JPH0580630B2 - - Google Patents
Info
- Publication number
- JPH0580630B2 JPH0580630B2 JP59061747A JP6174784A JPH0580630B2 JP H0580630 B2 JPH0580630 B2 JP H0580630B2 JP 59061747 A JP59061747 A JP 59061747A JP 6174784 A JP6174784 A JP 6174784A JP H0580630 B2 JPH0580630 B2 JP H0580630B2
- Authority
- JP
- Japan
- Prior art keywords
- partial discharge
- distribution pattern
- distribution
- void
- diagnosed
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Lifetime
Links
- 238000009826 distribution Methods 0.000 claims description 55
- 239000011800 void material Substances 0.000 claims description 29
- 230000007547 defect Effects 0.000 claims description 24
- 238000000034 method Methods 0.000 claims description 12
- 230000006866 deterioration Effects 0.000 claims description 5
- 238000003745 diagnosis Methods 0.000 description 7
- 238000009413 insulation Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 5
- 238000005259 measurement Methods 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- 239000012212 insulator Substances 0.000 description 4
- 238000012360 testing method Methods 0.000 description 3
- 238000007796 conventional method Methods 0.000 description 2
- 238000003909 pattern recognition Methods 0.000 description 2
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical group [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 1
- 230000008033 biological extinction Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- WABPQHHGFIMREM-UHFFFAOYSA-N lead(0) Chemical group [Pb] WABPQHHGFIMREM-UHFFFAOYSA-N 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000004804 winding Methods 0.000 description 1
Landscapes
- Locating Faults (AREA)
- Testing Relating To Insulation (AREA)
Description
【発明の詳細な説明】
本発明は被診断の電気機器におけるボイド欠陥
の種類、その発生箇所などを課電状態のまゝ診断
しうるパターン認識手法を用いた非破壊診断方法
に関するものである。DETAILED DESCRIPTION OF THE INVENTION The present invention relates to a non-destructive diagnostic method using a pattern recognition technique that allows diagnosing the type of void defect, the location of its occurrence, etc. in an electrical device to be diagnosed while the electrical device is being energized.
電力系統において安定な送電を確保するために
は、系統に接続された各種機器例えばトランス、
ケーブル、回転機などの絶縁状態を、実使用状態
即ち活線の状態において非破壊的に診断できるよ
うにすることが理想である。またこれに加えてボ
イド欠陥が絶縁物の剥離ボイドか、或いはクラツ
クによるものであるかなど、ボイド欠陥の種類と
その発生箇所例えばボイドの欠陥が、トランス内
のリード線部、巻線と外箱間に発生したかなどを
確実に与えて、修理などにおいて迅速適切な対策
をとりうるようにすることが理想である。そこで
従来から種々の研究がなされ、例えば絶縁の劣化
についてはボイド欠陥にもとづく部分放電パルス
の最大レベル、即ち見掛の最大放電電荷の絶縁劣
化の推移に伴う変化から判定する方法、損失角に
よる方法などが提案されている。しかし現在まで
のところボイド欠陥の種類とその発生箇所の検出
については、これを満足させるような方法は見出
されていない。 In order to ensure stable power transmission in the power grid, various devices connected to the grid, such as transformers,
It would be ideal to be able to non-destructively diagnose the insulation condition of cables, rotating machines, etc. under actual use conditions, ie, under live wire conditions. In addition to this, the type of void defect and its occurrence location, such as whether the void defect is a peeling void in the insulator or a crack, and the location where the void defect occurs, such as the lead wire part of the transformer, the winding wire, and the outer box. Ideally, it would be possible to provide information such as whether or not the problem occurred in the meantime, so that appropriate measures such as repairs can be taken quickly. Therefore, various studies have been carried out in the past, including methods for determining insulation deterioration based on changes in the maximum level of partial discharge pulses based on void defects, that is, the apparent maximum discharge charge as the insulation deteriorates, and methods using loss angles. etc. have been proposed. However, to date, no method has been found that satisfies this requirement for detecting the types of void defects and the locations where they occur.
本発明は上記の要望に応え得るボイド欠陥の診
断方法の提供を目的としてなされたもので、次に
図面を用いてその詳細を説明する。 The present invention has been made for the purpose of providing a method for diagnosing void defects that can meet the above-mentioned demands, and will next be described in detail with reference to the drawings.
