate the convergence time T2. Time T2 is the second time. Figures 5(a) and 5(b) are explanatory diagrams of the convergence determination process in the first embodiment. Note that the analog signal output from the sensor 102 is, for example, a voltage, and a digital output voltage value can be obtained by AD converting this output voltage. Therefore, the vertical axis of Figure 5(a) is the voltage value. The horizontal axis is the elapsed time.

In step S5, the signal processing unit 206 performs low-pass filtering on the sensing data obtained in step S4 to generate sensing data 501 that has been subjected to low-pass filtering, as shown in FIG. 5(a). The cutoff frequency of this low-pass filtering is, for example, 100 Hz. As a result, noise components (high-frequency fluctuation components) that are unnecessary for judgment are removed from the sensing data 501, and the sensing data 501 has a smooth profile over time. Therefore, by using the sensing data 501 that has been subjected to low-pass filtering, convergence judgment becomes easier. In other words, the variation in the calculation results in the calculation process for convergence judgment can be reduced. Note that, although it is preferable to perform low-pass filtering in the setting process 401, when the fluctuation components of the sensing data are small, that is, when there is no problem with the convergence judgment, low-pass filtering may be omitted.

As shown in FIG. 5(a), the sensing data 501 changes over time from a state in which it fluctuates due to a transient response to a state in which the fluctuations converge. Below, the convergence timing 504 is found based on the transient response of the sensing data 501 that has been subjected to low-pass filter processing.

That is, the signal processing unit 206 obtains the time T2, which is the convergence time at which the sensing data 501 satisfies the convergence condition. A specific example will be given. The signal processing unit 206 calculates the feature amount 502 for each predetermined period from the sensing data 501. In FIG. 5B, the vertical axis indicates the feature amount, and the horizontal axis indicates the elapsed time. The feature amount 502 is, for example, the first-order time differential value of the sensing data 501, that is, the gradient of the sensing data 501. The signal processing unit 206 compares the feature amount 502 with a threshold value 503 to obtain the timing 504 at which the feature amount 502 falls below the threshold value 503. The information on the threshold value 503 uses the threshold value set in the item 304 shown in FIG. 3A. In the case of the sensor 102, the threshold value is 0.03 in the example of FIG. 3A.

The timing 504 may be the point in time when multiple feature quantities 502 fall below a threshold value consecutively. Although the feature quantity 502 is a first-order time differential value, this is not limiting and may be, for example, a variance value or other value. Depending on the method of calculating the feature quantity, the timing 504 may be the point in time when the feature quantity 502 exceeds a threshold value.

Next, the signal processing unit 206 calculates the time from when power supply to the sensor 102 starts to the timing 504 as the convergence time, i.e., time T2. Thus, in step S5, the signal processing unit 206 determines the time T2 at which the sensing data 501 satisfies the convergence condition.

Next, in step S6, the signal processing unit 206 obtains information on time T1 from information on time T2. When time T1 has elapsed since power supply to the sensor 102 began, the sensing data is stable, so time T1 may be set to the same time as time T2. However, to further ensure the stability of the sensing data, it is preferable to set time T1 to a time longer than time T2. Therefore, in the first embodiment, in step S6, the signal processing unit 206 obtains time T1 to be longer than time T2.

In the first embodiment, as shown in FIG. 3(a), a coefficient is set in item 304. In the case of sensor 102, the coefficient is 1.2 in the example of FIG. 3. The coefficient is preferably greater than 1. The signal processing unit 206 obtains time T1 by multiplying time T2 by a coefficient (e.g., 1.2) that is preregistered in the setting table 250. As a result, time T1 becomes longer than time T2.

Next, in step S7, the signal processing unit 206 sets the obtained time T1. To explain this with a specific example, the signal processing unit 206 sets (registers) the information of the obtained time T1 in the setting table 250. In the example shown in FIG. 3(b), 150 msec is registered as the information of the time T1.

The above describes the case where the signal processing unit 206 sets the time T1 corresponding to the sensor 102, but the same is also set for the sensor 103. That is, in the first embodiment, the signal processing unit 206 sets the time T1 individually for each of the multiple sensors 102 and 103.

