WO2022064843A1 - Equipment diagnosing system - Google Patents

Equipment diagnosing system Download PDF

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Publication number
WO2022064843A1
WO2022064843A1 PCT/JP2021/028443 JP2021028443W WO2022064843A1 WO 2022064843 A1 WO2022064843 A1 WO 2022064843A1 JP 2021028443 W JP2021028443 W JP 2021028443W WO 2022064843 A1 WO2022064843 A1 WO 2022064843A1
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data
sensor
value
unit
index
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PCT/JP2021/028443
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French (fr)
Japanese (ja)
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浩一郎 永田
明博 中村
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株式会社日立製作所
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Publication of WO2022064843A1 publication Critical patent/WO2022064843A1/en

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring

Definitions

  • the present invention relates to a device diagnostic system for diagnosing the state of a device by acquiring and analyzing data from the device using a sensor.
  • the industrial equipment system is composed of a plurality of equipments, and for example, products are manufactured and inspected by these equipments.
  • a device diagnostic system that installs sensors (for example, mechanical sensors and temperature sensors) that measure mechanical physical quantities such as vibration, pressure, and temperature of devices in each device and acquires machine data from the devices and analyzes them. It may detect the status of the device.
  • the device diagnostic system can also acquire and analyze electrical data such as motor current using an electrical sensor that measures electrical physical quantities such as current and voltage. , The state of the device can be detected.
  • the device diagnostic system measures mechanical physical quantities including temperature, electrical physical quantities, and the position of moving objects with sensors, and acquires and analyzes these data. By doing so, the state of the device can be detected.
  • the device diagnostic system monitors the status of the devices that make up the industrial device system using the measurement data of the sensor, and detects the device that is likely to fail in advance, so that the industrial device system is stopped unplanned. Is prevented.
  • Patent Documents 1 and 2 Examples of conventional device diagnostic systems are disclosed in Patent Documents 1 and 2.
  • the diagnostic device described in Patent Document 1 includes a sensor set that is a combination of a plurality of sensors related to a device, the sensor outputs a sensor value according to a measurement result of a physical quantity related to the device, and the sensor value is used to make an abnormality of the sensor. Outputs the diagnostic result for.
  • the diagnostic apparatus described in Patent Document 2 includes a current sensor that acquires current information, and diagnoses a motor system using this current information.
  • An object of the present invention is to provide a device diagnostic system capable of reducing the amount of data used for diagnosis.
  • the device diagnostic system obtains the value of an index indicating the state of the device in which the sensor is installed from a plurality of sensors installed in the device that measure different physical quantities and the data acquired by the sensors. It includes a data analysis unit, a processing unit that selects the value of the index used for diagnosing the state of the device, and an output unit that outputs the value of the index selected by the processing unit.
  • the plurality of sensors include a first sensor and a second sensor.
  • the processing unit uses the value of the index used for diagnosing the state of the device as the value of the index obtained from the data acquired by the first sensor, and is obtained from the data acquired by the first sensor. When the value of the index exceeds a predetermined value, the value of the index used for diagnosing the state of the device is taken as the value of the index obtained from the data acquired by the second sensor.
  • the present invention it is possible to provide a device diagnostic system capable of reducing the amount of data used for diagnosis.
  • FIG. 1 shows the structure of the device diagnostic system according to Example 1 of this invention. It is a figure which shows the structure of the analysis result processing part in Example 1.
  • FIG. It is a figure explaining the example of the process of selecting the value of KPI used for the diagnosis of the state of an apparatus performed by the data determination unit in Example 1.
  • FIG. It is a figure which shows the structure of the device diagnostic system according to Example 2 of this invention. It is a figure which shows the structure of the analysis result processing part in Example 2. It is a figure explaining the example of the process of selecting the value of KPI used for the diagnosis of the state of an apparatus performed by the data determination unit in Example 2.
  • FIG. It is a figure which shows the structure of the device diagnostic system according to Example 3 of this invention.
  • FIG. It is a figure explaining the example of the process of selecting the value of KPI used for the diagnosis of the state of a device performed by the data determination unit in Example 3.
  • FIG. It is a figure which shows the data acquisition part provided in the apparatus diagnostic system according to Example 5 of this invention. It is a figure explaining the example of the process of selecting the value of KPI used for the diagnosis of the state of a moving body performed by the analysis result processing unit in Example 5.
  • the device diagnostic system acquires data from a device by using a plurality of sensors that measure different physical quantities (for example, current, voltage, vibration, pressure, temperature, humidity, sound, and position) in combination, and obtains data from the device. Diagnose the condition.
  • the data capacity used for diagnosis can be increased while maintaining the diagnostic accuracy of the device. Can be reduced.
  • the device diagnostic system according to the first embodiment of the present invention will be described with reference to FIGS. 1 to 3.
  • the device diagnostic system according to this embodiment targets an industrial device system including one or more devices, acquires data from each device using sensors installed in each device, and diagnoses the state of each device. ..
  • FIG. 1 is a diagram showing a configuration of a device diagnosis system according to this embodiment.
  • the device diagnosis system includes a first data acquisition unit 11, a second data acquisition unit 12, a first data analysis unit 21, a second data analysis unit 22, an analysis result processing unit 1, and an analysis result output unit 2.
  • the first data acquisition unit 11 and the second data acquisition unit 12 include a sensor or a data acquisition circuit including the sensor, and acquire data from the device of the industrial equipment system by the sensor. These sensors are installed in the equipment of the industrial equipment system.
  • the sensor included in the first data acquisition unit 11 and the sensor included in the second data acquisition unit 12 have different specifications and measure physical quantities different from each other, and are installed in the same device or other devices. It is installed in the equipment that drives and the equipment that is driven by this equipment.
  • the first data acquisition unit 11 and the second data acquisition unit 12 each include a storage device, and the data acquired by the sensor can be stored in the storage device.
  • One of the first data acquisition unit 11 and the second data acquisition unit 12 is provided with a sensor (for example, a mechanical sensor or a temperature sensor) for measuring mechanical physical quantities such as vibration, pressure, and temperature of the device, and data on the mechanical physical quantity.
  • a sensor for example, a mechanical sensor or a temperature sensor
  • mechanical data the data of the mechanical physical quantity
  • the temperature sensor is included in the mechanical sensor. Examples of machine data include equipment vibration, pressure and temperature data.
  • the other of the first data acquisition unit 11 and the second data acquisition unit 12 is provided with an electric sensor for measuring an electrical physical quantity such as a current or a voltage, and acquires data (electrical data) of the electrical physical quantity.
  • an electric sensor for measuring an electrical physical quantity such as a current or a voltage
  • data electrical data
  • Examples of electrical data include motor current data.
  • the electrical sensor is usually always in operation.
  • the first data analysis unit 21 acquires the data acquired by the first data acquisition unit 11 from the first data acquisition unit 11 as the first data.
  • the second data analysis unit 22 acquires the data acquired by the second data acquisition unit 12 from the second data acquisition unit 12 as the second data.
  • the first data and the second data are different types of data, one is mechanical data and the other is electrical data.
  • the first data analysis unit 21 and the second data analysis unit 22 analyze the data (first data and second data) acquired by using the sensor for the device, and from this data, any arbitrary device for which the sensor is installed. Find the value of KPI.
  • KPI is a KPI (Key Performance Indicator) in an industrial device, and is an index showing the state of the device (for example, the degree of abnormality, the degree of quality, and the degree of deterioration). Any of the conventionally used indicators can be used as the KPI.
  • the first data analysis unit 21 and the second data analysis unit 22 can obtain the value of KPI by using a conventional method.
  • the first data analysis unit 21 obtains an arbitrary KPI value for the device in which the sensor is installed from the value of the first data.
  • the second data analysis unit 22 obtains the same KPI value as that obtained by the first data analysis unit 21 for the device in which the sensor is installed from the value of the second data.
  • the analysis result processing unit 1 uses the analysis results of the first data and the second data, that is, the KPI values obtained by the first data analysis unit 21 and the second data analysis unit 22, and the KPI used for diagnosing the state of the device. Select a value for.
  • the analysis result output unit 2 includes an output device, and outputs the KPI value obtained by the first data analysis unit 21 and the second data analysis unit 22 and the diagnosis result of the state of the device using the KPI value to the output device. Output.
  • the analysis result output unit 2 displays the KPI value obtained by the first data analysis unit 21 and the second data analysis unit 22 and the KPI value selected by the analysis result processing unit 1 on the screen, or causes an abnormality in the device. It is possible to issue an alarm by light or sound to inform that the occurrence of the KPI, or to notify the management center of the KPI value or the abnormality of the device.
  • FIG. 2 is a diagram showing the configuration of the analysis result processing unit 1.
  • the analysis result processing unit 1 includes a data determination unit 101 and a data switching unit 102.
  • the data determination unit 101 uses the KPI value (analysis result of the first data) obtained by the first data analysis unit 21 and the KPI value (analysis result of the second data) obtained by the second data analysis unit 22. Then, select the value of KPI used for diagnosing the condition of the device.
  • the data switching unit 102 switches the KPI value used by the analysis result output unit 2 for diagnosing the state of the device to the KPI value selected by the data determination unit 101, and outputs the KPI value to the analysis result output unit 2.
  • FIG. 3 is a diagram illustrating an example of a process performed by the data determination unit 101 for selecting a KPI value used for diagnosing the state of the device.
  • FIG. 3 shows how the KPI value shown on the vertical axis (for example, the value of an index indicating an abnormality or deterioration of the device) increases with time. The value of KPI increases with time, and when it exceeds the threshold value Vt, it indicates that an abnormality has occurred in the device.
  • the data determination unit 101 sets the KPI value used for diagnosing the state of the device as the KPI value (analysis result of the first data) obtained by the first data analysis unit 21. That is, at the start of operation of the device, the data determination unit 101 uses the KPI value obtained from the data (first data) acquired by the first data acquisition unit 11 for diagnosing the state of the device.
  • the data switching unit 102 outputs the KPI value obtained by the first data analysis unit 21 to the analysis result output unit 2.
  • the KPI value obtained by the first data analysis unit 21 increases with time, and the predetermined value Vc is set at the time ct. If it exceeds, the value of KPI used for diagnosing the state of the device is taken as the value of KPI obtained by the second data analysis unit 22 (analysis result of the second data). That is, when the KPI value obtained from the data (first data) acquired by the first data acquisition unit 11 exceeds the predetermined value Vc, the data determination unit 101 obtains the data (first data) acquired by the second data acquisition unit 12. The value of KPI obtained from 2 data) is used for diagnosing the state of the device.
  • the data switching unit 102 switches the KPI value output to the analysis result output unit 2 from the KPI value obtained by the first data analysis unit 21 to the KPI value obtained by the second data analysis unit 22.
  • the analysis result output unit 2 outputs the KPI value selected and output by the analysis result processing unit 1 to the output device and uses it for diagnosing the state of the device.
  • the analysis result output unit 2 outputs a diagnosis result that an abnormality has occurred in the device to the output device.
  • the threshold value Vt can be arbitrarily set in advance according to the device in which the sensor is installed. When the value of KPI exceeds the threshold value Vt, it can be considered that an abnormality has occurred in the device.
  • the predetermined value Vc is a value smaller than the threshold value Vt, and can be arbitrarily predetermined according to the expected time change of the threshold value Vt, the device in which the sensor is installed, and the KPI value.
  • the predetermined value Vc is a value indicating that the value of KPI is close to reaching the threshold value Vt.
  • the first data (data acquired by the first data acquisition unit 11) and the second data (data acquired by the second data acquisition unit 12) have different sampling times.
  • the first data has a longer sampling time than the second data. That is, the sensor of the first data acquisition unit 11 acquires data from the device with a longer sampling time than the sensor of the second data acquisition unit 12.
  • the sampling time for acquiring the first data is 1 millisecond or more
  • the sampling time for acquiring the second data is 1 microsecond to several hundred microseconds.
  • the electric sensor Since the electric sensor usually constantly acquires data at intervals of several microseconds, the amount of data used for diagnosis is large. However, when the electric sensor is a sensor for acquiring the first data, as described above, the sampling time for acquiring the data can be lengthened, so that the data capacity used for the diagnosis can be reduced.
  • the KPI value when the KPI value is a predetermined value Vc or less, the first data having a long sampling time is used for diagnosing the state of the device, so that the data capacity used for the diagnosis can be reduced.
  • the second data having a short sampling time is used for diagnosing the state of the device, so that the device abnormality (the KPI value exceeds the threshold value Vt) can be accurately detected. It can be determined.
  • the sensor acquires data (second data) from the device in the second data acquisition unit 12 while the state of the device is diagnosed using the first data. It is possible to stop the operation or prevent the obtained data from being stored in the storage device even if the sensor acquires the data.
  • the first data acquisition unit 11 While diagnosing the state of the device using the second data, the first data acquisition unit 11 either stops the operation of the sensor acquiring data (first data) from the device, or the sensor acquires the data. Even so, the obtained data can be prevented from being stored in the storage device.
  • the device diagnosis system has the above configuration, and by switching the data (KPI value) used for diagnosing the state of the device, the data capacity used for diagnosis can be reduced and the data is stored. Diagnostic accuracy can be ensured while suppressing the load on the storage device (system load).
  • the device diagnostic system according to the second embodiment of the present invention will be described with reference to FIGS. 4 to 6.
  • the differences from the device diagnosis system according to the first embodiment will be mainly described.
  • FIG. 4 is a diagram showing the configuration of the device diagnosis system according to this embodiment.
  • the device diagnosis system includes N data acquisition units, N data analysis units, an analysis result processing unit 110, and an analysis result output unit 2.
  • the N data acquisition units are the first data acquisition unit 11, the second data acquisition unit 12, the third data acquisition unit 13, ..., And the Nth data acquisition unit 14.
