WO2018083746A1 - Appareil de diagnostic d'installation et procédé de diagnostic d'installation - Google Patents

Appareil de diagnostic d'installation et procédé de diagnostic d'installation Download PDF

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Publication number
WO2018083746A1
WO2018083746A1 PCT/JP2016/082537 JP2016082537W WO2018083746A1 WO 2018083746 A1 WO2018083746 A1 WO 2018083746A1 JP 2016082537 W JP2016082537 W JP 2016082537W WO 2018083746 A1 WO2018083746 A1 WO 2018083746A1
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Prior art keywords
feature
abnormality
detection
value
facility
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PCT/JP2016/082537
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English (en)
Japanese (ja)
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一夫 伊藤
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愛知機械工業株式会社
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Application filed by 愛知機械工業株式会社 filed Critical 愛知機械工業株式会社
Priority to JP2018548493A priority Critical patent/JP6786181B2/ja
Priority to PCT/JP2016/082537 priority patent/WO2018083746A1/fr
Publication of WO2018083746A1 publication Critical patent/WO2018083746A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M99/00—Subject matter not provided for in other groups of this subclass

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  • the present invention relates to a facility diagnosis apparatus and a facility diagnosis method for diagnosing a facility abnormality including a first device capable of detecting an abnormality with a first feature amount and a second device capable of detecting an abnormality with a second feature amount.
  • Patent Document 1 discloses a diagnosis for diagnosing abnormality of a rotating device including a motor and a pump having a rotating body supported by a rotating shaft of the motor via a bearing. An apparatus is described.
  • vibration waveform data is detected by a vibration meter attached to the bearing, and the detected vibration waveform data is directly detected, vibration waveform data obtained by subjecting the detected vibration waveform data to envelope processing, and detected vibration waveform data.
  • Each of the vibration waveform data after the predetermined number of data is thinned out is subjected to FFT analysis to detect which component of the rotating device has an abnormality. That is, by detecting one feature quantity of the vibration waveform data of the bearing, applying various processes to the feature quantity and performing FFT analysis, it is specified which component has an abnormality.
  • the present invention has been made in view of the above, and in equipment including a plurality of devices or component parts having different feature amounts suitable for abnormality detection, it is possible to reliably identify the device / component part in which the abnormality has occurred.
  • An object of the present invention is to provide a facility diagnosis apparatus that can perform such a process.
  • the equipment diagnostic apparatus and method of the present invention employ the following means in order to achieve the above-described object.
  • an abnormality of equipment comprising a first device capable of detecting an abnormality with the first feature quantity and a second device capable of detecting an abnormality with the second feature quantity is diagnosed.
  • An equipment diagnostic device is configured.
  • the facility diagnosis apparatus includes a first detection unit that detects a first feature amount, a second detection unit that detects a second feature amount, and a first feature amount and a second detection unit that are detected by the first detection unit.
  • Frequency analysis means for analyzing the frequency of the detected second feature value, and device specifying means for specifying a device in which an abnormality has occurred based on an analysis result by the frequency analysis means.
  • apparatus in the present invention is defined as a concept including components constituting the facility.
  • each feature quantity is detected separately and frequency analysis is performed separately, and the analysis result is based on the analysis result. Therefore, it is possible to reliably identify which device / component is abnormal.
  • the device since it is possible to perform a single device from detection of multiple feature values to identification of devices / components in which an abnormality has occurred, the device is simplified and costs are reduced compared to the case where a device is provided for each feature value. Can be achieved.
  • the facility diagnosis apparatus further includes instruction means for instructing start of detection of the first and second feature values by the first and second detection means.
  • the instruction means controls the first detection means so as to start the detection of the first feature value at the first timing and to continue the detection of the first feature value for the first time.
  • the detection of the second feature value is started at the timing, and the second detection unit is controlled so as to continue the detection of the second feature value for the second time.
