JP2018132409A - Deterioration determination device, method for deterioration determination, and program - Google Patents
Deterioration determination device, method for deterioration determination, and program Download PDFInfo
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Abstract
Description
本発明は、劣化判定装置、劣化判定方法、プログラムに関する。 The present invention relates to a deterioration determination device, a deterioration determination method, and a program.
測定対象機構の構造体から発せられた信号によってその構造体の欠陥を検査する手法が特許文献１に開示されている。当該特許文献１の技術は物体に誘導波を励起し、センサで検出された誘導波の検出信号を解析することにより物体内の欠陥を検査するものである。 Patent Document 1 discloses a technique for inspecting a defect of a structure based on a signal emitted from the structure of the measurement target mechanism. The technology of Patent Document 1 is to inspect defects in an object by exciting a guided wave on the object and analyzing a detection signal of the guided wave detected by a sensor.
ところで構造体の劣化を検査する場合に、上記の誘導波などを構造体に与えることなくより短時間で劣化を判定できることが望ましい。 By the way, when inspecting the deterioration of the structure, it is desirable that the deterioration can be determined in a shorter time without giving the above-described induced wave or the like to the structure.
そこでこの発明は、上述の課題を解決することのできる劣化判定装置、劣化判定方法、プログラムを提供することを目的としている。 Accordingly, an object of the present invention is to provide a deterioration determination device, a deterioration determination method, and a program that can solve the above-described problems.
本発明の第１の態様によれば、劣化判定装置は、劣化判定時に測定対象機構から実際に発せられた弾性波からノイズを除去してノイズ除去信号を抽出するノイズ除去部と、複数の異なる劣化状態を再現した試験体それぞれの発する弾性波の代表波形に相当する信号と前記ノイズ除去信号とに基づいて前記ノイズ除去信号に近い前記代表波形を特定する劣化状態判定部と、を備えることを特徴とする。 According to the first aspect of the present invention, the deterioration determination device is different from a noise removal unit that removes noise from an elastic wave actually emitted from the measurement target mechanism at the time of deterioration determination and extracts a noise removal signal. A deterioration state determination unit that specifies the representative waveform close to the noise removal signal based on a signal corresponding to a representative waveform of an elastic wave generated by each of the test bodies that reproduces the deterioration state and the noise removal signal. Features.
上述の劣化判定装置において、前記劣化状態判定部は、特定した代表波形に対応する劣化状態を前記ノイズ除去信号に対応する劣化状態と判定してよい。 In the above-described deterioration determination device, the deterioration state determination unit may determine a deterioration state corresponding to the identified representative waveform as a deterioration state corresponding to the noise removal signal.
また上述の劣化判定装置において、前記劣化状態判定部は、前記代表波形が示す弾性波の特徴情報と、前記ノイズ除去信号が示す弾性波の特徴情報とを分析して、前記ノイズ除去信号に近い前記代表波形を特定してよい。 Moreover, in the above-described deterioration determination device, the deterioration state determination unit analyzes the characteristic information of the elastic wave indicated by the representative waveform and the characteristic information of the elastic wave indicated by the noise removal signal, and is close to the noise removal signal. The representative waveform may be specified.
また上述の劣化判定装置において、前記劣化状態判定部は、前記代表波形が示す弾性波の特徴情報と、前記ノイズ除去信号が示す弾性波の特徴情報とを主成分分析により解析して、前記ノイズ除去信号に近い前記代表波形を特定してよい。 Further, in the above-described deterioration determination device, the deterioration state determination unit analyzes the characteristic information of the elastic wave indicated by the representative waveform and the characteristic information of the elastic wave indicated by the noise removal signal by principal component analysis, and performs the noise analysis. The representative waveform close to the removal signal may be specified.
また上述の劣化判定装置において、前記ノイズ除去部は、前記測定対象機構から実際に発せられた弾性波において所定の振幅閾値以上の第一区間と、当該第一区間に続く前記振幅閾値未満の第二区間の波形を特定し、前記第一区間と前記第二区間の波形を時間周波数解析した結果に対して短時間フーリエ変換を行い、当該短時間フーリエ変換の結果で得られた周波数ごとのエネルギーの時間平均値のデータを逆フーリエ変換することによって前記ノイズ除去信号を抽出してよい。 Moreover, in the above-described degradation determination device, the noise removing unit includes a first section that is equal to or greater than a predetermined amplitude threshold in an elastic wave actually emitted from the measurement target mechanism, and a first section that is less than the amplitude threshold that follows the first section. The energy of each frequency obtained from the result of the short-time Fourier transform is obtained by performing the short-time Fourier transform on the result of the time-frequency analysis of the waveform of the first and second sections, The noise-removed signal may be extracted by performing inverse Fourier transform on the time-averaged data.
