JP2012058046A - Abnormality diagnosis device for power device - Google Patents

Abnormality diagnosis device for power device Download PDF

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JP2012058046A
JP2012058046A JP2010200492A JP2010200492A JP2012058046A JP 2012058046 A JP2012058046 A JP 2012058046A JP 2010200492 A JP2010200492 A JP 2010200492A JP 2010200492 A JP2010200492 A JP 2010200492A JP 2012058046 A JP2012058046 A JP 2012058046A
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vibration
frequency
sensor
khz
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Etsuo Hotoda
保戸田悦生
Naoki Okada
岡田直喜
Hideto Oki
大木秀人
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Nissin Electric Co Ltd
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Abstract

PROBLEM TO BE SOLVED: To provide a device for diagnosing vibration caused by a foreign object in a device or vibration caused by loosening of a fastening screw at low costs without using any expensive AE sensor or the like, which is capable of solving the conventional problem, i.e., a vibration sensor or an AE sensor for a high-frequency region is necessary to measure the high-frequency region (20 kHz or higher), however since the AE sensor is expensive, the costs of the diagnosis device are increased.SOLUTION: In a low-frequency region (20 kHz or lower) conventionally considered to have much noise, vibration caused by a foreign object or the like in the device is measured by using the provided noise removal algorithm. This enables measurement of the vibration caused by the foreign object in the device without being affected by any noise even in the low-frequency region (20 kHz or lower). Thus, the low costs of the device are achieved by low costs of a vibration sensor and a CPU. Further, abnormal vibration such as loosening of a fastening screw caused by device vibration characteristically generated in the double sound component of a power frequency (50 Hz or 60 Hz) is measured.

Description

本発明は、ガス絶縁開閉器（ＧＩＳ：Gas Insulated Switchgear）やガス遮断器（ＧＣＢ：Gas Circuit Breaker）や電力用トランスなどの電力用機器の異常診断装置に関わり、詳しくは、異物による振動とねじの緩みによる異常振動を検出する装置に関するものである。   The present invention relates to an abnormality diagnosis apparatus for power equipment such as a gas insulated switchgear (GIS), a gas circuit breaker (GCB), and a power transformer. The present invention relates to an apparatus for detecting abnormal vibrations due to loosening of the head.

現状では、ガス絶縁開閉器等の点検は、定期的におこなっており、その点検の仕方は主に目視によりおこなっている。通常は、ベテランの保守員が実施している。しかしながら、ベテランの保守員自らが点検を行うのは、年に数回程度である。前回点検と次回点検の間に故障の予兆が発生した場合には、見つけることが出来ない。故障の予兆があったにもかかわらず、見つけるのが遅れ、実際に電力機器の故障をまねくことになってしまう。従って、ベテランの保守員等に頼らずとも機器で判断できるように、一般には電力機器にセンサを取付け、取込んだデータ信号を解析して、故障を診断する装置が開発されている。   At present, inspections of gas insulated switches and the like are regularly performed, and the inspection method is mainly performed visually. It is usually conducted by experienced maintenance personnel. However, it is only a few times a year that veteran maintenance personnel inspect themselves. If a sign of failure occurs between the previous inspection and the next inspection, it cannot be found. Even though there is a sign of a failure, finding it is delayed, and it will actually cause a failure of the power equipment. Therefore, a device has been developed that diagnoses a failure by attaching a sensor to a power device and analyzing the captured data signal so that it can be determined by the device without relying on experienced maintenance personnel.

特開平１１−２１８５２５には、実際の塵埃の音に近い音を発生させ、異物検出用のＡＥ（Acoustic
Emission）センサの較正を定量的に精度よく行う為に、異物がガス絶縁機器の接地容器に衝突したときに生ずる振動音に類似した一定の大きさの衝撃音を発生することができ、それを用いて、ＡＥセンサの較正を行う方法が挙げられている。 In Japanese Patent Laid-Open No. 11-218525, a sound close to the actual sound of dust is generated and AE (Acoustic for detecting foreign matter) is detected.
Emission) To calibrate the sensor quantitatively and accurately, it is possible to generate a certain level of impact sound similar to the vibration sound that occurs when a foreign object collides with the ground container of a gas insulation device. A method of using and calibrating the AE sensor is mentioned.