  • the N data analysis units are the first data analysis unit 21, the second data analysis unit 22, the third data analysis unit 23, ..., And the Nth data analysis unit 24.
  • Each of the N data acquisition units includes a sensor or a data acquisition circuit including the sensor. Since each of the N data acquisition units includes a sensor, the device diagnostic system includes a plurality of sensors.
  • the first data acquisition unit 11 includes an electric sensor installed in the motor driving the equipment of the industrial equipment system, and acquires the electric data of the motor by the electric sensor.
  • An electric sensor is a sensor that measures an electrical physical quantity such as an electric current or a voltage.
  • Electrical data is data on electrical physical quantities such as current and voltage.
  • the first data analysis unit 21 acquires the electrical data acquired by the first data acquisition unit 11 as the first data from the first data acquisition unit 11, and from the value of the first data, the device (motor) in which the electric sensor is installed. ) Is obtained as an arbitrary KPI value.
  • the second data acquisition unit 12 includes a mechanical sensor installed in the equipment of the industrial equipment system, and acquires the machine data of the equipment by the machine sensor.
  • a mechanical sensor is a sensor that measures mechanical physical quantities such as vibration, pressure, and temperature of equipment.
  • Machine data is data on mechanical physical quantities such as vibration, pressure, and temperature of equipment.
  • the second data analysis unit 22 acquires the machine data acquired by the second data acquisition unit 12 from the second data acquisition unit 12 as the second data, and from the value of the second data, the device on which the machine sensor is installed is subjected to. The same KPI value as that obtained by the first data analysis unit 21 is obtained.
  • the third data acquisition unit 13 includes a machine sensor installed at a position different from the sensors provided by the other data acquisition units, and acquires the machine data of the device by the machine sensor.
  • the third data analysis unit 23 acquires the machine data acquired by the third data acquisition unit 13 as the third data from the third data acquisition unit 13, and from the value of the third data, regarding the device in which the machine sensor is installed, the device. The same KPI value as that obtained by the first data analysis unit 21 is obtained.
  • the second data acquisition unit 12 to the Nth data acquisition unit 14 acquire the machine data of the device as described above.
  • the second data analysis unit 22 to the Nth data analysis unit 24 acquire the Nth data from the second data and obtain the KPI value as described above.
  • the second data acquisition unit 12 to the Nth data acquisition unit 14 mainly obtain machine data having a specific frequency component according to the device on which the machine sensor is installed and the position.
  • the first data analysis unit 21 to the Nth data analysis unit 24 supply the obtained KPI value to the analysis result processing unit 110, and supply the Nth data from the first data to the analysis result processing unit 110, respectively.
  • the analysis result processing unit 110 uses the analysis result of the first data to the Nth data, that is, the KPI value obtained by the first data analysis unit 21 to the Nth data analysis unit 24, and uses the KPI for diagnosing the state of the device. Select a value for. Further, the analysis result processing unit 110 uses the first data to the Nth data to specify a device for detecting an abnormality.
  • the analysis result output unit 2 outputs the KPI value obtained by the Nth data analysis unit 24 from the first data analysis unit 21 and the diagnosis result of the state of the device using the KPI value to the output device.
  • FIG. 5 is a diagram showing the configuration of the analysis result processing unit 110.
  • the analysis result processing unit 110 includes an abnormal frequency component determination unit 111 and a data determination unit 112.
  • the abnormal frequency component determination unit 111 frequency-analyzes the first data (that is, the electric data acquired by the first data acquisition unit 11), and when the value of the electric data shows an abnormality, the value of the electric data shows an abnormality.
  • the indicated frequency is obtained, and the obtained frequency is used as the frequency component to be detected.
  • electrical data is data including various frequency components, and often reflects abnormalities in the entire system. Therefore, the fact that the value of the electrical data indicates an abnormality means that there is a high possibility that an abnormality has occurred in the device, or that there is a high possibility that an abnormality has occurred in the device.
  • the data determination unit 112 frequency-analyzes the Nth data (that is, the machine data acquired by the Nth data acquisition unit 14 from the second data acquisition unit 12) from the second data, and from the second data to the Nth data. , The machine data including the frequency component to be detected obtained by the abnormal frequency component determination unit 111 is obtained.
  • the data determination unit 112 determines that the obtained machine data is data used for diagnosing the state of the device.
  • the machine data determined to be the data used for diagnosing the state of the device is called "diagnosis machine data".
  • the device for which the diagnostic machine data is obtained is the device for which an abnormality should be detected.
  • the data determination unit 112 identifies the device to detect the abnormality by obtaining the diagnostic machine data in this way.
  • the data determination unit 112 uses the KPI value obtained from the first data (electrical data) and the KPI value obtained from the diagnostic machine data to be used for diagnosing the state of the device for which an abnormality should be detected. Select a value for.
  • FIG. 6 is a diagram illustrating an example of a process performed by the data determination unit 112 for selecting a KPI value used for diagnosing the state of the device.
  • FIG. 6 shows how the KPI value shown on the vertical axis (for example, the value of an index indicating an abnormality or deterioration of the device) increases with time.
  • the data determination unit 112 executes the same processing as the data determination unit 101 in the first embodiment, and selects the value of the KPI used for diagnosing the state of the device for which an abnormality should be detected.
  • the data determination unit 112 sets the KPI value used for diagnosing the state of the device as the KPI value obtained from the electrical data (first data), and sets the KPI value obtained from the electrical data as the KPI value. It is output to the analysis result output unit 2.
  • the data determination unit 112 increases the KPI value with time, and when the predetermined value Vc is exceeded at the time ct, the KPI value used for diagnosing the state of the device is set to the diagnostic machine data (second data to second data).
  • the KPI value obtained from (data obtained from N data) is used, and the KPI value output to the analysis result output unit 2 is obtained from the diagnostic machine data from the KPI value obtained from the electrical data. Switch to the value of KPI.
  • the analysis result output unit 2 outputs the KPI value selected and output by the analysis result processing unit 110 to the output device and uses it for diagnosing the state of the device.
  • the machine sensor of the second data acquisition unit 12 to the Nth data acquisition unit 14 acquires machine data from the device. It is possible to stop the operation or prevent the obtained data from being saved in the storage device even if the machine sensor acquires the machine data.
  • the first data acquisition unit 11 stops the operation of the electric sensor to acquire the electric data from the device, or the electric sensor acquires the electric data. It is also possible to prevent the obtained data from being stored in the storage device.
  • the KPI value used for diagnosing the state of the device is set regardless of the magnitude of the KPI value (that is, KPI). (Whether the value of is larger or smaller than the predetermined value Vc), it can be the value of KPI obtained from the electric data acquired by the electric sensor. With such a configuration, the device diagnosis system according to the present embodiment can continue the diagnosis by using the electric data acquired by the electric sensor even if the mechanical sensor fails and cannot be used.
  • the KPI value obtained from the electrical data which is the data including various frequency components is used for diagnosing the state of the device, and the KPI is used.
  • the value of KPI exceeds a predetermined value Vc
  • the value of KPI obtained from the diagnostic machine data is used for diagnosing the state of the device.
  • the data (KPI value) used for diagnosing the state of the device is switched in this way, and the device for which an abnormality should be detected (machine data including the frequency component to be detected) is obtained.
  • the device diagnostic system according to the third embodiment of the present invention will be described with reference to FIGS. 7 and 8. Hereinafter, the differences from the device diagnosis system according to the second embodiment will be mainly described.
  • FIG. 7 is a diagram showing the configuration of the device diagnosis system according to this embodiment.
  • the device diagnostic system consists of N data acquisition units (1st data acquisition unit 11, 2nd data acquisition unit 12, ..., and Nth data acquisition unit 14) and N data analysis units (1st data). It includes an analysis unit 21, a second data analysis unit 22 and an Nth data analysis unit 24), an analysis result processing unit 210, and an analysis result output unit 2.
  • the industrial equipment system targeted by the equipment diagnosis system includes a plurality of equipments. That is, the industrial equipment system includes a motor 200 and M machines connected to the motor 200.
  • the M machines are the first machine 201, the second machine 202, the third machine 203, ..., And the M machine 204, which are arbitrary devices driven by the motor 200 and operated.
  • the first data acquisition unit 11 is installed in the motor 200. Other data acquisition units are installed in some of the M machines.
  • the second data acquisition unit 12, ..., And the Nth data acquisition unit 14 are installed in the second machine 202, ..., And the M machine 204, respectively, and the first machine 201.
  • the third machine 203 does not have a data acquisition unit.
  • the number of data acquisition units and data analysis units is less than or equal to the number of machines provided in the industrial equipment system (N ⁇ M).
  • the first data acquisition unit 11 includes an electric sensor installed in the motor 200, and acquires the electric data of the motor 200 by the electric sensor.
  • the first data analysis unit 21 acquires the electrical data acquired by the first data acquisition unit 11 as the first data from the first data acquisition unit 11, and obtains an arbitrary KPI value for the motor 200 from the value of the first data. Ask.
  • the second data acquisition unit 12 includes a machine sensor installed in the second machine 202, and acquires the machine data of the second machine 202 by the machine sensor.
  • the second data analysis unit 22 acquires the machine data acquired by the second data acquisition unit 12 as the second data from the second data acquisition unit 12, and from the value of the second data, the first data for the second machine 202. The same KPI value as that obtained by the analysis unit 21 is obtained.
  • the first data analysis unit 21 to the Nth data analysis unit 24 supply the obtained KPI value to the analysis result processing unit 210, and supply the Nth data from the first data to the analysis result processing unit 210, respectively.
  • the analysis result processing unit 210 does not acquire the machine data of the first machine 201 and the third machine 203.
  • the analysis result processing unit 210 has the same configuration as the analysis result processing unit 110 (FIG. 5) in the second embodiment, and includes an abnormal frequency component determination unit 111 and a data determination unit 112.
  • the analysis result processing unit 210 diagnoses the state of the machines (second machine 202, ..., And M machine 204) in which the data acquisition unit is installed in the same manner as in the second embodiment.
  • the analysis result processing unit 210 diagnoses the state of the machines (first machine 201 and third machine 203) in which the data acquisition unit is not installed by performing the processing described below.
  • FIG. 8 is a diagram illustrating an example of a process performed by the data determination unit 112 for selecting a KPI value used for diagnosing the state of the device.
  • the data determination unit 112 diagnoses the state of the machines (second machine 202, ..., And M machine 204) in which the data acquisition unit is installed in the same manner as in the second embodiment. ..
  • FIG. 8 shows an example in which the data determination unit 112 selects the value of the KPI used for diagnosing the state of the second machine 202.
  • the data determination unit 112 sets the KPI value used for diagnosing the state of the second machine 202 as the KPI value obtained from the electrical data at the start of operation of the device, and when the KPI value exceeds the predetermined value Vc, It is the value of KPI obtained from the diagnostic machine data.
  • the data determination unit 112 does not depend on the size of the KPI value (that is, the KPI value used for diagnosis is a predetermined value) for the machines (first machine 201 and third machine 203) in which the data acquisition unit is not installed.
  • the condition is diagnosed using only the KPI value (KPI value for the motor 200) obtained from the electrical data (whether larger or smaller than Vc).
  • FIG. 8 shows an example in which the data determination unit 112 uses only the KPI value obtained from the electrical data for diagnosing the state of the first machine 201.
  • the analysis result output unit 2 outputs the KPI value obtained by the Nth data analysis unit 24 from the first data analysis unit 21 and the diagnosis result of the state of the device using the KPI value to the output device.
  • the device diagnostic system it is not necessary to install sensors in all of the plurality of devices included in the industrial device system to be diagnosed, so as to affect the operation of a specific device (for example, the entire operation of the industrial device system).
  • Mechanical sensors can only be installed in (important equipment).
  • the state is diagnosed using the KPI value obtained from the electrical data.
  • the state is diagnosed using the KPI value obtained from the electrical data and the KPI value obtained from the mechanical data.
  • the device diagnostic system has the above configuration, can reduce the data capacity used for diagnosis, and can secure diagnostic accuracy while suppressing the load (system load) on the storage device for storing data. can.
  • the device diagnostic system according to the fourth embodiment of the present invention will be described. Hereinafter, the differences from the device diagnosis system according to the first embodiment will be mainly described.
  • the device diagnostic system can determine whether or not any sensor is operating normally among a plurality of sensors installed in the device by comparing with other sensors. For example, in the device diagnostic system according to this embodiment, when a sensor that has not been used for a while for diagnosis among a plurality of sensors installed in the device is used for diagnosis, it is compared with other sensors used for diagnosis. , It is possible to determine whether or not a sensor that has not been used for diagnosis for a while operates normally.
  • the sensor for which it is desired to determine whether or not it is operating normally is a mechanical sensor that has not been used for a while for diagnosis, and the sensor to be compared with this mechanical sensor is an electric sensor used for diagnosis.
  • the electric sensor is usually always in operation.
  • the analysis result processing unit 1 uses a mechanical sensor that has not been used for diagnosis for a while, the KPI value obtained from the data acquired by this mechanical sensor and the electricity used for the diagnosis Compare with the value of KPI obtained from the data acquired by the sensor.
  • the analysis result processing unit 1 standardizes the values of these KPIs and compares them with each other, for example.
  • the difference between the KPI value obtained from the data acquired by the machine sensor and the KPI value obtained from the data acquired by the electric sensor is smaller than the predetermined threshold value, the analysis result processing unit 1 performs the machine. Determine that the sensor is normal.
  • This threshold value can be arbitrarily set according to the equipment on which the sensor is installed, the specifications of the sensor, etc., and when the KPI value is standardized for comparison, the standardization method of the KPI value is also considered. Can be determined.
