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WO2021210437A1 - 異常診断装置、および、保守管理システム - Google Patents

異常診断装置、および、保守管理システム Download PDF

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Publication number
WO2021210437A1
WO2021210437A1 PCT/JP2021/014466 JP2021014466W WO2021210437A1 WO 2021210437 A1 WO2021210437 A1 WO 2021210437A1 JP 2021014466 W JP2021014466 W JP 2021014466W WO 2021210437 A1 WO2021210437 A1 WO 2021210437A1
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WIPO (PCT)
Prior art keywords
abnormality
unit
peak
frequency
accuracy
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Ceased
Application number
PCT/JP2021/014466
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English (en)
French (fr)
Japanese (ja)
Inventor
正禎 尾島
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Hitachi Ltd
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Hitachi Ltd
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Priority to DE112021000876.5T priority Critical patent/DE112021000876T5/de
Priority to CN202180026558.5A priority patent/CN115380197B/zh
Publication of WO2021210437A1 publication Critical patent/WO2021210437A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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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
    • G01M13/00—Testing of machine parts
    • G01M13/04—Bearings
    • G01M13/045—Acoustic or vibration analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
    • G01H1/003—Measuring characteristics of vibrations in solids by using direct conduction to the detector of rotating machines

Definitions

  • the present invention relates to an abnormality diagnosis device for diagnosing an abnormality in diagnostic coping equipment, and a maintenance management system using the same.
  • Patent Document 1 there is a method of diagnosing an abnormality in a rotating machine system by paying attention to an increase in signals in a specific frequency region as equipment deteriorates.
  • Signal sources such as current, vibration, sound, and torque are used for abnormality diagnosis (see paragraphs 0002 and 0003 of Patent Document 1), and the presence or absence of abnormality and the degree of deterioration are determined by the magnitude of the increased signal strength. To judge.
  • Abnormalities that can be detected by such an abnormality diagnosis method include deterioration of bearings, poor connection between the rotating machine and the load device, and deterioration of the load device.
  • an object of the present invention is to provide an abnormality diagnosis device for a rotating machine system, which can determine the accuracy of abnormality diagnosis and can improve the reliability of diagnosis as compared with the conventional case.
  • the abnormality diagnosis device of the present invention includes a data measurement unit that measures the output signal of a sensor attached to the equipment to be diagnosed, and a frequency decomposition unit that decomposes the measurement signal of the data measurement unit into frequency components.
  • a peak detection unit that detects the peak of the frequency component decomposed by the frequency decomposition unit, and an abnormality diagnosis unit that diagnoses the degree of abnormality of the equipment to be diagnosed based on the intensity of the peak detected by the peak detection unit. It is assumed to have a diagnostic accuracy determination unit for determining the accuracy of the abnormality degree based on the variation in the frequency of the peak detected by the peak detection unit.
  • the other abnormality diagnosis device of the present invention includes a data measurement unit that measures the output signal of a sensor attached to the equipment to be diagnosed, a frequency decomposition unit that decomposes the measurement signal of the data measurement unit into a combination of basic waveforms, and a frequency decomposition unit.
  • the degree of abnormality of the equipment to be diagnosed is diagnosed based on the frequency search width input unit that specifies the search width of the basic waveform decomposed by the frequency decomposition unit and the peak intensity of the basic waveform decomposed by the frequency decomposition unit. It is assumed that the abnormality diagnosis unit is provided and a diagnostic accuracy determination unit that determines the accuracy of the abnormality degree based on the frequency variation of the peak of the basic waveform decomposed by the frequency decomposition unit.
  • the diagnostic accuracy of the abnormality diagnosis can be determined, and the reliability of the diagnosis can be improved as compared with the conventional case.