本発明の第２の態様によれば、劣化判定方法は、劣化判定時に測定対象機構から実際に発せられた弾性波からノイズを除去してノイズ除去信号を抽出し、複数の異なる劣化状態を再現した試験体それぞれの発する弾性波の代表波形に相当する信号と前記ノイズ除去信号とに基づいて前記ノイズ除去信号に近い前記代表波形を特定することを特徴とする。 According to the second aspect of the present invention, the deterioration determination method removes noise from the elastic wave actually emitted from the measurement target mechanism at the time of deterioration determination, extracts a noise removal signal, and reproduces a plurality of different deterioration states. The representative waveform close to the noise removal signal is specified based on a signal corresponding to a representative waveform of an elastic wave generated by each of the test specimens and the noise removal signal.
本発明の第３の態様によれば、プログラムは、劣化判定装置のコンピュータを、劣化判定時に測定対象機構から実際に発せられた弾性波からノイズを除去してノイズ除去信号を抽出するノイズ除去手段、複数の異なる劣化状態を再現した試験体それぞれの発する弾性波の代表波形に相当する信号と前記ノイズ除去信号とに基づいて前記ノイズ除去信号に近い前記代表波形を特定する劣化状態判定手段、として機能させることを特徴とする。 According to the third aspect of the present invention, the program causes the computer of the deterioration determination device to remove noise from the elastic wave actually emitted from the measurement target mechanism at the time of deterioration determination and extract a noise removal signal. A deterioration state determining means for identifying the representative waveform close to the noise removal signal based on a signal corresponding to a representative waveform of an elastic wave generated by each of the test specimens reproducing a plurality of different deterioration states and the noise removal signal, It is made to function.
本発明によれば、測定対象機構の構造体の劣化を検査する場合に、誘導波などを構造体に与えることなくより短時間で劣化を判定することができる。 ADVANTAGE OF THE INVENTION According to this invention, when test | inspecting degradation of the structure of a measuring object mechanism, degradation can be determined in a short time, without giving an induced wave etc. to a structure.
以下、本発明の一実施形態による劣化判定装置、劣化判定方法、プログラムを図面を参照して説明する。
図１は本実施形態による劣化判定装置を備えた劣化判定システムを示す図である。
劣化判定装置１は一例として風力発電機２の内部に備わるＡＥセンサ２１に電気信号ケーブルにより接続される。ＡＥセンサ２１は測定対象機構である軸受に取り付けられている。劣化判定装置１はブレードの回転に伴って回転するロータ軸の軸受が発生するアコースティックエミッション波（弾性波）の電気信号をＡＥセンサ２１から受信する。以下、アコースティックエミッション波をＡＥ波と呼ぶ。劣化判定装置１はＡＥ波を解析して風力発電機２のロータ軸の軸受の劣化を判定する。劣化判定装置１はＡＥ波を解析して風力発電機２のロータ軸の軸受の劣化の劣化状態がどのような劣化状態の種別であるかを判定することができる。
Hereinafter, a deterioration determination device, a deterioration determination method, and a program according to an embodiment of the present invention will be described with reference to the drawings.
FIG. 1 is a diagram illustrating a deterioration determination system including a deterioration determination apparatus according to the present embodiment.
As an example, the degradation determination device 1 is connected to an AE sensor 21 provided inside the wind power generator 2 by an electric signal cable. The AE sensor 21 is attached to a bearing that is a measurement target mechanism. The degradation determination device 1 receives an electrical signal of an acoustic emission wave (elastic wave) generated by a bearing of a rotor shaft that rotates with the rotation of the blade from the AE sensor 21. Hereinafter, the acoustic emission wave is referred to as an AE wave. The deterioration determination device 1 analyzes the AE wave to determine deterioration of the bearing of the rotor shaft of the wind power generator 2. The deterioration determination device 1 can analyze the AE wave and determine the type of deterioration state of the deterioration state of the bearing of the rotor shaft of the wind power generator 2.
本実施形態において劣化判定装置１はロータ軸の軸受の劣化を判定するが、劣化判定装置１は他の測定対象機構の構造体の劣化を判定するようにしてもよい。軸受は例えばボールベアリングなどである。ボールベアリングを構成するボールはその回転によって摩耗や亀裂が発生する場合がある。本実施形態の劣化判定装置１はこのような摩耗や亀裂の何れの劣化であるかを判定する。 In the present embodiment, the deterioration determination device 1 determines the deterioration of the bearing of the rotor shaft, but the deterioration determination device 1 may determine the deterioration of the structure of the other measurement target mechanism. The bearing is, for example, a ball bearing. The ball constituting the ball bearing may be worn or cracked by its rotation. The degradation determination device 1 of this embodiment determines which degradation is such wear or crack.