機器内部の異物等や放電による振動を計測する手段として、特開２００２−９０４１３では振動センサやＡＥセンサを用いて取得したデータを、ノイズの多い低周波数領域（２０ｋＨｚ以下）を避け、ノイズの少ない高周波数領域（２０ｋＨｚ以上）についてＦＦＴ，ウェーブレット等の周波数解析などで計測する方法が挙げられている。   As a means of measuring vibrations caused by foreign matters or electric discharges inside a device, Japanese Patent Laid-Open No. 2002-90413 uses data obtained by using a vibration sensor or an AE sensor, avoiding a low frequency region (20 kHz or less) with much noise, and reducing noise. There is a method of measuring a high frequency region (20 kHz or more) by frequency analysis such as FFT and wavelet.

特開平１１−２１８５２５号公報JP-A-11-218525 特開２００２−９０４１３号公報JP 2002-90413 A

高周波数領域（２０ｋＨｚ以上）を計測するには、高周波数領域用の振動センサやＡＥセンサが必要である。これらのセンサは専用の特殊アンプが必要となり低周波数領域用の振動センサに比べ高価である。また、周波数解析においても処理時間の増加、メモリ容量の増加、高速ＡＤＣの使用などの問題を解決する為には高性能なＣＰＵが必要となり、ＣＰＵコストも高価となる。このため、機器内部の異物等による振動を計測する装置を低コストで実現することが不可能である。また、高周波数領域（２０ｋＨｚ以上）では、電源周波数（５０Ｈｚまたは６０Ｈｚ）の倍音成分に特徴的に現れる機器由来の振動成分が減少するため、締結ネジの緩みなどの、機器由来の振動が原因で起こる異常振動の計測が困難となる。   In order to measure a high frequency region (20 kHz or more), a vibration sensor or an AE sensor for the high frequency region is necessary. These sensors require special amplifiers and are expensive compared to vibration sensors for low frequency regions. Also in the frequency analysis, a high-performance CPU is required to solve problems such as an increase in processing time, an increase in memory capacity, and the use of a high-speed ADC, resulting in an increase in CPU cost. For this reason, it is impossible to realize an apparatus for measuring vibrations due to foreign matters or the like inside the device at low cost. Also, in the high frequency range (20 kHz or more), the vibration component derived from the device that appears characteristically in the harmonic component of the power supply frequency (50 Hz or 60 Hz) is reduced, so that the vibration derived from the device such as loosening of the fastening screw is the cause. Measurement of abnormal vibrations that occur is difficult.

電力機器において、重大事故につながる要因として、機器内部の異物混入が原因で発生する絶縁異常や、締結ネジの緩みなどの接触不良による通電異常が多くあり、これらの異常を初期の段階で発見することが重要な課題である。 In electrical power equipment, there are many insulation abnormalities caused by contamination of foreign matter inside the equipment and abnormal conduction due to poor contact such as loosening of fastening screws as factors leading to serious accidents. These abnormalities are detected at an early stage. This is an important issue.

従来、ノイズが多いとされていた低周波数領域（２０ｋＨｚ以下）にて、機器内部の異物等による振動を本考案で示すノイズ除去アルゴリズムを使用して計測することで、低周波数領域（２０ｋＨｚ以下）でもノイズの影響を受けることなく機器内部の異物等による振動を計測することが可能となる。また、電源周波数（５０Ｈｚまたは６０Ｈｚ）の倍音成分に特徴的に現れる機器由来の振動が原因で起こる締結ネジの緩みなどの異常振動の計測も可能となる。   Conventionally, vibrations due to foreign matter inside the device are measured using the noise removal algorithm shown in the present invention in the low frequency region (20 kHz or less), which has been considered to be noisy, and the low frequency region (20 kHz or less). However, it is possible to measure vibrations due to foreign matters inside the device without being affected by noise. In addition, it is possible to measure abnormal vibration such as loosening of a fastening screw caused by equipment-derived vibration that is characteristic of the harmonic component of the power supply frequency (50 Hz or 60 Hz).