When the above setting process is completed, in step S8, the signal processing unit 206 transitions from the setting mode to the measurement mode and starts the measurement routine process 402. The measurement routine process is a measurement process in which a measurement is performed using a sensor. The measurement routine process 402 will be described in detail. FIG. 5(c) is an explanatory diagram of the measurement routine process in the first embodiment. Note that the analog signal that is the output of the sensor 102 is, for example, a voltage, and a digital output voltage value can be obtained by AD converting this output voltage. Therefore, the vertical axis of FIG. 5(c) is the voltage value. The horizontal axis is the elapsed time.

When the event condition for measurement using the sensor 102 is satisfied, the signal processing unit 206 causes the power supply unit 204 to supply power to the sensor 102 and starts timing. Then, the signal processing unit 206 performs measurement from the point when the set time T1 has elapsed to the preset measurement time T3. That is, the signal processing unit 206 causes the signal input unit 205 to perform AD conversion processing, and acquires sensing data 505 from the signal input unit 205 after the point when time T1 has elapsed over the measurement time T3. The measurement time T3 is determined by the sampling frequency and the number of samples. That is, the signal processing unit 206 instructs the signal input unit 205 to have the sampling frequency and the number of samples when time T1 has elapsed. As a result, the signal input unit 205 outputs sensing data 505 of the instructed number of samples at the instructed sampling frequency to the signal processing unit 206.

After the measurement time T3 has elapsed, the signal processing unit 206 causes the power supply unit 204 to stop supplying power to the sensor 102. The signal processing unit 206 performs signal processing, such as average value processing, on the sensing data 505 to generate measurement data 506. The measurement data 506 is output by the output unit 207 in FIG. 2 to the monitoring gateway device 106 in FIG. 1.

In the first embodiment, the signal processing unit 206 executes the setting process 401 shown in FIG. 4 at the time of starting the monitoring node device 104 each time the monitoring node device 104 is started. Therefore, in the setting process 401, if the time T1 has already been set for the sensor, the signal processing unit 206 resets the time T1. For example, when a new sensor is added in addition to the sensors 102 and 103, the time T1 is already set for the sensors 102 and 103 at this point, and the time T1 is not set for the new sensor. By starting the monitoring node device 104 in this state, the time T1 is reset for the sensors 102 and 103, and the time T1 is newly set for the new sensor. The same applies when the sensor 102 is replaced with a new sensor. That is, the signal processing unit 206 executes the setting process 401 at the time of starting the monitoring node device 104, thereby setting or resetting the time T1 for each of the multiple sensors connected to the monitoring node device 104 at the time of starting the monitoring node device 104. In this way, the setting process 401 is executed each time the monitoring node device 104 is started, making it easy to add, replace, or change sensors.

In addition, when the monitoring node device 104 is started, i.e., when the power supply of the monitoring node device 104 is turned on, all information in item 306 in the setting table 250 may be erased. In other words, instead of overwriting and saving the information in item 306, it may be erased once and then newly written.

As described above, according to the first embodiment, the signal processing unit 206 automatically sets the time T1, so that the time T1 can be set autonomously without a person being aware of it. In addition, since the signal processing unit 206 automatically sets the time T1, the workload of the person is significantly reduced compared to when a person manually sets the time T1. In other words, if a person tries to set the time T1 accurately, it is necessary to carry out experiments and analyses, which imposes a large workload on the person, but this workload can be reduced. And stable measurement data 506 can be obtained.

In addition, the set time T1 is optimized, and the amount of power consumption in the monitoring node device 104 can be reduced. In other words, the capacity reduction in the battery 203 can be suppressed.

[Second embodiment]
An information processing method according to the second embodiment will be described. In the second embodiment, the overall configuration of the production facility is similar to the overall configuration of the production facility 1000 according to the first embodiment, and the description will be omitted. In the second embodiment, a part of the information processing method is different from that in the first embodiment.

That is, in the first embodiment, a case was described in which time T1 is set or reset for all sensors connected to the monitoring node device 104 when the monitoring node device 104 is started up. In the second embodiment, a case is described in which time T1 is set only for sensors for which time T1 has not been set when the monitoring node device 104 is started up. Below, the differences between the second embodiment and the first embodiment will be described in detail, and the same parts will not be described.