  • each feature amount can be detected at a timing and detection section suitable for abnormality detection, so that abnormality diagnosis can be performed after eliminating unnecessary data for abnormality diagnosis, and the diagnosis speed is improved.
  • the instruction means is configured to set the first and second timings based on the third feature amount.
  • the third feature value different from the first and second feature values suitable for detecting an abnormality of each device / component for example, the operating state of the equipment (the equipment is executing a predetermined process)
  • the detection start timing of the first and second feature amounts based on the feature amount suitable for detecting whether the facility is in the idle state before the execution of the predetermined process, or the like.
  • the detection sensitivity of the first and second feature amounts depends on the third feature amount, for example, when the detection sensitivity depends on the operating state of the equipment, the first and second timings have good detection sensitivity.
  • the feature amount can be detected. As a result, it is possible to perform abnormality diagnosis after eliminating data unnecessary for abnormality diagnosis, to improve the diagnosis speed, and to detect an abnormality of a device / component more accurately.
  • the third feature amount is an amount calculated based on at least one of the first and second feature amounts.
  • the detection start timing of the first and second feature values can be easily set.
  • the facility diagnosis apparatus further comprises storage means for storing the first and second feature quantities detected by the first and second detection means.
  • the first and second detection means are configured to detect the first and second feature amounts every first predetermined time.
  • the frequency analysis means is configured to perform frequency analysis after extracting at least one of the stored first and second feature quantities at a second predetermined time interval longer than the first predetermined time.
  • the first and second feature quantities are detected at the same time interval, control can be facilitated, and when performing frequency analysis, abnormalities are detected from the detected feature quantities. Since only the value (number of data) suitable for detection is extracted and frequency analysis is performed, abnormality diagnosis can be performed after removing low-sensitivity data unnecessary for abnormality diagnosis, and diagnostic speed can be improved. Can be planned.
  • the second predetermined time is set as a value that is an integer multiple of the first predetermined time.
  • an abnormality of a facility comprising a first device capable of detecting an abnormality with a first feature amount and a second device capable of detecting an abnormality with a second feature amount is diagnosed.
  • a facility diagnosis method is configured. In the equipment diagnosis method, (a) the first and second feature values are detected, (b) the detected first and second feature values are frequency-analyzed, and (c) the abnormality is based on the result of the frequency analysis. Identify the device where the problem occurred.
  • apparatus in the present invention is defined as a concept including components constituting the facility.
  • each feature quantity is detected separately and frequency analysis is performed separately, and the analysis result is based on the analysis result. Therefore, it is possible to reliably identify which device / component is abnormal.
  • it is possible to perform detection from multiple feature quantities to identification of abnormal devices / components with a single device it is possible to simplify the device and reduce costs compared to the case where a device is provided for each feature amount. Can do.
  • the method further comprises (d) a step of instructing start of detection of the first and second feature values.
  • step (d) the detection of the first feature value is started at the first timing, the detection of the first feature value is continued for the first time, and the second feature value is detected at the second timing.
  • the detection of the second feature amount is continued for the second time after the detection is started.
  • detection can be performed at a timing and detection interval suitable for abnormality detection, so that abnormality diagnosis can be performed after eliminating data unnecessary for abnormality diagnosis, and the diagnosis speed can be improved.
  • detection speed can be improved.
  • step (d) is a step of setting the first and second timings based on the third feature amount.
  • the third feature value different from the first and second feature values suitable for detecting an abnormality of each device / component for example, the operating state of the equipment (the equipment is executing a predetermined process)
  • the detection start timing of the first and second feature amounts based on the feature amount suitable for detecting whether the facility is in the idle state before the execution of the predetermined process, or the like.
  • the detection sensitivity of the first and second feature amounts depends on the third feature amount, for example, when the detection sensitivity depends on the operating state of the equipment, the first and second timings have good detection sensitivity.
  • the feature amount can be detected. As a result, it is possible to perform abnormality diagnosis after eliminating data unnecessary for abnormality diagnosis, to improve the diagnosis speed, and to detect an abnormality of a device / component more accurately.