  • the device diagnostic system it is possible to determine whether or not the sensor installed in the device is operating normally. For example, by performing this determination periodically, a sensor that is rarely used can be determined. Normality can be diagnosed on a regular basis.
  • the device diagnostic system according to the fifth embodiment of the present invention will be described with reference to FIGS. 9 and 10.
  • the differences from the device diagnosis system according to the first embodiment will be mainly described.
  • the equipment diagnosis system according to the present embodiment targets moving objects such as automobiles, railroads, and elevators, and diagnoses the state of the equipment installed on the moving objects.
  • the device diagnosis system includes a data acquisition unit including a sensor, a data analysis unit, an analysis result processing unit 1, and an analysis result output unit 2, similar to the device diagnosis system according to the first embodiment (FIG. 1).
  • the data analysis unit, the analysis result processing unit 1, and the analysis result output unit 2 have the same configuration as the device diagnosis system according to the first embodiment.
  • the data acquisition unit included in the device diagnostic system according to the present embodiment will be mainly described.
  • FIG. 9 is a diagram showing a data acquisition unit included in the device diagnosis system according to the present embodiment.
  • the sensor included in the data acquisition unit is installed in the mobile body 301.
  • the mobile body 301 is, for example, an automobile, a railroad, and an elevator, and includes a drive unit 303 which is a component for driving the mobile body 301.
  • the drive unit 303 includes, for example, a motor and gears.
  • the device diagnosis system includes a mobile data acquisition unit 302 and a drive unit data acquisition unit 304 as data acquisition units.
  • the mobile data acquisition unit 302 and the drive unit data acquisition unit 304 include a sensor or a data acquisition circuit including the sensor. These sensors are installed in the device included in the mobile body 301 and the device included in the drive unit 303.
  • the moving body data acquisition unit 302 includes a sensor for measuring physical quantities such as the position, speed, vibration, temperature, sound, and pressure of the moving body 301 itself, and the moving body data which is the physical quantity data of the moving body 301 is sensored. Get by.
  • the drive unit data acquisition unit 304 includes a sensor for measuring physical quantities such as current, voltage, vibration, pressure, temperature, and sound of the drive unit 303, and the drive unit data which is data of the physical quantity of the drive unit 303 is obtained by the sensor. get.
  • the data determination unit 101 (FIG. 2) of the analysis result processing unit 1 is obtained from the KPI value obtained from the moving body data (for example, the value of an index indicating abnormality or deterioration of the moving body 301) and the driving unit data.
  • the value of KPI used for diagnosing the state of the moving body 301 is selected by using the value of KPI (for example, the value of an index indicating abnormality or deterioration of the driving unit 303).
  • FIG. 10 is a diagram illustrating an example of a process performed by the data determination unit 101 for selecting a KPI value used for diagnosing the state of the moving body 301.
  • FIG. 10 shows how the value of KPI shown on the vertical axis increases with time. The value of KPI increases with time, and when it exceeds the threshold value Vt, it indicates that an abnormality has occurred in the moving body 301.
  • the data determination unit 101 sets the KPI value used for diagnosing the state of the device as the KPI value obtained from the mobile body data. That is, at the start of operation of the mobile body 301, the data determination unit 101 uses the KPI value obtained from the mobile body data for diagnosing the state of the mobile body 301.
  • the data determination unit 101 investigates the cause of the abnormality from the state of the drive unit 303 by using the value of the drive unit data.
  • the data determination unit 101 increases the KPI value obtained from the moving body data with time, and when the threshold value Vt is exceeded at the time dt, the data determining unit 101 sets the KPI value used for diagnosing the state of the moving body 301 to the driving unit. Switch to the KPI value obtained from the data.
  • the data determination unit 101 determines that an abnormality has occurred in the moving body 301, and determines that an abnormality has occurred in the moving body 301, and the KPI obtained from the driving unit data.
  • the value is used to estimate what the drive unit 303 is, which is the cause of the abnormality.
  • the data determination unit 101 searches for a drive unit 303 in which the KPI value obtained from the drive unit data is different from the normal time, and causes the drive unit 303 in which the KPI value different from the normal time is different from the normal time. It is estimated to be the drive unit 303. In this way, the device diagnosis system according to the present embodiment can detect the abnormality of the mobile body 301 and estimate the cause of the abnormality.
  • the device diagnosis system by switching the data (KPI value) used for diagnosing the state of the moving body 301 as described above, the data capacity used for the diagnosis can be reduced and the data is stored. Diagnostic accuracy can be ensured while suppressing the load on the storage device (system load).
  • the present invention is not limited to the above embodiment, and various modifications are possible.
  • the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to the embodiment including all the described configurations.

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Abstract

An equipment diagnosing system according to the present invention is provided with: a plurality of sensors (11, 12) which are installed in a piece of equipment to measure mutually different physical quantities; data analyzing units (21, 22) which obtain, from data acquired by the sensors (11, 12), the values of indicators (KPIs) indicating the status of the equipment in which the sensors (11, 12) are installed; a processing unit (1) which selects the value of the indicator (KPI) to be used to diagnose the status of the equipment; and an output unit (2) which outputs the value of the indicator (KPI) selected by the processing unit (1). The plurality of sensors (11, 12) include a first sensor (11) and a second sensor (12). The processing unit (1) sets the value of the indicator (KPI) obtained from the data acquired by the first sensor (11) to be the value of the indicator (KPI) to be used to diagnose the status of the equipment, and if the value of the indicator (KPI) obtained from the data acquired by the first sensor (11) exceeds a predetermined value (Vc), sets the value of the indicator (KPI) obtained from the data acquired by the second sensor (12) to be the value of the indicator (KPI) to be used to diagnose the status of the equipment.

Description

機器診断システムEquipment diagnostic system
　本発明は、センサを用いて機器からデータを取得し分析して、機器の状態を診断する機器診断システムに関する。 The present invention relates to a device diagnostic system for diagnosing the state of a device by acquiring and analyzing data from the device using a sensor.
　産業機器システムは、複数の機器から構成され、これらの機器により例えば製品の製造や検査を行う。産業機器システムでは、構成機器が故障を起こすと計画外停止が発生して操業に大きな影響が起き、多額の損失が生じることがある。このため、機器の振動や圧力や温度などの機械的物理量を測定するセンサ（例えば、機械センサや温度センサ）を各機器に設置し、機械データを機器から取得して分析する機器診断システムにより、機器の状態を検知することがある。また、機器がモータで駆動されている場合には、機器診断システムは、電流や電圧などの電気的物理量を測定する電気センサを用いてモータ電流などの電気データを取得して分析することによっても、機器の状態を検知することができる。また、自動車、鉄道、及びエレベータなどの移動体でも、機器診断システムは、温度を含む機械的物理量、電気的物理量、及び移動体の位置などをセンサで測定し、これらのデータを取得して分析することで、機器の状態を検知することができる。 The industrial equipment system is composed of a plurality of equipments, and for example, products are manufactured and inspected by these equipments. In an industrial equipment system, if a component equipment fails, an unplanned outage occurs, which has a great impact on the operation and may cause a large loss. For this reason, a device diagnostic system that installs sensors (for example, mechanical sensors and temperature sensors) that measure mechanical physical quantities such as vibration, pressure, and temperature of devices in each device and acquires machine data from the devices and analyzes them. It may detect the status of the device. In addition, when the device is driven by a motor, the device diagnostic system can also acquire and analyze electrical data such as motor current using an electrical sensor that measures electrical physical quantities such as current and voltage. , The state of the device can be detected. Also, for moving objects such as automobiles, railroads, and elevators, the device diagnostic system measures mechanical physical quantities including temperature, electrical physical quantities, and the position of moving objects with sensors, and acquires and analyzes these data. By doing so, the state of the device can be detected.
　このように、従来では、機器診断システムがセンサの測定データを使って産業機器システムを構成する機器の状態をモニタし、故障しそうな機器を事前に検知することで、産業機器システムの計画外停止を防いでいる。 In this way, conventionally, the device diagnostic system monitors the status of the devices that make up the industrial device system using the measurement data of the sensor, and detects the device that is likely to fail in advance, so that the industrial device system is stopped unplanned. Is prevented.
　従来の機器診断システムの例は、特許文献１、２に開示されている。特許文献１に記載の診断装置は、機器に関する複数のセンサの組み合わせであるセンサセットを備え、機器に関する物理量の測定結果に応じたセンサ値をセンサが出力し、このセンサ値を用いてセンサの異常に関する診断結果を出力する。特許文献２に記載の診断装置は、電流情報を取得する電流センサを備え、この電流情報を用いてモータシステムを診断する。 Examples of conventional device diagnostic systems are disclosed in Patent Documents 1 and 2. The diagnostic device described in Patent Document 1 includes a sensor set that is a combination of a plurality of sensors related to a device, the sensor outputs a sensor value according to a measurement result of a physical quantity related to the device, and the sensor value is used to make an abnormality of the sensor. Outputs the diagnostic result for. The diagnostic apparatus described in Patent Document 2 includes a current sensor that acquires current information, and diagnoses a motor system using this current information.
特開２０１９－９６２３６号公報Japanese Unexamined Patent Publication No. 2019-96236 国際公開第２０１８／１５８９１０号International Publication No. 2018/158910
　特許文献１に記載の診断装置などのように、複数のセンサを使用する従来の機器診断システムでは、センサを各々の機器に設置するので使用するセンサの数が多く、機器診断システムが扱う全体のデータ容量が大きくなるとともに、センサを設置するコストや工数が増加するという課題がある。 In a conventional device diagnostic system that uses a plurality of sensors, such as the diagnostic device described in Patent Document 1, since the sensors are installed in each device, the number of sensors used is large, and the entire device diagnostic system handles the whole. As the data capacity increases, there is a problem that the cost and manpower for installing the sensor increase.
　特許文献２に記載の診断装置などのように、電流センサを使用する従来の機器診断システムでは、例えばモータに流れる電流成分を電流センサで検出する。電流信号には機器固有の周波数成分が現れるので、電流センサを用いるとモータシステムの全体をまとめて診断することができる。しかし、電流センサを用いると、数マイクロ秒程度の間隔でデータを常に取得する必要があり、データの容量が大きくなるという課題がある。 In a conventional device diagnostic system that uses a current sensor, such as the diagnostic device described in Patent Document 2, for example, the current component flowing through the motor is detected by the current sensor. Since the frequency component peculiar to the device appears in the current signal, the entire motor system can be diagnosed collectively by using the current sensor. However, when a current sensor is used, it is necessary to constantly acquire data at intervals of about several microseconds, and there is a problem that the amount of data becomes large.
　このように、従来の機器診断システムでは、機器の測定精度を上げて正確な診断をするためには、診断に用いるデータ容量が大きくなりデータを保存する記憶装置にかかる負荷が大きいという課題がある。 As described above, in the conventional device diagnosis system, in order to improve the measurement accuracy of the device and perform an accurate diagnosis, there is a problem that the data capacity used for the diagnosis becomes large and the load on the storage device for storing the data is large. ..
　本発明は、診断に用いるデータ容量を減らすことができる機器診断システムを提供することを目的とする。 An object of the present invention is to provide a device diagnostic system capable of reducing the amount of data used for diagnosis.
　本発明による機器診断システムは、機器に設置された、互いに異なる物理量を測定する複数のセンサと、前記センサが取得したデータから、前記センサが設置された前記機器の状態を示す指標の値を求めるデータ分析部と、前記機器の状態の診断に用いる前記指標の値を選択する処理部と、前記処理部が選択した前記指標の値を出力する出力部とを備える。複数の前記センサは、第１のセンサと第２のセンサを備える。前記処理部は、前記機器の状態の診断に用いる前記指標の値を、前記第１のセンサが取得したデータから得られた前記指標の値とし、前記第１のセンサが取得したデータから得られた前記指標の値が予め定めた値を超えたら、前記機器の状態の診断に用いる前記指標の値を、前記第２のセンサが取得したデータから得られた前記指標の値とする。 The device diagnostic system according to the present invention obtains the value of an index indicating the state of the device in which the sensor is installed from a plurality of sensors installed in the device that measure different physical quantities and the data acquired by the sensors. It includes a data analysis unit, a processing unit that selects the value of the index used for diagnosing the state of the device, and an output unit that outputs the value of the index selected by the processing unit. The plurality of sensors include a first sensor and a second sensor. The processing unit uses the value of the index used for diagnosing the state of the device as the value of the index obtained from the data acquired by the first sensor, and is obtained from the data acquired by the first sensor. When the value of the index exceeds a predetermined value, the value of the index used for diagnosing the state of the device is taken as the value of the index obtained from the data acquired by the second sensor.
　本発明によると、診断に用いるデータ容量を減らすことができる機器診断システムを提供することができる。 According to the present invention, it is possible to provide a device diagnostic system capable of reducing the amount of data used for diagnosis.
本発明の実施例１による機器診断システムの構成を示す図である。It is a figure which shows the structure of the device diagnostic system according to Example 1 of this invention. 実施例１において、分析結果処理部の構成を示す図である。It is a figure which shows the structure of the analysis result processing part in Example 1. FIG. 実施例１において、データ判定部が行う、機器の状態の診断に用いるＫＰＩの値を選択する処理の例を説明する図である。It is a figure explaining the example of the process of selecting the value of KPI used for the diagnosis of the state of an apparatus performed by the data determination unit in Example 1. FIG. 本発明の実施例２による機器診断システムの構成を示す図である。It is a figure which shows the structure of the device diagnostic system according to Example 2 of this invention. 実施例２において、分析結果処理部の構成を示す図である。It is a figure which shows the structure of the analysis result processing part in Example 2. 実施例２において、データ判定部が行う、機器の状態の診断に用いるＫＰＩの値を選択する処理の例を説明する図である。It is a figure explaining the example of the process of selecting the value of KPI used for the diagnosis of the state of an apparatus performed by the data determination unit in Example 2. FIG. 本発明の実施例３による機器診断システムの構成を示す図である。It is a figure which shows the structure of the device diagnostic system according to Example 3 of this invention. 実施例３において、データ判定部が行う、機器の状態の診断に用いるＫＰＩの値を選択する処理の例を説明する図である。It is a figure explaining the example of the process of selecting the value of KPI used for the diagnosis of the state of a device performed by the data determination unit in Example 3. FIG. 本発明の実施例５による機器診断システムが備えるデータ取得部を示す図である。It is a figure which shows the data acquisition part provided in the apparatus diagnostic system according to Example 5 of this invention. 実施例５において、分析結果処理部が行う、移動体の状態の診断に用いるＫＰＩの値を選択する処理の例を説明する図である。It is a figure explaining the example of the process of selecting the value of KPI used for the diagnosis of the state of a moving body performed by the analysis result processing unit in Example 5.