本発明により、このため、振動センサとＣＰＵの低コスト化により機器内部の異物等による振動を計測する装置が低コストで実現できる。また、機器の締結ネジの緩みなどに起因する振動を初期の段階で発見することができ、適切な処置を行うことが可能となるので、機器のネジの緩みが原因で、発生する可能性がある事故や故障を、事前に防ぐことが可能となる。   According to the present invention, for this reason, an apparatus for measuring vibrations due to foreign matters inside the apparatus can be realized at low cost by reducing the cost of the vibration sensor and CPU. In addition, vibrations caused by loosening of the fastening screws of equipment can be detected at an early stage, and appropriate measures can be taken. A certain accident or failure can be prevented in advance.

本発明におけるハードウェア構成例である。It is a hardware structural example in this invention. 本発明における診断フローである。It is a diagnosis flow in the present invention. 本発明におけるＦＦＴ解析によるデータ抽出例である。（電源周波数５０Ｈｚ、サンプリング周波数１２．５Ｈｚ） （ａ）ＦＦＴ、 （ｂ）データ群１ （部分放電発生の原因となる機器内部異物の振動検出用）、 （ｃ)データ群２ （ネジの緩み等の機器由来振動による異常検出用）It is an example of data extraction by FFT analysis in the present invention. (Power supply frequency 50 Hz, Sampling frequency 12.5 Hz) (a) FFT, (b) Data group 1 (for detecting vibrations of foreign substances inside the equipment that cause partial discharge), (c) Data group 2 (Screw loosening, etc.) For detecting abnormalities caused by vibrations from equipment 本発明による電力診断例である。 （ａ)ノイズ処理前 異常振動なし、 （ｂ)ノイズ処理前 異常振動あり、 （ｃ）ノイズ処理後 異常振動なし、 （ｄ）ノイズ処理後 異常振動ありIt is an example of electric power diagnosis by this invention. (A) Abnormal vibration before noise processing, (b) Abnormal vibration before noise processing, (c) No abnormal vibration after noise processing, (d) Abnormal vibration after noise processing

本発明者らは、電力機器の故障診断装置の開発を長らくおこなっており、長年の経験から、低周波数領域（２０ｋＨｚ以下）の信号は、ねじやボルトの緩みに由来する振動によるものが多く、その機器由来の振動は電源周波数（５０Ｈｚまたは６０Ｈｚ）の倍音成分に強く現れる傾向があることを見出した。   The present inventors have long developed a failure diagnosis device for electric power equipment, and from many years of experience, signals in the low frequency region (20 kHz or less) are often due to vibrations derived from loosening of screws and bolts. It was found that vibrations derived from the equipment tend to appear strongly in the harmonic component of the power supply frequency (50 Hz or 60 Hz).

前記のねじ等の緩みによる振動は、部分放電発生の原因となる機器内部の金属異物などによる異常振動を検出しようとする場合には、外部ノイズとなる。しかしながら、ＦＦＴ等の周波数解析において電源周波数（５０Ｈｚまたは６０Ｈｚ）の倍音成分を間引くことで、ねじ等の緩みによる振動、すなわち外部ノイズを除去することができる。   The vibration due to the looseness of the screw or the like becomes an external noise when an abnormal vibration due to a metallic foreign object or the like inside the apparatus that causes partial discharge is detected. However, by thinning out the harmonic component of the power source frequency (50 Hz or 60 Hz) in frequency analysis such as FFT, vibration due to loosening of screws or the like, that is, external noise can be removed.

また、締結ネジの緩みなどによる振動は機器由来の振動に起因するものであり、電源周波数（５０Ｈｚまたは６０Ｈｚ）の倍音成分に特徴的に現れるため、この電源周波数（５０Ｈｚまたは６０Ｈｚ）の倍音成分を抽出することで締結ネジの緩みなどによる異常振動を検出できる。以下に本考案において、周波数解析手法としてＦＦＴ（Fast Fourier Transform）解析を適用した場合のハードウェア構成と診断フローを示す。 In addition, vibration due to loosening of the fastening screw is caused by vibrations derived from the equipment, and since it appears characteristically in the harmonic component of the power frequency (50 Hz or 60 Hz), the harmonic component of this power frequency (50 Hz or 60 Hz) By extracting, abnormal vibration due to loosening of the fastening screw can be detected. The hardware configuration and diagnosis flow when FFT (Fast Fourier Transform) analysis is applied as a frequency analysis method in the present invention will be described below.