  • Configuration example of the abnormality diagnosis device An example of frequency decomposition and peak detection when equipment deterioration is severe An example of frequency decomposition and peak detection when equipment deterioration is mild Examples of abnormalities, diagnostic accuracy, and abnormal risks Configuration example of the abnormality diagnosis device according to the second embodiment Example of frequency search width of Example 3 Configuration example of the abnormality diagnosis device according to the fourth embodiment Configuration example of the abnormality diagnosis system according to the fifth embodiment Configuration example of the abnormality diagnosis device according to the fifth embodiment Example of calculation of abnormality degree and diagnostic accuracy for each deterioration in Example 5 Configuration example of recorded data of the maintenance management system according to the sixth embodiment Configuration example of recorded data of the maintenance management system according to the sixth embodiment
  • the abnormality diagnostic apparatus 1 according to the first embodiment of the present invention will be described with reference to FIGS. 1 to 4.
  • FIG. 1 is a functional block diagram showing an outline of the abnormality diagnosis system of this embodiment.
  • This system includes a sensor 2 attached to the equipment to be diagnosed, an abnormality diagnosis device 1 for diagnosing the output signal of the sensor 2, and a display device 3 for displaying the diagnosis result of the equipment to be diagnosed by the abnormality diagnosis device 1.
  • the abnormality diagnosis device 1 includes a data measurement unit 11, a frequency decomposition unit 12, a peak detection unit 13, an abnormality diagnosis unit 14, a diagnosis accuracy determination unit 15, and an abnormality risk calculation unit 16.
  • the abnormality diagnosis device 1 is a computer such as a personal computer equipped with a computing device such as a CPU, a main storage device such as a semiconductor memory, an auxiliary storage device, and hardware such as a communication device. Then, while referring to the database recorded in the auxiliary storage device, the arithmetic unit executes the program loaded in the main storage device, so that each of the above functions (abnormality diagnosis unit 14, diagnosis accuracy determination unit 15, etc.) is executed.
  • a computer such as a personal computer equipped with a computing device such as a CPU, a main storage device such as a semiconductor memory, an auxiliary storage device, and hardware such as a communication device.
  • This abnormality diagnosis device 1 diagnoses an abnormality in the equipment to be diagnosed as follows.
  • the data measurement unit 11 measures the output signal of the sensor 2, and the frequency decomposition unit 12 obtains the frequency component of the measurement signal and decomposes it into a combination of a plurality of basic waveforms.
  • the frequency decomposition method used here is, for example, the Fourier transform.
  • the peak detection unit 13 detects the peak P of the frequency component and outputs the variation of the peak intensity and the peak frequency for each peak P.
  • the abnormality diagnosis unit 14 diagnoses the degree of abnormality of the equipment to be diagnosed based on the peak intensity in a specific frequency region. Further, the diagnostic accuracy determination unit 15 determines the diagnostic accuracy based on the variation in the peak frequency.
  • the abnormality risk calculation unit 16 calculates the abnormality risk based on the outputs of the abnormality diagnosis unit 14 and the diagnosis accuracy determination unit 15. As a result, the display device 3 displays the degree of abnormality, the accuracy of diagnosis, and the risk of abnormality of the equipment to be diagnosed. The abnormality risk calculation unit 16 may be omitted. In that case, the display device 3 displays the degree of abnormality and the accuracy of diagnosis of the equipment to be diagnosed.
  • FIG. 2 shows an example of frequency decomposition and peak detection when the equipment to be diagnosed is severely deteriorated, and the black dots indicate the peak P detected by the peak detection unit 13.
  • This example is a graph expressed by a combination of five basic waveforms, in addition to the intrinsic peak P 1 is observed also when diagnosed equipment is normal, within certain frequency range diagnosed equipment deteriorates degradation peaks P 2 that elicited also been observed. Since the frequency of the deterioration peak P 2 corresponds to the deterioration factor, the abnormality diagnosis unit 14 can diagnose the presence or absence of an abnormality for each deterioration factor based on the peak intensity of the deterioration peak P 2.
  • FIG. 3 shows an example of frequency decomposition and peak detection when the deterioration of the equipment to be diagnosed is slight.