本発明は次の研究結果にもとづいてなされたも
のである。即ちボイド欠陥にもとづく部分放電パ
ルスを検出し、その印加電圧の適宜サイクル区間
において発生した正極性および負極性部分放電パ
ルスのレベルから求めた見掛けの放電電荷ｑと、
その印加電圧に対する発生位相角の分布、即ち部
分放電位相特性であるφ−ｑ分布パターンを、各
種のボイド欠陥を設けた機器について求めたとこ
ろ、そのφ−ｑ分布パターンが例えば第１図のよ
うに、ボイド欠陥の種類とその発生箇所によつて
異なることを発見した。なお第１図ａはモールド
トランスにおける剥離ボイドがコイルと絶縁体間
において発生した場合、第１図ｂは剥離ボイドが
鉄心と絶縁体間において発生した場合、また第１
図ｃはクラツクボイドの場合である。 The present invention was made based on the following research results. That is, the apparent discharge charge q is determined from the levels of positive polarity and negative polarity partial discharge pulses generated in appropriate cycle sections of the applied voltage by detecting partial discharge pulses based on void defects;
When the distribution of the generated phase angle with respect to the applied voltage, that is, the φ-q distribution pattern which is the partial discharge phase characteristic, was obtained for devices with various void defects, the φ-q distribution pattern was found, for example, as shown in Figure 1. In addition, we discovered that the defects differ depending on the type of void defect and the location where it occurs. Figure 1a shows a case where a peeling void in a molded transformer occurs between the coil and the insulator, and Figure 1b shows a case where a peeling void occurs between the iron core and the insulator, and a case where the peeling void occurs between the core and the insulator.
Figure c shows the case of crack void.
そこで予め各種のボイド欠陥およびその発生箇
所を変えて、例えば被診断機器と同一絶縁階級、
同一電圧階級の機器により、診断用の基準φ−ｑ
分布パターンを作製しておき、この既知のパター
ンと被診断機器から求められたφ−ｑ分布パター
ンとを比較して、被診断機器のφ−ｑ分布パター
ンと類似した診断用の基準φ−ｑ分布パターンを
選別することにより、ボイド欠陥の種類やその発
生箇所など機器の絶縁状態を非破壊的に知りうる
ことを着想したものである。 Therefore, by changing various void defects and their occurrence locations in advance, for example, the same insulation class as the equipment to be diagnosed,
Diagnosis standard φ-q with equipment of the same voltage class
A distribution pattern is prepared in advance, and this known pattern is compared with the φ-q distribution pattern obtained from the device to be diagnosed to determine a standard φ-q for diagnosis similar to the φ-q distribution pattern of the device to be diagnosed. The idea was that by sorting the distribution pattern, it would be possible to non-destructively learn the insulation condition of equipment, such as the type of void defects and where they occur.
第２図は本発明の一実施装置例ブロツク系統図
であつて、図において１は被診断機器、２はその
接地線、３は電流検出器、４，５は極性弁別器
で、部分放電パルスを正極性と負極性パルスとに
分離する。６，７はパルスのレベルと発生位相角
の検出器で、部分放電パルスのレベル即ち見掛け
の放電電荷ｑと、交流印加電圧に対する発生位相
角を正極性および負極性パルスについて検出す
る。８，９は被診断φ−ｑ分布パターンの演算器
であつて、これらの回路は次のように動作する。
即ち印加電圧Vaの１サイクル毎の位相角（360°）
を、Ｎ個の位相角区間（ウインドウ）ｉ＝１……
Ｎに区分してＬサイクル測定し、各サイクルのウ
インドウに生じた部分放電パルス、例えば第３図
ａ，ｂ，ｃ，ｄに示すように第１サイクルにおい
てはq10.1，q13.1，q40.1、第２サイクルにおいては
q10.2，q15.2，q37.2，q45.1、また第３サイクルにお
いてはq6.3，q13.3，q15.3，q35.3，q46.3、第Ｎサイ
クルにおいてはq3.o，q10.o，q15.o，q34.o，q40.o，
q44.o、（なお足字の最初の数字はウインドウ番号、
次の足字はサイクル番号）を同一ウインドウ毎に
集計して、第３図ｅのような、見掛けの放電電荷
ｑの印加電圧の位相角φに対する分布であるサイ
クル平均φ−ｑ分布に変換する。即ち一般的には
φ−ｑサイクル平均分布はＬサイクルの測定に対
して、測定開始後ｌ番目（ｌ＝１……Ｌ）の印加
電圧サイクルのｉ番目（ｉ＝１……Ｎ）のウイン
ドウに、大きさqilの部分放電パルスが発生したと
き
qci＝１／ＬL
〓l=1
qil ……(1)
によつて、第４図ａに示す実測例（剥離ボイドの
場合）のような平均φ−ｑ分布パターンを正、負
パルスについて求める。（なお(1)式において部分
放電パルスが発生しなかつたウインドウではqil＝
０として演算する。）１０，１１は診断用の基準
φ−ｑ分布パターン（サイクル平均）の記憶装置
を示し、こゝには各種のボイド欠陥と各種の発生
箇所をもたせて測定された正極性および負極性に
対する診断用基準φ−ｑ分布パターンが記憶され
る。１２，１３は比較器即ち類似パターン検出器
を示し、上記記憶装置１０，１１から読出された
診断用基準φ−ｑ分布パターンと、被診断機器か
ら得られた被診断φ−ｑ分布パターンを比較し、
被診断φ−ｑ分布パターンに最も類似した診断用
基準φ−ｑ分布パターンを選出するものであつ
て、例えばその比較方法として次の方法が採用さ
れる。 FIG. 2 is a block system diagram of an example of an apparatus for carrying out the present invention. is separated into positive polarity and negative polarity pulses. 6 and 7 are pulse level and generation phase angle detectors, which detect the level of the partial discharge pulse, that is, the apparent discharge charge q, and the generation phase angle with respect to the AC applied voltage for positive and negative polarity pulses. 8 and 9 are arithmetic units for the φ-q distribution pattern to be diagnosed, and these circuits operate as follows.
