WO2022131170A1 - Anomaly detection device, anomaly detection method, anomaly detection program, and system for detecting anomaly in bearing - Google Patents

Anomaly detection device, anomaly detection method, anomaly detection program, and system for detecting anomaly in bearing Download PDF

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Publication number
WO2022131170A1
WO2022131170A1 PCT/JP2021/045659 JP2021045659W WO2022131170A1 WO 2022131170 A1 WO2022131170 A1 WO 2022131170A1 JP 2021045659 W JP2021045659 W JP 2021045659W WO 2022131170 A1 WO2022131170 A1 WO 2022131170A1
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Prior art keywords
abnormality
signal
frequency
data
bearing
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PCT/JP2021/045659
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French (fr)
Japanese (ja)
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聡志 木村
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ミツミ電機株式会社
聡志 木村
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Publication of WO2022131170A1 publication Critical patent/WO2022131170A1/en

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16C—SHAFTS; FLEXIBLE SHAFTS; ELEMENTS OR CRANKSHAFT MECHANISMS; ROTARY BODIES OTHER THAN GEARING ELEMENTS; BEARINGS
    • F16C19/00—Bearings with rolling contact, for exclusively rotary movement
    • F16C19/02—Bearings with rolling contact, for exclusively rotary movement with bearing balls essentially of the same size in one or more circular rows
    • F16C19/04—Bearings with rolling contact, for exclusively rotary movement with bearing balls essentially of the same size in one or more circular rows for radial load mainly
    • F16C19/06—Bearings with rolling contact, for exclusively rotary movement with bearing balls essentially of the same size in one or more circular rows for radial load mainly with a single row or balls
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16C—SHAFTS; FLEXIBLE SHAFTS; ELEMENTS OR CRANKSHAFT MECHANISMS; ROTARY BODIES OTHER THAN GEARING ELEMENTS; BEARINGS
    • F16C19/00—Bearings with rolling contact, for exclusively rotary movement
    • F16C19/52—Bearings with rolling contact, for exclusively rotary movement with devices affected by abnormal or undesired conditions
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16C—SHAFTS; FLEXIBLE SHAFTS; ELEMENTS OR CRANKSHAFT MECHANISMS; ROTARY BODIES OTHER THAN GEARING ELEMENTS; BEARINGS
    • F16C33/00—Parts of bearings; Special methods for making bearings or parts thereof
    • F16C33/30—Parts of ball or roller bearings
    • F16C33/58—Raceways; Race rings
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16C—SHAFTS; FLEXIBLE SHAFTS; ELEMENTS OR CRANKSHAFT MECHANISMS; ROTARY BODIES OTHER THAN GEARING ELEMENTS; BEARINGS
    • F16C41/00—Other accessories, e.g. devices integrated in the bearing not relating to the bearing function as such
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
    • 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

Definitions

  • the abnormality determination unit 340 detects the state of the object to be measured (bearing 250) based on the processed data processed by the data processing unit 330. More specifically, the abnormality determination unit 340 determines whether or not the state of the measurement object is abnormal, detects a sign of abnormality of the measurement object, and the like.
  • the notification generation unit 350 generates a notification indicating an abnormality or a sign of an abnormality when the abnormality determination unit 340 detects an abnormality or a sign of the abnormality.
  • the outer ring 251 is damaged by detecting a sign before the outer ring 251 is damaged and notifying the user. You can prevent it from entering.
  • the information processing device 300 of the present embodiment includes an input device 31, an output device 32, a drive device 33, an auxiliary storage device 34, a memory device 35, an arithmetic processing device 36, and an interface device 37, which are connected to each other by a bus B, respectively. It is a computer including, and is an example of an abnormality detection device.
  • the abnormality detection program that realizes the communication unit 310, the data acquisition unit 320, the data processing unit 330, the abnormality determination unit 340, and the notification generation unit 350 is at least a part of various programs that control the information processing device 300.
  • the abnormality detection program is provided, for example, by distributing the storage medium 38, downloading from the network, or the like.
  • the storage medium 38 on which the abnormality detection program is recorded includes various types of storage media such as a storage medium for optically, electrically or magnetically recording information, a semiconductor memory for electrically recording information such as a ROM and a flash memory, and the like.
  • a storage medium can be used.
  • the abnormality detection program is installed in the auxiliary storage device 34 from the storage medium 38 via the drive device 33.
  • the abnormality detection program downloaded from the network is installed in the auxiliary storage device 34 via the interface device 37.
  • FIG. 3 is a first flowchart illustrating the processing of the information processing apparatus of the first embodiment.
  • the process shown in FIG. 3 is mainly the process of the data processing unit 330.
  • the process of FIG. 3 is executed every time the communication unit 310 receives digital data.
  • the data processing unit 330 calculates the frequency at which the power becomes the maximum value and the maximum value from the acquired waveform data in the frequency region, and sets that frequency as the frequency of the passing vibration of the rolling element 252 (step S302).
  • the waveform of the frequency of the passing vibration of the rolling element 252 may be referred to as a basic waveform, and the waveform data showing the basic waveform may be referred to as the basic waveform data.
  • the passing vibration of the rolling element 252 refers to the vibration of the outer ring 251 generated when the rolling element 252 passes through the portion of the outer ring 251 to which the strain gauge 210 is attached.
  • the data processing unit 330 performs inverse FFT on each of the extracted frequency components, converts the waveform data in the frequency domain into waveform data in the time domain, and calculates the effective value of the amplitude of each waveform data in the time domain. (Step S304).
  • the data processing unit 330 stores the feature amount calculated in step S305 in the storage unit 360 (step S307), and ends the process.
  • the feature amount group stored in the storage unit 360 during the collection period may be referred to as normal data.
  • step S306 of FIG. 3 the abnormality determination unit 340 of the present embodiment reads normal data from the storage unit 360 and extracts normalization parameters when the collection period has elapsed (step S401).
  • the abnormality determination unit 340 normalizes the evaluation data using the normalization parameters used for normalizing the normal data (step S402).
  • the abnormality determination unit 340 has a data density in the vicinity of the evaluation data normalized in step S402 and a data density in the vicinity of the normal data normalized in step S401 on the space using the feature amount as the coordinate value.
  • the ratio of is calculated (step S403).
  • the ratio of data density is defined as the degree of abnormality.
  • the degree of abnormality is a value that is an index for determining whether or not the state of the bearing 250 is abnormal.
  • the abnormality determination unit 340 determines whether or not the condition that "the degree of abnormality exceeds a certain threshold value and the frequency exceeds a predetermined value" is satisfied (step S404).
  • the threshold value of the degree of abnormality and a predetermined value may be set in advance. Details of steps S403 and S404 will be described later.
  • step S404 If the condition is satisfied in step S404, the abnormality determination unit 340 determines that the state of the bearing 250 is an abnormal state, the notification generation unit 350 generates a notification indicating an abnormality, and the communication unit 310 transmits the notification ( Step S405), the process is terminated.
  • the notification of the present embodiment may be, for example, a message indicating that an abnormality has occurred in the bearing 250, and in that case, for example, the notification is displayed on a display or the like connected to the information processing apparatus 300. You may. Further, the notification of the present embodiment may be an alarm or the like indicating that the bearing 250 is in an abnormal state, and this alarm may be output to the sensor board 200. The sensor board 200 may receive this alarm and notify the alarm to, for example, a higher-level device of the bearing 250.
  • step S404 if the condition that "the degree of abnormality exceeds a certain threshold value and the frequency exceeds a predetermined value" is not satisfied, the abnormality determination unit 340 determines that it is normal (step S406) and performs processing. finish. In the present embodiment, even when the abnormality determination unit 340 determines that the abnormality is normal, the notification generation unit 350 may generate and output a notification indicating the normality.
  • the abnormality determination by the abnormality determination unit 340 will be further described with reference to FIGS. 5 and 6.
  • FIG. 5 is the first diagram illustrating the abnormality determination by the abnormality determination unit.
  • the case where the post-normalized evaluation data is normal data is shown.
  • the normalized data after normalization and the evaluation data after normalization are referred to as normalized data after normalization and evaluation data after normalization.
  • the anomaly determination unit 340 calculates the density of the data arranged in the vicinity of the normalized evaluation data 52 in the feature quantity space (example; number of neighborhoods 3).
  • the region R including three surrounding data is specified centering on the normalized evaluation data 52.
  • a region R including three post-normalized normal data 51a, 51b, 51c arranged near the post-normalized evaluation data 52 is specified.
  • the number of neighborhoods is not limited to 3.
  • the abnormality determination unit 340 identifies the regions R1, R2, and R3 including the normalized normal data 51a, 51b, and 51c, respectively.
  • the abnormality determination unit 340 calculates the data density in the region R and the data density of the normalized normal data in each of the regions R1, R2, and R3. Specifically, the abnormality determination unit 340 may use the number of normalized normal data in the regions R, R1, R2, and R3 as the data density.
  • the abnormality determination unit 340 calculates the ratio between the data density of the region R and the average data density of the regions R1, R2, and R3 as the degree of abnormality.
  • the digital data when the normalized evaluation data 52 is acquired is the normal data acquired when the bearing 250 is in a normal state.
  • the abnormality determination unit 340 specifies the region R and the regions R4, R5, and R6 including the normalized normal data 51d, 51e, and 51f, respectively. Then, the abnormality determination unit 340 calculates the ratio between the data density of the region R and the average data density of the regions R4, R5, and R6 as the degree of abnormality.