  • step (d) is a step of calculating a third feature quantity based on at least one of the first and second feature quantities.
  • the detection start timing of the first and second feature values can be easily set.
  • the method further comprises the step of (e) storing the detected first and second feature quantities.
  • Step (a) is a step of detecting the first and second feature values every first predetermined time.
  • Step (b) is a step of performing frequency analysis after extracting at least one of the stored first and second feature quantities at a second predetermined time interval longer than the first predetermined time.
  • the first and second feature quantities are detected at the same time interval, control can be facilitated, and when performing frequency analysis, abnormalities are detected from the detected feature quantities. Since only the value (number of data) suitable for detection is extracted and frequency analysis is performed, abnormality diagnosis can be performed after removing low-sensitivity data unnecessary for abnormality diagnosis, and diagnostic speed can be improved. Can be planned.
  • step (b) is a step of setting the second predetermined time as a value that is an integer multiple of the first predetermined time.
  • an equipment diagnosis apparatus that can reliably identify equipment / components in which an abnormality has occurred in equipment comprising a plurality of equipment / components having different feature quantities suitable for abnormality detection. Can do.
  • FIG. 5 is a flowchart illustrating an example of an abnormal device identification process executed by the abnormality determination device 2.
  • the time change of the power value P calculated from the current value I and the voltage value V extracted at 20 msec intervals, and the current value I, vibration value fa, extracted at each extraction interval (0.25 msec, 0.5 msec, 20 msec) It is explanatory drawing which shows the time change of fb and stress ST. It is explanatory drawing which shows the frequency analysis result of the extracted electric current value I, vibration value fa, fb, and stress ST.
  • the facility diagnosis apparatus 1 includes an abnormality determination device 2 that is electrically connected to a processing facility 10 that performs processing on a workpiece W.
  • the apparatus is configured as a device for diagnosing whether or not an abnormality has occurred in a component.
  • the facility diagnosis apparatus 1 corresponds to the “diagnosis apparatus” in the present invention
  • the processing facility 10 is an example of an implementation configuration corresponding to the “equipment” in the present invention.
  • the processing facility 10 includes a fixed base 12 that fixes the workpiece W, a slide table 14 that is slidably attached to the fixed base 12, and a gear box GB that is fixed to the slide table 14.
  • the blade BLD attached to the gear box GB via the tool holder 15, the spindle motor M1 connected to the gear box GB via the belt BLT, and the ball screw for sliding the slide table 14 relative to the fixed base 12.
  • an AC servo amplifier 18 electrically connected to the spindle motor M1
  • an AC servo amplifier 19 electrically connected to the drive motor M2, and each AC servo
  • a control device 20 that outputs a command signal to the amplifiers 18 and 19.
  • the AC servo amplifier 18 corresponds to the “first device” in the present invention
  • the fixed base 12, the slide table 14, and the spindle motor M1 are an example of an implementation configuration corresponding to the “second device” in the present invention.
  • the spindle motor M1 and the drive motor M2 are configured as synchronous AC servomotors.
  • the main shaft motor M1 and the drive motor M2 are provided with a detector (not shown) such as a rotary encoder that can detect the rotation speed and rotation angle (position) of a rotation shaft (not shown).
  • the ball screw 16 is mainly composed of a screw shaft 17a connected to the rotation shaft of the drive motor M2 and a nut member 17b fixed to the screw shaft 17a.
  • the nut member 17b is fixed to the slide table 14. Accordingly, when the drive motor M2 is driven, the screw shaft 17a is rotated together with the rotation shaft of the drive motor M2, and the slide table is reciprocated in the axial direction (left and right direction in FIG. 1) together with the nut portion 32b.
  • the AC servo amplifiers 18 and 19 are composed of a main circuit unit and a control circuit unit, and the main circuit unit controls the frequency, voltage, current, phase, etc. of AC power from a power source (not shown).