図２は本実施形態による劣化判定装置の構成を示すブロック図である。
図２で示すように劣化判定装置１は、ＣＰＵ（Central Processing Unit）１０１、ＲＯＭ（Read Only Memory）１０２、ＲＡＭ（Random Access Memory）１０３、ＨＤＤ（Hard Disk Drive）１０４、信号受信モジュール１０５を備えるコンピュータである。
FIG. 2 is a block diagram showing the configuration of the deterioration determination apparatus according to this embodiment.
As shown in FIG. 2, the degradation determination apparatus 1 includes a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, an HDD (Hard Disk Drive) 104, and a signal receiving module 105. It is a computer.
図３は本実施形態による劣化判定装置の機能ブロック図である。
劣化判定装置１のＣＰＵ１０１が記憶するプログラムを実行することにより、劣化判定装置１は制御部１１、ノイズ除去部１２、劣化状態判定部１３、表示部１４の各構成を備える。
FIG. 3 is a functional block diagram of the degradation determination apparatus according to the present embodiment.
By executing a program stored in the CPU 101 of the deterioration determination apparatus 1, the deterioration determination apparatus 1 includes the control unit 11, the noise removal unit 12, the deterioration state determination unit 13, and the display unit 14.
制御部１１は劣化判定装置１に備わる他の機能部を制御する。
ノイズ除去部１２は劣化判定時に測定対象機構から実際に発せられたＡＥ波からノイズを除去してノイズ除去信号を抽出する。
劣化状態判定部１３は、複数の異なる劣化状態を再現した試験体それぞれの発するＡＥ波の代表波形に相当する信号と前記ノイズ除去信号とに基づいて前記ノイズ除去信号に近い前記代表波形を特定する。劣化状態判定部１３は、上記の代表波形が示すＡＥ波の特徴情報と、ノイズ除去信号が示すＡＥ波の特徴情報とを分析して、ノイズ除去信号に近い代表波形を特定する。劣化状態判定部１３はその特定した代表波形に基づいて、測定対象機構の劣化状態を判定する。
表示部１４は例えば劣化判定装置１の出力情報を表示する。
本実施形態において測定対象機構は軸受である。
The control unit 11 controls other functional units provided in the deterioration determination device 1.
The noise removing unit 12 removes noise from the AE wave actually emitted from the measurement target mechanism when determining deterioration, and extracts a noise removal signal.
The deterioration state determination unit 13 specifies the representative waveform close to the noise removal signal based on the signal corresponding to the representative waveform of the AE wave emitted by each of the test specimens reproducing a plurality of different deterioration states and the noise removal signal. . The degradation state determination unit 13 analyzes the feature information of the AE wave indicated by the representative waveform and the feature information of the AE wave indicated by the noise removal signal, and identifies a representative waveform close to the noise removal signal. The deterioration state determination unit 13 determines the deterioration state of the measurement target mechanism based on the identified representative waveform.
For example, the display unit 14 displays output information of the deterioration determination device 1.
In the present embodiment, the measurement target mechanism is a bearing.
劣化判定装置１を用いて劣化判定を行う担当者は、複数の異なる劣化状態を再現した試験体それぞれが発するＡＥ波の代表波形の情報を予め劣化判定装置１に記録しておく。具体的には、担当者は軸受に対応する試験体に対して第一の劣化状態である亀裂型の損傷を人為的に発生させる。一例として、亀裂型の損傷は軸受内部のボールに発生するピーリングである。また担当者は軸受に対応する試験体に対して第二の劣化状態である摩耗型の損傷を人為的に発生させる。一例として、摩耗型の損傷は軸受内部のボールに発生するボール形状の摩耗である。第一の劣化状態、第二の劣化状態はそれぞれ、軸受を回転させる際の単位時間当たりの回転数、軸受に与える荷重、軸受内部に使用する潤滑油、回転時間などを異にすることにより発生させる。 The person in charge who performs the deterioration determination using the deterioration determination apparatus 1 records in advance in the deterioration determination apparatus 1 information on the representative waveform of the AE wave generated by each of the specimens reproducing a plurality of different deterioration states. Specifically, the person in charge artificially generates crack-type damage, which is the first deterioration state, on the test body corresponding to the bearing. As an example, crack-type damage is peeling that occurs on balls inside the bearing. Further, the person in charge artificially generates a wear-type damage, which is the second deterioration state, on the specimen corresponding to the bearing. As an example, wear-type damage is ball-shaped wear that occurs on balls inside the bearing. The first deterioration state and the second deterioration state are caused by different rotation speed per unit time when rotating the bearing, load applied to the bearing, lubricating oil used in the bearing, rotation time, etc. Let
担当者は試験体に取り付けられたＡＥセンサから出力された電気信号を、劣化判定装置１や他の受信装置等を用いて取得し、その検出信号からノイズを除去して各劣化状態についてのＡＥ波の代表波を取得する。担当者は各劣化状態についてのＡＥ波の代表波の情報を劣化判定装置１に記録する。 The person in charge acquires the electrical signal output from the AE sensor attached to the specimen using the degradation determination device 1 or another receiving device, removes noise from the detection signal, and performs AE for each degradation state. Get a representative wave. The person in charge records information on the representative wave of the AE wave for each deterioration state in the deterioration determination apparatus 1.