  • the digital data when the normalized evaluation data 52 is acquired can be said to be the abnormal data acquired when the bearing 250 is in an abnormal state.
  • the abnormality determination unit 340 of the present embodiment detects an abnormality in the bearing 250 when the normalized evaluation data 52 becomes abnormality data a plurality of times. good.
  • the bearing 250 anomalies can be detected.
  • the influence of the temperature characteristic of the strain gauge 210 can be reduced, and the abnormality of the bearing 250 can be detected only by the strain.
  • the abnormality determination unit 340 of the present embodiment detects the abnormality of the bearing 250 when the abnormality degree exceeds the threshold value, but the abnormality determination unit 340 detects a sign of abnormality according to the abnormality degree. It may be detected.
  • the abnormality determination unit 340 detects a sign of abnormality before the degree of abnormality reaches the threshold value, and generates a notification to the notification generation unit 350 indicating that there is a sign of abnormality. You may let me. This notification may be transmitted to the outside by the communication unit 310.
  • the second embodiment will be described below with reference to the drawings.
  • the second embodiment is different from the first embodiment in that the function of the information processing apparatus 300 is realized by a semiconductor integrated circuit. Therefore, in the description of the second embodiment, the reference numerals used in the description of the first embodiment are given to those having the same functional configuration as that of the first embodiment, and the description thereof will be omitted.
  • the abnormality detection device 400 of the present embodiment includes a communication circuit 410, a data acquisition circuit 420, a data processing circuit 430, an abnormality determination circuit 440, a notification output circuit 450, and a storage device 460.
  • the communication circuit 410 communicates with the sensor board 200.
  • the data acquisition circuit 420 realizes the function of the data acquisition unit 320.
  • the data processing circuit 430 realizes the function of the data processing unit 330.
  • the abnormality determination circuit 440 realizes the function of the abnormality determination unit 340.
  • the notification output circuit 450 realizes the function of the notification generation unit 350.
  • the storage device 460 corresponds to the storage unit 360.
  • the abnormality detection device 400 includes, but is not limited to, the storage device 460.
  • the abnormality detection device 400 does not have to have the storage device 460.
  • the storage device 460 is mounted outside the abnormality detection device 400 and becomes a data processing circuit 430 and an abnormality determination circuit 440. All you have to do is connect.
  • the abnormality detection device 400 by setting the function of the information processing device 300 to the abnormality detection device 400 which is an integrated circuit, for example, the abnormality detection device 400 can be mounted on the sensor board 200.
  • the information processing device 300 for detecting the abnormality of the object to be measured it is not necessary to arrange the information processing device 300 for detecting the abnormality of the object to be measured, and in particular, the bearing 250, the sensor board 200, and the abnormality detecting device 400 are provided inside the host device. It can be built in.
  • the third embodiment will be described below with reference to the drawings.
  • the third embodiment is different from the second embodiment in that the sensor substrate is included in the abnormality detection device shown in the second embodiment. Therefore, in the following description of the third embodiment, the differences from the second embodiment will be described, and the functional configuration similar to that of the second embodiment will be described with reference to the reference numerals used in the description of the second embodiment. Is given, and the description is omitted.
  • FIG. 8 is a diagram showing an abnormality detection device according to a third embodiment.
  • the abnormality detection device 400A of the present embodiment includes a strain gauge 210, an amplifier 220, an ADC 230, a data acquisition circuit 420, a data processing circuit 430, an abnormality determination circuit 440, and a notification output circuit 450. Further, the abnormality detection device 400A of the present embodiment is connected to a storage device 460 in which data is written by the data processing circuit 430 and the data is read out by the abnormality determination circuit 440.
  • the rolling element 252 in the measurement object can be rolled by simply attaching the abnormality detection device 400A to the outer ring of the measurement object. Abnormal vibration caused by motion can be detected.
  • the abnormality detection device 400A of the present embodiment does not include the bearing 250, the abnormality detection device 400A may include the bearing 250.
  • the present invention has been described above based on each embodiment, the present invention is not limited to the requirements shown in the above embodiments. With respect to these points, the gist of the present invention can be changed to the extent that the gist of the present invention is not impaired, and can be appropriately determined according to the application form thereof.

Abstract

This anomaly detection device has: a data acquisition unit that acquires a signal that captures the passing vibration of a rolling element; a data processing unit that, using said signal, calculates a feature value indicating the ratio between the amplitude of a frequency indicating the passing vibration of the rolling element and the amplitude of a signal component of the Nth harmonic of a frequency indicating the passing vibration; and an anomaly determination unit that, on the basis of said feature value, determines whether or not the state of a measured object including the rolling element is abnormal.

Description

異常検出装置、異常検出方法、異常検出プログラム、ベアリングの異常検出システムAnomaly detection device, anomaly detection method, anomaly detection program, bearing anomaly detection system
　本発明は、異常検出装置、異常検出方法、異常検出プログラム、ベアリングの異常検出システムに関する。 The present invention relates to an abnormality detection device, an abnormality detection method, an abnormality detection program, and a bearing abnormality detection system.
　従来から、ベアリング等の測定対象物に取り付けてられたひずみゲージにより観測される観測波形に基づき、転動体の内輪（回転輪）の回転数、ラジアル荷重を算出することで、ベアリングの状態を監視する技術が知られている。 Conventionally, the state of the bearing is monitored by calculating the rotation speed and radial load of the inner ring (rotary wheel) of the rolling element based on the observation waveform observed by the strain gauge attached to the object to be measured such as the bearing. The technology to do is known.
特開２０１８－１４５９９８号公報Japanese Unexamined Patent Publication No. 2018-145998
　上述した従来の技術では、観測波形の周期や振幅が既知である。また、従来の技術では、例えば、観測波形の周期や振幅に不規則な変動やノイズを含む異常振動波形であった場合に、転動体の剥離や保持器の破損等の転がり軸受の異常な振動と誤検出する。このため、従来の技術では、観測波形の周期や振幅が未知である場合や、回転速度が変動する場合等には、ひずみゲージによる測定対象物の異常を検出することが困難である。 In the above-mentioned conventional technique, the period and amplitude of the observed waveform are known. Further, in the conventional technique, for example, when the period or amplitude of the observed waveform is an abnormal vibration waveform including irregular fluctuations or noise, abnormal vibration of the rolling bearing such as peeling of the rolling element or breakage of the cage is performed. Is falsely detected. Therefore, in the conventional technique, it is difficult to detect an abnormality of the object to be measured by the strain gauge when the period or amplitude of the observed waveform is unknown or the rotation speed fluctuates.
　開示の技術は、上記事情に鑑みてなされたものであり、測定対象物の異常を検出することを目的としている。 The disclosed technique was made in view of the above circumstances, and aims to detect abnormalities in the object to be measured.
　開示の技術は、転動体（２５２）の通過振動を捉えた信号を取得するデータ取得部（３２０）と、
　前記信号を用いて、前記転動体（２５２）の通過振動を示す周波数の振幅と、前記通過振動を示す周波数のＮ次高調波の信号成分の振幅と、の比率を示す特徴量を算出するデータ処理部（３３０）と、
　前記特徴量に基づき、前記転動体（２５２）を含む測定対象物（２５０）の状態が異常であるか否かを判定する異常判定部（３４０）と、を有する異常検出装置（３００）である。 The disclosed techniques include a data acquisition unit (320) that acquires a signal that captures the passing vibration of the rolling element (252).
Data for calculating a feature amount indicating the ratio between the amplitude of the frequency indicating the passing vibration of the rolling element (252) and the amplitude of the signal component of the Nth harmonic of the frequency indicating the passing vibration using the signal. Processing unit (330) and
An abnormality detection device (300) including an abnormality determination unit (340) for determining whether or not the state of the measurement object (250) including the rolling element (252) is abnormal based on the feature amount. ..
　測定対象物の異常を検出できる。 Abnormality of the object to be measured can be detected.
第一の実施形態の異常検出システムのシステム構成の一例を示す図である。It is a figure which shows an example of the system configuration of the abnormality detection system of 1st Embodiment. 第一の実施形態の情報処理装置のハードウェア構成の一例を示す図である。It is a figure which shows an example of the hardware composition of the information processing apparatus of 1st Embodiment. 第一の実施形態の情報処理装置の処理を説明する第一のフローチャートである。It is a 1st flowchart explaining the process of the information processing apparatus of 1st Embodiment. 第一の実施形態の情報処理装置の処理を説明する第二のフローチャートである。It is the 2nd flowchart explaining the process of the information processing apparatus of 1st Embodiment. 異常判定部による異常判定について説明する第一の図である。It is the first figure explaining the abnormality determination by the abnormality determination part. 異常判定部による異常判定について説明する第二の図である。It is the 2nd figure explaining the abnormality determination by the abnormality determination part. 第二の実施形態の異常検出システムのシステム構成の一例を示す図である。It is a figure which shows an example of the system configuration of the abnormality detection system of the 2nd Embodiment. 第三の実施形態の異常検出装置を示す図である。It is a figure which shows the abnormality detection apparatus of the 3rd Embodiment.