In other words, the phase angle (360°) for each cycle of the applied voltage V a
, N phase angle intervals (windows) i=1...
The partial discharge pulses generated in the window of each cycle are measured, for example , as shown in FIG . In the second cycle
q 10.2 , q 15.2 , q 37.2 , q 45.1 , and in the third cycle q 6.3 , q 13.3 , q 15.3 , q 35.3 , q 46.3 , and in the Nth cycle q 3.o , q 10.o , q 15 .o , q 34.o , q 40.o ,
q 44.o , (the first number in the foot is the window number,
The next subscript is the cycle number) are aggregated for each same window and converted into the cycle average φ-q distribution, which is the distribution of the apparent discharge charge q with respect to the phase angle φ of the applied voltage, as shown in Figure 3e. . In other words, in general, the φ-q cycle average distribution is determined by the i-th (i=1...N) window of the l-th (l=1...L) applied voltage cycle after the start of measurement for L-cycle measurements. When a partial discharge pulse of magnitude q il occurs, q ci = 1/L L 〓 l=1 q il ...(1) According to (1), the actual measurement example shown in Figure 4a (in the case of peeling void) is obtained. The average φ-q distribution pattern is obtained for positive and negative pulses. (In equation (1), in the window where no partial discharge pulse occurs, q il =
Calculate as 0. ) 10 and 11 indicate a storage device for the standard φ-q distribution pattern (cycle average) for diagnosis. A standard φ-q distribution pattern is stored. Reference numerals 12 and 13 indicate comparators, that is, similar pattern detectors, which compare the diagnostic reference φ-q distribution pattern read from the storage devices 10 and 11 with the diagnosed φ-q distribution pattern obtained from the device to be diagnosed. death,
The diagnostic standard φ-q distribution pattern that is most similar to the diagnosed φ-q distribution pattern is selected, and for example, the following method is adopted as a comparison method.
今交流印加電圧Vaによつて測定された被診断
φ−ｑ分布パターンを（φ，Va）とし（放電々
荷は印加電圧Vaに比例する）、予め測定してある
Ｍ種類の診断用基準φ−ｑ分布パターンの一つを
gi（φ，Va）（こゝでｉ＝１……Ｎ）とする。また
φ−ｑ分布パターンを比較するため、印加電圧
Vaを部分放電の消滅電圧により除いて規格化し
（以下これを規格化電圧ηと呼ぶ）、その比が同一
の場合の分布パターン同志を順次比較する。即ち
（φ，Va）とgi（φ，Va）を、上記規格化電圧
ηに対する分布である（φ，η）およびgi（φ，
η）とし、測定されたηに対して
D1＝∫〓2〓1∫2〓0（（φ，η）−gi（φ，η））
2dφ，dη
……(2)
を演算する。そして正極性および負極性の被診断
φ−ｑ分布パターンに対して、D1の値を最も小
さくする分布（φ，η）とgi（φ，η）の近似値
を考え、このgi（φ，η）を生じさせたボイド欠
陥と被診断機器のボイド欠陥とが同等であると診
断する。１４は表示装置例えばプリンタやブラウ
ン管表示装置であつて、診断結果を例えば記号に
よつて表示する。従つて本発明によればボイド欠
陥がどのような種類のものか、その発生箇所が何
処にあるかなどを常に監視できる。 Let the φ-q distribution pattern to be diagnosed measured by the applied AC voltage V a be (φ, V a ) (the discharge load is proportional to the applied voltage V a ), and make the M types of diagnosis measured in advance. One of the standard φ-q distribution patterns for
Let g i (φ, V a ) (here i=1...N). In addition, in order to compare the φ-q distribution pattern, the applied voltage
V a is normalized by removing it by the extinction voltage of partial discharge (hereinafter referred to as normalized voltage η), and the distribution patterns when the ratio is the same are sequentially compared. That is, (φ, V a ) and g i (φ, V a ) are the distributions for the normalized voltage η (φ, η) and g i (φ,
η), and for the measured η, D 1 =∫〓 2 〓 1 ∫ 2 〓 0 ((φ, η)−g i (φ, η))
2 dφ, dη
...Calculate (2). Then, for the diagnosed φ-q distribution patterns of positive polarity and negative polarity, consider the distribution (φ, η) that minimizes the value of D 1 and the approximate value of g i (φ, η), and calculate this g i ( It is diagnosed that the void defect that caused φ, η) and the void defect of the device to be diagnosed are the same. Reference numeral 14 denotes a display device, such as a printer or a cathode ray tube display device, which displays the diagnostic results using, for example, symbols. Therefore, according to the present invention, it is possible to constantly monitor the type of void defect and where it occurs.