図４はノイズ除去処理の概要を示す図である。
ＡＥセンサ２１から出力された電気信号のノイズ除去手法を説明する。担当者は、取得したＡＥ波の電気信号の時刻歴データ（４２）において、波形の振幅を示す電圧が所定の閾値を超える第一区間（５１）を特定する。時刻歴データ（４２）において縦軸は電圧、横軸は時間を示す。担当者は、当該ＡＥ波の電気信号の時刻歴データ（４２）において、第一区間（５１）に続く波形であって、振幅を示す電圧が上記所定の閾値未満の第二区間（５２）の波形を特定する。担当者は、第一区間（５１）と第二区間（５２）の波形に対して短時間フーリエ変換（ＳＴＦＴ）処理を行う。その結果、担当者は時間に応じた信号の周波数とその周波数におけるエネルギーの関係を示す時間周波数解析データ（４１）を得る。図４で示す時間周波数解析データ（４１）において縦軸は周波数、横軸は時間、濃淡はエネルギーを表す。担当者は時間周波数解析データにおける上記第二区間に対応する時間区間おけるエネルギーの時間平均値を周波数ごとに算出する。担当者は、エネルギーの時間平均値に所定の係数を乗じた値を減算する処理を、第一区間と第二区間の対応する周波数のエネルギーについて行いノイズ除去する（４３）。ノイズ除去後の周波数と時間とエネルギーの関係を示すデータ（４３）において縦軸は周波数、横軸は時間、濃淡はエネルギーを表す。担当者はそのノイズ除去の結果を逆フーリエ変換してＡＥ波のノイズ除去信号（４４）を算出する。ノイズ除去信号（４４）において縦軸は電圧、横軸は時間を示す。当該ノイズ除去信号がＡＥ波の代表波となる。担当者はこのようなノイズ除去を行ったＡＥ波の代表波を各劣化状態それぞれについて算出し、劣化装置に記録する。
FIG. 4 is a diagram showing an outline of the noise removal processing.
A method for removing noise from the electrical signal output from the AE sensor 21 will be described. The person in charge specifies the first section (51) in which the voltage indicating the waveform amplitude exceeds the predetermined threshold in the time history data (42) of the acquired electrical signal of the AE wave. In the time history data (42), the vertical axis represents voltage and the horizontal axis represents time. The person in charge in the time history data (42) of the electrical signal of the AE wave has a waveform following the first section (51), and the voltage indicating the amplitude is less than the predetermined threshold in the second section (52). Identify the waveform. The person in charge performs short-time Fourier transform (STFT) processing on the waveforms in the first section (51) and the second section (52). As a result, the person in charge obtains time frequency analysis data (41) indicating the relationship between the frequency of the signal according to time and the energy at that frequency. In the time-frequency analysis data (41) shown in FIG. 4, the vertical axis represents frequency, the horizontal axis represents time, and the shading represents energy. The person in charge calculates the time average value of the energy in the time interval corresponding to the second interval in the time frequency analysis data for each frequency. The person in charge performs a process of subtracting a value obtained by multiplying the time average value of energy by a predetermined coefficient for the energy of the corresponding frequency in the first section and the second section to remove noise (43). In the data (43) showing the relationship between frequency, time and energy after noise removal, the vertical axis represents frequency, the horizontal axis represents time, and the shading represents energy. The person in charge calculates the AE wave noise removal signal (44) by performing an inverse Fourier transform on the result of the noise removal. In the noise removal signal (44), the vertical axis represents voltage and the horizontal axis represents time. The noise removal signal becomes a representative wave of the AE wave. The person in charge calculates the representative wave of the AE wave subjected to such noise removal for each deterioration state and records it in the deterioration device.
上述の各劣化状態のＡＥ波の代表波は劣化判定装置１が試験体から得た電気信号に基づいて、上記手法に対応する演算を行って抽出するようにしてもよい。試験体は、測定対象機構である軸受そのものであってもよいし、軸受とは異なる試験体であってもよい。試験体が測定対象機構である軸受と異なる場合には、試験体に基づいて算出したＡＥ波の代表波に、係数を乗じて、測定対象機構の劣化判定に利用できる、対応する代表波として算出してもよい。 The representative wave of the above-described AE wave in each deterioration state may be extracted by performing an operation corresponding to the above method based on the electrical signal obtained from the specimen by the deterioration determination device 1. The test body may be a bearing itself as a measurement target mechanism, or may be a test body different from the bearing. When the test specimen is different from the bearing that is the measurement target mechanism, the representative wave of the AE wave calculated based on the test specimen is multiplied by a coefficient to calculate the corresponding representative wave that can be used for determining the deterioration of the measurement target mechanism. May be.