　（第一の実施形態）
　以下に図面を参照して、第一の実施形態について説明する。図１は、第一の実施形態の異常検出システムのシステム構成の一例を示す図である。 (First embodiment)
The first embodiment will be described below with reference to the drawings. FIG. 1 is a diagram showing an example of a system configuration of the abnormality detection system of the first embodiment.
　本実施形態の異常検出システム１００は、センサ基板２００と、情報処理装置（異常検出装置）３００と、を有し、センサ基板２００と情報処理装置３００とは、無線通信等によって通信を行う。尚、センサ基板２００と情報処理装置３００との通信方法は、無線通信に限定されず、有線通信であってもよい。センサ基板２００と情報処理装置３００とは、通信が可能であれば、どのような方法で接続されてもよい。また、無線通信を行う場合には、センサ基板２００に別途電源が供給されてもよい。 The abnormality detection system 100 of the present embodiment includes a sensor board 200 and an information processing device (abnormality detection device) 300, and the sensor board 200 and the information processing device 300 communicate with each other by wireless communication or the like. The communication method between the sensor board 200 and the information processing device 300 is not limited to wireless communication, and may be wired communication. The sensor board 200 and the information processing apparatus 300 may be connected by any method as long as communication is possible. Further, in the case of wireless communication, power may be separately supplied to the sensor board 200.
　本実施形態のセンサ基板２００には、例えば、ひずみゲージ２１０、アンプ２２０、ＡＤＣ（Analog-to-Digital Converter）２３０、通信回路２４０が実装されている。 For example, a strain gauge 210, an amplifier 220, an ADC (Analog-to-Digital Converter) 230, and a communication circuit 240 are mounted on the sensor board 200 of the present embodiment.
　尚、本実施形態では、ひずみゲージ２１０が実装された基板と、アンプ２２０、ＡＤＣ（Analog-to-Digital Converter）２３０、通信回路２４０とが実装された基板とが、別々の基板であってもよい。 In this embodiment, even if the board on which the strain gauge 210 is mounted and the board on which the amplifier 220, the ADC (Analog-to-Digital Converter) 230, and the communication circuit 240 are mounted are separate boards. good.
　ひずみゲージ２１０は、例えば、ベアリング２５０に設けられる。ベアリング２５０は、例えば、外輪（固定輪）２５１と、複数の転動体２５２と、内輪（回転輪）２５３とを有し、複数の転動体２５２は、外輪２５１と内輪２５３との間に転動自在に配設されている。 The strain gauge 210 is provided on the bearing 250, for example. The bearing 250 has, for example, an outer ring (fixed ring) 251 and a plurality of rolling elements 252 and an inner ring (rotating ring) 253, and the plurality of rolling elements 252 roll between the outer ring 251 and the inner ring 253. It is arranged freely.
　ひずみゲージ２１０は、外輪２５１に取り付けられる。また、ひずみゲージ２１０は、転動体２５２がひずみゲージ２１０が設けられた位置を通過する際に、外輪２５１に生じるひずみを検出し、ひずみに応じた抵抗値の変化を示すアナログデータ（波形データ）を出力する。尚、図１の例では、ひずみゲージ２１０は外輪２５１に取り付けられるものとしたが、ひずみゲージ２１０は、外輪２５１以外に取り付けられていてもよい。 The strain gauge 210 is attached to the outer ring 251. Further, the strain gauge 210 detects the strain generated in the outer ring 251 when the rolling element 252 passes through the position where the strain gauge 210 is provided, and analog data (waveform data) showing the change in the resistance value according to the strain. Is output. In the example of FIG. 1, the strain gauge 210 is attached to the outer ring 251. However, the strain gauge 210 may be attached to other than the outer ring 251.
　つまり、ひずみゲージ２１０は、ひずみを測定する測定対象物にひずみが生じると、ひずみに応じたアナログデータ（波形データ）を出力する。本実施形態では、ベアリング２５０は、ひずみゲージ２１０による測定対象物の一例である。本実施形態の測定対象物は、例えば、転動体が固定された部材上で自在に転動する構造を有するものであればよく、ベアリングに限定されない。 That is, when the strain is generated in the measurement object for which the strain is measured, the strain gauge 210 outputs analog data (waveform data) corresponding to the strain. In this embodiment, the bearing 250 is an example of an object to be measured by the strain gauge 210. The measurement object of the present embodiment may be, for example, any one having a structure in which the rolling element freely rolls on a fixed member, and is not limited to the bearing.
　また、本実施形態では、測定対象物のひずみを検出する手段の一例として、ひずみゲージ２１０を用いるが、ひずみの検出は、ひずみゲージ２１０以外の手段によって行われてもよい。 Further, in the present embodiment, the strain gauge 210 is used as an example of the means for detecting the strain of the object to be measured, but the strain may be detected by a means other than the strain gauge 210.
　アンプ２２０は、ひずみゲージ２１０から出力されるアナログデータを増幅させる。ＡＤＣ２３０は、増幅させたアナログデータをデジタルデータに変換する。通信回路２４０は、ＡＤＣ２３０から出力されるデジタルデータを、情報処理装置３００へ送信する。 The amplifier 220 amplifies the analog data output from the strain gauge 210. The ADC 230 converts the amplified analog data into digital data. The communication circuit 240 transmits the digital data output from the ADC 230 to the information processing apparatus 300.
　情報処理装置３００は、通信部３１０、データ取得部３２０、データ処理部３３０、異常判定部３４０、通知生成部３５０、記憶部３６０を有する。 The information processing device 300 has a communication unit 310, a data acquisition unit 320, a data processing unit 330, an abnormality determination unit 340, a notification generation unit 350, and a storage unit 360.
　尚、通信部３１０、データ取得部３２０、データ処理部３３０、異常判定部３４０は、情報処理装置３００の演算処理装置がメモリ装置に格納された異常検出プログラムを読み出して実行することで実現される。また、記憶部３６０は、例えば、情報処理装置３００が有する補助記憶装置等によって実現される。情報処理装置３００のハードウェア構成の詳細は後述する。 The communication unit 310, the data acquisition unit 320, the data processing unit 330, and the abnormality determination unit 340 are realized by the arithmetic processing device of the information processing device 300 reading and executing the abnormality detection program stored in the memory device. .. Further, the storage unit 360 is realized by, for example, an auxiliary storage device included in the information processing device 300. Details of the hardware configuration of the information processing apparatus 300 will be described later.
　通信部３１０は、センサ基板２００を含む外部の装置と通信を行う。具体的には、通信部３１０は、センサ基板２００から送信されるデジタルデータを受信する。尚、通信部３１０は、予め設定された周期で、間欠的に、センサ基板２００からデジタルデータを受信してもよい。また、通信部３１０は、異常判定部３４０により、転動体２５２の回転の異常が検出された場合、通知生成部３５０で生成された通知を外部の装置へ送信する。 The communication unit 310 communicates with an external device including the sensor board 200. Specifically, the communication unit 310 receives the digital data transmitted from the sensor board 200. The communication unit 310 may intermittently receive digital data from the sensor board 200 at a preset cycle. Further, when the abnormality determination unit 340 detects an abnormality in the rotation of the rolling element 252, the communication unit 310 transmits the notification generated by the notification generation unit 350 to an external device.
　データ取得部３２０は、通信部３１０が受信したデジタルデータを取得する。尚、データ取得部３２０が取得するデジタルデータは、転動体の通過振動を捉えた時系列信号である。 The data acquisition unit 320 acquires the digital data received by the communication unit 310. The digital data acquired by the data acquisition unit 320 is a time-series signal that captures the passing vibration of the rolling element.
　データ処理部３３０は、記憶部３６０に格納されたデジタルデータに対し、異常判定部３４０による異常判定を行うための処理を行い、処理が施された後のデータを記憶部３６０に格納する。以下の説明では、デジタルデータに対してデータ処理部３３０の処理を行った後のデータを、処理済みデータと呼ぶ場合がある。 The data processing unit 330 performs processing for performing abnormality determination by the abnormality determination unit 340 on the digital data stored in the storage unit 360, and stores the processed data in the storage unit 360. In the following description, the data after processing the digital data by the data processing unit 330 may be referred to as processed data.
　異常判定部３４０は、データ処理部３３０による処理が施された処理済みデータに基づき、測定対象物（ベアリング２５０）の状態を検出する。より具体的には、異常判定部３４０は、測定対象物の状態が異常であるか否かの判定や、測定対象物の異常の予兆の検出等を行う。 The abnormality determination unit 340 detects the state of the object to be measured (bearing 250) based on the processed data processed by the data processing unit 330. More specifically, the abnormality determination unit 340 determines whether or not the state of the measurement object is abnormal, detects a sign of abnormality of the measurement object, and the like.
　尚、本実施形態におけるベアリング２５０の異常とは、例えば、ベアリング２５０の損傷（転動体、外輪、内輪を含む）、グリスの劣化、異物混入による回転の不具合等である。 The abnormality of the bearing 250 in the present embodiment is, for example, damage to the bearing 250 (including rolling elements, outer ring, inner ring), deterioration of grease, rotation failure due to foreign matter contamination, and the like.
　例えば、ベアリング２５０の外輪２５１に傷が入ると、転動体２５２の通過振動の高調波成分の振幅値が増加する。本実施形態では、例えば、転動体２５２の通過振動の高調波成分の振幅値の変化を、外輪２５１に傷が入る前の予兆として検出してもよい。 For example, if the outer ring 251 of the bearing 250 is scratched, the amplitude value of the harmonic component of the passing vibration of the rolling element 252 increases. In the present embodiment, for example, a change in the amplitude value of the harmonic component of the passing vibration of the rolling element 252 may be detected as a sign before the outer ring 251 is damaged.