周波数解析手法として、ＦＦＴ（Fast Fourier Transform）解析を適用した場合の構成を図１に示す。振動センサで収集したデータを、アンプを通して増幅した後、Ａ／Ｄ変換器でディジタルデータに変換して、ＣＰＵへ取り込む。内部で、図２に示す診断処理を行った後、診断結果を出力装置へ送付する。   FIG. 1 shows a configuration when FFT (Fast Fourier Transform) analysis is applied as a frequency analysis method. After the data collected by the vibration sensor is amplified through an amplifier, it is converted into digital data by an A / D converter and is taken into the CPU. Internally, after performing the diagnostic processing shown in FIG. 2, the diagnostic result is sent to the output device.

図２の診断フローを用いて各処理を説明する。データ取得のサンプリング周波数（ｆsmp）はサンプリング定理より計測周波数範囲の最大値の２倍以上とする。ＦＦＴの基本周波数が電源周波数（５０Ｈｚまたは６０Ｈｚ）の２ｎ分の１倍になるように設定する。このときｎは自然数とする。ノイズ除去処理、ＦＦＴにより基本周波数が電源周波数（５０Ｈｚまたは６０Ｈｚ）の２ｎ分の１倍ごとに分割された周波数成分のデータから２種類のデータ群へ抽出する。データ群１は、部分放電発生の原因となる機器内部異物の振動検査用で、電源周波数（５０Ｈｚまたは６０Ｈｚ）をｆとする式（1）を満たす周波数成分（ｆｔｍｐ１）のみを抽出する。抽出したｆｔｍｐ１の全てのデータを計測データ群１として保存する。
ｆｔｍｐ１
＝ ｆ × N + ｆ × （１／２ｎ）・・・・（1）
＊ ｆｓｍｐ／２ ＜ ｆｔｍｐ１
＊ N ＝ （１，２，３，‥‥）
＊ １／２ｎはＦＦＴ実施時に設定した値
＊ ｆ × （１／２ｎ）については電源周波数（５０Ｈｚまたは６０Ｈｚ）を超えなければ更に自然数倍してもよい。
例えば：ｆ × （１／２ｎ）を２倍で行う時
ｆｔｍｐ1 ＝ ｆ × N + （（ｆ × （１／２ｎ））×２）・・・・（1’） Each process is demonstrated using the diagnostic flow of FIG. The sampling frequency (f smp ) for data acquisition is at least twice the maximum value of the measurement frequency range based on the sampling theorem. The basic frequency of FFT is set to be 1 / 2n times the power supply frequency (50 Hz or 60 Hz). At this time, n is a natural number. The fundamental frequency is extracted into two types of data groups from the frequency component data divided every 2n times the power source frequency (50 Hz or 60 Hz) by noise removal processing and FFT. The data group 1 is for vibration inspection of foreign matter inside the equipment that causes partial discharge, and extracts only the frequency component (f tmp1 ) that satisfies the equation (1) where the power supply frequency (50 Hz or 60 Hz) is f. All the extracted data of f tmp1 is stored as measurement data group 1.
f tmp1
= F × N + f × (1/2 n ) (1)
* F smp / 2 <F tmp1
* N = (1, 2, 3, ...)
* 1/2 n is a value set at the time of performing the FFT. * F × (1/2 n ) may be further multiplied by a natural number as long as it does not exceed the power supply frequency (50 Hz or 60 Hz).
For example: When f × (1/2 n ) is doubled, f tmp1 = f × N + ((f × (1/2 n )) × 2) (1 ′)

データ群2は、ネジの緩み等の機器由来振動による異常検出用で、電源周波数（５０Ｈｚまたは６０Ｈｚ）を、ｆとする式（2）を満たす周波数成分（ｆｔｍｐ２）のみを抽出。抽出したｆｔｍｐ２の全てのデータを計測データ群２として保存する。
ｆｔｍｐ2 ＝ ｆ × N ・・・・（2）
＊ ｆｓｍｐ／２ ＜
＊ N ＝ （１，２，３，ｆｔｍｐ２‥‥） Data group 2 is for anomaly detection due to equipment-derived vibrations such as loose screws, and extracts only the frequency component (f tmp2 ) that satisfies equation (2) where f is the power frequency (50 Hz or 60 Hz). All the extracted data of f tmp2 is stored as measurement data group 2.
f tmp2 = f × N (2)
* F smp / 2 <
* N = (1, 2, 3, f tmp2 ...)