図５は本実施形態による劣化判定装置の処理フローを示す図である。
次に劣化判定装置の処理フローについて順を追って説明する。
劣化判定装置１は軸受においてＡＥセンサ２１がセンシングした電気信号を受信する（ステップＳ４０１）。ノイズ除去部１２は電気信号を取得する。ノイズ除去部１２は取得した電気信号の時刻歴データにおいて、波形の振幅を示す電圧が所定の閾値を超える第一区間を特定する。ノイズ除去部１２は第一区間に続く波形であって、振幅を示す電圧が上記所定の閾値未満の第二区間の波形を特定する。ノイズ除去部１２は第一区間と第二区間の波形に対して短時間フーリエ変換（ＳＴＦＴ）処理を行う。その結果、ノイズ除去部１２は、時間に応じた信号の周波数とその周波数におけるエネルギーの関係を示す時間周波数解析データを得る。ノイズ除去部１２は、時間周波数解析データにおける上記第二区間に対応する時間区間おけるエネルギーの時間平均値を周波数ごとに算出する。そしてノイズ除去部１２は、エネルギーの時間平均値に所定の係数を乗じた値を減算する処理を、第一区間と第二区間の対応する周波数のエネルギーについて行う。またノイズ除去部１２は次にその算出結果を逆フーリエ変換してノイズ除去信号を算出する（ステップＳ４０２）。ノイズ除去部１２はこのノイズ除去信号を軸受におけるＡＥ波として劣化状態判定部１３へ出力する。ノイズ除去部１２におけるノイズ除去の処理は、Ｐｒｕｎｉｎｇ法、Ｓｏｆｔ−ｔｈｒｅｓｈｈｏｌｄ法などの公知の技術を用いる。ステップＳ４０２のノイズ除去信号の算出手法は図４を用いて説明した手法と同様である。
FIG. 5 is a diagram illustrating a processing flow of the degradation determination apparatus according to the present embodiment.
Next, the processing flow of the deterioration determination apparatus will be described in order.
The degradation determination device 1 receives the electrical signal sensed by the AE sensor 21 at the bearing (step S401). The noise removal unit 12 acquires an electrical signal. The noise removing unit 12 specifies a first section in which the voltage indicating the waveform amplitude exceeds a predetermined threshold in the acquired time history data of the electrical signal. The noise removing unit 12 specifies a waveform in a second section that is a waveform following the first section and whose voltage indicating the amplitude is less than the predetermined threshold. The noise removing unit 12 performs a short-time Fourier transform (STFT) process on the waveforms in the first section and the second section. As a result, the noise removing unit 12 obtains time-frequency analysis data indicating the relationship between the frequency of the signal according to time and the energy at that frequency. The noise removing unit 12 calculates a time average value of energy in the time interval corresponding to the second interval in the time frequency analysis data for each frequency. And the noise removal part 12 performs the process which subtracts the value which multiplied the predetermined coefficient to the time average value of energy about the energy of the frequency corresponding to a 1st area and a 2nd area. The noise removing unit 12 then calculates the noise removal signal by performing inverse Fourier transform on the calculation result (step S402). The noise removal unit 12 outputs the noise removal signal to the deterioration state determination unit 13 as an AE wave in the bearing. The noise removal processing in the noise removal unit 12 uses a known technique such as a Prune method or a Soft-threshold method. The calculation method of the noise removal signal in step S402 is the same as the method described with reference to FIG.
劣化状態判定部１３は劣化判定装置１において担当者によって予め記録された試験体の各劣化状態についてのＡＥ波の代表波形を読み取る（ステップＳ４０３）。そして劣化状態判定部１３は軸受のＡＥ波の特徴量と、試験体に生じた異なる２つの劣化状態の場合のＡＥ波の各代表波の特徴量とを用いて主成分分析を行う（ステップＳ４０４）。この分析においてまず劣化状態判定部１３は軸受のＡＥ波の特徴量を算出する。劣化状態判定部１３は、試験体に生じた異なる２つの劣化状態の場合のＡＥ波を示す各代表波の特徴量を記憶部から読み取る。なお、試験体に生じた異なる２つの劣化状態の場合のＡＥ波を示す各代表波の特徴量は予め算出して劣化状態判定部１３が記憶している。ＡＥ波や代表波の特徴量は、振幅、エネルギー、ＲＭＳ（二乗平均平方根）、第一区間における波の事象率など値である。事象率は第一区間において、ある閾値電圧を超えた波形の個数を示す。 The deterioration state determination unit 13 reads the representative waveform of the AE wave for each deterioration state of the test specimen recorded in advance by the person in charge in the deterioration determination apparatus 1 (step S403). Then, the deterioration state determination unit 13 performs principal component analysis using the feature amount of the AE wave of the bearing and the feature amount of each representative wave of the AE wave in the case of two different deterioration states generated in the specimen (step S404). ). In this analysis, first, the deterioration state determination unit 13 calculates a feature amount of the AE wave of the bearing. The deterioration state determination unit 13 reads the characteristic amount of each representative wave indicating the AE wave in the case of two different deterioration states generated in the specimen from the storage unit. Note that the characteristic amount of each representative wave indicating the AE wave in the case of two different deterioration states generated in the specimen is calculated in advance and stored in the deterioration state determination unit 13. The feature quantities of the AE wave and the representative wave are values such as amplitude, energy, RMS (root mean square), and event rate of the wave in the first section. The event rate indicates the number of waveforms exceeding a certain threshold voltage in the first section.