　通知生成部３５０は、異常判定部３４０により、異常や異常の予兆が検出された場合に、その旨を示す通知を生成する。 The notification generation unit 350 generates a notification indicating an abnormality or a sign of an abnormality when the abnormality determination unit 340 detects an abnormality or a sign of the abnormality.
　本実施形態では、例えば、転動体２５２の通過振動の高調波成分の振幅値の変化に基づき、外輪２５１に傷が入る前の予兆を検出し、ユーザに通知することで、外輪２５１に傷が入ることを未然に防ぐことができる。 In the present embodiment, for example, based on the change in the amplitude value of the harmonic component of the passing vibration of the rolling element 252, the outer ring 251 is damaged by detecting a sign before the outer ring 251 is damaged and notifying the user. You can prevent it from entering.
　記憶部３６０は、データ処理部３３０による処理済みデータが格納される。 The storage unit 360 stores the processed data by the data processing unit 330.
　次に、図２を参照して、本実施形態の情報処理装置３００のハードウェア構成について説明する。図２は、第一の実施形態の情報処理装置のハードウェア構成の一例を示す図である。 Next, the hardware configuration of the information processing apparatus 300 of the present embodiment will be described with reference to FIG. FIG. 2 is a diagram showing an example of the hardware configuration of the information processing apparatus of the first embodiment.
　本実施形態の情報処理装置３００は、それぞれバスＢで相互に接続されている入力装置３１、出力装置３２、ドライブ装置３３、補助記憶装置３４、メモリ装置３５、演算処理装置３６及びインターフェース装置３７を含むコンピュータであり、異常検出装置の一例である。 The information processing device 300 of the present embodiment includes an input device 31, an output device 32, a drive device 33, an auxiliary storage device 34, a memory device 35, an arithmetic processing device 36, and an interface device 37, which are connected to each other by a bus B, respectively. It is a computer including, and is an example of an abnormality detection device.
　入力装置３１は、各種の情報の入力を行うための装置であり、例えばタッチパネル等により実現される。出力装置３２は、各種の情報の出力を行うためものであり、例えばディスプレイ等により実現される。インターフェース装置３７は、ネットワークに接続する為に用いられる。 The input device 31 is a device for inputting various information, and is realized by, for example, a touch panel or the like. The output device 32 is for outputting various kinds of information, and is realized by, for example, a display or the like. The interface device 37 is used to connect to the network.
　通信部３１０、データ取得部３２０、データ処理部３３０、異常判定部３４０，通知生成部３５０を実現させる異常検出プログラムは、情報処理装置３００を制御する各種プログラムの少なくとも一部である。異常検出プログラムは、例えば、記憶媒体３８の配布やネットワークからのダウンロード等によって提供される。異常検出プログラムを記録した記憶媒体３８は、情報を光学的、電気的或いは磁気的に記録する記憶媒体、ＲＯＭ、フラッシュメモリ等の様に情報を電気的に記録する半導体メモリ等、様々なタイプの記憶媒体を用いることができる。 The abnormality detection program that realizes the communication unit 310, the data acquisition unit 320, the data processing unit 330, the abnormality determination unit 340, and the notification generation unit 350 is at least a part of various programs that control the information processing device 300. The abnormality detection program is provided, for example, by distributing the storage medium 38, downloading from the network, or the like. The storage medium 38 on which the abnormality detection program is recorded includes various types of storage media such as a storage medium for optically, electrically or magnetically recording information, a semiconductor memory for electrically recording information such as a ROM and a flash memory, and the like. A storage medium can be used.
　また、異常検出プログラムは、異常検出プログラムを記録した記憶媒体３８がドライブ装置３３にセットされると、記憶媒体３８からドライブ装置３３を介して補助記憶装置３４にインストールされる。ネットワークからダウンロードされた異常検出プログラムは、インターフェース装置３７を介して補助記憶装置３４にインストールされる。 Further, when the storage medium 38 in which the abnormality detection program is recorded is set in the drive device 33, the abnormality detection program is installed in the auxiliary storage device 34 from the storage medium 38 via the drive device 33. The abnormality detection program downloaded from the network is installed in the auxiliary storage device 34 via the interface device 37.
　記憶部３６０を実現する補助記憶装置３４は、情報処理装置３００にインストールされた異常検出プログラムを格納すると共に、情報処理装置３００による各種の必要なファイル、データ等を格納する。メモリ装置３５は、情報処理装置３００の起動時に補助記憶装置３４から異常検出プログラムを読み出して格納する。そして、演算処理装置３６はメモリ装置３５に格納された異常検出プログラムに従って、後述するような各種処理を実現している。 The auxiliary storage device 34 that realizes the storage unit 360 stores the abnormality detection program installed in the information processing device 300, and also stores various necessary files, data, and the like by the information processing device 300. The memory device 35 reads and stores the abnormality detection program from the auxiliary storage device 34 when the information processing device 300 is started. Then, the arithmetic processing device 36 realizes various processes as described later according to the abnormality detection program stored in the memory device 35.
　次に、図３を参照して、本実施形態の情報処理装置３００の処理について説明する。図３は、第一の実施形態の情報処理装置の処理を説明する第一のフローチャートである。図３に示す処理は、主にデータ処理部３３０の処理である。図３の処理は、通信部３１０がデジタルデータを受信する度に実行される。 Next, the processing of the information processing apparatus 300 of the present embodiment will be described with reference to FIG. FIG. 3 is a first flowchart illustrating the processing of the information processing apparatus of the first embodiment. The process shown in FIG. 3 is mainly the process of the data processing unit 330. The process of FIG. 3 is executed every time the communication unit 310 receives digital data.
　本実施形態のデータ処理部３３０は、データ取得部３２０が取得したデジタルデータに対し、高速フーリエ変換処理（ＦＦＴ；fast Fourier transform）を実行し、周波数領域の波形データを取得する（ステップＳ３０１）。 The data processing unit 330 of the present embodiment executes a fast Fourier transform (FFT) on the digital data acquired by the data acquisition unit 320, and acquires waveform data in the frequency domain (step S301).
　続いて、データ処理部３３０は、取得した周波数領域の波形データから、パワーが極大値かつ最大値となる周波数を算出し、その周波数を転動体２５２の通過振動の周波数とする（ステップＳ３０２）。以下の説明では、転動体２５２の通過振動の周波数の波形を基本波形と呼び、基本波形を示す波形データを基本波形データと呼ぶ場合がある。また、転動体２５２の通過振動とは、転動体２５２が、外輪２５１においてひずみゲージ２１０が取り付けられた箇所を通過する際に生じる外輪２５１の振動を示す。 Subsequently, the data processing unit 330 calculates the frequency at which the power becomes the maximum value and the maximum value from the acquired waveform data in the frequency region, and sets that frequency as the frequency of the passing vibration of the rolling element 252 (step S302). In the following description, the waveform of the frequency of the passing vibration of the rolling element 252 may be referred to as a basic waveform, and the waveform data showing the basic waveform may be referred to as the basic waveform data. Further, the passing vibration of the rolling element 252 refers to the vibration of the outer ring 251 generated when the rolling element 252 passes through the portion of the outer ring 251 to which the strain gauge 210 is attached.
　続いて、データ処理部３３０は、基本波形の周波数の＋１０％から－１０％までの範囲の周波数成分を抽出する。また、データ処理部３３０は、転動体２５２の通過振動のＮ次高調波成分のそれぞれについて、周波数の＋１０％から－１０％までの範囲の周波数成分を抽出する（ステップＳ３０３）。尚、本実施形態では、基本波形の周波数は、Ｎ＝１のときであり、Ｎ次高調波とは、Ｎ＝２～５の周波数の高調波とした。ただし、Ｎの値は、これに限定されるものではない。 Subsequently, the data processing unit 330 extracts frequency components in the range of + 10% to -10% of the frequency of the basic waveform. Further, the data processing unit 330 extracts a frequency component in the range of + 10% to -10% of the frequency for each of the Nth harmonic components of the passing vibration of the rolling element 252 (step S303). In the present embodiment, the frequency of the basic waveform is when N = 1, and the Nth harmonic is a harmonic having a frequency of N = 2 to 5. However, the value of N is not limited to this.
　続いて、データ処理部３３０は、抽出した各周波数成分に対して逆ＦＦＴを行って、周波数領域の波形データを時間領域の波形データとし、各波形データの時間領域における振幅の実効値を算出する（ステップＳ３０４）。 Subsequently, the data processing unit 330 performs inverse FFT on each of the extracted frequency components, converts the waveform data in the frequency domain into waveform data in the time domain, and calculates the effective value of the amplitude of each waveform data in the time domain. (Step S304).
　具体的には、データ処理部３３０は、基本波形の周波数を中心とした＋１０％から－１０％までの範囲の周波数成分に対し、逆ＦＦＴを行った結果の波形データの振幅の実効値を算出する。また、データ処理部３３０は、Ｎ次高調波成分（Ｎ＝２～５）を中心とした＋１０％から－１０％までの範囲の周波数成分に対し、逆ＦＦＴを行った結果の波形データの振幅の実効値を算出する。 Specifically, the data processing unit 330 calculates the effective value of the amplitude of the waveform data as a result of performing the inverse FFT for the frequency component in the range of + 10% to -10% centered on the frequency of the basic waveform. do. Further, the data processing unit 330 performs inverse FFT on a frequency component in the range of + 10% to -10% centered on the Nth harmonic component (N = 2 to 5), and the amplitude of the waveform data as a result. Calculate the effective value of.