Figure 6 is a flowchart of the information processing method according to the second embodiment. That is, Figure 6 is a flowchart of the processing after the monitoring node device 104 is started.

First, in step S61, the power switch is turned on and the monitoring node device 104 starts up. In step S62, the signal processing unit 206 executes a predetermined node startup process.

Then, in step S63, the signal processing unit 206 reads the setting table 250 from the memory unit 210. As a result, the signal processing unit 206 obtains information on the channel number and time T1 for the sensor performing the measurement.

In step S64, the signal processing unit 206 determines whether or not information on time T1 is set for each of the sensors 102 and 103 connected to the monitoring node device 104. That is, the signal processing unit 206 determines whether or not information on time T1 corresponding to each of the sensors 102 and 103 is registered in the setting table 250.

If the time T1 information has not been set for either of the sensors 102 and 103 (S64: YES), the setting process 401 is executed in the setting mode of step S65. If the time T1 information has already been set for both sensors (S64: NO), the process of step S65 is skipped. That is, the signal processing unit 206 executes the setting process 401 when the time T1 has not been set for either of the sensors 102 and 103.

For example, if the time T1 information has already been set for both sensors 102 and 103, the signal processing unit 206 skips the process of step S65. If the time T1 information has not been set for sensor 102 and the time T1 information has already been set for sensor 103, the signal processing unit 206 sets the time T1 information only for sensor 102 in step S65. If the time T1 information has not been set for both sensors 102 and 103, the signal processing unit 206 sets the time T1 information for both sensors 102 and 103 in step S65.

In the measurement mode of step S66, the signal processing unit 206 executes the measurement routine processing 402.

As described above, in the second embodiment, when the setting process 401 is executed, information on time T1 is registered in the setting table 250, and the information on time T1 is retained even if the power supply of the monitoring node device 104 is turned off. Then, the signal processing unit 206 automatically sets time T1 only if there is no information on time T1 the next time the monitoring node device 104 is started up. This makes it possible to further reduce the amount of power consumed by the monitoring node device 104, thereby achieving further energy savings.

[Third embodiment]
An information processing method according to the third embodiment will be described. In the third embodiment, the overall configuration of the production facility is similar to the overall configuration of the production facility 1000 according to the first embodiment, and the description will be omitted. In the third embodiment, a part of the information processing method is different from that in the first embodiment.

First, in the first embodiment, it is possible for only one sensor or multiple sensors to be connected to the monitoring node device 104, but in the third embodiment, it is assumed that multiple sensors are connected to the monitoring node device 104.

In the first embodiment, a case was described in which, when multiple sensors are connected to the monitoring node device 104, time T1 is set individually for each sensor. In the third embodiment, a case is described in which time T1 is set for each group, and the same time is set as time T1 for sensors belonging to a certain group. Below, the third embodiment will be described in detail with respect to the differences from the first embodiment, and a description of the similarities will be omitted.

In FIG. 1, an example will be described in which four sensors (not shown) are connected to the four channel terminals ch1 to ch4 of the terminal unit 105. FIG. 7 is an explanatory diagram showing an example of a setting table 250B according to the third embodiment. In the third embodiment, the setting table 250B shown in FIG. 7 is stored in the memory unit 210 instead of the setting table 250 shown in FIG. 2.

The setting table 250B includes an item 702 in which the channel number assigned to each channel terminal in the terminal unit 105 is set. The setting table 250B also includes an item 703 in which information on the model number of each sensor is set. The setting table 250B also includes an item 704 in which information on the operating voltage applied to each sensor is set. The setting table 250B also includes an item 705 in which a coefficient for calculating each time T1 is set, and an item 706 in which a threshold value used to determine the convergence of the output voltage of each sensor is set. The setting table 250B also includes an item 707 in which information on the time T1', which is the provisional first time obtained corresponding to each sensor, is set. The setting table 250B also includes an item 708 in which information on the group number to which each sensor belongs is set. The setting table 250B also includes an item 709 in which information on the time T1, which is the first time obtained corresponding to each sensor, is set. In addition, in the setting table 250B shown in FIG. 7, items 707 to 709 are blank before the setting process is executed. The information in items 702 to 706 is set manually.