  • the power form is converted into a form suitable for driving the spindle motor M1 and the drive motor M2, and the spindle motor M1 and the drive motor are utilized by using signals from detectors (rotary encoders) of the spindle motor M1 and the drive motor M2. Feedback control is performed so that M2 is driven in accordance with a command signal from the control device 20.
  • the control device 20 includes a microprocessor centered on a CPU (not shown).
  • the control device 20 includes a ROM (not shown) for storing a processing program, an input / output port, a communication port (all not shown), and the like.
  • a command signal or the like corresponding to the machining program stored in advance in the ROM is output to the AC servo amplifiers 18 and 19 via the output port.
  • the abnormality determination device 2 includes a microprocessor centered on the CPU 52.
  • the abnormality determination device 2 includes a ROM 56 that stores a processing program, a RAM 54 that temporarily stores data, and an input / output port and a communication port (not shown). ing.
  • the abnormality determination device 2 includes devices / parts constituting the processing equipment 10, specifically, the fixed base 12, the slide table 14, the ball screw 16, the AC servo amplifiers 18, 19, the spindle motor M1, the drive motor M2, and the cutting tool.
  • a signal necessary for determining whether or not an abnormality has occurred in the BLD or the like for example, an XYZ accelerometer that detects vibration from the XYZ accelerometer 62 that detects vibration of the fixed base 12 or vibration of the slide table 14 64, the stress from the stress sensor 66 for detecting the stress acting on the tool holder 15, the current and voltage supplied to the spindle motor M1 and the drive motor M2, and the like are input.
  • the abnormality determination device 2 is connected to the control device 20 through a communication port, and exchanges various control signals and data with the control device 20 as necessary.
  • the abnormality determination device 2 to which the current supplied to the spindle motor M1 is input corresponds to the “first detection means” in the present invention, and the XYZ accelerometers 62 and 64 and the stress sensor 66 are the “second detection in the present invention. It is an example of the implementation structure corresponding to a means.
  • FIG. 2 is a flowchart showing an example of abnormal device / component identification processing executed by the abnormality determination device 2. This process is performed from the time when the processing facility 10 starts operating.
  • the CPU 52 of the abnormality determination device 2 first inputs the current value I and the voltage value V input to the AC servo amplifier 18 (step S100), and the input current value I and A process of storing the voltage value V in the current value buffer and the voltage value buffer set in a predetermined area of the RAM 54 is executed (step S102).
  • the current value I and the voltage value V are input at intervals of 0.125 msec.
  • a process of calculating the power value P using the stored current value I and voltage value V is executed (step S104), and it is determined whether or not the processing of the workpiece W by the cutting tool BLD of the processing equipment 10 has started. Is performed (step S106).
  • the processing start determination is performed based on the calculated power value P.
  • the machining start determination based on the power value P is performed, for example, by detecting the rate of change of the power value P using the fact that the power value P varies greatly before and after the cutting tool BLD contacts the workpiece W. Can do.
  • the vibration values fa and fb of the fixed base 12 and the slide table 14 are input (step S108), and the input vibration value fa , Fb are respectively stored in the fixed table vibration value buffer and the slide table vibration value buffer set in a predetermined area of the RAM 54 (step S110).
  • the vibration values fa and fb are input at intervals of 0.125 msec, similar to the input of the current value I and the voltage value V.
  • the abnormality determination device 2 that determines whether or not the processing of the workpiece W by the blade BLD has started and executes the processing of steps S106 and S108 that inputs the vibration values fa and fb corresponds to the “instruction means” in the present invention. It is an example of the implementation structure to do.
  • step S112 it is determined whether or not the processing of the workpiece W by the processing equipment 10 has been completed.
  • the determination of the end of processing is configured based on the power value P, similar to the determination of the start of processing described above.
  • the determination of the end of machining based on the power value P is similar to the above-described determination of machining start. This can be done by detecting the rate of change.