　本発明による機器診断システムは、互いに異なる物理量（例えば、電流、電圧、振動、圧力、温度、湿度、音、及び位置）を測定する複数のセンサを併用して機器からデータを取得し、機器の状態を診断する。本発明による機器診断システムでは、このような複数のセンサを併用し、診断に用いるデータを取得するセンサを条件に応じて変更することで、機器の診断精度を保ちながら、診断に用いるデータ容量を減らすことができる。 The device diagnostic system according to the present invention acquires data from a device by using a plurality of sensors that measure different physical quantities (for example, current, voltage, vibration, pressure, temperature, humidity, sound, and position) in combination, and obtains data from the device. Diagnose the condition. In the device diagnostic system according to the present invention, by using a plurality of such sensors in combination and changing the sensor that acquires the data used for diagnosis according to the conditions, the data capacity used for diagnosis can be increased while maintaining the diagnostic accuracy of the device. Can be reduced.
　以下、本発明の実施例による機器診断システムについて、図面を用いて説明する。なお、本明細書で用いる図面において、同一のまたは対応する構成要素には同一の符号を付け、これらの構成要素については繰り返しの説明を省略する場合がある。 Hereinafter, the device diagnostic system according to the embodiment of the present invention will be described with reference to the drawings. In the drawings used in the present specification, the same or corresponding components may be designated by the same reference numerals, and repeated description of these components may be omitted.
　本発明の実施例１による機器診断システムについて、図１から図３を用いて説明する。本実施例による機器診断システムは、１つまたは複数の機器を備える産業機器システムを診断対象とし、各機器に設置されたセンサを用いて各機器からデータを取得し、各機器の状態を診断する。 The device diagnostic system according to the first embodiment of the present invention will be described with reference to FIGS. 1 to 3. The device diagnostic system according to this embodiment targets an industrial device system including one or more devices, acquires data from each device using sensors installed in each device, and diagnoses the state of each device. ..
　図１は、本実施例による機器診断システムの構成を示す図である。機器診断システムは、第１データ取得部１１と第２データ取得部１２と、第１データ分析部２１と第２データ分析部２２と、分析結果処理部１と、分析結果出力部２を備える。 FIG. 1 is a diagram showing a configuration of a device diagnosis system according to this embodiment. The device diagnosis system includes a first data acquisition unit 11, a second data acquisition unit 12, a first data analysis unit 21, a second data analysis unit 22, an analysis result processing unit 1, and an analysis result output unit 2.
　第１データ取得部１１と第２データ取得部１２は、センサ、またはセンサを備えるデータ取得回路を備え、センサによって産業機器システムの機器からデータを取得する。これらのセンサは、産業機器システムが備える機器に設置されている。第１データ取得部１１が備えるセンサと、第２データ取得部１２が備えるセンサは、互いに仕様が異なり、互いに異なる物理量を測定するセンサであり、同一の機器に設置されている、または他の機器を駆動する機器とこの機器により駆動される機器に設置されている。 The first data acquisition unit 11 and the second data acquisition unit 12 include a sensor or a data acquisition circuit including the sensor, and acquire data from the device of the industrial equipment system by the sensor. These sensors are installed in the equipment of the industrial equipment system. The sensor included in the first data acquisition unit 11 and the sensor included in the second data acquisition unit 12 have different specifications and measure physical quantities different from each other, and are installed in the same device or other devices. It is installed in the equipment that drives and the equipment that is driven by this equipment.
　第１データ取得部１１と第２データ取得部１２は、それぞれ記憶装置を備え、センサが取得したデータを記憶装置に保存することができる。 The first data acquisition unit 11 and the second data acquisition unit 12 each include a storage device, and the data acquired by the sensor can be stored in the storage device.
　第１データ取得部１１と第２データ取得部１２の一方は、機器の振動や圧力や温度などの機械的物理量を測定するセンサ（例えば、機械センサや温度センサ）を備え、機械的物理量のデータ（機械データ）を取得する。以下の説明では、機械的物理量のデータを「機械データ」と呼び、温度センサを機械センサに含める。機械データの例には、機器の振動や圧力や温度のデータが含まれる。 One of the first data acquisition unit 11 and the second data acquisition unit 12 is provided with a sensor (for example, a mechanical sensor or a temperature sensor) for measuring mechanical physical quantities such as vibration, pressure, and temperature of the device, and data on the mechanical physical quantity. Acquire (machine data). In the following description, the data of the mechanical physical quantity is referred to as "mechanical data", and the temperature sensor is included in the mechanical sensor. Examples of machine data include equipment vibration, pressure and temperature data.
　第１データ取得部１１と第２データ取得部１２の他方は、電流や電圧などの電気的物理量を測定する電気センサを備え、電気的物理量のデータ（電気データ）を取得する。以下の説明では、電気的物理量のデータを「電気データ」と呼ぶ。電気データの例には、モータの電流のデータが含まれる。電気センサは、通常は、常に動作している。 The other of the first data acquisition unit 11 and the second data acquisition unit 12 is provided with an electric sensor for measuring an electrical physical quantity such as a current or a voltage, and acquires data (electrical data) of the electrical physical quantity. In the following description, the data of the electrical physical quantity is referred to as "electrical data". Examples of electrical data include motor current data. The electrical sensor is usually always in operation.
　第１データ分析部２１は、第１データ取得部１１が取得したデータを、第１データとして第１データ取得部１１から取得する。第２データ分析部２２は、第２データ取得部１２が取得したデータを、第２データとして第２データ取得部１２から取得する。第１データと第２データは、互いに種類の異なるデータであり、一方が機械データであり、他方が電気データである。 The first data analysis unit 21 acquires the data acquired by the first data acquisition unit 11 from the first data acquisition unit 11 as the first data. The second data analysis unit 22 acquires the data acquired by the second data acquisition unit 12 from the second data acquisition unit 12 as the second data. The first data and the second data are different types of data, one is mechanical data and the other is electrical data.
　第１データ分析部２１と第２データ分析部２２は、機器についてセンサを用いて取得したデータ（第１データと第２データ）を分析し、このデータからセンサが設置された機器についての任意のＫＰＩの値を求める。ＫＰＩは、産業機器におけるＫＰＩ（Key Performance Indicator）であり、機器の状態（例えば、異常度、品質、及び劣化度）を示す指標である。ＫＰＩには、従来用いられている指標のうち、任意のものを用いることができる。第１データ分析部２１と第２データ分析部２２は、従来の方法を用いて、ＫＰＩの値を求めることができる。 The first data analysis unit 21 and the second data analysis unit 22 analyze the data (first data and second data) acquired by using the sensor for the device, and from this data, any arbitrary device for which the sensor is installed. Find the value of KPI. KPI is a KPI (Key Performance Indicator) in an industrial device, and is an index showing the state of the device (for example, the degree of abnormality, the degree of quality, and the degree of deterioration). Any of the conventionally used indicators can be used as the KPI. The first data analysis unit 21 and the second data analysis unit 22 can obtain the value of KPI by using a conventional method.
　第１データ分析部２１は、第１データの値から、センサが設置された機器について任意のＫＰＩの値を求める。第２データ分析部２２は、第２データの値から、センサが設置された機器について、第１データ分析部２１が求めたのと同じＫＰＩの値を求める。 The first data analysis unit 21 obtains an arbitrary KPI value for the device in which the sensor is installed from the value of the first data. The second data analysis unit 22 obtains the same KPI value as that obtained by the first data analysis unit 21 for the device in which the sensor is installed from the value of the second data.
　分析結果処理部１は、第１データと第２データの分析結果、すなわち第１データ分析部２１と第２データ分析部２２が求めたＫＰＩの値を用いて、機器の状態の診断に用いるＫＰＩの値を選択する。 The analysis result processing unit 1 uses the analysis results of the first data and the second data, that is, the KPI values obtained by the first data analysis unit 21 and the second data analysis unit 22, and the KPI used for diagnosing the state of the device. Select a value for.
　分析結果出力部２は、出力装置を備え、第１データ分析部２１と第２データ分析部２２が求めたＫＰＩの値と、ＫＰＩの値を用いた機器の状態の診断結果を、出力装置に出力する。例えば、分析結果出力部２は、第１データ分析部２１と第２データ分析部２２が求めたＫＰＩの値や分析結果処理部１が選択したＫＰＩの値を画面に表示したり、機器に異常が発生したことを知らせる警報を光や音で発したり、管理センタへＫＰＩの値や機器の異常を通知したりすることができる。 The analysis result output unit 2 includes an output device, and outputs the KPI value obtained by the first data analysis unit 21 and the second data analysis unit 22 and the diagnosis result of the state of the device using the KPI value to the output device. Output. For example, the analysis result output unit 2 displays the KPI value obtained by the first data analysis unit 21 and the second data analysis unit 22 and the KPI value selected by the analysis result processing unit 1 on the screen, or causes an abnormality in the device. It is possible to issue an alarm by light or sound to inform that the occurrence of the KPI, or to notify the management center of the KPI value or the abnormality of the device.
　図２は、分析結果処理部１の構成を示す図である。分析結果処理部１は、データ判定部１０１と、データ切替部１０２を備える。 FIG. 2 is a diagram showing the configuration of the analysis result processing unit 1. The analysis result processing unit 1 includes a data determination unit 101 and a data switching unit 102.
　データ判定部１０１は、第１データ分析部２１が求めたＫＰＩの値（第１データの分析結果）と、第２データ分析部２２が求めたＫＰＩの値（第２データの分析結果）を用いて、機器の状態の診断に用いるＫＰＩの値を選択する。 The data determination unit 101 uses the KPI value (analysis result of the first data) obtained by the first data analysis unit 21 and the KPI value (analysis result of the second data) obtained by the second data analysis unit 22. Then, select the value of KPI used for diagnosing the condition of the device.
　データ切替部１０２は、分析結果出力部２が機器の状態の診断に用いるＫＰＩの値を、データ判定部１０１が選択したＫＰＩの値に切り替えて、分析結果出力部２に出力する。 The data switching unit 102 switches the KPI value used by the analysis result output unit 2 for diagnosing the state of the device to the KPI value selected by the data determination unit 101, and outputs the KPI value to the analysis result output unit 2.
　図３は、データ判定部１０１が行う、機器の状態の診断に用いるＫＰＩの値を選択する処理の例を説明する図である。図３には、縦軸に示したＫＰＩの値（例えば、機器の異常や劣化を示す指標の値）が時間とともに増加していく様子を示している。ＫＰＩの値は、時間とともに増加していき、閾値であるＶｔを超えると機器に異常が発生したことを示す。 FIG. 3 is a diagram illustrating an example of a process performed by the data determination unit 101 for selecting a KPI value used for diagnosing the state of the device. FIG. 3 shows how the KPI value shown on the vertical axis (for example, the value of an index indicating an abnormality or deterioration of the device) increases with time. The value of KPI increases with time, and when it exceeds the threshold value Vt, it indicates that an abnormality has occurred in the device.
　データ判定部１０１は、機器の運転開始時には、機器の状態の診断に用いるＫＰＩの値を、第１データ分析部２１が求めたＫＰＩの値（第１データの分析結果）とする。すなわち、データ判定部１０１は、機器の運転開始時には、第１データ取得部１１が取得したデータ（第１データ）から得られたＫＰＩの値を、機器の状態の診断に用いる。データ切替部１０２は、第１データ分析部２１が求めたＫＰＩの値を分析結果出力部２に出力する。 At the start of operation of the device, the data determination unit 101 sets the KPI value used for diagnosing the state of the device as the KPI value (analysis result of the first data) obtained by the first data analysis unit 21. That is, at the start of operation of the device, the data determination unit 101 uses the KPI value obtained from the data (first data) acquired by the first data acquisition unit 11 for diagnosing the state of the device. The data switching unit 102 outputs the KPI value obtained by the first data analysis unit 21 to the analysis result output unit 2.
　データ判定部１０１は、第１データ分析部２１が求めたＫＰＩの値（すなわち、機器の状態の診断に用いているＫＰＩの値）が時間とともに増加していき、時刻ｔｃにて所定値Ｖｃを超えたら、機器の状態の診断に用いるＫＰＩの値を、第２データ分析部２２が求めたＫＰＩの値（第２データの分析結果）とする。すなわち、データ判定部１０１は、第１データ取得部１１が取得したデータ（第１データ）から得られたＫＰＩの値が所定値Ｖｃを超えたら、第２データ取得部１２が取得したデータ（第２データ）から得られたＫＰＩの値を、機器の状態の診断に用いる。データ切替部１０２は、分析結果出力部２に出力するＫＰＩの値を、第１データ分析部２１が求めたＫＰＩの値から、第２データ分析部２２が求めたＫＰＩの値に切り替える。 In the data determination unit 101, the KPI value obtained by the first data analysis unit 21 (that is, the KPI value used for diagnosing the state of the device) increases with time, and the predetermined value Vc is set at the time ct. If it exceeds, the value of KPI used for diagnosing the state of the device is taken as the value of KPI obtained by the second data analysis unit 22 (analysis result of the second data). That is, when the KPI value obtained from the data (first data) acquired by the first data acquisition unit 11 exceeds the predetermined value Vc, the data determination unit 101 obtains the data (first data) acquired by the second data acquisition unit 12. The value of KPI obtained from 2 data) is used for diagnosing the state of the device. The data switching unit 102 switches the KPI value output to the analysis result output unit 2 from the KPI value obtained by the first data analysis unit 21 to the KPI value obtained by the second data analysis unit 22.