The following is a specific description of the setting process executed by the signal processing unit 206 in the setting mode of the third embodiment. Note that in the setting table 250B shown in FIG. 7, items 707 to 709 are assumed to be blank before setting, and the signal processing unit 206 will be assumed to set these automatically.

When the monitoring node device 104 is started, the signal processing unit 206 performs grouping of multiple sensors based on the information already set in the setting table 250B. For example, the signal processing unit 206 performs grouping by referring to the model number item 703 or the operating voltage item 704. The signal processing unit 206 registers the group number assigned to each sensor as a result of grouping in item 708.

Here, an example of a grouping method will be explained. Channel numbers 1 to 3 have the same model number "XX-YY-00", while channel number 4 has a model number "AA-BB-11", which is different from channel numbers 1 to 3. Therefore, the signal processing unit 206 assigns group number 1 to channel numbers 1 to 3 with model number "XX-YY-00", and assigns group number 2 to channel number 4 with model number "AA-BB-11".

In this way, each of the multiple (four) sensors is included in one of the multiple groups. In the example of Figure 7, three sensors assigned channel numbers 1 to 3 belong to group number 1, and one sensor assigned channel number 4 belongs to group number 2.

The grouping method is not limited to this. For example, the signal processing unit 206 may perform grouping using the information in the operating voltage item 303 shown in FIG. 7. In addition, although not included in the setting table 250B shown in FIG. 7, the signal processing unit 206 may use a sensor type identifier or a measurement sampling period as information used for grouping. Alternatively, a person may register group information in item 708 in advance.

When any of the multiple groups includes two or more sensors, the signal processing unit 206 sets the time T1 to be the same for two or more sensors. In the example of FIG. 7, there are two groups, and group number 1 includes two or more sensors, i.e., three sensors. Therefore, the signal processing unit 206 sets the time T1 to be the same, 500 msec, for each of these three sensors.

In the third embodiment, the signal processing unit 206 obtains a time T1' for each of these two or more sensors in the setting process, and sets the maximum of the two or more times T1' for the two or more sensors as the time T1. Note that the method for obtaining the time T1', which is a provisional time, is the same as the method for obtaining the time T1 in the first embodiment.

In the setting process, the signal processing unit 206 may supply power to multiple sensors simultaneously and acquire sensing data corresponding to each sensor all at once, or may supply power to multiple sensors in sequence and acquire sensing data in sequence.

The signal processing unit 206, which has acquired the sensing data corresponding to each sensor, registers the maximum information of time T1' corresponding to sensors belonging to the same group in item 709 as information of time T1. In the measurement routine processing in the measurement mode, the information of time T1 set in item 709 in FIG. 7 is referenced.

In the example of FIG. 7, of the three sensors belonging to group number 1, the time T1' of channel number 1 is 500 msec, the time T1' of channel number 2 is 350 msec, and the time T1' of channel number 3 is 400 msec. Comparing these times T1', the maximum is 500 msec. Therefore, in item 709, the time T1 of channel numbers 1 to 3 is set to 500 msec.

At the time of the setting process, the sensor with channel number 2 and the sensor with channel number 3 have a time of 350 msec and 400 msec, respectively, which is shorter than 500 msec. However, considering that the time T1' varies over time, it is preferable to set the time T1 to the longest possible value of 500 msec within the same group.

As described above, the third embodiment provides the effects of the first embodiment as well as enabling stable measurements over a long period of time.

[Fourth embodiment]
An information processing method according to the fourth embodiment will be described. In the fourth embodiment, the overall configuration of the production facility is similar to the overall configuration of the production facility 1000 according to the first embodiment, and the description will be omitted. In the fourth embodiment, a part of the information processing method is different from that in the first embodiment.

In the first embodiment, a case was described in which the signal processing unit 206 performs the setting process separately from the measurement routine process, i.e., acquires sensing data for setting separately from acquiring sensing data for measurement. In the fourth embodiment, a case is described in which the signal processing unit 206 does not distinguish between sensing data for measurement and sensing data for setting, but generates measurement data from a series of sensing data while also setting the time T1. Below, the parts of the fourth embodiment that differ from the first embodiment are described in detail, and explanations of similar parts are omitted.