　続いて、データ処理部３３０は、ステップＳ３０４において、転動体２５２のＮ次高調波成分（Ｎ＝２～５）に基づき算出されたそれぞれの振幅の実効値を、基本波形データに基づき算出された振幅の実効値で除算した値を算出し、この値を特徴量とする（ステップＳ３０５）。 Subsequently, in step S304, the data processing unit 330 calculated the effective value of each amplitude calculated based on the Nth harmonic component (N = 2 to 5) of the rolling element 252 based on the basic waveform data. A value divided by the effective value of the amplitude is calculated, and this value is used as a feature amount (step S305).
　言い換えれば、データ処理部３３０は、基本波形データに基づき算出された振幅の実効値と、Ｎ次高調波成分に基づき算出されたそれぞれの振幅の実効値との比率を、特徴量として算出する。本実施形態の特徴量とは、転動体２５２の回転の状態を示す値であり、言い換えれば、ベアリング２５０（測定対象物）の状態を示す値である。 In other words, the data processing unit 330 calculates the ratio of the effective value of the amplitude calculated based on the basic waveform data and the effective value of each amplitude calculated based on the Nth harmonic component as the feature amount. The feature amount of the present embodiment is a value indicating a state of rotation of the rolling element 252, in other words, a value indicating a state of the bearing 250 (measurement object).
　続いて、データ処理部３３０は、正常データの収集期間が経過したか否かを判定する（ステップＳ３０６）。 Subsequently, the data processing unit 330 determines whether or not the normal data collection period has elapsed (step S306).
　収集期間とは、ベアリング２５０が正常な状態で動作していると推定される期間であり、正常データとは、収集期間中に取得されたデジタルデータから算出された特徴量である。 The collection period is the period during which the bearing 250 is estimated to be operating in a normal state, and the normal data is the feature amount calculated from the digital data acquired during the collection period.
　本実施形態の収集期間とは、例えば、ベアリング２５０の工場出荷時から所定の期間であってもよいし、ベアリング２５０の稼働時間が所定時間に到達するまでの期間であってもよい。本実施形態の収集期間は、任意に設定が可能であってもよい。 The collection period of the present embodiment may be, for example, a predetermined period from the factory shipment of the bearing 250, or may be a period until the operating time of the bearing 250 reaches the predetermined time. The collection period of the present embodiment may be arbitrarily set.
　ステップＳ３０６において、収集期間が経過していない場合、データ処理部３３０は、ステップＳ３０５で算出した特徴量を記憶部３６０に保存し（ステップＳ３０７）、処理を終了する。以下の説明では、収集期間に記憶部３６０に保存された特徴量群を、正常データと呼ぶ場合がある。 If the collection period has not elapsed in step S306, the data processing unit 330 stores the feature amount calculated in step S305 in the storage unit 360 (step S307), and ends the process. In the following description, the feature amount group stored in the storage unit 360 during the collection period may be referred to as normal data.
　本実施形態の正常データには、Ｎ＝２と対応する特徴量群と、Ｎ＝３と対応する特徴量群と、Ｎ＝４と対応する特徴量群と、Ｎ＝５と対応する特徴量群とが含まれる。 The normal data of this embodiment includes a feature amount group corresponding to N = 2, a feature amount group corresponding to N = 3, a feature amount group corresponding to N = 4, and a feature amount corresponding to N = 5. Groups and are included.
　ステップＳ３０６において、収集期間が経過している場合、情報処理装置３００は、異常判定部３４０により、ステップＳ３０５で算出した特徴量を用いた異常判定処理を行い（ステップＳ３０８）、処理を終了する。 In step S306, when the collection period has elapsed, the information processing apparatus 300 performs an abnormality determination process using the feature amount calculated in step S305 by the abnormality determination unit 340 (step S308), and ends the process.
　以下に、図４を参照して、本実施形態の異常判定部３４０の処理について説明する。図４は、第一の実施形態の情報処理装置の処理を説明する第二のフローチャートである。図４に示す処理は、主に、異常判定部３４０の処理である。 Hereinafter, the processing of the abnormality determination unit 340 of the present embodiment will be described with reference to FIG. FIG. 4 is a second flowchart illustrating the processing of the information processing apparatus of the first embodiment. The process shown in FIG. 4 is mainly the process of the abnormality determination unit 340.
　本実施形態の異常判定部３４０は、図３のステップＳ３０６において、収集期間が経過している場合、記憶部３６０から正常データを読み出し、正規化パラメータを抽出する（ステップＳ４０１）。 In step S306 of FIG. 3, the abnormality determination unit 340 of the present embodiment reads normal data from the storage unit 360 and extracts normalization parameters when the collection period has elapsed (step S401).
　具体的には、異常判定部３４０は、正常データに含まれるＮ＝２と対応する特徴量群と、Ｎ＝３と対応する特徴量群と、Ｎ＝４と対応する特徴量群と、Ｎ＝５と対応する特徴量群と、のそれぞれについて、平均値と分散と算出する。 Specifically, the abnormality determination unit 340 includes a feature amount group corresponding to N = 2, a feature amount group corresponding to N = 3, a feature amount group corresponding to N = 4, and N. = 5 and the corresponding feature group, and the average value and variance are calculated for each.
　続いて、異常判定部３４０は、正常データの正規化に用いた正規化パラメータを用いて、評価データを正規化する（ステップＳ４０２）。評価データとは、収集期間が経過した後に、データ取得部３２０が取得したデジタルデータに基づき、データ処理部３３０が算出したＮ＝２～５のそれぞれと対応する特徴量である。 Subsequently, the abnormality determination unit 340 normalizes the evaluation data using the normalization parameters used for normalizing the normal data (step S402). The evaluation data is a feature amount corresponding to each of N = 2 to 5 calculated by the data processing unit 330 based on the digital data acquired by the data acquisition unit 320 after the collection period has elapsed.
　ステップＳ４０２において、また、異常判定部３４０は、ステップＳ４０２において、この評価データを、ステップＳ４０２で用いた正規化パラメータ（平均値と分散）を用いて正規化し、後述する特徴量空間における座標を示す値とする。 In step S402, and in step S402, the abnormality determination unit 340 normalizes this evaluation data using the normalization parameters (mean value and variance) used in step S402, and shows the coordinates in the feature amount space described later. Let it be a value.
　続いて、異常判定部３４０は、特徴量を座標値とした空間上における、ステップＳ４０２で正規化された評価データの近傍のデータ密度と、ステップＳ４０１で正規化された正常データの近傍のデータ密度の比を算出する（ステップＳ４０３）。本実施形態では、データ密度の比を異常度とする。異常度とは、ベアリング２５０の状態が異常であるか否かを判定する際の指標なる値である。 Subsequently, the abnormality determination unit 340 has a data density in the vicinity of the evaluation data normalized in step S402 and a data density in the vicinity of the normal data normalized in step S401 on the space using the feature amount as the coordinate value. The ratio of is calculated (step S403). In this embodiment, the ratio of data density is defined as the degree of abnormality. The degree of abnormality is a value that is an index for determining whether or not the state of the bearing 250 is abnormal.
　続いて、異常判定部３４０は、「異常度がある閾値を超え、且つ、その頻度が所定の値を超えた」、という条件を満たすか否かを判定する（ステップＳ４０４）。尚、異常度の閾値や、所定の値は、予め設定されていてもよい。ステップＳ４０３、ステップＳ４０４の詳細は後述する。 Subsequently, the abnormality determination unit 340 determines whether or not the condition that "the degree of abnormality exceeds a certain threshold value and the frequency exceeds a predetermined value" is satisfied (step S404). The threshold value of the degree of abnormality and a predetermined value may be set in advance. Details of steps S403 and S404 will be described later.
　ステップＳ４０４において、条件を満たす場合、異常判定部３４０は、ベアリング２５０の状態が異常な状態と判定し、通知生成部３５０により、異常を示す通知を生成し、通信部３１０により通知を送信し（ステップＳ４０５）、処理を終了する。 If the condition is satisfied in step S404, the abnormality determination unit 340 determines that the state of the bearing 250 is an abnormal state, the notification generation unit 350 generates a notification indicating an abnormality, and the communication unit 310 transmits the notification ( Step S405), the process is terminated.
　本実施形態の通知は、例えば、ベアリング２５０に異常が生じていることを示すメッセージ等であってもよく、その場合には、例えば、情報処理装置３００と接続されたディスプレイ等に通知を表示させてもよい。また、本実施形態の通知は、ベアリング２５０が異常な状態であることを示す警報等であってもよく、この警報は、センサ基板２００に対して出力されてもよい。センサ基板２００は、この警報を受け付けて、例えば、ベアリング２５０の上位装置等にも警報を通知してもよい。 The notification of the present embodiment may be, for example, a message indicating that an abnormality has occurred in the bearing 250, and in that case, for example, the notification is displayed on a display or the like connected to the information processing apparatus 300. You may. Further, the notification of the present embodiment may be an alarm or the like indicating that the bearing 250 is in an abnormal state, and this alarm may be output to the sensor board 200. The sensor board 200 may receive this alarm and notify the alarm to, for example, a higher-level device of the bearing 250.