そして劣化状態判定部１３は、試験体の第一劣化状態におけるＡＥ波の代表波形の特徴量(1,2,…n)それぞれの主成分得点Ｐ１＿１，Ｐ１＿２，・・・，Ｐ１＿ｎを算出する。また劣化状態判定部１３は、試験体の第二劣化状態におけるＡＥ波の代表波形の特徴量(1,2,…n)それぞれの主成分得点Ｐ２＿１，Ｐ２＿２，・・・，Ｐ２＿ｎを算出する。また劣化状態判定部１３は、各特徴量(1,2,…n)の主成分負荷量Ａ１，Ａ２，・・・Ａｎを算出する。劣化状態判定部１３は軸受のＡＥ波の特徴量(1,2,…n)それぞれの主成分得点Ｐ３＿１，Ｐ３＿２，・・・，Ｐ１＿ｎを算出する。 Then, the deterioration state determination unit 13 calculates principal component scores P1_1, P1_2,..., P1_n of the feature quantities (1, 2,... N) of the representative waveform of the AE wave in the first deterioration state of the test body. Further, the deterioration state determination unit 13 calculates principal component scores P2_1, P2_2,..., P2_n of the feature amounts (1, 2,... N) of the representative waveform of the AE wave in the second deterioration state of the specimen. The degradation state determination unit 13 calculates principal component load amounts A1, A2,... An for each feature amount (1, 2,... N). The deterioration state determination unit 13 calculates principal component scores P3_1, P3_2,..., P1_n of the feature values (1, 2,... N) of the AE wave of the bearing.
そして劣化状態判定部１３は、以下の式（１）により軸受のＡＥ波と、試験体に生じた第一の劣化状態のＡＥ波の第一評価距離を算出する。また劣化状態判定部１３は、以下の式（２）により軸受のＡＥ波と、試験体に生じた第二の劣化状態のＡＥ波の第二評価距離を算出する。 Then, the deterioration state determination unit 13 calculates the first evaluation distance between the AE wave of the bearing and the AE wave in the first deterioration state generated in the specimen by the following equation (1). Moreover, the deterioration state determination part 13 calculates the 2nd evaluation distance of the AE wave of a bearing and the AE wave of the 2nd deterioration state which arose in the test body by the following formula | equation (2).
第一評価距離
＝√{|A1|*(P3_1 - P1_1)^2 + |A2|*(P3_2 - P1-2)^2 + ,…,|An|*(P3_n - P1_n)^2｝
第二評価距離
＝√{|A1|*(P3_1 - P2_1)^2 + |A2|*(P3_2 - P2-2)^2 + ,…,|An|*(P3_n - P2_n)^2｝
First evaluation distance = √ {| A1 | * (P3_1-P1_1) ^ 2 + | A2 | * (P3_2-P1-2) ^ 2 +,…, | An | * (P3_n-P1_n) ^ 2}
Second evaluation distance ＝ √ {| A1 | * (P3_1-P2_1) ^ 2 + | A2 | * (P3_2-P2-2) ^ 2 +,…, | An | * (P3_n-P2_n) ^ 2}
劣化状態判定部１３は第一評価距離と第二評価距離とを比較し、第一評価距離が第二評価距離よりも値が小さければ軸受からのＡＥ波は第一の劣化状態を示すと判定する。また劣化状態判定部１３は第二評価距離が第一評価距離よりも値が小さければ軸受からのＡＥ波は第二の劣化状態を示すと判定する。 The deterioration state determination unit 13 compares the first evaluation distance and the second evaluation distance, and determines that the AE wave from the bearing indicates the first deterioration state if the first evaluation distance is smaller than the second evaluation distance. To do. Further, the deterioration state determination unit 13 determines that the AE wave from the bearing indicates the second deterioration state if the second evaluation distance is smaller than the first evaluation distance.