Figure 8 is an explanatory diagram showing an example of a measurement routine process according to the fourth embodiment. In the fourth embodiment, similar to the first to third embodiments, the signal processing unit 206 executes the process of setting the time T1 only once after the monitoring node device 104 is started. However, in the fourth embodiment, unlike the first to third embodiments, the signal processing unit 206 resets the time T1 using the sensing data 801 used to acquire the measurement data 806.

That is, after the power is turned on, the signal processing unit 206 performs a predetermined node startup process. Then, after performing the node startup process, the signal processing unit 206 performs the measurement routine process.

Here, the memory unit 210 stores information on the default time 802 in advance. That is, in the first embodiment, in the setting table 250 shown in FIG. 3(a), the item 303 in which the information on time T1 is set is blank. In the fourth embodiment, the information on the default time 802 is already set in the item 303 in the setting table 250. The default time 802 is set by a person. The default time 802 need only be set to a time sufficiently longer than the convergence time, and does not have to be an exact time. The time for sampling the sensing data 801 during the first measurement after the monitoring node device 104 is started is long, but this is only the first time after the monitoring node device 104 is started. Therefore, the amount of power consumed by this measurement is small.

In the first measurement of the measurement routine process, the signal processing unit 206 acquires sensing data 801 from the signal input unit 205, from the time when power supply to the sensor starts until the time when the total time of the default time 802 and the measurement time 803 required for measurement has elapsed. The sensing data 801 consists of sensing data 804 acquired at the default time 802 and sensing data 805 acquired at the measurement time 803. The signal processing unit 206 generates measurement data 806 by signal processing such as average value processing, using sensing data 805, which is sensing data after power supply to the sensor starts and is from the time when the default time 802 has elapsed since power supply to the sensor started. The measurement data 806 is generated from stable sensing data 805 of the sensing data 801.

After completing this initial measurement task, the signal processing unit 206 uses the sensing data 801 to execute a setting process to derive and register the time T1. That is, the signal processing unit 206 executes a setting process using the sensing data 801, as in the first embodiment, and reconfigures the information on the time T1 in the setting table 250.

When performing the second or subsequent measurement after the monitoring node device 104 is started, the signal processing unit 206 refers to the setting table 250 and performs the measurement, as in the first embodiment.

In the fourth embodiment, the information on time T1 is reset, so that a person does not need to accurately calculate the convergence time. Thus, according to the fourth embodiment, a person sets the default time 802 as time T1, but later time T1 is automatically reset. Therefore, as in the first embodiment, the workload of a person is significantly reduced. In addition, since there is no longer a need to acquire sensing data just for the setting process, further energy savings can be achieved.

When the monitoring node device 104 is started for the second or subsequent times, the signal processing unit 206 may rewrite the information of time T1 in the setting table 250 to the information of the default time 802, or may leave the information registered as is. In either case, the time T1 is already set, and the above-mentioned process is executed at the time of the first measurement after the monitoring node device 104 is started.

Also, a table (not shown) in which the default time 802 is registered may be stored in the storage unit 210, separate from the setting table 250. Then, at the first measurement after the monitoring node device 104 is started, instead of referring to the information on the time T1 registered in item 306 of the setting table 250, the information on another table (not shown) may be referred to. Then, at the second or subsequent measurement after the monitoring node device 104 is started, the signal processing unit 206 may refer to item 306 of the setting table 250, or may refer to the table (not shown).

[Fifth embodiment]
An information processing method according to the fifth embodiment will be described. In the fifth embodiment, the overall configuration of the production facility is similar to the overall configuration of the production facility 1000 according to the first embodiment, and the description will be omitted. In the fifth embodiment, a part of the information processing method is different from that in the first embodiment.

In the first embodiment, a case was described in which, in measurement mode, the signal processing unit 206 starts supplying power to the sensor when an event condition is met. In the fifth embodiment, a processing operation of the signal processing unit 206 in a case in which the event condition is that the scheduled measurement time is reached will be described. Below, in the fifth embodiment, differences from the first embodiment will be described in detail, and similarities will not be described.