図３に電源周波数が５０Ｈｚ時で基本周波数を１２．５ＨｚでＦＦＴを行った時のデータ群１とデータ群２のデータ抽出を示す。データ群１では式（1’）より行った。
ｆｔｍｐ1 ＝ ５０ × N + （（５０ × （１／２2））×２）
ｆｔｍｐ1 ＝ ２５、７５、１２５、１７５‥‥ FIG. 3 shows data extraction of data group 1 and data group 2 when FFT is performed at a power supply frequency of 50 Hz and a basic frequency of 12.5 Hz. In the data group 1, it carried out from Formula (1 ').
f tmp1 = 50 × N + ((50 × (1/2 2 )) × 2)
f tmp1 = 25, 75, 125, 175 ...

データ群１の診断は、正常時に計測したデータ群１と異常時に計測したデータ群１から、予め決めた閾値を超えたときに異常としてもよいし、常設形の場合には過去の学習データより閾値を算出しその閾値を超えたときに異常としてもよい。閾値を超えるデータ数は１個でもよいしそれ以上でも良い。   The diagnosis of the data group 1 may be an abnormality when a predetermined threshold is exceeded from the data group 1 measured at the normal time and the data group 1 measured at the abnormal time. It is good also as abnormal when a threshold value is calculated and the threshold value is exceeded. The number of data exceeding the threshold may be one or more.

データ群２の診断は、正常時に計測したデータ群２と異常時に計測したデータ群２から、予め決めた周波数毎に設定した閾値を超えたときに異常としてもよいし、常設形の場合には過去の学習データより閾値を周波数毎で個別に算出しその閾値を超えたときに異常としてもよい。閾値を超えるデータ数は１個でもよいしそれ以上でも良い。   The diagnosis of the data group 2 may be abnormal when the threshold value set for each predetermined frequency is exceeded from the data group 2 measured at the normal time and the data group 2 measured at the abnormal time. A threshold may be calculated individually for each frequency from past learning data, and an abnormality may be detected when the threshold is exceeded. The number of data exceeding the threshold may be one or more.

以下にＧＩＳなどの電力設備に上記手法を適用した例を示す。図４に電力設備の正常振動と異常振動のデータをそれぞれ基本周波数１２．５ＨｚとしてＦＦＴを実施後、０Ｈｚから２ｋＨｚにおいてノイズ除去処理を実施した周波数解析データと、ノイズ除去処理を実施していない周波数解析データを示す。ノイズ除去処理を実施した周波数解析データはデータ群１（部分放電発生の原因となる機器内部異物振動検出用）の処理を実施したものを示す。   An example in which the above method is applied to power equipment such as GIS is shown below. FIG. 4 shows frequency analysis data obtained by performing noise removal processing from 0 Hz to 2 kHz after performing FFT with normal frequency and abnormal vibration data of power equipment set to a basic frequency of 12.5 Hz, and frequencies where noise removal processing is not performed. Analysis data is shown. The frequency analysis data that has been subjected to the noise removal processing shows data that has been subjected to the processing of data group 1 (for detecting internal foreign matter vibration that causes partial discharge).

図４よりノイズ処理実施前では異常振動なし（a）と、異常振動あり（b）の差が明確ではないが、ノイズ除去処理を実施することで電源周波数（５０Ｈｚまたは６０Ｈｚ）の倍音成分に特徴的に現れる機器由来の振動成分が除去され、図４の異常振動（c）と、異常振動あり（d）より、機器内部の異物による振動が抽出されていることがわかる。   From FIG. 4, the difference between the absence of abnormal vibration (a) and the presence of abnormal vibration (b) is not clear before noise processing is performed, but it is characterized by harmonic components of the power supply frequency (50 Hz or 60 Hz) by performing noise removal processing. It can be seen that the vibration component due to the foreign substance inside the device is extracted from the abnormal vibration (c) and the abnormal vibration (d) in FIG.