以上、本発明の実施形態について説明したが、上述の処理によれば、劣化判定装置１は測定対象機構の構造体に誘導波を与えることなく測定対象機構から発生られたＡＥ波により劣化状態を判定することができる。
また上述の処理によれば劣化判定装置は、試験体が異なる劣化状態である場合のＡＥ波の代表波形を予め記憶しており、その代表波形と、測定対象機構から発生られたＡＥ波とを主成分分析により比較するのみで劣化状態を判定できる。したがって短時間で測定対象機構から発生られたＡＥ波による当該測定対象機構の劣化状態を判定することができる。
また上述の処理によれば測定対象機構から発生られたＡＥ波からノイズを除去する際に短時間フーリエ変換を利用しているためノイズ除去の時間を短縮することができ、短時間で測定対象機構の劣化状態を判定することができる。
As mentioned above, although embodiment of this invention was described, according to the above-mentioned process, the deterioration determination apparatus 1 does not give a induced wave to the structure of a measurement object mechanism, but a deterioration state by the AE wave generated from the measurement object mechanism. Can be determined.
Further, according to the above-described processing, the deterioration determination apparatus stores in advance a representative waveform of the AE wave when the specimen is in a different deterioration state, and the representative waveform and the AE wave generated from the measurement target mechanism are stored. The deterioration state can be determined only by comparison by principal component analysis. Accordingly, it is possible to determine the deterioration state of the measurement target mechanism due to the AE wave generated from the measurement target mechanism in a short time.
Further, according to the above-described processing, since the short-time Fourier transform is used when noise is removed from the AE wave generated from the measurement target mechanism, the noise removal time can be shortened, and the measurement target mechanism can be shortened in a short time. Can be determined.
上述の実施形態において劣化判定装置１は測定対象機構から発生られたＡＥ波が２つの劣化状態の何れを示すかについて判定しているが、さらに多くの劣化状態の何れを示すかを判定してもよい。この場合、劣化判定装置１は３つ以上の劣化状態の代表波形を記憶しておく。そして、それら代表波形と測定対象機構から発生られたＡＥ波とを用いて、主成分分析により測定対象機構から発生られたＡＥ波が示す劣化状態を判定する。この場合劣化状態判定部１３は、軸受のＡＥ波との評価距離が最も小さい代表波に対応する劣化状態を、軸受の劣化状態と判定する。 In the above-described embodiment, the deterioration determination device 1 determines which of the two deterioration states the AE wave generated from the measurement target mechanism indicates, but determines which of the more deterioration states it indicates. Also good. In this case, the deterioration determination device 1 stores representative waveforms of three or more deterioration states. Then, the deterioration state indicated by the AE wave generated from the measurement target mechanism is determined by principal component analysis using the representative waveform and the AE wave generated from the measurement target mechanism. In this case, the deterioration state determination unit 13 determines the deterioration state corresponding to the representative wave having the smallest evaluation distance from the AE wave of the bearing as the deterioration state of the bearing.
また上述の実施形態において劣化判定装置１は主成分分析を用いて測定対象機構から発生られたＡＥ波が示す劣化状態を判定しているが他の分析手法を用いて測定対象機構から発生られたＡＥ波が示す劣化状態を判定してもよい。例えば代表波形に基づいて特定されるＡＥ波の所定の特徴量に対応する、測定対象機構から発生られたＡＥ波が示す所定の特徴量との割合を判定する。そして劣化判定装置１は、その割合が閾値以上である場合に、その割合の算出に利用した代表波形に対応する劣化状態かどうかを判定するようにしてもよい。 In the above-described embodiment, the deterioration determination apparatus 1 determines the deterioration state indicated by the AE wave generated from the measurement target mechanism using principal component analysis, but is generated from the measurement target mechanism using another analysis method. The deterioration state indicated by the AE wave may be determined. For example, a ratio with a predetermined feature amount indicated by an AE wave generated from the measurement target mechanism corresponding to a predetermined feature amount of the AE wave specified based on the representative waveform is determined. And when the ratio is more than a threshold value, the deterioration determination apparatus 1 may determine whether or not the deterioration state corresponds to the representative waveform used for calculating the ratio.
なお上述の劣化判定装置１は内部に、コンピュータシステムを有している。そして、劣化判定装置１に上述した各処理を行わせるためのプログラムは、当該劣化判定装置１のコンピュータ読み取り可能な記録媒体に記憶されており、このプログラムを劣化判定装置１のコンピュータが読み出して実行することによって、上記処理が行われる。ここでコンピュータ読み取り可能な記録媒体とは、磁気ディスク、光磁気ディスク、ＣＤ−ＲＯＭ、ＤＶＤ−ＲＯＭ、半導体メモリ等をいう。また、このコンピュータプログラムを通信回線によってコンピュータに配信し、この配信を受けたコンピュータが当該プログラムを実行するようにしても良い。 In addition, the above-described degradation determination apparatus 1 has a computer system inside. A program for causing the deterioration determination device 1 to perform the above-described processes is stored in a computer-readable recording medium of the deterioration determination device 1, and the computer of the deterioration determination device 1 reads and executes the program. Thus, the above process is performed. Here, the computer-readable recording medium means a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Alternatively, the computer program may be distributed to the computer via a communication line, and the computer that has received the distribution may execute the program.