Figure 9 is an explanatory diagram of the measurement routine processing according to the fifth embodiment. Figure 9 is a time chart with time on the horizontal axis. During periods when measurements are not being performed in the measurement mode, the signal processing unit 206 performs a sleep operation that stops power supply to the sensor. The sleep operation can also be referred to as an energy-saving operation.

In the measurement mode of the fifth embodiment, as shown in FIG. 9, the signal processing unit 206 starts supplying power to the sensor at timing 904, which is earlier than the scheduled measurement time 901 by the time T1 set in the setting process of the setting mode. Then, the signal processing unit 206 waits for the time T1 from the timing 904 when the supply of power to the sensor starts. Then, the signal processing unit 206 starts measurement at timing 905 when the time T1 has elapsed, and ends the measurement at timing 907 when the time T3 has elapsed.

Here, in the fifth embodiment, the signal processing unit 206 calculates the scheduled measurement time 901 from the measurement information stored in the memory unit 210 before entering the sleep operation. The signal processing unit 206 subtracts the time T1 from the calculated scheduled measurement time 901 to obtain the timing 904 of starting power supply, and records the timing 905 of starting measurement in the memory unit 210 as the timing 904 of starting next power supply. By repeating the above routine processing, the scheduled measurement time 901 and the timing 905 of starting measurement can be made to match. Then, during the sleep operation, when it is time to start power supply, power supply to the sensor is started, and when it is time to start measurement, a measured value from the sensor is obtained. As a result, even during the sleep operation, power supply to the sensor can be started at an appropriate timing, and a measured value can be obtained from the sensor at an appropriate timing.

According to the fifth embodiment, the scheduled measurement time and the actual measurement start time can be made to coincide, making it possible to provide a system with high real-time performance. Furthermore, even when multiple sensors are connected to the monitoring node device 104, the actual measurement timing of each sensor can be aligned with its respective scheduled measurement time.

In this embodiment, power supply to the sensor is stopped during sleep operation, and power continues to be supplied to all functional units of the monitoring node 101. However, if power consumption is to be further reduced, power may be supplied only to the trigger generating unit 202, power supply unit 204, signal processing unit 206, and memory unit 210 during sleep operation, and the rest may be stopped.

Sixth Embodiment
An information processing method according to the sixth embodiment will be described. In the sixth embodiment, the overall configuration of the production facility is similar to the overall configuration of the production facility 1000 in the first embodiment, and a description thereof will be omitted. In the sixth embodiment, a part of the information processing method is different from that in the first embodiment. Hereinafter, in the sixth embodiment, the parts that are different from the first embodiment will be described in detail, and a description of the similar parts will be omitted.

In the memory unit 210 of the monitoring node device 104, an upper limit value and a lower limit value of the predetermined time T0 used for the judgment are set. Note that either the upper limit value or the lower limit value may be omitted as necessary. FIG. 10 is a flowchart of an information processing method according to the sixth embodiment. That is, FIG. 10 is a flowchart of the processing after the monitoring node device 104 is started up.

First, in step S101, the power switch is turned on and the monitoring node device 104 starts up. In step S102, the signal processing unit 206 executes a predetermined node startup process.

Then, in step S103, the signal processing unit 206 executes a setting process and sets a time T1, similar to the first embodiment. In step S104, the signal processing unit 206 determines whether the time T1 is within the range of the predetermined time T0. If the time T1 is within the range of the predetermined time T0 (S104: YES), the signal processing unit 206 executes a measurement routine process (S105), similar to the first embodiment.

If the time T1 exceeds the range of the predetermined time T0 (S104: NO), the signal processing unit 206 executes an alert process to output an alert (S106). Outputting an alert means outputting a signal or data indicating an alert.

A specific example of the alert process is described below. As the alert process, the signal processing unit 206 causes the output unit 207 to transmit data including an abnormality identifier to the higher-level device, the monitoring gateway device 106, wirelessly or via cable. Then, the terminal 109 can issue a warning to a person by displaying an image indicating the alert.

The alert process is not limited to this. For example, as the alert process, the signal processing unit 206 may perform a process of turning on an LED (not shown), a process of displaying a warning image on a display (not shown), or a process of sounding a buzzer (not shown).