  • the intrinsic peak P 1 is observed regardless of the order of equipment degradation is manifested, the peak intensity of the degradation peak P 2 is small since it is degraded early stages of equipment, under cover of the signal strength of the noise There is.
  • the peak detection unit 13 detects the intrinsic peak P 1 and the deterioration peak P 2 for each output signal (hereinafter referred to as “period data”) collected by the sensor 2 in different periods.
  • periodic data each output signal collected by the sensor 2 in different periods.
  • unique peak P 1 and the degraded peak P 2 is to focus on a specific region detected from the period data.
  • the deterioration peak P 2 in the initial stage of deterioration since the peak intensity is mixed with the signal intensity of noise, even if the peak intensity of the deterioration peak P 2 is substantially constant, the frequency varies greatly depending on the period data. Deterioration peak P 2 is detected. Therefore, even when used as a degradation peak P 2 of FIG. 3, can not distinguish between the peak intensity and the noise signal strength, decreases the accuracy of the abnormality diagnosis, it is difficult to abnormality determination.
  • the frequency variation ⁇ f 2 of the deterioration peak P 2 detected from a large number of period data is large, and the variation ⁇ f 2 becomes small as the deterioration progresses. Focusing on this, it was decided to improve the reliability of the diagnosis at the time of slight deterioration by calculating the accuracy of the abnormality diagnosis based on the variation ⁇ f 2.
  • the calculation of the diagnostic accuracy, a variation Delta] f 0 of the frequency of the peak P of the normal facilities, etc. percentage variation Delta] f t frequency of the current peak P can be determined for example by the following equation.
  • Figure 4 calculated in the diagnostic accuracy determining unit 15 with reference to (a) and calculated degree of abnormality by the abnormality diagnosis section 14 with a peak intensity of degradation peak P 2, (b) variations in the peak frequency of the degradation peak P 2 An example of the diagnostic accuracy obtained and (c) the abnormal risk calculated by the abnormal risk calculation unit 16 is shown.
  • Abnormality degree shown in FIG. 4 (a) is a value calculated from the peak intensity of the degradation peak P 2, it should exhibit a tendency to abnormal degree in accordance with the progress of degradation from the original degradation initial increase. However, in the initial stage of deterioration, the deterioration peak P 2 is smaller than the noise signal intensity, and the peak detection unit 13 detects the noise signal, so that the abnormality degree higher than the original abnormality degree (dotted line) is calculated. ..
  • the diagnostic accuracy shown in FIG. 4 (b), in the deterioration initial calculated small diagnostic accuracy for variations Delta] f 2 is larger frequency degradation peak P 2 (see Equation 1 above), the degradation peak P 2
  • the frequency variation ⁇ f 2 gradually decreases and the diagnostic accuracy increases. Then, when the deterioration peak P 2 is always detected, the diagnostic accuracy becomes constant at a high value.
  • FIG. 4 (c) is an abnormality risk of the equipment to be diagnosed calculated by multiplying the degree of abnormality in FIG. 4 (a) and the accuracy of diagnosis in FIG. 4 (b). Since both the degree of abnormality and the accuracy of diagnosis are reflected in this abnormality risk, the accuracy of diagnosis by the abnormality diagnosis device 1 can be roughly grasped only by monitoring the abnormality risk.
  • the abnormality diagnosis device of this embodiment it is possible to detect a decrease in diagnostic accuracy in the initial stage of deterioration in which an abnormality degree higher than the original abnormality degree is calculated. In addition, it is possible to calculate the abnormal risk that reflects the decrease in diagnostic accuracy. Therefore, if it can be judged that the reliability of the abnormality is low by referring to the diagnosis accuracy and the risk of abnormality, it is possible to take measures such as not performing the abnormality diagnosis, so that the reliability of the entire abnormality diagnosis can be ensured. can.
  • the abnormality diagnostic device 1 according to the second embodiment of the present invention will be described with reference to FIG. It should be noted that the common points with the first embodiment will be omitted.