　ステップＳ４０４において、「異常度がある閾値を超え、且つ、その頻度が所定の値を超えた」、という条件を満たさない場合、異常判定部３４０は、正常と判定し（ステップＳ４０６）、処理を終了する。尚、本実施形態では、異常判定部３４０により、正常と判定された場合も、正常であることを示す通知を通知生成部３５０により生成して出力してもよい。 In step S404, if the condition that "the degree of abnormality exceeds a certain threshold value and the frequency exceeds a predetermined value" is not satisfied, the abnormality determination unit 340 determines that it is normal (step S406) and performs processing. finish. In the present embodiment, even when the abnormality determination unit 340 determines that the abnormality is normal, the notification generation unit 350 may generate and output a notification indicating the normality.
　以下に、図５及び図６を参照して、異常判定部３４０による異常判定ついて、さらに説明する。尚、本実施形態では、特徴量空間は、Ｎ次高調波成分（Ｎ＝２～５）に応じた４次元で表現されるものであるが、図５及び図６の説明では、理解を容易にするため、特徴量空間を２次元の空間として説明する。 Hereinafter, the abnormality determination by the abnormality determination unit 340 will be further described with reference to FIGS. 5 and 6. In the present embodiment, the feature space is represented in four dimensions according to the Nth harmonic component (N = 2 to 5), but it is easy to understand in the explanations of FIGS. 5 and 6. Therefore, the feature space will be described as a two-dimensional space.
　図５は、異常判定部による異常判定について説明する第一の図である。図５の例では、横軸をＮ＝２と対応した特徴量とし、縦軸をＮ＝３と対応した特徴量としており、正規化後評価データが正常なデータである場合を示している。 FIG. 5 is the first diagram illustrating the abnormality determination by the abnormality determination unit. In the example of FIG. 5, the horizontal axis is the feature amount corresponding to N = 2, the vertical axis is the feature amount corresponding to N = 3, and the case where the post-normalized evaluation data is normal data is shown.
　図５において、点群５１は、ステップＳ４０１で正規化された正常データを示す。また、点５２は、Ｎ＝２と対応する正規化後の正常データと、Ｎ＝３と対応する正規化後の正常データとを用いて、正規化した評価データを示す。以下の図５及び図６の説明では、正規化後の正常データと、正規化後の評価データを、正規化後正常データと、正規化後評価データと呼ぶ。 In FIG. 5, the point cloud 51 shows the normal data normalized in step S401. Further, point 52 shows the evaluation data normalized by using the normalized normal data corresponding to N = 2 and the normalized normal data corresponding to N = 3. In the following description of FIGS. 5 and 6, the normalized data after normalization and the evaluation data after normalization are referred to as normalized data after normalization and evaluation data after normalization.
　異常判定部３４０は、特徴量空間において、正規化後評価データ５２の近傍に配置されたデータの密度を算出する（例；近傍数３）。本実施形態では、近傍数を３つとしているため、正規化後評価データ５２を中心に、周囲のデータが３つ含まれる領域Ｒが特定される。図５の例では、正規化後評価データ５２の近くに配置された３つの正規化後正常データ５１ａ、５１ｂ、５１ｃを含む領域Ｒが特定される。尚、近傍数は、３に限定されない。 The anomaly determination unit 340 calculates the density of the data arranged in the vicinity of the normalized evaluation data 52 in the feature quantity space (example; number of neighborhoods 3). In the present embodiment, since the number of neighborhoods is three, the region R including three surrounding data is specified centering on the normalized evaluation data 52. In the example of FIG. 5, a region R including three post-normalized normal data 51a, 51b, 51c arranged near the post-normalized evaluation data 52 is specified. The number of neighborhoods is not limited to 3.
　また、異常判定部３４０は、正規化後正常データ５１ａ、５１ｂ、５１ｃのそれぞれを含む領域Ｒ１、Ｒ２、Ｒ３を特定する。 Further, the abnormality determination unit 340 identifies the regions R1, R2, and R3 including the normalized normal data 51a, 51b, and 51c, respectively.
　そして、異常判定部３４０は、領域Ｒにおけるデータ密度と、領域Ｒ１、Ｒ２、Ｒ３のそれぞれにおける正規化後正常データのデータ密度とを算出する。具体的には、異常判定部３４０は、領域Ｒ、Ｒ１、Ｒ２、Ｒ３内の正規化後正常データの個数をデータ密度としてもよい。 Then, the abnormality determination unit 340 calculates the data density in the region R and the data density of the normalized normal data in each of the regions R1, R2, and R3. Specifically, the abnormality determination unit 340 may use the number of normalized normal data in the regions R, R1, R2, and R3 as the data density.
　次に、異常判定部３４０は、領域Ｒのデータ密度と、領域Ｒ１、Ｒ２、Ｒ３の平均データ密度との比率を、異常度として算出する。 Next, the abnormality determination unit 340 calculates the ratio between the data density of the region R and the average data density of the regions R1, R2, and R3 as the degree of abnormality.
　図５の例では、正規化後評価データ５２を取得したときのデジタルデータは、ベアリング２５０が正常な状態において取得された正常時のデータと言える。 In the example of FIG. 5, it can be said that the digital data when the normalized evaluation data 52 is acquired is the normal data acquired when the bearing 250 is in a normal state.
　図６は、異常判定部による異常判定について説明する第二の図である。図６では、横軸をＮ＝２と対応した特徴量とし、縦軸をＮ＝３と対応した特徴量としており、正規化後評価データが異常なデータである場合を示している。 FIG. 6 is a second diagram illustrating an abnormality determination by the abnormality determination unit. In FIG. 6, the horizontal axis is the feature amount corresponding to N = 2, and the vertical axis is the feature amount corresponding to N = 3, indicating a case where the normalized evaluation data is abnormal data.
　図６の例では、異常判定部３４０は、領域Ｒと、正規化後正常データ５１ｄ、５１ｅ、５１ｆのそれぞれを含む領域Ｒ４、Ｒ５、Ｒ６を特定する。そして、異常判定部３４０は、領域Ｒのデータ密度と、領域Ｒ４、Ｒ５、Ｒ６の平均データ密度との比率を、異常度として算出する。 In the example of FIG. 6, the abnormality determination unit 340 specifies the region R and the regions R4, R5, and R6 including the normalized normal data 51d, 51e, and 51f, respectively. Then, the abnormality determination unit 340 calculates the ratio between the data density of the region R and the average data density of the regions R4, R5, and R6 as the degree of abnormality.
　図６の例では、正規化後評価データ５２を取得したときのデジタルデータは、ベアリング２５０が異常な状態において取得された異常時のデータと言える。 In the example of FIG. 6, the digital data when the normalized evaluation data 52 is acquired can be said to be the abnormal data acquired when the bearing 250 is in an abnormal state.
　本実施形態の異常判定部３４０は、例えば、図６に示すように、正規化後評価データ５２が異常のデータとなることが、複数回続いた場合に、ベアリング２５０の異常を検出してもよい。 For example, as shown in FIG. 6, the abnormality determination unit 340 of the present embodiment detects an abnormality in the bearing 250 when the normalized evaluation data 52 becomes abnormality data a plurality of times. good.
　このように、本実施形態によれば、ベアリング２５０の定常状態における内輪２５３の回転数や、観測波形の周期及び振幅等が未知である場合や、回転速度が変動する場合であっても、ベアリング２５０の異常を検出することができる。 As described above, according to the present embodiment, even when the rotation speed of the inner ring 253 in the steady state of the bearing 250, the period and amplitude of the observed waveform are unknown, or the rotation speed fluctuates, the bearing 250 anomalies can be detected.
　また、本実施形態では、ひずみゲージ２１０から出力される信号から、転動体２５２の通過振動を示す周波数の振幅と、この周波数のＮ次高調波成分の振幅との比率によって示される特徴量に基づき、ベアリング２５０の異常を検出する。 Further, in the present embodiment, based on the feature amount indicated by the ratio of the amplitude of the frequency indicating the passing vibration of the rolling element 252 to the amplitude of the Nth harmonic component of this frequency from the signal output from the strain gauge 210. , Detects an abnormality in the bearing 250.
　このため、本実施形態では、ひずみゲージ２１０の温度特性の影響を低減し、ひずみのみで、ベアリング２５０の異常を検出することができる。 Therefore, in the present embodiment, the influence of the temperature characteristic of the strain gauge 210 can be reduced, and the abnormality of the bearing 250 can be detected only by the strain.
　また、本実施形態では、ベアリングの異常の有無を検出する際に、測定対象物となるベアリング毎に、正常データを収集し、収集した正常データを基準とする。そして、本実施形態では、特徴量空間上で、測定対象のベアリングの正常データのデータ密度に着目し異常度を算出している。このため、本実施形態では、異常を検出する条件が一定であれば、ベアリングの機種が異なっても、ベアリングの種類によって事前に基準値を設定する必要がない。 Further, in the present embodiment, when detecting the presence or absence of an abnormality in the bearing, normal data is collected for each bearing to be measured, and the collected normal data is used as a reference. Then, in the present embodiment, the degree of abnormality is calculated by paying attention to the data density of the normal data of the bearing to be measured in the feature space. Therefore, in the present embodiment, if the conditions for detecting an abnormality are constant, it is not necessary to set a reference value in advance depending on the type of bearing, even if the bearing model is different.