　分析結果出力部２は、分析結果処理部１が選択して出力したＫＰＩの値を、出力装置に出力するとともに機器の状態の診断に用いる。分析結果出力部２は、ＫＰＩの値が閾値Ｖｔを超えたら、機器に異常が発生したという診断結果を出力装置に出力する。 The analysis result output unit 2 outputs the KPI value selected and output by the analysis result processing unit 1 to the output device and uses it for diagnosing the state of the device. When the KPI value exceeds the threshold value Vt, the analysis result output unit 2 outputs a diagnosis result that an abnormality has occurred in the device to the output device.
　閾値Ｖｔは、センサが設置された機器に応じて任意に予め定めることができる。ＫＰＩの値が閾値Ｖｔを超えると、機器に異常が発生したとみなすことができる。 The threshold value Vt can be arbitrarily set in advance according to the device in which the sensor is installed. When the value of KPI exceeds the threshold value Vt, it can be considered that an abnormality has occurred in the device.
　所定値Ｖｃは、閾値Ｖｔより小さい値であり、閾値Ｖｔ、センサが設置された機器、及びＫＰＩの値の予想される時間変化に応じて任意に予め定めることができる。所定値Ｖｃは、ＫＰＩの値が閾値Ｖｔに到達するのが近いことを示す値である。 The predetermined value Vc is a value smaller than the threshold value Vt, and can be arbitrarily predetermined according to the expected time change of the threshold value Vt, the device in which the sensor is installed, and the KPI value. The predetermined value Vc is a value indicating that the value of KPI is close to reaching the threshold value Vt.
　第１データ（第１データ取得部１１が取得したデータ）と第２データ（第２データ取得部１２が取得したデータ）は、取得するサンプリング時間が互いに異なるのが好ましい。本実施例では、第１データは、第２データよりも取得するサンプリング時間が長いものとする。すなわち、第１データ取得部１１のセンサは、第２データ取得部１２のセンサよりも長いサンプリング時間で、機器からデータを取得する。例えば、第１データを取得するサンプリング時間が１ミリ秒以上であり、第２データを取得するサンプリング時間が１マイクロ秒から数百マイクロ秒であるとする。 It is preferable that the first data (data acquired by the first data acquisition unit 11) and the second data (data acquired by the second data acquisition unit 12) have different sampling times. In this embodiment, it is assumed that the first data has a longer sampling time than the second data. That is, the sensor of the first data acquisition unit 11 acquires data from the device with a longer sampling time than the sensor of the second data acquisition unit 12. For example, it is assumed that the sampling time for acquiring the first data is 1 millisecond or more, and the sampling time for acquiring the second data is 1 microsecond to several hundred microseconds.
　電気センサは、通常、数マイクロ秒程度の間隔でデータを常に取得するので、診断に用いるデータ容量が大きい。しかし、電気センサが第１データを取得するセンサである場合には、上述したように、データを取得するサンプリング時間を長くすることができるので、診断に用いるデータ容量を減らすことができる。 Since the electric sensor usually constantly acquires data at intervals of several microseconds, the amount of data used for diagnosis is large. However, when the electric sensor is a sensor for acquiring the first data, as described above, the sampling time for acquiring the data can be lengthened, so that the data capacity used for the diagnosis can be reduced.
　本実施例による機器診断システムでは、ＫＰＩの値が所定値Ｖｃ以下の場合には、サンプリング時間が長い第１データを機器の状態の診断に用いるので、診断に用いるデータ容量を減らすことができる。ＫＰＩの値が所定値Ｖｃを超えて閾値Ｖｔに近づいたら、サンプリング時間が短い第２データを機器の状態の診断に用いるので、機器の異常（ＫＰＩの値が閾値Ｖｔを超えること）を正確に判定することができる。 In the device diagnosis system according to this embodiment, when the KPI value is a predetermined value Vc or less, the first data having a long sampling time is used for diagnosing the state of the device, so that the data capacity used for the diagnosis can be reduced. When the KPI value exceeds the predetermined value Vc and approaches the threshold value Vt, the second data having a short sampling time is used for diagnosing the state of the device, so that the device abnormality (the KPI value exceeds the threshold value Vt) can be accurately detected. It can be determined.
　また、本実施例による機器診断システムでは、第１データを用いて機器の状態を診断している間には、第２データ取得部１２は、センサが機器からデータ（第２データ）を取得する動作を停止するか、センサがデータを取得しても得られたデータを記憶装置に保存しないようにすることができる。第２データを用いて機器の状態を診断している間には、第１データ取得部１１は、センサが機器からデータ（第１データ）を取得する動作を停止するか、センサがデータを取得しても得られたデータを記憶装置に保存しないようにすることができる。 Further, in the device diagnosis system according to the present embodiment, the sensor acquires data (second data) from the device in the second data acquisition unit 12 while the state of the device is diagnosed using the first data. It is possible to stop the operation or prevent the obtained data from being stored in the storage device even if the sensor acquires the data. While diagnosing the state of the device using the second data, the first data acquisition unit 11 either stops the operation of the sensor acquiring data (first data) from the device, or the sensor acquires the data. Even so, the obtained data can be prevented from being stored in the storage device.
　本実施例による機器診断システムは、以上のような構成を備え、機器の状態の診断に用いるデータ（ＫＰＩの値）を切り替えることで、診断に用いるデータ容量を減らすことができ、データを保存する記憶装置にかかる負荷（システム負荷）を抑えつつ、診断精度を確保することができる。 The device diagnosis system according to this embodiment has the above configuration, and by switching the data (KPI value) used for diagnosing the state of the device, the data capacity used for diagnosis can be reduced and the data is stored. Diagnostic accuracy can be ensured while suppressing the load on the storage device (system load).
　本発明の実施例２による機器診断システムについて、図４から図６を用いて説明する。以下では、実施例１による機器診断システムと異なる点を主に説明する。 The device diagnostic system according to the second embodiment of the present invention will be described with reference to FIGS. 4 to 6. Hereinafter, the differences from the device diagnosis system according to the first embodiment will be mainly described.
　図４は、本実施例による機器診断システムの構成を示す図である。機器診断システムは、Ｎ個のデータ取得部と、Ｎ個のデータ分析部と、分析結果処理部１１０と、分析結果出力部２を備える。Ｎ個のデータ取得部は、第１データ取得部１１、第２データ取得部１２、第３データ取得部１３、・・・、及び第Ｎデータ取得部１４である。Ｎ個のデータ分析部は、第１データ分析部２１、第２データ分析部２２、第３データ分析部２３、・・・、及び第Ｎデータ分析部２４である。 FIG. 4 is a diagram showing the configuration of the device diagnosis system according to this embodiment. The device diagnosis system includes N data acquisition units, N data analysis units, an analysis result processing unit 110, and an analysis result output unit 2. The N data acquisition units are the first data acquisition unit 11, the second data acquisition unit 12, the third data acquisition unit 13, ..., And the Nth data acquisition unit 14. The N data analysis units are the first data analysis unit 21, the second data analysis unit 22, the third data analysis unit 23, ..., And the Nth data analysis unit 24.
　Ｎ個のデータ取得部は、それぞれ、センサ、またはセンサを備えるデータ取得回路を備える。Ｎ個のデータ取得部がそれぞれセンサを備えるので、機器診断システムは、複数のセンサを備える。 Each of the N data acquisition units includes a sensor or a data acquisition circuit including the sensor. Since each of the N data acquisition units includes a sensor, the device diagnostic system includes a plurality of sensors.
　第１データ取得部１１は、産業機器システムの機器を駆動しているモータに設置されている電気センサを備え、電気センサによって、モータの電気データを取得する。電気センサは、電流や電圧などの電気的物理量を測定するセンサである。電気データは、電流や電圧などの電気的物理量のデータである。 The first data acquisition unit 11 includes an electric sensor installed in the motor driving the equipment of the industrial equipment system, and acquires the electric data of the motor by the electric sensor. An electric sensor is a sensor that measures an electrical physical quantity such as an electric current or a voltage. Electrical data is data on electrical physical quantities such as current and voltage.
　第１データ分析部２１は、第１データ取得部１１が取得した電気データを第１データとして第１データ取得部１１から取得し、第１データの値から、電気センサが設置された機器（モータ）について任意のＫＰＩの値を求める。 The first data analysis unit 21 acquires the electrical data acquired by the first data acquisition unit 11 as the first data from the first data acquisition unit 11, and from the value of the first data, the device (motor) in which the electric sensor is installed. ) Is obtained as an arbitrary KPI value.
　第２データ取得部１２は、産業機器システムの機器に設置されている機械センサを備え、機械センサによって、機器の機械データを取得する。機械センサは、機器の振動や圧力や温度などの機械的物理量を測定するセンサである。機械データは、機器の振動や圧力や温度などの機械的物理量のデータである。 The second data acquisition unit 12 includes a mechanical sensor installed in the equipment of the industrial equipment system, and acquires the machine data of the equipment by the machine sensor. A mechanical sensor is a sensor that measures mechanical physical quantities such as vibration, pressure, and temperature of equipment. Machine data is data on mechanical physical quantities such as vibration, pressure, and temperature of equipment.
　第２データ分析部２２は、第２データ取得部１２が取得した機械データを第２データとして第２データ取得部１２から取得し、第２データの値から、機械センサが設置された機器について、第１データ分析部２１が求めたのと同じＫＰＩの値を求める。 The second data analysis unit 22 acquires the machine data acquired by the second data acquisition unit 12 from the second data acquisition unit 12 as the second data, and from the value of the second data, the device on which the machine sensor is installed is subjected to. The same KPI value as that obtained by the first data analysis unit 21 is obtained.
　第３データ取得部１３は、他のデータ取得部が備えるセンサと異なる位置に設置されている機械センサを備え、機械センサによって、機器の機械データを取得する。 The third data acquisition unit 13 includes a machine sensor installed at a position different from the sensors provided by the other data acquisition units, and acquires the machine data of the device by the machine sensor.
　第３データ分析部２３は、第３データ取得部１３が取得した機械データを第３データとして第３データ取得部１３から取得し、第３データの値から、機械センサが設置された機器について、第１データ分析部２１が求めたのと同じＫＰＩの値を求める。 The third data analysis unit 23 acquires the machine data acquired by the third data acquisition unit 13 as the third data from the third data acquisition unit 13, and from the value of the third data, regarding the device in which the machine sensor is installed, the device. The same KPI value as that obtained by the first data analysis unit 21 is obtained.
　第２データ取得部１２から第Ｎデータ取得部１４は、以上のようにして機器の機械データを取得する。第２データ分析部２２から第Ｎデータ分析部２４は、以上のようにして、それぞれ第２データから第Ｎデータを取得してＫＰＩの値を求める。 The second data acquisition unit 12 to the Nth data acquisition unit 14 acquire the machine data of the device as described above. The second data analysis unit 22 to the Nth data analysis unit 24 acquire the Nth data from the second data and obtain the KPI value as described above.
　第２データ取得部１２から第Ｎデータ取得部１４では、機械センサが設置された機器や位置に応じた特定の周波数成分を持つ機械データが、主に得られる。 The second data acquisition unit 12 to the Nth data acquisition unit 14 mainly obtain machine data having a specific frequency component according to the device on which the machine sensor is installed and the position.
　第１データ分析部２１から第Ｎデータ分析部２４は、求めたＫＰＩの値を分析結果処理部１１０に供給するとともに、第１データから第Ｎデータをそれぞれ分析結果処理部１１０に供給する。 The first data analysis unit 21 to the Nth data analysis unit 24 supply the obtained KPI value to the analysis result processing unit 110, and supply the Nth data from the first data to the analysis result processing unit 110, respectively.
　分析結果処理部１１０は、第１データから第Ｎデータの分析結果、すなわち第１データ分析部２１から第Ｎデータ分析部２４が求めたＫＰＩの値を用いて、機器の状態の診断に用いるＫＰＩの値を選択する。さらに、分析結果処理部１１０は、第１データから第Ｎデータを用いて、異常を検知すべき機器を特定する。 The analysis result processing unit 110 uses the analysis result of the first data to the Nth data, that is, the KPI value obtained by the first data analysis unit 21 to the Nth data analysis unit 24, and uses the KPI for diagnosing the state of the device. Select a value for. Further, the analysis result processing unit 110 uses the first data to the Nth data to specify a device for detecting an abnormality.
　分析結果出力部２は、第１データ分析部２１から第Ｎデータ分析部２４が求めたＫＰＩの値と、ＫＰＩの値を用いた機器の状態の診断結果を、出力装置に出力する。 The analysis result output unit 2 outputs the KPI value obtained by the Nth data analysis unit 24 from the first data analysis unit 21 and the diagnosis result of the state of the device using the KPI value to the output device.
　図５は、分析結果処理部１１０の構成を示す図である。分析結果処理部１１０は、異常周波数成分判定部１１１と、データ判定部１１２を備える。 FIG. 5 is a diagram showing the configuration of the analysis result processing unit 110. The analysis result processing unit 110 includes an abnormal frequency component determination unit 111 and a data determination unit 112.