  • step S112 If it is determined in step S112 that the processing of the workpiece W by the processing facility 10 has not been completed, the processing of steps S108 to S112 is repeated until the processing of the workpiece W by the processing facility 10 is completed. That is, the vibration values fa and fb are input until the processing of the workpiece W by the processing equipment 10 is completed (step S108), and the input vibration values fa and fb are respectively input to the fixed base vibration value buffer and the slide table vibration value buffer. The storing process (step S110) is repeatedly executed.
  • the vibration value fa and the current value I (0%) Stored in the fixed base vibration value buffer and the current value buffer, respectively.
  • the vibration value fa and current value I) input at intervals of 125 msec are extracted at intervals of 0.25 msec, and the vibration value fb (vibration value fb input at intervals of 0.125 msec) stored in the slide table vibration value buffer is 0. Extraction is performed at intervals of .5 msec, and processing for performing frequency analysis is performed on each of the extracted vibration value fa, current value I, and vibration value fb every 0.5 msec (step S114).
  • the extraction interval of the vibration value fa and the current value I is set to 0.25 msec and the extraction interval of the vibration value fb is set to 0.5 msec.
  • the extraction interval of the vibration values fa and fb and the current value I) can be set to a specific value at which an abnormality is easily found in each device / component.
  • the abnormality determination device 2 that executes the process of step S114 for performing frequency analysis on the extracted vibration value fa every 0.25 msec, current value I and vibration value fb every 0.5 msec is the “frequency analysis means of the present invention. ".
  • step S116 it is determined whether or not an abnormal value has occurred in the vibration values fa and fb and the current value I (step S116). If no abnormal value has occurred, nothing is done.
  • the process ends, and an abnormal value has occurred the devices and components related to the vibration values fa and fb and the current value I where the abnormal value has occurred are displayed (step S118), and this process ends. .
  • the abnormality determination device 2 that executes the process of step S118 for displaying the devices / components related to the vibration values fa and fb and the current value I in which the abnormal value has occurred is an implementation configuration corresponding to the “device specifying means” in the present invention. It is an example.
  • whether or not an abnormal value has occurred in the vibration values fa and fb and the current value I is determined according to the vibration values fa and fb and the current value I in a normal state of the device / component. Is obtained in advance and stored in the ROM 56 as a reference value, and is compared with the frequency analysis results of the vibration values fa and fb and the current value I detected when the workpiece W is machined by the machining equipment 10. The configuration.
  • an abnormal value is detected in the frequency analysis of the vibration value fa, it can be detected that an abnormality has occurred in the fixed base 12, and if an abnormal value is detected in the frequency analysis of the vibration value fb, the slide
  • an abnormal value is detected in the table 14 and an abnormal value has been detected in the frequency analysis of the current value I, it is detected that an abnormality has occurred in the AC servo amplifier 18. it can.
  • step S120 the stress ST of the tool holder 15 is input (step S120).
  • the input stress ST is stored in a stress buffer set in a predetermined area of the RAM 54 (step S122).
  • the input of the stress ST is executed at intervals of 0.125 msec, similar to the input of the vibration values fa and fb, the current value I, and the voltage value V.
  • step S124 it is determined whether or not the processing of the workpiece W by the processing equipment 10 has been started.
  • the process start determination is performed based on the power value P, similar to the process start determination described above. If it is determined in step S124 that the processing of the workpiece W by the processing facility 10 has not started, the processing of steps S120 to S124 is repeated until the processing of the workpiece W by the processing facility 10 is started. That is, the stress ST is input until processing of the workpiece W by the processing equipment 10 is started (step S120), and the input stress ST is stored in the stress buffer (step S122), and the process is repeatedly executed.
  • the stress ST stored in the stress buffer (stress ST input at intervals of 0.125 msec) is extracted at intervals of 20 msec. Then, a frequency analysis process is executed for the extracted stress ST every 20 msec (step S126).
  • the stress ST extraction interval is set to 20 msec.