  • the frequency decomposition unit 12 of the first embodiment the frequency decomposition was performed by using the Fourier transform, but in the frequency decomposition unit 12 of the present embodiment, the method of decomposing the signal into continuous frequency components is not performed as in the Fourier transform.
  • a method such as generalized harmonic analysis or non-harmonic analysis is used to directly calculate the peak intensity and peak frequency in a specific frequency range.
  • the frequency range for searching the peak P is input from the frequency search width input unit 17 to the frequency decomposition unit 12 and the diagnostic accuracy determination unit 15, and the peak intensity and the peak intensity are directly obtained from the frequency decomposition result without using the peak detection unit 13.
  • the peak frequency is calculated, and abnormality diagnosis and diagnosis accuracy judgment are performed.
  • the calculation accuracy of the peak intensity depends on the time length of the measurement signal. Therefore, long-term measurement is required for accurate diagnosis. I need a signal.
  • the calculation accuracy of the peak intensity does not depend on the time length of the measurement signal. A good abnormality diagnosis is possible.
  • the abnormality diagnostic device 1 according to the third embodiment of the present invention will be described with reference to FIG. It should be noted that the common points with the above embodiment will be omitted.
  • Example 2 As in Example 2, to directly calculate the intrinsic peak P 1 and degradation peak P 2 from among the given frequency calculation width, even under degraded conditions such as deterioration peak P 2 is always detected, it is detected It is not possible to distinguish whether the peak intensity is due to deterioration or a noise signal, and the diagnostic accuracy is reduced regardless of the deterioration state, so that the abnormality diagnosis result cannot be used.
  • the abnormality diagnosis result calculated by using such a frequency decomposition method can be used.
  • the frequency decomposition unit 12 directly calculates the peak intensity and the peak frequency in a specific frequency range such as generalized harmonic analysis and non-harmonic analysis as in Example 2, the calculation is performed.
  • the time required depends on the width of the specified frequency range. Therefore, in this embodiment, the detection time of the deterioration peak P 2 is further shortened by limiting the search width W in advance to the frequency domain where the deterioration peak P 2 is expected to be detected.
  • the frequency search time can be minimized by calculating one peak from the search width W of one search frequency region. Further, since the variance of the frequency can be calculated for each peak, the diagnostic accuracy for each peak can be calculated.
  • the diagnostic accuracy determination unit 15 of this embodiment can calculate the diagnostic accuracy by the following equation instead of the equation 1 of the first embodiment.
  • the abnormality diagnostic device 1 according to the fourth embodiment of the present invention will be described with reference to FIG. 7. It should be noted that the common points with the above embodiment will be omitted.
  • the peak intensity of the deterioration peak P 2 is generally smaller than the peak intensity of the intrinsic peak P 1. Therefore, as in Embodiment 2, when a method of directly calculating the peak intensities and peak frequency in a specific frequency range, such as generalized harmonic analysis and non-harmonic analysis in the frequency decomposition unit 12, degradation peak P 2 Difficult to detect.
  • the intrinsic peak subtracting section 19 a waveform corresponding to the intrinsic peak P 1 calculated after subtracting from the measurement data to calculate only the degradation peak P 2 in the degradation peak calculation unit 20.
  • the deterioration peak P 2 can be calculated without being affected by the intrinsic peak P 1 , so that the abnormality of the equipment to be diagnosed can be diagnosed with higher accuracy.
  • the equipment to be diagnosed by the abnormality diagnosis device 1 was not specified, but in this embodiment, the equipment to be diagnosed was the rotary machine system 4.
  • the rotary machine system 4 includes a motor M, a transmission device 41, a load device 42, a power supply line 43, and an AC power supply 44, and the motor M has a power supply line 43 from the AC power supply 44. It is a rotating machine driven by three-phase alternating current power supplied via, and drives a load device 42 via a transmission device 41 such as a shaft or a belt.