An example will be described in which the lower limit of the predetermined time T0 is set to 5 msec. If there is a break in the cable between the sensor and the monitoring node device, the voltage value of the sensor remains unchanged from the start of power supply to the sensor. Therefore, the time T1 is calculated as 0 msec and registered in the memory unit 210. The signal processing unit 206 executes an alert process because the time T1 is 0 msec, which is below the lower limit of the predetermined time T0, which is 5 msec. As the alert process, the signal processing unit 206 turns on an LED (not shown), for example. This allows users and other people to know that there is an abnormality in the sensor or cable before the production equipment starts operating.

The present invention is not limited to the embodiments described above, and many variations are possible within the technical concept of the present invention. Furthermore, the effects described in the embodiments are merely a list of the most favorable effects resulting from the present invention, and the effects of the present invention are not limited to those described in the embodiments.

In the above embodiment, a case has been described in which the machine device 101 to be monitored is provided with multiple sensors, for example, two sensors 102 and 103, but this is not limited to the above. It is preferable that the machine device 101 is provided with multiple sensors, but it is also possible for the machine device 101 to be provided with only one sensor.

In addition, in the above embodiment, a pump has been described as an example of the mechanical device 101 to be monitored, but the present invention is not limited to this. For example, the mechanical device 101 may be a six-axis articulated robot, or a machine that can automatically perform movements such as expanding and contracting, bending and stretching, moving up and down, moving left and right, or turning, or a combination of these movements, based on information from a storage device provided in the control device.

In addition, in the above embodiment, the monitoring node device is powered by a battery, but this is not limited to this. The above embodiment is suitable for reducing capacity loss in the battery, i.e., for extending the battery life, but from the viewpoint of energy conservation, the present invention is also applicable when the monitoring node device is powered by a power supply unit or commercial power source.

Other Examples
The present invention can also be realized by a process in which a program for implementing one or more of the functions of the above-described embodiments is supplied to a system or device via a network or a storage medium, and one or more processors in a computer of the system or device read and execute the program. The present invention can also be realized by a circuit (e.g., ASIC) that implements one or more of the functions.

100...Monitoring system (system), 101...Machine, 102...Sensor, 103...Sensor, 104...Monitoring node device (information processing device, node device), 106...Monitoring gateway device (gateway device), 206...Signal processing unit (processing unit)

Claims (28)