  • the stress ST extraction interval may be set to a specific value at which an abnormality is easily found in each device / component. it can.
  • step S116 it is determined whether or not an abnormal value has occurred in the stress ST (step S116). If no abnormal value has occurred, the process is terminated without doing anything. If the error occurs, the device / part in which an abnormality has occurred, for example, the spindle motor M1, the blade tool BLD, the gear box GB, etc. is displayed (step S118), and this process is terminated.
  • the determination as to which device / part has an abnormality is made by previously obtaining a specific frequency component generated when an abnormality has occurred in each device / part. When a frequency component exceeding the reference value is found, the device / part in which an abnormality has occurred is identified from the frequency component.
  • FIG. 3 shows the time change of the power value P calculated from the current value I and the voltage value V extracted at 20 msec intervals, and the current value I extracted at each extraction interval (0.25 msec, 0.5 msec, 20 msec)
  • FIG. 4 is an explanatory diagram showing temporal changes in vibration values fa, fb and stress ST
  • FIG. 4 is an explanatory diagram showing frequency analysis results of the extracted current value I, vibration values fa, fb and stress ST.
  • the current value I and the voltage value V are input every 0.125 msec (step S100), and the input current value I and voltage value V are the current value buffer and voltage.
  • the current value I and voltage value V are extracted from the stored current value I and voltage value V at intervals of 20 msec from the stored current value I and voltage value V to calculate the power value P (step S104).
  • step S106 determines whether it is medium (section MAC in FIG. 3A) (step S106), and if it is determined that it is in the idle state, as shown in FIG. 3E, an input is made every 0.125 msec.
  • the stress ST is extracted at intervals of 20 msec from the stress ST of the spindle motor M1 stored in the stress buffer (steps S120 and S122), and the frequency analysis of the extracted stress ST is performed as shown in FIG. (Step S126).
  • the data is inputted every 0.125 msec and stored in the current value buffer and the fixed base vibration value degree buffer.
  • the current value I and vibration value fa are extracted from the measured current value I and vibration value fa at intervals of 0.25 msec (steps S108 and S110), and are input every 0.125 msec as shown in FIG.
  • Vibration values fb are extracted at intervals of 0.5 msec from vibration values fb stored in the slide table vibration value degree buffer (steps S108 and S110).
  • frequency analysis of the extracted current value I and vibration values fa and fb is performed (step S114).
  • each frequency band (Ha, Hb, Hc, Hd, He, Hf) suitable for abnormality determination in each feature amount (current value I, vibration value fa, fb, and stress ST). ) Is compared with a reference value (two-dot chain line in FIG. 4), and devices / components related to a feature amount indicating an amplitude larger than the reference value are determined to be abnormal and displayed (step S116). , S118).
  • Hd is a frequency band suitable for the abnormality determination of the spindle motor M1
  • He is a frequency band suitable for the abnormality determination of the cutting tool BLD
  • Hf is a frequency band suitable for the abnormality determination of the gear box GB.
  • the fixed base 12, the slide table 14, the spindle motor M1, and the AC servo amplifier 18, which are a plurality of devices and components constituting the processing equipment 10, are provided.
  • a plurality of (suitable) feature quantities (current value I, vibration values fa, fb, stress ST) useful for detecting an abnormality are detected, and each detected feature quantity (current value I, vibration values fa, fb) is detected.
  • Stress ST and frequency / frequency analysis can be performed to identify the device / component in which an abnormality has occurred based on the frequency analysis result.
  • one device can perform from the detection of a plurality of feature values (current value I, vibration values fa, fb, stress ST) to the identification of the device / component in which an abnormality has occurred, each feature value ( Compared with the case where a device is provided for each of the current value I, the vibration values fa and fb, and the stress ST), the device can be simplified and the cost can be reduced.
  • each feature amount (current value I, vibration value fa, fb, stress ST) is detected at a timing and detection section suitable for abnormality detection, and the frequency is detected.