なお、起動後に１回閾値用のデータを取得するか或いは、数回分のデータの標準偏差等を用いて予め閾値を算出し、ノイズ除去処理を実施したデータが、その閾値を超えた場合（閾値を超えるデータ数は１個でもそれ以上でも良い）、或いは常設形においては過去の学習データより閾値を算出しノイズ除去処理を実施したデータがその閾値を超えた場合（閾値を超えるデータ数は１個でもそれ以上でも良い）に異常とすることで低周波数領域（２０ｋＨｚ以下）での異常振動診断が可能である。   Note that if threshold data is acquired once after startup, or the threshold value is calculated in advance using the standard deviation of the data for several times and the noise-removed data exceeds the threshold value (threshold value) The number of data exceeding 1 may be one or more), or in the case of a permanent form, the threshold is calculated from past learning data and the data subjected to noise removal processing exceeds the threshold (the number of data exceeding the threshold is 1 Abnormal vibration diagnosis in the low-frequency region (20 kHz or less) is possible by making the abnormality abnormal.

さらに、データ群１とデータ群２のそれぞれのデータで診断することで、部分放電の原因となる機器内部の異物の振動と、ネジの緩みなど機器由来の振動に起因する異常の両方を同時に診断できる。その結果によりユーザは、機器内部の確認や、ネジの緩みなどがないかを確認して、適切な保守を行うことで、機器の故障や不具合を事前に防ぐことができる。   In addition, by diagnosing each of the data group 1 and data group 2, both the vibration of the foreign substance inside the device that causes partial discharge and the abnormality caused by the vibration derived from the device such as the loosening of screws are diagnosed at the same time. it can. As a result, the user can check the inside of the device, check for loose screws, etc., and perform appropriate maintenance to prevent the device from malfunctioning or malfunctioning in advance.

この発明は、たとえば、ガス絶縁開閉器などの、部分放電の原因となる機器内部の異物の振動や、機器を締結するねじ類のゆるみを検出する機器の異常診断装置に適応できる。   The present invention can be applied to, for example, a device abnormality diagnosis device that detects the vibration of foreign matter inside a device that causes partial discharge, such as a gas insulated switch, and the looseness of screws that fasten the device.

Claims (2)

電力機器に取付けられて、機器の振動を検出する振動センサと、振動センサの信号を増幅するアンプと、アンプの出力信号をディジタル信号に変換するＡ／Ｄ変換器と、前記Ａ／Ｄ変換器の出力信号を計測する手段を有し、２０ｋＨｚ以下の周波数帯域でＦＦＴ解析を行い、電源周波数の倍音成分を除去することで、部分放電の原因となる機器内部の異物による振動を検出することを特徴とする電力機器の異常診断装置。 A vibration sensor that is attached to a power device and detects vibration of the device, an amplifier that amplifies the signal of the vibration sensor, an A / D converter that converts an output signal of the amplifier into a digital signal, and the A / D converter To detect the vibration due to foreign matter inside the equipment that causes partial discharge by performing FFT analysis in a frequency band of 20 kHz or less and removing harmonic components of the power supply frequency. An apparatus for diagnosing abnormalities in power equipment. 電力機器に取付けられて、機器の振動を検出する振動センサと、振動センサの信号を増幅するアンプと、アンプの出力信号をディジタル信号に変換するＡ／Ｄ変換器と、前記Ａ／Ｄ変換器の出力信号を計測する手段を有し、２０ｋＨｚ以下の周波数帯域でＦＦＴ解析を行い、電源周波数の倍音成分を抽出することで、機器を締結するネジの緩みによる振動を検出することを特徴とする電力機器の異常診断装置。 A vibration sensor that is attached to a power device and detects vibration of the device, an amplifier that amplifies the signal of the vibration sensor, an A / D converter that converts an output signal of the amplifier into a digital signal, and the A / D converter It is characterized by detecting the vibration due to the looseness of the screw fastening the device by performing FFT analysis in a frequency band of 20 kHz or less and extracting the harmonic component of the power supply frequency. An abnormality diagnosis device for electric power equipment.
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