  • a sensor 2 is attached to the power supply line 43, and the current waveform during driving of the motor M measured here is input to the abnormality diagnosis device 1 of any of Examples 1 to 4.
  • the abnormality diagnosis device 1 calculates the abnormality degree, the diagnosis accuracy, and the abnormality risk of the rotary machine system 4 and displays them in.
  • the operator of the rotary machine system 4 can know the diagnosis result by the abnormality diagnosis device 1 via the display device 3.
  • the abnormality of the rotating machine system 4 is diagnosed from the current waveform, but the abnormality of the rotating machine system 4 may be diagnosed based on the vibration or sound detected while the motor M is being driven. Needless to say, in these cases, a vibration sensor or a microphone is used for the sensor 2.
  • the natural peak P 1 is an AC wave of the AC power supply 44 or a harmonic thereof. Further, deterioration of the bearings, the deterioration of the load device 42, the mode of degradation, such as degradation of transmission 41, the degradation peak P 2 at different frequency domain is observed.
  • the deterioration peak intensity is calculated by providing the AC wave subtraction unit 21 for removing the influence of the AC wave in front of the deterioration peak calculation unit 20.
  • the accuracy can be improved.
  • the AC wave subtraction unit 21 for example, a notch filter, an envelope processing, a method of calculating a DC current waveform from a plurality of power supply waveforms, and the like can be used.
  • the maintenance management system of this embodiment records the degree of abnormality, accuracy, abnormality risk, etc. for each of the motor M of the rotary machine system 4 and its deterioration method, which is obtained by the abnormality diagnosis system of Example 5, and displays the display device. By displaying on 3, the maintenance management of the rotary machine system 4 is assisted.
  • FIG. 11 the maintenance management system of this embodiment, the two motors M A, for each of M B, 2 types of degradation D A, the abnormality degree and accuracy of D B, in the past from the present (today)
  • the motor M A, M B is any motor deterioration of the same kind is observed, it may be a combination of a motor mounted on the same rotating machine system 4, it is mounted on different rotary machine system 4 It may be a combination of motors.
  • maintenance system of this embodiment the two motors M a, and M B, 2 types of degradation D a, each D B, an example of data recorded abnormal risk and maintenance plan from two days before until after two days Is.
  • maintenance rules are stipulated to carry out temporary maintenance when the abnormal risk exceeds 10.
  • the necessity of temporary maintenance is determined according to the magnitude of the abnormality risk, but the necessity of temporary maintenance is determined according to the magnitude of the abnormality degree and the diagnosis accuracy as shown in FIG. Is also good. For example, if the accuracy of diagnosis is very high even if the degree of abnormality is small to medium, or if the degree of abnormality is very high even if the degree of abnormality is small to medium, it is based only on the degree of abnormality or the accuracy of diagnosis. Therefore, it may be determined that temporary maintenance will be carried out.
  • the present invention is not limited to the above-described examples, and includes various modifications.
  • the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to the one including all the described configurations.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
  • Testing And Monitoring For Control Systems (AREA)
PCT/JP2021/014466 2020-04-13 2021-04-05 異常診断装置、および、保守管理システム Ceased WO2021210437A1 (ja)

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DE112021000876.5T DE112021000876T5 (de) 2020-04-13 2021-04-05 Anomaliediagnosevorrichtung und wartungsmanagementsystem
CN202180026558.5A CN115380197B (zh) 2020-04-13 2021-04-05 异常诊断装置和维护管理系统

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JP7798522B2 (ja) * 2021-10-01 2026-01-14 三菱重工業株式会社 信号解析装置、信号解析方法及びプログラム
US12399481B2 (en) * 2022-04-26 2025-08-26 Hitachi, Ltd. Versatile anomaly detection system for industrial systems
CN118731565B (zh) * 2024-08-30 2024-10-29 东电检测技术服务(天津)有限公司 基于电参数分析的电磁兼容智能化检测方法

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CN115380197A (zh) 2022-11-22
CN115380197B (zh) 2025-03-28

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