　異常周波数成分判定部１１１は、第１データ（すなわち、第１データ取得部１１が取得した電気データ）を周波数分析し、電気データの値が異常を示す場合には、電気データの値が異常を示す周波数を求め、求めた周波数を検知すべき周波数成分とする。なお、一般的に、電気データは、様々な周波数成分を含むデータであり、システム全体の異常が反映されることが多い。従って、電気データの値が異常を示すということは、機器に異常が起きている可能性が高いこと、または機器に異常が起こる可能性が高いことを意味する。 The abnormal frequency component determination unit 111 frequency-analyzes the first data (that is, the electric data acquired by the first data acquisition unit 11), and when the value of the electric data shows an abnormality, the value of the electric data shows an abnormality. The indicated frequency is obtained, and the obtained frequency is used as the frequency component to be detected. In general, electrical data is data including various frequency components, and often reflects abnormalities in the entire system. Therefore, the fact that the value of the electrical data indicates an abnormality means that there is a high possibility that an abnormality has occurred in the device, or that there is a high possibility that an abnormality has occurred in the device.
　データ判定部１１２は、第２データから第Ｎデータ（すなわち、第２データ取得部１２から第Ｎデータ取得部１４が取得した機械データ）を周波数分析し、第２データから第Ｎデータの中から、異常周波数成分判定部１１１が求めた検知すべき周波数成分を含む機械データを求める。データ判定部１１２は、求めた機械データを、機器の状態の診断に用いるデータと判定する。機器の状態の診断に用いるデータと判定された機械データを、「診断用機械データ」と呼ぶ。診断用機械データが得られた機器は、異常を検知すべき機器である。データ判定部１１２は、このようにして診断用機械データを求めることで、異常を検知すべき機器を特定する。 The data determination unit 112 frequency-analyzes the Nth data (that is, the machine data acquired by the Nth data acquisition unit 14 from the second data acquisition unit 12) from the second data, and from the second data to the Nth data. , The machine data including the frequency component to be detected obtained by the abnormal frequency component determination unit 111 is obtained. The data determination unit 112 determines that the obtained machine data is data used for diagnosing the state of the device. The machine data determined to be the data used for diagnosing the state of the device is called "diagnosis machine data". The device for which the diagnostic machine data is obtained is the device for which an abnormality should be detected. The data determination unit 112 identifies the device to detect the abnormality by obtaining the diagnostic machine data in this way.
　データ判定部１１２は、第１データ（電気データ）から得られたＫＰＩの値と、診断用機械データから得られたＫＰＩの値を用いて、異常を検知すべき機器の状態の診断に用いるＫＰＩの値を選択する。 The data determination unit 112 uses the KPI value obtained from the first data (electrical data) and the KPI value obtained from the diagnostic machine data to be used for diagnosing the state of the device for which an abnormality should be detected. Select a value for.
　図６は、データ判定部１１２が行う、機器の状態の診断に用いるＫＰＩの値を選択する処理の例を説明する図である。図６には、縦軸に示したＫＰＩの値（例えば、機器の異常や劣化を示す指標の値）が時間とともに増加していく様子を示している。 FIG. 6 is a diagram illustrating an example of a process performed by the data determination unit 112 for selecting a KPI value used for diagnosing the state of the device. FIG. 6 shows how the KPI value shown on the vertical axis (for example, the value of an index indicating an abnormality or deterioration of the device) increases with time.
　データ判定部１１２は、実施例１でのデータ判定部１０１と同様の処理を実行して、異常を検知すべき機器の状態の診断に用いるＫＰＩの値を選択する。 The data determination unit 112 executes the same processing as the data determination unit 101 in the first embodiment, and selects the value of the KPI used for diagnosing the state of the device for which an abnormality should be detected.
　データ判定部１１２は、機器の運転開始時には、機器の状態の診断に用いるＫＰＩの値を、電気データ（第１データ）から得られたＫＰＩの値とし、電気データから得られたＫＰＩの値を分析結果出力部２に出力する。 At the start of operation of the device, the data determination unit 112 sets the KPI value used for diagnosing the state of the device as the KPI value obtained from the electrical data (first data), and sets the KPI value obtained from the electrical data as the KPI value. It is output to the analysis result output unit 2.
　データ判定部１１２は、ＫＰＩの値が時間とともに増加していき、時刻ｔｃにて所定値Ｖｃを超えたら、機器の状態の診断に用いるＫＰＩの値を、診断用機械データ（第２データから第Ｎデータの中から求められたデータ）から得られたＫＰＩの値とし、分析結果出力部２に出力するＫＰＩの値を、電気データから得られたＫＰＩの値から、診断用機械データから得られたＫＰＩの値に切り替える。 The data determination unit 112 increases the KPI value with time, and when the predetermined value Vc is exceeded at the time ct, the KPI value used for diagnosing the state of the device is set to the diagnostic machine data (second data to second data). The KPI value obtained from (data obtained from N data) is used, and the KPI value output to the analysis result output unit 2 is obtained from the diagnostic machine data from the KPI value obtained from the electrical data. Switch to the value of KPI.
　分析結果出力部２は、実施例１での分析結果出力部２と同様に、分析結果処理部１１０が選択し出力したＫＰＩの値を、出力装置に出力するとともに機器の状態の診断に用いる。 Similar to the analysis result output unit 2 in the first embodiment, the analysis result output unit 2 outputs the KPI value selected and output by the analysis result processing unit 110 to the output device and uses it for diagnosing the state of the device.
　本実施例による機器診断システムでは、電気データを用いて機器の状態を診断している間には、第２データ取得部１２から第Ｎデータ取得部１４は、機械センサが機器から機械データを取得する動作を停止するか、機械センサが機械データを取得しても得られたデータを記憶装置に保存しないようにすることができる。機械データを用いて機器の状態を診断している間には、第１データ取得部１１は、電気センサが機器から電気データを取得する動作を停止するか、電気センサが電気データを取得しても得られたデータを記憶装置に保存しないようにすることができる。 In the device diagnosis system according to this embodiment, while the state of the device is diagnosed using electrical data, the machine sensor of the second data acquisition unit 12 to the Nth data acquisition unit 14 acquires machine data from the device. It is possible to stop the operation or prevent the obtained data from being saved in the storage device even if the machine sensor acquires the machine data. While diagnosing the state of the device using the machine data, the first data acquisition unit 11 stops the operation of the electric sensor to acquire the electric data from the device, or the electric sensor acquires the electric data. It is also possible to prevent the obtained data from being stored in the storage device.
　また、本実施例による機器診断システムでは、機械センサが故障などにより機械データを取得できないときは、機器の状態の診断に用いるＫＰＩの値を、ＫＰＩの値の大きさによらず（すなわち、ＫＰＩの値が所定値Ｖｃより大きくても小さくても）、電気センサが取得した電気データから得られたＫＰＩの値とすることができる。このような構成により、本実施例による機器診断システムは、機械センサが故障して使用できなくなっても、電気センサが取得した電気データを利用することで、診断を継続することができる。 Further, in the device diagnosis system according to the present embodiment, when the machine sensor cannot acquire machine data due to a failure or the like, the KPI value used for diagnosing the state of the device is set regardless of the magnitude of the KPI value (that is, KPI). (Whether the value of is larger or smaller than the predetermined value Vc), it can be the value of KPI obtained from the electric data acquired by the electric sensor. With such a configuration, the device diagnosis system according to the present embodiment can continue the diagnosis by using the electric data acquired by the electric sensor even if the mechanical sensor fails and cannot be used.
　本実施例による機器診断システムは、ＫＰＩの値が所定値Ｖｃ以下の場合には、様々な周波数成分を含むデータである電気データから得られたＫＰＩの値を機器の状態の診断に用い、ＫＰＩの値が所定値Ｖｃを超えたら、診断用機械データ（電気データの値が異常を示す周波数成分を含む機械データ）から得られたＫＰＩの値を機器の状態の診断に用いる。本実施例による機器診断システムでは、このようにして、機器の状態の診断に用いるデータ（ＫＰＩの値）を切り替え、異常を検知すべき機器（検知すべき周波数成分を含む機械データが得られた機器）のみについて状態を診断することで、診断に用いるデータ容量を減らすことができ、データを保存する記憶装置にかかる負荷（システム負荷）を抑えつつ、診断精度を確保することができる。 In the device diagnosis system according to this embodiment, when the KPI value is a predetermined value Vc or less, the KPI value obtained from the electrical data which is the data including various frequency components is used for diagnosing the state of the device, and the KPI is used. When the value of KPI exceeds a predetermined value Vc, the value of KPI obtained from the diagnostic machine data (machine data including the frequency component whose electrical data value indicates an abnormality) is used for diagnosing the state of the device. In the device diagnosis system according to this embodiment, the data (KPI value) used for diagnosing the state of the device is switched in this way, and the device for which an abnormality should be detected (machine data including the frequency component to be detected) is obtained. By diagnosing the state of only the device), the data capacity used for the diagnosis can be reduced, and the diagnostic accuracy can be ensured while suppressing the load (system load) on the storage device for storing the data.
　本発明の実施例３による機器診断システムについて、図７と図８を用いて説明する。以下では、実施例２による機器診断システムと異なる点を主に説明する。 The device diagnostic system according to the third embodiment of the present invention will be described with reference to FIGS. 7 and 8. Hereinafter, the differences from the device diagnosis system according to the second embodiment will be mainly described.
　図７は、本実施例による機器診断システムの構成を示す図である。機器診断システムは、Ｎ個のデータ取得部（第１データ取得部１１、第２データ取得部１２、・・・、及び第Ｎデータ取得部１４）と、Ｎ個のデータ分析部（第１データ分析部２１、第２データ分析部２２、及び第Ｎデータ分析部２４）と、分析結果処理部２１０と、分析結果出力部２を備える。 FIG. 7 is a diagram showing the configuration of the device diagnosis system according to this embodiment. The device diagnostic system consists of N data acquisition units (1st data acquisition unit 11, 2nd data acquisition unit 12, ..., and Nth data acquisition unit 14) and N data analysis units (1st data). It includes an analysis unit 21, a second data analysis unit 22 and an Nth data analysis unit 24), an analysis result processing unit 210, and an analysis result output unit 2.
　本実施例による機器診断システムが診断対象とする産業機器システムは、複数の機器を備える。すなわち、産業機器システムは、モータ２００と、モータ２００に接続されたＭ個の機械を備える。Ｍ個の機械は、第１機械２０１、第２機械２０２、第３機械２０３、・・・、及び第Ｍ機械２０４であり、モータ２００に駆動されて作動する任意の装置である。 The industrial equipment system targeted by the equipment diagnosis system according to this embodiment includes a plurality of equipments. That is, the industrial equipment system includes a motor 200 and M machines connected to the motor 200. The M machines are the first machine 201, the second machine 202, the third machine 203, ..., And the M machine 204, which are arbitrary devices driven by the motor 200 and operated.
　第１データ取得部１１は、モータ２００に設置されている。その他のデータ取得部は、Ｍ個の機械のうち一部の機械に設置されている。本実施例では、第２データ取得部１２、・・・、及び第Ｎデータ取得部１４は、それぞれ第２機械２０２、・・・、及び第Ｍ機械２０４に設置されており、第１機械２０１と第３機械２０３には、データ取得部が設置されていない。データ取得部とデータ分析部の数は、産業機器システムが備える機械の数以下である（Ｎ≦Ｍ）。 The first data acquisition unit 11 is installed in the motor 200. Other data acquisition units are installed in some of the M machines. In this embodiment, the second data acquisition unit 12, ..., And the Nth data acquisition unit 14 are installed in the second machine 202, ..., And the M machine 204, respectively, and the first machine 201. And the third machine 203 does not have a data acquisition unit. The number of data acquisition units and data analysis units is less than or equal to the number of machines provided in the industrial equipment system (N ≦ M).
　第１データ取得部１１は、モータ２００に設置されている電気センサを備え、電気センサによって、モータ２００の電気データを取得する。 The first data acquisition unit 11 includes an electric sensor installed in the motor 200, and acquires the electric data of the motor 200 by the electric sensor.
　第１データ分析部２１は、第１データ取得部１１が取得した電気データを第１データとして第１データ取得部１１から取得し、第１データの値から、モータ２００について任意のＫＰＩの値を求める。 The first data analysis unit 21 acquires the electrical data acquired by the first data acquisition unit 11 as the first data from the first data acquisition unit 11, and obtains an arbitrary KPI value for the motor 200 from the value of the first data. Ask.
　第２データ取得部１２は、第２機械２０２に設置されている機械センサを備え、機械センサによって、第２機械２０２の機械データを取得する。 The second data acquisition unit 12 includes a machine sensor installed in the second machine 202, and acquires the machine data of the second machine 202 by the machine sensor.
　第２データ分析部２２は、第２データ取得部１２が取得した機械データを第２データとして第２データ取得部１２から取得し、第２データの値から、第２機械２０２について、第１データ分析部２１が求めたのと同じＫＰＩの値を求める。 The second data analysis unit 22 acquires the machine data acquired by the second data acquisition unit 12 as the second data from the second data acquisition unit 12, and from the value of the second data, the first data for the second machine 202. The same KPI value as that obtained by the analysis unit 21 is obtained.
　第１データ分析部２１から第Ｎデータ分析部２４は、求めたＫＰＩの値を分析結果処理部２１０に供給するとともに、第１データから第Ｎデータをそれぞれ分析結果処理部２１０に供給する。 The first data analysis unit 21 to the Nth data analysis unit 24 supply the obtained KPI value to the analysis result processing unit 210, and supply the Nth data from the first data to the analysis result processing unit 210, respectively.
　第１機械２０１と第３機械２０３にはデータ取得部が設置されていないので、分析結果処理部２１０は、第１機械２０１と第３機械２０３の機械データを取得しない。 Since the data acquisition unit is not installed in the first machine 201 and the third machine 203, the analysis result processing unit 210 does not acquire the machine data of the first machine 201 and the third machine 203.