　さらに、本実施形態の異常判定部３４０は、異常度が閾値を超えた場合に、ベアリング２５０の異常を検出するものとしたが、異常判定部３４０は、異常度に応じて、異常の予兆を検出してもよい。 Further, the abnormality determination unit 340 of the present embodiment detects the abnormality of the bearing 250 when the abnormality degree exceeds the threshold value, but the abnormality determination unit 340 detects a sign of abnormality according to the abnormality degree. It may be detected.
　具体的には、例えば、異常判定部３４０は、異常度が閾値に到達する前の段階で、異常の予兆を検出し、通知生成部３５０に対し、異常の予兆があることを示す通知を生成させてもよい。この通知は、通信部３１０によって、外部へ送信されてもよい。 Specifically, for example, the abnormality determination unit 340 detects a sign of abnormality before the degree of abnormality reaches the threshold value, and generates a notification to the notification generation unit 350 indicating that there is a sign of abnormality. You may let me. This notification may be transmitted to the outside by the communication unit 310.
　（第二の実施形態）
　以下に図面を参照して、第二の実施形態について説明する。第二の実施形態は、情報処理装置３００の機能を、半導体集積回路によって実現した点が、第一の実施形態と相違する。よって、第二の実施形態の説明では、第一の実施形態と同様の機能構成を有するものには、第一の実施形態の説明で用いた符号を付与し、その説明を省略する。 (Second embodiment)
The second embodiment will be described below with reference to the drawings. The second embodiment is different from the first embodiment in that the function of the information processing apparatus 300 is realized by a semiconductor integrated circuit. Therefore, in the description of the second embodiment, the reference numerals used in the description of the first embodiment are given to those having the same functional configuration as that of the first embodiment, and the description thereof will be omitted.
　図７は、第二の実施形態の異常検出システムのシステム構成の一例を示す図である。本実施形態の異常検出システム１００Ａは、センサ基板２００と、異常検出装置４００とを含む。異常検出システム１００Ａにおいて、異常検出装置４００は、情報処理装置３００の各部の機能を有する回路を１つに認めた、用途特定向け集積回路（ＡＳＩＣ；application specific integrated circuit）である。 FIG. 7 is a diagram showing an example of the system configuration of the abnormality detection system of the second embodiment. The abnormality detection system 100A of the present embodiment includes a sensor board 200 and an abnormality detection device 400. In the abnormality detection system 100A, the abnormality detection device 400 is an application specific integrated circuit (ASIC) in which a circuit having the functions of each part of the information processing device 300 is recognized as one.
　本実施形態の異常検出装置４００は、通信回路４１０、データ取得回路４２０、データ処理回路４３０、異常判定回路４４０、通知出力回路４５０、記憶装置４６０を有する。 The abnormality detection device 400 of the present embodiment includes a communication circuit 410, a data acquisition circuit 420, a data processing circuit 430, an abnormality determination circuit 440, a notification output circuit 450, and a storage device 460.
　通信回路４１０は、センサ基板２００と通信を行う。データ取得回路４２０は、データ取得部３２０の機能を実現する。データ処理回路４３０は、データ処理部３３０の機能を実現する。異常判定回路４４０は、異常判定部３４０の機能を実現する。通知出力回路４５０は、通知生成部３５０の機能を実現する。記憶装置４６０は、記憶部３６０に対応する。 The communication circuit 410 communicates with the sensor board 200. The data acquisition circuit 420 realizes the function of the data acquisition unit 320. The data processing circuit 430 realizes the function of the data processing unit 330. The abnormality determination circuit 440 realizes the function of the abnormality determination unit 340. The notification output circuit 450 realizes the function of the notification generation unit 350. The storage device 460 corresponds to the storage unit 360.
　尚、異常検出装置４００は、記憶装置４６０を含むものとしたが、これに限定されない。異常検出装置４００は、記憶装置４６０を有していなくてもよく、その場合には、記憶装置４６０は、異常検出装置４００の外部に実装されて、データ処理回路４３０と異常判定回路４４０とに接続されればよい。 The abnormality detection device 400 includes, but is not limited to, the storage device 460. The abnormality detection device 400 does not have to have the storage device 460. In that case, the storage device 460 is mounted outside the abnormality detection device 400 and becomes a data processing circuit 430 and an abnormality determination circuit 440. All you have to do is connect.
　本実施形態では、このように、情報処理装置３００の機能を集積回路である異常検出装置４００とすることで、例えば、センサ基板２００上に、異常検出装置４００を実装することができる。 In the present embodiment, by setting the function of the information processing device 300 to the abnormality detection device 400 which is an integrated circuit, for example, the abnormality detection device 400 can be mounted on the sensor board 200.
　したがって、本実施形態では、測定対象物の異常を検知するための情報処理装置３００を配置する必要がなく、特に、上位装置の内部に、ベアリング２５０と、センサ基板２００と異常検出装置４００とを内蔵させることができる。 Therefore, in the present embodiment, it is not necessary to arrange the information processing device 300 for detecting the abnormality of the object to be measured, and in particular, the bearing 250, the sensor board 200, and the abnormality detecting device 400 are provided inside the host device. It can be built in.
　（第三の実施形態）
　以下に図面を参照して、第三の実施形態について説明する。第三の実施形態では、第二の実施形態に示す異常検出装置にセンサ基板を含めた点が、第二の実施形態と相違する。よって、以下の第三の実施形態の説明では、第二の実施形態との相違点について説明し、第二の実施形態と同様の機能構成については、第二の実施形態の説明で用いた符号を付与し、説明を省略する。 (Third embodiment)
The third embodiment will be described below with reference to the drawings. The third embodiment is different from the second embodiment in that the sensor substrate is included in the abnormality detection device shown in the second embodiment. Therefore, in the following description of the third embodiment, the differences from the second embodiment will be described, and the functional configuration similar to that of the second embodiment will be described with reference to the reference numerals used in the description of the second embodiment. Is given, and the description is omitted.
　図８は、第三の実施形態の異常検出装置を示す図である。本実施形態の異常検出装置４００Ａは、ひずみゲージ２１０、アンプ２２０、ＡＤＣ２３０、データ取得回路４２０、データ処理回路４３０、異常判定回路４４０、通知出力回路４５０を有する。また、本実施形態の異常検出装置４００Ａは、データ処理回路４３０によってデータが書き込まれ、異常判定回路４４０によってデータが読み出される記憶装置４６０が接続される。 FIG. 8 is a diagram showing an abnormality detection device according to a third embodiment. The abnormality detection device 400A of the present embodiment includes a strain gauge 210, an amplifier 220, an ADC 230, a data acquisition circuit 420, a data processing circuit 430, an abnormality determination circuit 440, and a notification output circuit 450. Further, the abnormality detection device 400A of the present embodiment is connected to a storage device 460 in which data is written by the data processing circuit 430 and the data is read out by the abnormality determination circuit 440.
　本実施形態では、このように、異常検出装置４００Ａにひずみゲージ２１０を含む構成とすることで、異常検出装置４００Ａを測定対象物の外輪に取り付けるだけで、この測定対象物における転動体２５２の転動によって生じる振動の異常を検出することができる。 In the present embodiment, by configuring the abnormality detection device 400A to include the strain gauge 210 in this way, the rolling element 252 in the measurement object can be rolled by simply attaching the abnormality detection device 400A to the outer ring of the measurement object. Abnormal vibration caused by motion can be detected.
　また、本実施形態の異常検出装置４００Ａは、ベアリング２５０を含んでいないが、異常検出装置４００Ａには、ベアリング２５０が含まれてもよい。 Further, although the abnormality detection device 400A of the present embodiment does not include the bearing 250, the abnormality detection device 400A may include the bearing 250.
　以上、各実施形態に基づき本発明の説明を行ってきたが、上記実施形態に示した要件に本発明が限定されるものではない。これらの点に関しては、本発明の主旨をそこなわない範囲で変更することができ、その応用形態に応じて適切に定めることができる。 Although the present invention has been described above based on each embodiment, the present invention is not limited to the requirements shown in the above embodiments. With respect to these points, the gist of the present invention can be changed to the extent that the gist of the present invention is not impaired, and can be appropriately determined according to the application form thereof.
　また、本国際出願は、２０２０年１２月１８日に出願された日本国特許出願２０２０－２１０６１１に基づく優先権を主張するものであり、日本国特許出願２０２０－２１０６１１の全内容を本国際出願に援用する。 In addition, this international application claims priority based on the Japanese patent application 2020-210611 filed on December 18, 2020, and the entire contents of the Japanese patent application 2020-210611 are included in this international application. Use it.