また、上記プログラムは、前述した各処理部の機能の一部を実現するためのものであっても良い。さらに、前述した機能をコンピュータシステムにすでに記録されているプログラムとの組み合わせで実現できるもの、いわゆる差分ファイル（差分プログラム）であっても良い。 Further, the program may be for realizing a part of the functions of each processing unit described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.
１・・・劣化判定装置
２・・・風力発電機
１１・・・制御部
１２・・・ノイズ除去部
１３・・・劣化状態判定部
１４・・・表示部
１０１・・・ＣＰＵ
１０２・・・ＲＯＭ
１０３・・・ＲＡＭ
１０４・・・ＨＤＤ
１０５・・・信号受信モジュール
DESCRIPTION OF SYMBOLS 1 ... Degradation determination apparatus 2 ... Wind power generator 11 ... Control part 12 ... Noise removal part 13 ... Degradation state determination part 14 ... Display part 101 ... CPU
102 ... ROM
103 ... RAM
104 ... HDD
105 ... Signal receiving module
Claims (7)
複数の異なる劣化状態を再現した試験体それぞれの発する弾性波の代表波形に相当する信号と前記ノイズ除去信号とに基づいて前記ノイズ除去信号に近い前記代表波形を特定する劣化状態判定部と、
を備える劣化判定装置。 A noise removal unit that removes noise from an elastic wave actually emitted from the measurement target mechanism at the time of deterioration determination and extracts a noise removal signal;
A deterioration state determination unit that identifies the representative waveform close to the noise removal signal based on a signal corresponding to a representative waveform of an elastic wave generated by each of the test bodies that reproduces a plurality of different deterioration states and the noise removal signal;
A deterioration determination device comprising:
請求項１に記載の劣化判定装置。 The deterioration determination device according to claim 1, wherein the deterioration state determination unit determines a deterioration state corresponding to the identified representative waveform as a deterioration state corresponding to the noise removal signal.
請求項１または請求項２に記載の劣化判定装置。 The degradation state determination unit analyzes the characteristic information of the elastic wave indicated by the representative waveform and the characteristic information of the elastic wave indicated by the noise removal signal, and identifies the representative waveform close to the noise removal signal. The deterioration determination apparatus according to claim 1 or 2.
請求項１から請求項３の何れか一項に記載の劣化判定装置。 The deterioration state determination unit analyzes the characteristic information of the elastic wave indicated by the representative waveform and the characteristic information of the elastic wave indicated by the noise removal signal by principal component analysis, and determines the representative waveform close to the noise removal signal. The deterioration determination apparatus according to any one of claims 1 to 3.
請求項１から請求項４の何れか一項に記載の劣化判定装置。 The noise removing unit specifies a waveform of a first section that is greater than or equal to a predetermined amplitude threshold in an elastic wave actually emitted from the measurement target mechanism and a second section that is less than the amplitude threshold following the first section, Short-time Fourier transform is performed on the result of time-frequency analysis of the waveforms of the first and second sections, and the time-averaged energy data for each frequency obtained as a result of the short-time Fourier transform is inverted. The degradation determination apparatus according to any one of claims 1 to 4, wherein the noise removal signal is extracted by performing a Fourier transform.
複数の異なる劣化状態を再現した試験体それぞれの発する弾性波の代表波形に相当する信号と前記ノイズ除去信号とに基づいて前記ノイズ除去信号に近い前記代表波形を特定する
劣化判定方法。 Noise is removed from the elastic wave actually emitted from the measurement target mechanism at the time of deterioration judgment, and the noise removal signal is extracted.
A degradation determination method for identifying the representative waveform close to the noise removal signal based on a signal corresponding to a representative waveform of an elastic wave generated by each of the test specimens reproducing a plurality of different degradation states and the noise removal signal.
劣化判定時に測定対象機構から実際に発せられた弾性波からノイズを除去してノイズ除去信号を抽出するノイズ除去手段、
複数の異なる劣化状態を再現した試験体それぞれの発する弾性波の代表波形に相当する信号と前記ノイズ除去信号とに基づいて前記ノイズ除去信号に近い前記代表波形を特定する劣化状態判定手段、
として機能させるプログラム。 The computer of the deterioration judgment device
A noise removing means for removing noise from an elastic wave actually emitted from a measurement target mechanism at the time of deterioration judgment and extracting a noise removal signal;
A deterioration state determining means for identifying the representative waveform close to the noise removal signal based on a signal corresponding to a representative waveform of an elastic wave generated by each of the test specimens reproducing a plurality of different deterioration states and the noise removal signal;
Program to function as.
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