An information processing device capable of acquiring data from a sensor after a first time has elapsed since a process for acquiring data from the sensor was executed,
obtaining a second time based on data from the sensor;
If the first time obtained based on the second time obtained is outside a predetermined range, notify the user;
If the first time acquired based on the acquired second time is within a predetermined range, the first time is automatically set as information to be used when acquiring data from the sensor .
23. An information processing apparatus comprising: The first time is a time to wait.
2. The information processing apparatus according to claim 1, The process for acquiring data from the sensor is powering the sensor.
3. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer. obtaining a first time period using data from the sensor from a time when power supply to the sensor is started;
4. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer. acquiring a first time period using data from the sensor from a time point when power supply to the sensor is started in a state in which it is considered that there is no change in the measurement environment of the sensor;
5. The information processing apparatus according to claim 1, low-pass filtering the data from the sensor; and obtaining a first time using the low-pass filtered data from the sensor.
6. The information processing apparatus according to claim 1, acquiring a time at which data from the sensor satisfies a convergence condition as a second time;
7. The information processing apparatus according to claim 1, wherein the information processing apparatus further comprises: a first input section; The convergence condition is that a feature amount in the data from the sensor is within a threshold range.
8. The information processing apparatus according to claim 7, the convergence condition is that the feature amount is continuously within the range of the threshold value;
9. The information processing apparatus according to claim 8, The feature amount is at least one of a first-order time differential value and a variance value of the data from the sensor.
10. The information processing apparatus according to claim 8, wherein the first and second inputs are connected to the first and second inputs. An information processing device capable of acquiring data from a sensor after a first time has elapsed since a process for acquiring data from the sensor was executed,
obtaining a second time at which data from the sensor satisfies a convergence condition;
Obtaining a first time period that is greater than a second time period ;
automatically setting the first time as information to be used when acquiring data from the sensor;
23. An information processing apparatus comprising: The control unit is operable to execute a setting mode for setting a first time period and a measurement mode for acquiring measurement data for acquiring a state of a mechanical device that is a measurement target of the sensor based on data from the sensor.
12. The information processing apparatus according to claim 1, An information processing device capable of acquiring data from a sensor after a first time has elapsed since a process for acquiring data from the sensor was executed,
The first time is automatically set as information to be used when acquiring data from the sensor,
a setting mode for setting a first time period and a measurement mode for acquiring measurement data when acquiring a state of a mechanical device that is a measurement target of the sensor based on data from the sensor,
In the measurement mode, power supply to the sensor is started at a timing earlier than a scheduled measurement time by a first time period set in the setting mode.
23. An information processing apparatus comprising: automatically setting the first time when the information processing device is started;
14. The information processing apparatus according to claim 1, If the first time has already been set for the sensor , reset the first time.
15. The information processing apparatus according to claim 1, a first time is preset for the sensor;
In a first measurement using the sensor after the start of power supply to the sensor, data is obtained from the sensor after the start of power supply to the sensor and the previously set first time has elapsed, and the first time is reset.
16. The information processing apparatus according to claim 1, If the first time has not been set for the sensor , the first time is automatically set.
17. The information processing apparatus according to claim 1, An information processing device capable of acquiring data from a sensor after a first time has elapsed since a process for acquiring data from the sensor was executed,
The first time is automatically set as information to be used when acquiring data from the sensor,
the sensor being one of a plurality of sensors;
Each of the plurality of sensors is included in one of a plurality of groups;
When any one of the plurality of groups includes two or more sensors, the first time is set to be the same for the two or more sensors.
23. An information processing apparatus comprising: determining a tentative first time for each of the two or more sensors, and setting a maximum of the two or more tentative first times for the two or more sensors;
20. The information processing apparatus according to claim 18, acquiring data from the sensor after the first time period has elapsed as measurement data for acquiring a state of a mechanical device that is a measurement target of the sensor;
20. The information processing apparatus according to claim 1, The information processing device according to any one of claims 1 to 20 is a node device.
23. An information processing apparatus comprising: 2. A method for manufacturing a finished product or an intermediate product by operating a production facility while monitoring a state of the production facility based on data acquired by the information processing device according to claim 1 .
A method for producing an article. 1. An information processing method of an information processing device capable of acquiring data from a sensor after a first time has elapsed since a process for acquiring data from the sensor was executed, comprising:
obtaining a second time based on data from the sensor;
If the first time obtained based on the second time obtained is outside a predetermined range, notify the user;
If the first time acquired based on the acquired second time is within a predetermined range, the first time is automatically set as information to be used when acquiring data from the sensor .
23. An information processing method comprising: 1. An information processing method of an information processing device capable of acquiring data from a sensor after a first time has elapsed since a process for acquiring data from the sensor was executed, comprising:
obtaining a second time at which data from the sensor satisfies a convergence condition;
Obtaining a first time period that is greater than a second time period;
automatically setting the first time as information to be used when acquiring data from the sensor;
23. An information processing method comprising: 1. An information processing method of an information processing device capable of acquiring data from a sensor after a first time has elapsed since a process for acquiring data from the sensor was executed, comprising:
The first time is automatically set as information to be used when acquiring data from the sensor,
A setting mode for setting a first time period and a measurement mode for acquiring measurement data for acquiring a state of a mechanical device that is a measurement target of the sensor based on data from the sensor are executable.
23. An information processing method comprising: 1. An information processing method of an information processing device capable of acquiring data from a sensor after a first time has elapsed since a process for acquiring data from the sensor was executed, comprising:
The first time is automatically set as information to be used when acquiring data from the sensor,
the sensor being one of a plurality of sensors;
Each of the plurality of sensors is included in one of a plurality of groups;
When any one of the plurality of groups includes two or more sensors, the first time is set to be the same for the two or more sensors.
23. An information processing method comprising: 27. A program for causing a computer to execute the information processing method according to claim 23 . A computer-readable recording medium having the program according to claim 7 recorded thereon.

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