１００、１００Ａ　異常検出システム、２００　センサ基板，２１０　ひずみゲージ，２２０　アンプ，２３０　ＡＤＣ，２４０　通信回路，３００　情報処理装置，３１０　通信部，３２０　データ取得部，３３０　データ処理部，３４０　異常判定部，３５０　通知生成部，３６０　記憶部，４００、４００Ａ　異常検出装置 100, 100A abnormality detection system, 200 sensor board, 210 strain gauge, 220 amplifier, 230 ADC, 240 communication circuit, 300 information processing device, 310 communication unit, 320 data acquisition unit, 330 data processing unit, 340 abnormality determination unit, 350 Notification generation unit, 360 storage unit, 400, 400A abnormality detection device

Claims (10)

  1. 　転動体の通過振動を捉えた信号を取得するデータ取得部と、
    　前記信号を用いて、前記転動体の通過振動を示す周波数の振幅と、前記通過振動を示す周波数のＮ次高調波の信号成分の振幅と、の比率を示す特徴量を算出するデータ処理部と、
    　前記特徴量に基づき、前記転動体を含む測定対象物の状態が異常であるか否かを判定する異常判定部と、を有する異常検出装置。     A data acquisition unit that acquires signals that capture the passing vibration of the rolling elements,
    Using the signal, a data processing unit that calculates a feature amount indicating the ratio between the amplitude of the frequency indicating the passing vibration of the rolling element and the amplitude of the signal component of the Nth harmonic of the frequency indicating the passing vibration. ,
    An abnormality detection device including an abnormality determination unit for determining whether or not the state of a measurement object including the rolling element is abnormal based on the feature amount.
  2. 　前記データ処理部は、
    　前記信号を高速フーリエ変換により、周波数領域の信号に変換し、
    　前記転動体の通過振動を示す周波数を含む所定範囲の周波数成分と、前記通過振動を示す周波数のＮ次高調波を含む所定範囲の周波数成分とを抽出し、
    　抽出した周波数成分の信号を逆高速フーリエ変換により時間領域の信号に変換し、
    　前記時間領域に変換された前記通過振動を示す周波数の振幅の実効値と、前記時間領域に変換された前記Ｎ次高調波の振幅の実効値との比率を算出する、請求項１記載の異常検出装置。     The data processing unit
    The signal is converted into a signal in the frequency domain by a fast Fourier transform, and the signal is converted into a signal in the frequency domain.
    A frequency component in a predetermined range including a frequency indicating the passing vibration of the rolling element and a frequency component in a predetermined range including the Nth harmonic of the frequency indicating the passing vibration are extracted.
    The extracted frequency component signal is converted into a time domain signal by inverse fast Fourier transform.
    The abnormality according to claim 1, wherein the ratio of the effective value of the amplitude of the frequency indicating the passing vibration converted into the time domain and the effective value of the amplitude of the Nth harmonic converted into the time domain is calculated. Detection device.
  3. 　前記転動体の通過振動によって生じるひずみを検出し、アナログデータを出力するひずみセンサと、
    　前記アナログデータを増幅するアンプと、
    　前記アンプから出力されたアナログデータを前記信号に変換する変換器と、
    　前記信号を前記データ取得部へ送信する通信回路と、が実装されたセンサ基板を含む、請求項１記載の異常検出装置。     A strain sensor that detects the strain caused by the passing vibration of the rolling element and outputs analog data,
    An amplifier that amplifies the analog data and
    A converter that converts analog data output from the amplifier into the signal, and
    The abnormality detection device according to claim 1, further comprising a communication circuit for transmitting the signal to the data acquisition unit and a sensor board on which the signal is mounted.
  4. 　前記異常判定部により、前記測定対象物の異常が検出された場合に、前記異常を示す通知を生成する通知生成部を有する、請求項１記載の異常検出装置。 The abnormality detection device according to claim 1, further comprising a notification generation unit that generates a notification indicating the abnormality when the abnormality determination unit detects an abnormality in the measurement object.
  5. 　異常検出装置による異常検出方法であって、前記異常検出装置が、
    　転動体の通過振動を捉えた信号を取得し、
    　前記信号を用いて、前記転動体の通過振動を示す周波数の振幅と、前記通過振動を示す周波数のＮ次高調波の信号成分の振幅と、の比率を示す特徴量を算出し、
    　前記特徴量に基づき、前記転動体を含む測定対象物の状態が異常であるか否かを判定する、異常検出方法。     An abnormality detection method using an abnormality detection device, wherein the abnormality detection device is
    Acquires a signal that captures the passing vibration of the rolling element,
    Using the signal, a feature amount indicating the ratio between the amplitude of the frequency indicating the passing vibration of the rolling element and the amplitude of the signal component of the Nth harmonic of the frequency indicating the passing vibration was calculated.
    An abnormality detection method for determining whether or not the state of a measurement object including the rolling element is abnormal based on the feature amount.
  6. 　転動体の通過振動を捉えた信号を取得し、
    　前記信号を用いて、前記転動体の通過振動を示す周波数の振幅と、前記通過振動を示す周波数のＮ次高調波の信号成分の振幅と、の比率を示す特徴量を算出し、
    　前記特徴量に基づき、前記転動体を含む測定対象物の状態が異常であるか否かを判定する、処理をコンピュータに実行させる、異常検出プログラム。     Acquires a signal that captures the passing vibration of the rolling element,
    Using the signal, a feature amount indicating the ratio between the amplitude of the frequency indicating the passing vibration of the rolling element and the amplitude of the signal component of the Nth harmonic of the frequency indicating the passing vibration was calculated.
    An abnormality detection program that causes a computer to execute a process of determining whether or not the state of a measurement object including the rolling element is abnormal based on the feature amount.
  7. 　ベアリングと、
    　前記ベアリングの通過振動によって生じるひずみを検出し、アナログデータを出力する、前記ベアリングに取り付けられたひずみセンサと、
    　前記アナログデータを増幅するアンプと、
    　前記アンプから出力されたアナログデータをデジタルデータに変換する変換器と、
    　前記デジタルデータを用いて、前記ベアリングの通過振動を示す周波数の振幅と、前記通過振動を示す周波数のＮ次高調波の信号成分の振幅と、の比率を示す特徴量を算出するデータ処理部と、
    　前記特徴量に基づき、前記ベアリングの状態が異常であるか否かを判定する異常判定部と、を有するベアリングの異常検出システム。     Bearings and
    A strain sensor attached to the bearing that detects the strain caused by the passing vibration of the bearing and outputs analog data.
    An amplifier that amplifies the analog data and
    A converter that converts analog data output from the amplifier into digital data,
    Using the digital data, a data processing unit that calculates a feature amount indicating the ratio between the amplitude of the frequency indicating the passing vibration of the bearing and the amplitude of the signal component of the Nth harmonic of the frequency indicating the passing vibration. ,
    An abnormality detection system for bearings, comprising an abnormality determination unit for determining whether or not the state of the bearing is abnormal based on the feature amount.
  8. 　前記データ処理部は、
    　前記デジタルデータを高速フーリエ変換により、周波数領域のデジタルデータに変換し、
    　前記ベアリングの通過振動を示す周波数を含む所定範囲の周波数成分と、前記通過振動を示す周波数のＮ次高調波を含む所定範囲の周波数成分とを抽出し、
    　抽出した周波数成分のデジタルデータを逆高速フーリエ変換により時間領域のデジタルデータに変換し、
    　前記時間領域に変換された前記通過振動を示す周波数の振幅の実効値と、前記時間領域に変換された前記Ｎ次高調波の振幅の実効値との比率を算出する、請求項７記載のベアリングの異常検出システム。     The data processing unit
    The digital data is converted into digital data in the frequency domain by the fast Fourier transform.
    A predetermined range of frequency components including the frequency indicating the passing vibration of the bearing and a predetermined range of frequency components including the Nth harmonic of the frequency indicating the passing vibration are extracted.
    The extracted digital data of the frequency component is converted into the digital data in the time domain by the inverse fast Fourier transform.
    The bearing according to claim 7, wherein the ratio of the effective value of the amplitude of the frequency indicating the passing vibration converted into the time domain and the effective value of the amplitude of the Nth harmonic converted into the time domain is calculated. Abnormality detection system.
  9. 　前記異常判定部により、前記ベアリングの異常が検出された場合に、前記異常を示す通知を生成する通知生成部を有する、請求項７記載のベアリングの異常検出システム。 The bearing abnormality detection system according to claim 7, further comprising a notification generation unit that generates a notification indicating the abnormality when the abnormality determination unit detects an abnormality in the bearing.
  10. 　前記ベアリングの通過振動による信号は、前記ひずみセンサによるひずみのみを検出する、請求項７記載のベアリングの異常検出システム。 The bearing abnormality detection system according to claim 7, wherein the signal due to the passing vibration of the bearing detects only the strain by the strain sensor.
PCT/JP2021/045659 2020-12-18 2021-12-10 Anomaly detection device, anomaly detection method, anomaly detection program, and system for detecting anomaly in bearing WO2022131170A1 (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH11173956A (en) * 1997-12-15 1999-07-02 Omron Corp Method and apparatus for judging quality
JP2020056801A (en) * 2020-01-10 2020-04-09 中国電力株式会社 Measurement diagnostic apparatus and measurement diagnostic method
US20200225117A1 (en) * 2019-01-15 2020-07-16 Computational Systems, Inc. Bearing and Fault Frequency Identification From Vibration Spectral Plots

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH11173956A (en) * 1997-12-15 1999-07-02 Omron Corp Method and apparatus for judging quality
US20200225117A1 (en) * 2019-01-15 2020-07-16 Computational Systems, Inc. Bearing and Fault Frequency Identification From Vibration Spectral Plots
JP2020056801A (en) * 2020-01-10 2020-04-09 中国電力株式会社 Measurement diagnostic apparatus and measurement diagnostic method

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