　分析結果処理部２１０は、実施例２での分析結果処理部１１０（図５）と同様の構成を備え、異常周波数成分判定部１１１と、データ判定部１１２を備える。 The analysis result processing unit 210 has the same configuration as the analysis result processing unit 110 (FIG. 5) in the second embodiment, and includes an abnormal frequency component determination unit 111 and a data determination unit 112.
　分析結果処理部２１０は、データ取得部が設置された機械（第２機械２０２、・・・、及び第Ｍ機械２０４）については、実施例２と同様にして、状態を診断する。分析結果処理部２１０は、データ取得部が設置されていない機械（第１機械２０１と第３機械２０３）については、以下に説明する処理を行って状態を診断する。 The analysis result processing unit 210 diagnoses the state of the machines (second machine 202, ..., And M machine 204) in which the data acquisition unit is installed in the same manner as in the second embodiment. The analysis result processing unit 210 diagnoses the state of the machines (first machine 201 and third machine 203) in which the data acquisition unit is not installed by performing the processing described below.
　図８は、データ判定部１１２が行う、機器の状態の診断に用いるＫＰＩの値を選択する処理の例を説明する図である。 FIG. 8 is a diagram illustrating an example of a process performed by the data determination unit 112 for selecting a KPI value used for diagnosing the state of the device.
　上述したように、データ判定部１１２は、データ取得部が設置された機械（第２機械２０２、・・・、及び第Ｍ機械２０４）については、実施例２と同様にして、状態を診断する。図８には、データ判定部１１２が、第２機械２０２の状態の診断に用いるＫＰＩの値を選択する例を示している。データ判定部１１２は、第２機械２０２の状態の診断に用いるＫＰＩの値を、機器の運転開始時には、電気データから得られたＫＰＩの値とし、このＫＰＩの値が所定値Ｖｃを超えたら、診断用機械データから得られたＫＰＩの値とする。 As described above, the data determination unit 112 diagnoses the state of the machines (second machine 202, ..., And M machine 204) in which the data acquisition unit is installed in the same manner as in the second embodiment. .. FIG. 8 shows an example in which the data determination unit 112 selects the value of the KPI used for diagnosing the state of the second machine 202. The data determination unit 112 sets the KPI value used for diagnosing the state of the second machine 202 as the KPI value obtained from the electrical data at the start of operation of the device, and when the KPI value exceeds the predetermined value Vc, It is the value of KPI obtained from the diagnostic machine data.
　データ判定部１１２は、データ取得部が設置されていない機械（第１機械２０１と第３機械２０３）については、ＫＰＩの値の大きさによらず（すなわち、診断に用いるＫＰＩの値が所定値Ｖｃより大きくても小さくても）、電気データから得られたＫＰＩの値（モータ２００についてのＫＰＩの値）のみを用いて状態を診断する。図８には、データ判定部１１２が、第１機械２０１の状態の診断に、電気データから得られたＫＰＩの値のみを用いる例を示している。 The data determination unit 112 does not depend on the size of the KPI value (that is, the KPI value used for diagnosis is a predetermined value) for the machines (first machine 201 and third machine 203) in which the data acquisition unit is not installed. The condition is diagnosed using only the KPI value (KPI value for the motor 200) obtained from the electrical data (whether larger or smaller than Vc). FIG. 8 shows an example in which the data determination unit 112 uses only the KPI value obtained from the electrical data for diagnosing the state of the first machine 201.
　分析結果出力部２は、第１データ分析部２１から第Ｎデータ分析部２４が求めたＫＰＩの値と、ＫＰＩの値を用いた機器の状態の診断結果を、出力装置に出力する。 The analysis result output unit 2 outputs the KPI value obtained by the Nth data analysis unit 24 from the first data analysis unit 21 and the diagnosis result of the state of the device using the KPI value to the output device.
　本実施例による機器診断システムでは、診断対象とする産業機器システムが備える複数の機器の全てにセンサを設置する必要がなく、特定の機器（例えば、産業機器システムの全体の運転に影響を与えるような重要な機器）にのみ機械センサを設置することができる。機械センサが設置されてなくモータ２００に接続されている機器については、電気データから得られたＫＰＩの値を用いて状態を診断する。機械センサが設置されている機器については、電気データから得られたＫＰＩの値と機械データから得られたＫＰＩの値を用いて状態を診断する。 In the device diagnostic system according to this embodiment, it is not necessary to install sensors in all of the plurality of devices included in the industrial device system to be diagnosed, so as to affect the operation of a specific device (for example, the entire operation of the industrial device system). Mechanical sensors can only be installed in (important equipment). For equipment without a mechanical sensor installed and connected to the motor 200, the state is diagnosed using the KPI value obtained from the electrical data. For the equipment in which the mechanical sensor is installed, the state is diagnosed using the KPI value obtained from the electrical data and the KPI value obtained from the mechanical data.
　また、機械センサが設置されていない機器について詳細に診断をしたい場合には、正常に動作している機器から機械センサを取り外し、取り外した機械センサを診断したい機器に設置してもよい。これにより、機器診断システムが使用するセンサの数を低減するとともに、システム全体の状態を診断することができる。 If you want to make a detailed diagnosis of a device that does not have a mechanical sensor installed, you may remove the mechanical sensor from the device that is operating normally and install the removed mechanical sensor in the device you want to diagnose. As a result, the number of sensors used in the device diagnosis system can be reduced, and the state of the entire system can be diagnosed.
　本実施例による機器診断システムは、以上の構成を備え、診断に用いるデータ容量を減らすことができ、データを保存する記憶装置にかかる負荷（システム負荷）を抑えつつ、診断精度を確保することができる。 The device diagnostic system according to this embodiment has the above configuration, can reduce the data capacity used for diagnosis, and can secure diagnostic accuracy while suppressing the load (system load) on the storage device for storing data. can.
　本発明の実施例４による機器診断システムについて、説明する。以下では、実施例１による機器診断システムと異なる点を主に説明する。 The device diagnostic system according to the fourth embodiment of the present invention will be described. Hereinafter, the differences from the device diagnosis system according to the first embodiment will be mainly described.
　本実施例による機器診断システムは、機器に設置された複数のセンサのうち、任意のセンサが正常に動作しているか否かを、他のセンサと比較することで判定することができる。例えば、本実施例による機器診断システムでは、機器に設置された複数のセンサのうち診断に暫く使われていないセンサを診断に使用するときには、診断に使われている他のセンサと比較することで、診断に暫く使われていなかったセンサが正常に動作するか否かを判定することができる。 The device diagnostic system according to this embodiment can determine whether or not any sensor is operating normally among a plurality of sensors installed in the device by comparing with other sensors. For example, in the device diagnostic system according to this embodiment, when a sensor that has not been used for a while for diagnosis among a plurality of sensors installed in the device is used for diagnosis, it is compared with other sensors used for diagnosis. , It is possible to determine whether or not a sensor that has not been used for diagnosis for a while operates normally.
　以下では、一例として、機械センサが正常に動作しているか否かを、電気センサと比較することで判定する場合について説明する。より具体的には、正常に動作しているか否かを判定したいセンサが、診断に暫く使われていない機械センサであり、この機械センサと比較されるセンサが、診断に使われている電気センサである例について説明する。なお、電気センサは、通常は、常に動作している。 In the following, as an example, a case where it is determined by comparing with an electric sensor whether or not the mechanical sensor is operating normally will be described. More specifically, the sensor for which it is desired to determine whether or not it is operating normally is a mechanical sensor that has not been used for a while for diagnosis, and the sensor to be compared with this mechanical sensor is an electric sensor used for diagnosis. An example is described. The electric sensor is usually always in operation.
　分析結果処理部１（図１）は、診断に暫く使われていない機械センサを診断に使用するときには、この機械センサが取得したデータから得られたＫＰＩの値と、診断に使われている電気センサが取得したデータから得られたＫＰＩの値とを比較する。分析結果処理部１は、例えば、これらのＫＰＩの値を規格化して互いに比較する。分析結果処理部１は、機械センサが取得したデータから得られたＫＰＩの値と、電気センサが取得したデータから得られたＫＰＩの値の差が、予め定めた閾値より小さい場合には、機械センサが正常であると判定する。この閾値は、センサが設置された機器、及びセンサの仕様などに応じて任意に定めることができ、ＫＰＩの値を比較のために規格化した場合には、ＫＰＩの値の規格化方法も考慮して定めることができる。 When the analysis result processing unit 1 (FIG. 1) uses a mechanical sensor that has not been used for diagnosis for a while, the KPI value obtained from the data acquired by this mechanical sensor and the electricity used for the diagnosis Compare with the value of KPI obtained from the data acquired by the sensor. The analysis result processing unit 1 standardizes the values of these KPIs and compares them with each other, for example. When the difference between the KPI value obtained from the data acquired by the machine sensor and the KPI value obtained from the data acquired by the electric sensor is smaller than the predetermined threshold value, the analysis result processing unit 1 performs the machine. Determine that the sensor is normal. This threshold value can be arbitrarily set according to the equipment on which the sensor is installed, the specifications of the sensor, etc., and when the KPI value is standardized for comparison, the standardization method of the KPI value is also considered. Can be determined.
　本実施例による機器診断システムでは、機器に設置されたセンサが正常に動作しているか否かを判定することができ、例えば、この判定を定期的に行うことで、使われる頻度が少ないセンサの正常性を定期的に診断することができる。 In the device diagnostic system according to this embodiment, it is possible to determine whether or not the sensor installed in the device is operating normally. For example, by performing this determination periodically, a sensor that is rarely used can be determined. Normality can be diagnosed on a regular basis.
　本発明の実施例５による機器診断システムについて、図９と図１０を用いて説明する。以下では、実施例１による機器診断システムと異なる点を主に説明する。本実施例による機器診断システムは、産業機器システムとして、自動車、鉄道、及びエレベータなどの移動体を診断対象とし、移動体に設置された機器の状態を診断する。 The device diagnostic system according to the fifth embodiment of the present invention will be described with reference to FIGS. 9 and 10. Hereinafter, the differences from the device diagnosis system according to the first embodiment will be mainly described. As an industrial equipment system, the equipment diagnosis system according to the present embodiment targets moving objects such as automobiles, railroads, and elevators, and diagnoses the state of the equipment installed on the moving objects.
　本実施例による機器診断システムは、実施例１による機器診断システム（図１）と同様に、センサを備えるデータ取得部、データ分析部、分析結果処理部１、及び分析結果出力部２を備える。本実施例による機器診断システムでは、データ分析部と分析結果処理部１と分析結果出力部２は、実施例１による機器診断システムと同様の構成を備える。以下では、主に、本実施例による機器診断システムが備えるデータ取得部について説明する。 The device diagnosis system according to the present embodiment includes a data acquisition unit including a sensor, a data analysis unit, an analysis result processing unit 1, and an analysis result output unit 2, similar to the device diagnosis system according to the first embodiment (FIG. 1). In the device diagnosis system according to the present embodiment, the data analysis unit, the analysis result processing unit 1, and the analysis result output unit 2 have the same configuration as the device diagnosis system according to the first embodiment. Hereinafter, the data acquisition unit included in the device diagnostic system according to the present embodiment will be mainly described.
　図９は、本実施例による機器診断システムが備えるデータ取得部を示す図である。データ取得部が備えるセンサは、移動体３０１に設置されている。 FIG. 9 is a diagram showing a data acquisition unit included in the device diagnosis system according to the present embodiment. The sensor included in the data acquisition unit is installed in the mobile body 301.
　移動体３０１は、例えば自動車、鉄道、及びエレベータであり、移動体３０１を駆動する構成要素である駆動部３０３を備える。駆動部３０３は、例えばモータ及びギアを備える。 The mobile body 301 is, for example, an automobile, a railroad, and an elevator, and includes a drive unit 303 which is a component for driving the mobile body 301. The drive unit 303 includes, for example, a motor and gears.
　本実施例による機器診断システムは、データ取得部として、移動体データ取得部３０２と駆動部データ取得部３０４を備える。移動体データ取得部３０２と駆動部データ取得部３０４は、センサ、またはセンサを備えるデータ取得回路を備える。これらのセンサは、移動体３０１が備える機器と駆動部３０３が備える機器に設置されている。 The device diagnosis system according to this embodiment includes a mobile data acquisition unit 302 and a drive unit data acquisition unit 304 as data acquisition units. The mobile data acquisition unit 302 and the drive unit data acquisition unit 304 include a sensor or a data acquisition circuit including the sensor. These sensors are installed in the device included in the mobile body 301 and the device included in the drive unit 303.
　移動体データ取得部３０２は、移動体３０１自身の位置、速度、振動、温度、音、及び圧力などの物理量を測定するセンサを備え、移動体３０１の物理量のデータである移動体データを、センサによって取得する。 The moving body data acquisition unit 302 includes a sensor for measuring physical quantities such as the position, speed, vibration, temperature, sound, and pressure of the moving body 301 itself, and the moving body data which is the physical quantity data of the moving body 301 is sensored. Get by.
　駆動部データ取得部３０４は、駆動部３０３の電流、電圧、振動、圧力、温度、及び音などの物理量を測定するセンサを備え、駆動部３０３の物理量のデータである駆動部データを、センサによって取得する。 The drive unit data acquisition unit 304 includes a sensor for measuring physical quantities such as current, voltage, vibration, pressure, temperature, and sound of the drive unit 303, and the drive unit data which is data of the physical quantity of the drive unit 303 is obtained by the sensor. get.