  • the analysis is performed, that is, the vibration values fa and fb and the current value I are subjected to frequency analysis using values detected during the processing of the workpiece W by the cutting tool BLD, and the stress ST is determined by the cutting tool BLD. Since it is configured to perform frequency analysis using the value detected in the idle state before processing, it is possible to perform abnormality diagnosis after eliminating unnecessary data for abnormality diagnosis, and it is possible to improve the diagnosis speed Therefore, it is possible to detect the abnormality of the device / component more accurately.
  • each feature amount (current value I, vibration value fa, fb, stress ST) is detected only in a predetermined detection section, and each feature amount (current value I, vibration value fa, fb, stress ST) can be frequency-analyzed to identify the device / component in which an abnormality has occurred, so that the occurrence of abnormality of the device / component can be diagnosed in real time while the facility is operating. it can.
  • the operating status of the processing equipment 10 based on the value of the power value P calculated using the current value I that is one of the feature values, that is, Since it is configured to determine whether the workpiece W is being machined by the blade BLD or whether the workpiece W is in an idle state before machining by the blade BLD, the timing and detection interval suitable for detecting an abnormality can be easily set. can do.
  • all the feature quantities (current value I, vibration values fa, fb, stress ST) to which the voltage value V is added are detected every 0.125 msec.
  • the stored feature values (current value I, vibration values fa, fb, stress ST) are necessary intervals (0.25 msec, (5 msec, 20 msec), that is, a configuration in which a predetermined number of data is thinned out from stored data and a power value P is calculated and a frequency analysis is performed.
  • each feature amount (current value I, vibration) Compared to a configuration in which the values fa, fb, and stress ST) are detected at different timings, control can be facilitated, and abnormality diagnosis can be performed after eliminating unnecessary data, thereby improving the diagnostic speed. It is possible .
  • each feature amount current value I, vibration value fa, fb, stress ST
  • each feature amount current value I, vibration value fa, fb, stress. Since it is set to an integral multiple of the detection time (0.125 msec) of ST), only the number of data suitable for abnormality detection is extracted from each stored feature quantity (current value I, vibration value fa, fb, stress ST). Can be easily performed.
  • the present invention is applied to the processing equipment 10 that processes the workpiece W, but is not limited thereto.
  • the abnormality such as the spindle motor M1, the cutting tool BLD, and the gear box GB is determined based on the stress ST of the tool holder 15, but the abnormality such as the spindle motor M1, the cutting tool BLD, and the gear box GB is determined as follows. It is good also as a structure determined based on the electric current value I. Also in this case, any device / part can be detected by detecting whether the amplitude value exceeds the reference value in the specific frequency band generated when an abnormality occurs in each device / part from the frequency analysis result of the current value I. It is possible to identify whether an abnormality has occurred.
  • the determination as to whether or not the workpiece W is being processed by the cutting tool BLD is made based on the power value P.
  • the present invention is not limited to this.
  • the determination as to whether or not the workpiece W is being machined by the cutting tool BLD may be performed, for example, based on a machining program that has been programmed in advance and stored in the ROM 56. good.
  • each feature amount (current value I, vibration values fa, fb, and stress ST) is extracted from each feature amount (current value I, vibration values fa, fb, and stress ST) stored in RAM 54. (0.25 msec, 0.5 msec, 20 msec) is set to an integral multiple of the detection interval (0.125 msec) of each feature amount (current value I, vibration value fa, fb, and stress ST), but is not limited thereto. .
  • This embodiment shows an example of a form for carrying out the present invention. Therefore, the present invention is not limited to the configuration of the present embodiment.
