# US 2019/0170704 A1 · Rotating machine abnormality detection device and method, and rotating machine > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0170704 A1 - Document ID: US20190170704A1 - Status: Published application - Kind: A1 - Application number: 16/325,192 - Filed: 2017-08-28 - Published: 2019-06-06 - Earliest claimed: 2016-10-06 - Assignees: Kabushiki Kaisha Kobe Seiko Sho (Kobe Steel, Ltd.) - Applicants: KABUSHIKI KAISHA KOBE SEIKO SHO (Kobe Steel, Ltd.) - Inventors: Kaname ARAKI; Eiji TAKAHASHI; Shugo TAKAKI; Masato HAYASHI - Web page: https://patentgrep.com/patent/US20190170704A1 ## CPC - G01M 13/028: Acoustic or vibration analysis - G01N 29/46: by spectral analysis, e.g. Fourier analysis {or wavelet analysis (spectral signal processing per se G06F17/14)} - G01H 17/00: Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the other groups of this subclass - G01M 99/00: Subject matter not provided for in other groups of this subclass - G01N 29/14: using acoustic emission techniques {(echo of particles G01N29/046; measuring mechanical vibrations or acoustic waves in solids in general G01H1/00)} - G01N 29/4472: {Mathematical theories or simulation} - G01M: TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - G01H: MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES ## Abstract In a rotating machine abnormality detection device, a rotating machine abnormality detection method, and a rotating machine according to the present invention, vibration caused by at least one of first and second rotating bodies is measured, a predetermined feature amount related to a frequency component is obtained based on a frequency spectrum of the measurement data, and determination is made on presence/absence of abnormality based on the obtained predetermined feature amount. On this occasion, when determination is made that abnormality is present, determination whether the determination of abnormality is caused by noise or not is made based on the frequency spectrum, and when determination is made that the determination of abnormality is not caused by the noise, the determined abnormality is ultimately considered as abnormality. ## Claims ### Claim 1 A rotating machine abnormality detection device which detects abnormality in a rotating machine having at least a first rotating body and a second rotating body which rotate around respective predetermined shafts while engaging with each other with a predetermined gap provided therebetween in a normal state, the device comprising: a vibration measurement unit which measures vibration caused by at least one of the first and second rotating bodies; a spectrum processing unit which obtains a frequency spectrum of measurement data measured by the vibration measurement unit; a feature amount processing unit which obtains a predetermined feature amount related to a predetermined frequency component, based on the frequency spectrum obtained by the spectrum processing unit; an abnormality determination unit which determines presence/absence of abnormality in the rotating machine, based on the predetermined feature amount obtained by the feature amount processing unit; and a noise determination unit which when determination is made that abnormality is present by the abnormality determination unit, determines, based on the frequency spectrum obtained by the spectrum process unit, whether the determination of abnormality is caused by noise or not, wherein when the noise determination unit determines that the determination of abnormality is not caused by the noise, the abnormality determination unit ultimately considers the determined abnormality as abnormality. ### Claim 2 (depends on 1) The rotating machine abnormality detection device according to claim 1, further comprising a storage unit which stores, as a normal frequency spectrum, the frequency spectrum of measurement data measured by the vibration measurement unit, when the abnormality determination unit determines that abnormality is absent, wherein the noise determination unit determines whether the determination of abnormality is caused by noise or not, based on a difference between the frequency spectrum obtained by the spectrum processing unit and the normal frequency spectrum stored in the storage unit. ### Claim 3 (depends on 2) The rotating machine abnormality detection device according to claim 2, wherein the noise determination unit determines whether the determination of abnormality is caused by noise or not, based on a subtraction result obtained by subtracting an average value of the difference from a maximum value of the difference. ### Claim 4 (depends on 2) The rotating machine abnormality detection device according to claim 2, wherein the noise determination unit determines whether the determination of abnormality is caused by noise or not, based on a subtraction result obtained by subtracting an intermediate value of the difference from a maximum value of the difference. ### Claim 5 (depends on 1) The rotating machine abnormality detection device according to claim 1, wherein when a first number of teeth and a first rotation frequency of the first rotating body are represented as MA [unit] and VA [Hz], respectively, a second number of teeth of the second rotating body is represented as MB [unit], a least common multiple of the first number of teeth MA and the second number of teeth MB is represented as XAB, a basic wave mesh frequency VA/MA obtained by dividing the first rotation frequency VA by the first number of teeth MA is represented as f1 [Hz], and n-th harmonic mesh frequencies (n is an integer of 2 or more) with respect to the basic wave mesh frequency f1 are represented as fn [Hz], the feature amount processing unit obtains, from the frequency spectrum, a basic wave component F1 of the basic wave mesh frequency f1 and n-th harmonic components Fn of the n-th harmonic mesh frequencies fn (n=2 to XAB) up to the least common multiple XAB, and obtains the predetermined feature amount based on the obtained basic wave component F1 and n-th harmonic components Fn. ### Claim 6 (depends on 5) The rotating machine abnormality detection device according to claim 5, wherein the spectrum processing unit obtains first and second frequency spectra of first and second measurement data measured in first and second periods different from each other, respectively, and the feature amount processing unit obtains the basic wave component F1 and the n-th harmonic components Fn in the first and