　分析結果処理部１のデータ判定部１０１（図２）は、移動体データから得られたＫＰＩの値（例えば、移動体３０１の異常や劣化を示す指標の値）と、駆動部データから得られたＫＰＩの値（例えば、駆動部３０３の異常や劣化を示す指標の値）を用いて、移動体３０１の状態の診断に用いるＫＰＩの値を選択する。 The data determination unit 101 (FIG. 2) of the analysis result processing unit 1 is obtained from the KPI value obtained from the moving body data (for example, the value of an index indicating abnormality or deterioration of the moving body 301) and the driving unit data. The value of KPI used for diagnosing the state of the moving body 301 is selected by using the value of KPI (for example, the value of an index indicating abnormality or deterioration of the driving unit 303).
　図１０は、データ判定部１０１が行う、移動体３０１の状態の診断に用いるＫＰＩの値を選択する処理の例を説明する図である。図１０には、縦軸に示したＫＰＩの値が時間とともに増加していく様子を示している。ＫＰＩの値は、時間とともに増加していき、閾値であるＶｔを超えると移動体３０１に異常が発生したことを示す。 FIG. 10 is a diagram illustrating an example of a process performed by the data determination unit 101 for selecting a KPI value used for diagnosing the state of the moving body 301. FIG. 10 shows how the value of KPI shown on the vertical axis increases with time. The value of KPI increases with time, and when it exceeds the threshold value Vt, it indicates that an abnormality has occurred in the moving body 301.
　データ判定部１０１は、移動体３０１の運転開始時には、機器の状態の診断に用いるＫＰＩの値を、移動体データから得られたＫＰＩの値とする。すなわち、データ判定部１０１は、移動体３０１の運転開始時には、移動体データから得られたＫＰＩの値を、移動体３０１の状態の診断に用いる。 At the start of operation of the mobile body 301, the data determination unit 101 sets the KPI value used for diagnosing the state of the device as the KPI value obtained from the mobile body data. That is, at the start of operation of the mobile body 301, the data determination unit 101 uses the KPI value obtained from the mobile body data for diagnosing the state of the mobile body 301.
　データ判定部１０１は、移動体データの値が異常を示した場合には、駆動部データの値を用いて、駆動部３０３の状態から異常の原因を調べる。データ判定部１０１は、移動体データから得られたＫＰＩの値が時間とともに増加していき、時刻ｔｄにて閾値Ｖｔを超えたら、移動体３０１の状態の診断に用いるＫＰＩの値を、駆動部データから得られたＫＰＩの値に切り替える。 When the value of the moving object data indicates an abnormality, the data determination unit 101 investigates the cause of the abnormality from the state of the drive unit 303 by using the value of the drive unit data. The data determination unit 101 increases the KPI value obtained from the moving body data with time, and when the threshold value Vt is exceeded at the time dt, the data determining unit 101 sets the KPI value used for diagnosing the state of the moving body 301 to the driving unit. Switch to the KPI value obtained from the data.
　すなわち、データ判定部１０１は、移動体データから得られたＫＰＩの値が時刻ｔｄにて閾値Ｖｔを超えたら、移動体３０１に異常が発生したと判断し、駆動部データから得られたＫＰＩの値を用いて、異常の原因である駆動部３０３が何かを推定する。例えば、データ判定部１０１は、駆動部データから得られたＫＰＩの値が正常時と異なる値を示す駆動部３０３を探し、正常時と異なるＫＰＩの値を示す駆動部３０３を異常の原因である駆動部３０３と推定する。このようにして、本実施例による機器診断システムは、移動体３０１の異常を検知し、異常の原因を推定することができる。 That is, when the value of the KPI obtained from the moving body data exceeds the threshold value Vt at the time td, the data determination unit 101 determines that an abnormality has occurred in the moving body 301, and determines that an abnormality has occurred in the moving body 301, and the KPI obtained from the driving unit data. The value is used to estimate what the drive unit 303 is, which is the cause of the abnormality. For example, the data determination unit 101 searches for a drive unit 303 in which the KPI value obtained from the drive unit data is different from the normal time, and causes the drive unit 303 in which the KPI value different from the normal time is different from the normal time. It is estimated to be the drive unit 303. In this way, the device diagnosis system according to the present embodiment can detect the abnormality of the mobile body 301 and estimate the cause of the abnormality.
　本実施例による機器診断システムでは、以上のようにして、移動体３０１の状態の診断に用いるデータ（ＫＰＩの値）を切り替えることで、診断に用いるデータ容量を減らすことができ、データを保存する記憶装置にかかる負荷（システム負荷）を抑えつつ、診断精度を確保することができる。 In the device diagnosis system according to the present embodiment, by switching the data (KPI value) used for diagnosing the state of the moving body 301 as described above, the data capacity used for the diagnosis can be reduced and the data is stored. Diagnostic accuracy can be ensured while suppressing the load on the storage device (system load).
　なお、本発明は、上記の実施例に限定されるものではなく、様々な変形が可能である。例えば、上記の実施例は、本発明を分かりやすく説明するために詳細に説明したものであり、本発明は、必ずしも説明した全ての構成を備える態様に限定されるものではない。また、ある実施例の構成の一部を他の実施例の構成に置き換えることが可能である。また、ある実施例の構成に他の実施例の構成を加えることも可能である。また、各実施例の構成の一部について、削除したり、他の構成を追加・置換したりすることが可能である。 The present invention is not limited to the above embodiment, and various modifications are possible. For example, the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to the embodiment including all the described configurations. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment. It is also possible to add the configuration of another embodiment to the configuration of one embodiment. Further, it is possible to delete a part of the configuration of each embodiment and add / replace another configuration.
　１…分析結果処理部、２…分析結果出力部、１１…第１データ取得部、１２…第２データ取得部、１３…第３データ取得部、１４…第Ｎデータ取得部、２１…第１データ分析部、２２…第２データ分析部、２３…第３データ分析部、２４…第Ｎデータ分析部、１０１…データ判定部、１０２…データ切替部、１１０…分析結果処理部、１１１…異常周波数成分判定部、１１２…データ判定部、２００…モータ、２０１…第１機械、２０２…第２機械、２０３…第３機械、２０４…第Ｍ機械、２１０…分析結果処理部、３０１…移動体、３０２…移動体データ取得部、３０３…駆動部、３０４…駆動部データ取得部。 1 ... Analysis result processing unit, 2 ... Analysis result output unit, 11 ... First data acquisition unit, 12 ... Second data acquisition unit, 13 ... Third data acquisition unit, 14 ... Nth data acquisition unit, 21 ... First Data analysis unit, 22 ... 2nd data analysis unit, 23 ... 3rd data analysis unit, 24 ... Nth data analysis unit, 101 ... data judgment unit, 102 ... data switching unit, 110 ... analysis result processing unit, 111 ... abnormality Frequency component determination unit, 112 ... Data determination unit, 200 ... Motor, 201 ... First machine, 202 ... Second machine, 203 ... Third machine, 204 ... M machine, 210 ... Analysis result processing unit, 301 ... Moving object , 302 ... Moving object data acquisition unit, 303 ... Drive unit, 304 ... Drive unit data acquisition unit.

Claims (9)

  1. 　機器に設置された、互いに異なる物理量を測定する複数のセンサと、
    　前記センサが取得したデータから、前記センサが設置された前記機器の状態を示す指標の値を求めるデータ分析部と、
    　前記機器の状態の診断に用いる前記指標の値を選択する処理部と、
    　前記処理部が選択した前記指標の値を出力する出力部と、
    を備え、
    　複数の前記センサは、第１のセンサと第２のセンサを備え、
    　前記処理部は、
    前記機器の状態の診断に用いる前記指標の値を、前記第１のセンサが取得したデータから得られた前記指標の値とし、
    前記第１のセンサが取得したデータから得られた前記指標の値が予め定めた値を超えたら、前記機器の状態の診断に用いる前記指標の値を、前記第２のセンサが取得したデータから得られた前記指標の値とする、
    ことを特徴とする機器診断システム。     Multiple sensors installed in the device to measure different physical quantities and
    From the data acquired by the sensor, a data analysis unit that obtains the value of an index indicating the state of the device in which the sensor is installed, and a data analysis unit.
    A processing unit that selects the value of the index used for diagnosing the state of the device, and
    An output unit that outputs the value of the index selected by the processing unit, and
    Equipped with
    The plurality of said sensors include a first sensor and a second sensor.
    The processing unit
    The value of the index used for diagnosing the state of the device is taken as the value of the index obtained from the data acquired by the first sensor.
    When the value of the index obtained from the data acquired by the first sensor exceeds a predetermined value, the value of the index used for diagnosing the state of the device is obtained from the data acquired by the second sensor. The value of the obtained index,
    A device diagnostic system characterized by that.
  2. 　前記第１のセンサは、電気的物理量を測定する電気センサであり、
    　前記第２のセンサは、機械的物理量を測定する機械センサである、
    請求項１に記載の機器診断システム。     The first sensor is an electric sensor that measures an electrical physical quantity, and is an electric sensor.
    The second sensor is a mechanical sensor that measures a mechanical physical quantity.
    The device diagnostic system according to claim 1.
  3. 　前記機器は、移動体に設置されており、
    　前記第１のセンサは、前記移動体の物理量を測定するセンサであり、
    　前記第２のセンサは、前記移動体を駆動する駆動部の物理量を測定するセンサである、請求項１に記載の機器診断システム。     The device is installed on a moving body and
    The first sensor is a sensor that measures a physical quantity of the moving body.
    The device diagnostic system according to claim 1, wherein the second sensor is a sensor that measures a physical quantity of a driving unit that drives the moving body.
  4. 　前記予め定めた値は、閾値より小さい値であり、
    　前記閾値は、前記指標の値が前記閾値を超えると、前記機器に異常が発生したとみなすことができる値である、
    請求項１に記載の機器診断システム。     The predetermined value is smaller than the threshold value and is smaller than the threshold value.
    The threshold value is a value at which it can be considered that an abnormality has occurred in the device when the value of the index exceeds the threshold value.
    The device diagnostic system according to claim 1.
  5. 　前記処理部は、前記機械センサがデータを取得できないときは、前記機器の状態の診断に用いる前記指標の値を、前記指標の値の大きさによらず、前記電気センサが取得したデータから得られた前記指標の値とする、
    請求項２に記載の機器診断システム。     When the mechanical sensor cannot acquire data, the processing unit obtains the value of the index used for diagnosing the state of the device from the data acquired by the electric sensor regardless of the magnitude of the value of the index. It shall be the value of the above-mentioned index.
    The device diagnostic system according to claim 2.
  6. 　前記第２のセンサは、前記機器の状態の診断に用いる前記指標の値が、前記第１のセンサが取得したデータから得られた前記指標の値である場合には、データを取得する動作を停止する、または取得したデータを記憶装置に保存せず、
    　前記第１のセンサは、前記機器の状態の診断に用いる前記指標の値が、前記第２のセンサが取得したデータから得られた前記指標の値である場合には、データを取得する動作を停止する、または取得したデータを記憶装置に保存しない、
    請求項１に記載の機器診断システム。     The second sensor operates to acquire data when the value of the index used for diagnosing the state of the device is the value of the index obtained from the data acquired by the first sensor. Stop or do not save the acquired data in storage
    The first sensor operates to acquire data when the value of the index used for diagnosing the state of the device is the value of the index obtained from the data acquired by the second sensor. Stop or do not save the acquired data in storage
    The device diagnostic system according to claim 1.
  7. 　複数の前記センサは、複数の前記機器に設置され、
    　前記機械センサは、複数の前記機器のうち一部の前記機器に設置されており、
    　前記処理部は、前記機械センサが設置されていない前記機器の状態の診断に用いる前記指標の値を、前記指標の値の大きさによらず、前記電気センサが取得したデータから得られた前記指標の値とする、
    請求項２に記載の機器診断システム。     The plurality of said sensors are installed in the plurality of said devices, and the plurality of said sensors are installed in the plurality of said devices.
    The mechanical sensor is installed in some of the devices among the plurality of devices.
    The processing unit obtains the value of the index used for diagnosing the state of the device in which the mechanical sensor is not installed from the data acquired by the electric sensor regardless of the magnitude of the value of the index. Use as the index value,
    The device diagnostic system according to claim 2.
  8. 　前記第１のセンサは、前記第２のセンサよりも長いサンプリング時間でデータを取得する、
    請求項１に記載の機器診断システム。     The first sensor acquires data in a longer sampling time than the second sensor.
    The device diagnostic system according to claim 1.
  9. 　前記処理部は、前記第１のセンサが取得したデータから得られた前記指標の値と、前記第２のセンサが取得したデータから得られた前記指標の値の差が、予め定めた閾値より小さい場合には、前記第２のセンサが正常であると判定する、
    請求項１に記載の機器診断システム。     In the processing unit, the difference between the value of the index obtained from the data acquired by the first sensor and the value of the index obtained from the data acquired by the second sensor is greater than a predetermined threshold value. If it is small, it is determined that the second sensor is normal.
    The device diagnostic system according to claim 1.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005122411A (en) * 2003-10-16 2005-05-12 Hioki Ee Corp Sequencer monitoring device
JP2011153840A (en) * 2010-01-26 2011-08-11 Hitachi Ltd Apparatus and method for diagnosis of electric equipment, and diagnostic device mounting body
WO2018052015A1 (en) * 2016-09-14 2018-03-22 日本電気株式会社 Analysis support device for system, analysis support method and program for system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005122411A (en) * 2003-10-16 2005-05-12 Hioki Ee Corp Sequencer monitoring device
JP2011153840A (en) * 2010-01-26 2011-08-11 Hitachi Ltd Apparatus and method for diagnosis of electric equipment, and diagnostic device mounting body
WO2018052015A1 (en) * 2016-09-14 2018-03-22 日本電気株式会社 Analysis support device for system, analysis support method and program for system

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