  • Equipment abnormality diagnosis device (diagnosis device) 2 Abnormality determination device (first detection means, frequency analysis means, device identification means, instruction means) 10 Processing equipment (equipment) 12 Fixed base (second equipment) 14 Slide table (second device) 15 Tool holder 16 Ball screw 17a Screw shaft 17b Nut member 18 AC servo amplifier (first device) 19 AC servo amplifier 20 Control device 52 CPU 54 RAM (storage means) 56 ROM 62 XYZ accelerometer (second detection means) 64 XYZ accelerometer (second detection means) 66 Stress sensor (second detection means) M1 spindle motor (second device) M2 Drive motor GB Gearbox BLT Belt BLD Cutting tool I Current value (first feature) V Voltage value fa Vibration value (second feature value) fb Vibration value (second feature value) ST stress (second feature) P Power value (third feature value)

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  • Testing And Monitoring For Control Systems (AREA)

Abstract

L'objectif de l'invention est la fourniture d'un appareil de diagnostic d'installation grâce auquel un dispositif dans lequel une anomalie s'est produite peut être spécifié de manière fiable dans une installation pourvue d'une pluralité de dispositifs ayant différentes quantités de caractéristiques appropriées pour une détection d'anomalie. Selon l'invention, une pluralité de quantités de caractéristiques (valeur de courant I, valeurs de vibration fa, fb, contrainte ST) appropriées pour détecter une anomalie dans une pluralité de dispositifs/composants constitutifs constituant une installation de traitement 10 sont détectées (étapes S102, S108, S120), une analyse de fréquence est effectuée pour les quantités de caractéristiques détectées (étapes S114, S126), et un dispositif/composant constitutif dans lequel une anomalie s'est produite est spécifié sur la base du résultat de l'analyse de fréquence (étape S118). Il est ainsi possible qu'un dispositif/composant constitutif dans lequel une anomalie s'est produite soit spécifié à partir de la détection d'une pluralité de quantités de caractéristiques même par un seul appareil, et l'appareil peut ainsi être simplifié et réduit en coût par rapport à un cas dans lequel un appareil est prévu pour chaque quantité de caractéristiques.
PCT/JP2016/082537 2016-11-02 2016-11-02 Appareil de diagnostic d'installation et procédé de diagnostic d'installation WO2018083746A1 (fr)

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JP2018548493A JP6786181B2 (ja) 2016-11-02 2016-11-02 設備診断装置および設備診断方法
PCT/JP2016/082537 WO2018083746A1 (fr) 2016-11-02 2016-11-02 Appareil de diagnostic d'installation et procédé de diagnostic d'installation

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021012032A (ja) * 2019-07-03 2021-02-04 三菱電機株式会社 異常診断装置およびロボット制御装置
CN113155435A (zh) * 2021-04-30 2021-07-23 深圳素士科技股份有限公司 陶瓷刀片检测方法、剃须刀检测装置和剃须刀

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JPH04273036A (ja) * 1991-02-28 1992-09-29 Toshiba Corp 信号特徴成分解析装置
JP2000314686A (ja) * 1999-05-06 2000-11-14 Saginomiya Seisakusho Inc スード試験における最適パラメータ決定方法、スード試験方法およびスード試験装置
JP2006161677A (ja) * 2004-12-07 2006-06-22 Mitsubishi Electric Corp 圧縮機検査装置
JP2014002003A (ja) * 2012-06-18 2014-01-09 Canon Inc 電子機器

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH04273036A (ja) * 1991-02-28 1992-09-29 Toshiba Corp 信号特徴成分解析装置
JP2000314686A (ja) * 1999-05-06 2000-11-14 Saginomiya Seisakusho Inc スード試験における最適パラメータ決定方法、スード試験方法およびスード試験装置
JP2006161677A (ja) * 2004-12-07 2006-06-22 Mitsubishi Electric Corp 圧縮機検査装置
JP2014002003A (ja) * 2012-06-18 2014-01-09 Canon Inc 電子機器

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021012032A (ja) * 2019-07-03 2021-02-04 三菱電機株式会社 異常診断装置およびロボット制御装置
CN113155435A (zh) * 2021-04-30 2021-07-23 深圳素士科技股份有限公司 陶瓷刀片检测方法、剃须刀检测装置和剃须刀

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