second periods, respectively, from the first and second frequency spectra, to obtain, as the predetermined feature amount, an amount of change in the obtained basic wave component F1 and n-th harmonic components Fn in each of the first and second periods. ### Claim 7 (depends on 6) The rotating machine abnormality detection device according to claim 6, wherein the feature amount processing unit obtains, as the amount of change, a square sum of a difference in components of the obtained basic wave components F1 and n-th harmonic components Fn in each of the first and second periods. ### Claim 8 (depends on 5) The rotating machine abnormality detection device according to claim 5, wherein the feature amount processing unit further obtains, from the frequency spectrum, non-harmonic components G of predetermined frequencies g present between adjacent frequencies among the basic wave mesh frequency f1 and the n-th harmonic mesh frequencies fn (n=2 to XAB) up to the least common multiple XAB to obtain the predetermined feature amount based on the obtained basic wave component FI, n-th harmonic components Fn, and non-harmonic components G. ### Claim 9 (depends on 5) The rotating machine abnormality detection device according to claim 5, further comprising a model information storage unit which stores in advance, as model information, model values of the basic wave component F1 and the n-th harmonic components Fn corresponding to modes of abnormality occurring in the first and second rotating bodies, wherein the feature amount processing unit obtains a matching degree indicative of a degree of matching between the obtained basic wave component F1 and n-th harmonic components Fn, and the model information for each mode of abnormality, and obtains, as the predetermined feature amount, a maximum matching degree among the matching degrees obtained for each mode of abnormality. ### Claim 10 (depends on 9) The rotating machine abnormality detection device according to claim 9, wherein the abnormality determination unit determines the presence of abnormality in the rotating machine in the mode of abnormality having the maximum matching degree among the matching degrees obtained for each mode of abnormality by the feature amount processing unit. ### Claim 11 (depends on 5) The rotating machine abnormality detection device according to claim 5, further comprising a model information storage unit which stores in advance, as model information, model values of the basic wave component F1 and the n-th harmonic components Fn corresponding to modes of abnormality occurring in the first and second rotating bodies, wherein: the spectrum processing unit obtains first and second frequency spectra of first and second measurement data measured in first and second periods different from each other, respectively; and the feature amount processing unit conducts a plurality of processes among followings: a total sum calculation process for obtaining a total sum of the obtained basic wave component F1 and n-th harmonic components Fn; an amount of change calculation process for obtaining the basic wave components F1 and the n-th harmonic components Fn in the first and second periods, respectively, from both the first and second frequency spectra, and then obtaining an amount of change of the obtained basic wave components F1 and n-th harmonic components Fn in each of the first and second periods; a total sum ratio of component calculation process for further obtaining, from the frequency spectrum, non-harmonic components Gi (i: integer from 1 to (n−1)) of predetermined frequencies gi present between adjacent frequencies among the basic wave mesh frequency f1 and the n-th harmonic mesh frequencies fir (n=2 to XAB) up to the least common multiple XAB, and then obtaining a total sum ratio of component by dividing a total sum of the obtained basic wave component F1 and n-th harmonic components Fn by a total sum of the obtained non-harmonic components Gi; and a maximum matching degree calculation process for obtaining a matching degree indicative of a degree of matching between the obtained basic wave component F1 and n-th harmonic components Fn, and the model information for each mode of abnormality, and then obtaining a maximum matching degree among the matching degrees obtained for each mode of abnormality, and obtains the predetermined feature amount based on process results of the plurality of processes conducted. ### Claim 12 (depends on 1) The rotating machine abnormality detection device according to claim 1, wherein the spectrum processing unit includes a high pass filter which eliminates noise, and a sub-spectrum processing unit which obtains a frequency spectrum of measurement data, the measurement data being measured by the vibration measurement unit and having passed through the high pass filter. ### Claim 13 A rotating machine abnormality detection method for detecting abnormality in a rotating machine having a first rotating body and a second rotating body which rotate around respective predetermined shaft while engaging with each other with a predetermined gap provided therebetween in a normal state, the method comprising: a vibration measuring step for measuring vibration caused by at least one of the first and second rotating bodies; a spectrum process step for obtaining a frequency spectrum of measurement data measured in the vibration measuring step; a feature amount process step for obtaining a predetermined feature amount related to a predetermined frequency component, based on the frequency spectrum obtained in the spectrum process step; an abnormality determination step for determining presence/absence of abnormality in the rotating machine, based on the predetermined feature amount obtained in the feature amount process step; and a noise determination step for determining presence/absence of noise superimposing on the measurement data measured in the vibration measuring step, based on the frequency spectrum obtained in the spectrum process step, wherein the noise determination step is conducted when determination is made in the abnormality determination step that abnormality is present, and when determination is made in the noise determination step that the noise is absent, the determined abnormality is ultimately considered as abnormality in the abnormality determination step. ### Claim 14 (depends on 1) A rotating machine comprising the rotating machine abnormality detection device according to claim 1.