以上本発明を一実施例について説明したが、前
記(1)式によつて説明したサイクル平均φ−ｑ分布
の代りに、ウインド毎のパルス発生数niを用いて
次の(3)式により与えられる、パルス平均φ−ｑ分
布を用いることもできる。 The present invention has been described above with respect to one embodiment, but instead of the cycle average φ-q distribution explained using equation (1) above, the number of pulses generated per window n i is used to calculate the following equation (3). It is also possible to use the pulse-averaged φ-q distribution given by
qpi＝１／niL
〓l=1
qil ……(3)
なお第４図ｂは剥離ボイド発生時の実測例であ
る。 q pi =1/n iL 〓 l=1 q il ...(3) Fig. 4b is an example of actual measurement when peeling voids occur.
また第２図に示した実施例において説明した診
断基準φ−ｑ分布パターンと被測定機器により得
られた被診断φ−ｑ分布パターンとの比較器即ち
類似パターン検出装置１２，１３によるパターン
認識では回路が複雑となり、印加電圧の各サイク
ル毎に対応して高速処理を行わなければならな
い。これを防ぐためには例えば第５図に示すよう
に、演算器８，９によつて演算された平均φ−ｑ
分布出力の歪度Ｓの分布の演算器１５，１６を設
け、また診断用基準パターン１０，１１の記憶装
置には診断用基準平均φ−ｑ分布を歪度Ｓの分布
パターンによつて記憶させて、パターン検出装置
１２，１３により類似パターンを検出すればよ
い。この場合パターン検出装置１２，１３におけ
る検出は前記(3)式の代りに
D2＝∫〓2〓1（Ｓ（η）−Si（η））2dη ……(4)
にもとづいて行われる。なおこゝでＳ（η）は被
測定機器における歪度Ｓの規格化電圧ηに対する
依存性、Si（η）は予め測定された既知ボイド欠
陥によるＭ種類のφ−ｑ分布のうちの一つの分布
の歪度Siの規格化電圧ηに対する依存性である。 In addition, in pattern recognition by the comparators, that is, the similar pattern detection devices 12 and 13, between the diagnostic standard φ-q distribution pattern explained in the embodiment shown in FIG. 2 and the diagnosed φ-q distribution pattern obtained by the device under test. The circuit becomes complicated, and high-speed processing must be performed for each cycle of applied voltage. In order to prevent this, for example, as shown in FIG.
Arithmetic units 15 and 16 for the distribution of the skewness S of the distribution output are provided, and the storage devices for the diagnostic reference patterns 10 and 11 store the diagnostic reference average φ-q distribution according to the distribution pattern of the skewness S. Then, similar patterns may be detected by the pattern detection devices 12 and 13. In this case, the detection in the pattern detection devices 12 and 13 is performed based on D 2 =∫〓 2 〓 1 (S(η)−S i (η)) 2 dη ……(4) instead of the above equation (3). be exposed. Here, S (η) is the dependence of the distortion S in the device under test on the normalized voltage η, and S i (η) is one of the M types of φ-q distributions due to known void defects measured in advance. This is the dependence of the distribution skewness S i on the normalized voltage η.
また類似パターン検出の別な方法として第６図
のように、平均φ−ｑ分布の演算器８，９の出力
から、φ−ｑ分布の歪度Ｓ、尖度Ｋ、を求める演
算器１７，１８を設けて、Ｓ（η）の分布の尖度
Ｋのη依存性の傾向例えばds／dη＞０、または
０または＜０によつて類似パターンを検出した
り、φ−ｑ分布から見掛けの最大放電々荷qnaxの
規格化電圧ηに対する依存性の傾向例えば
dqnax／dη＞０、または０、または＜０を使用
して、診断することもできるなどの各種の変形が
可能である。 Another method for detecting similar patterns is as shown in FIG. 18 is provided to detect similar patterns based on the tendency of the η dependence of the kurtosis K of the distribution of S(η), for example, when ds/dη>0, or 0 or <0, or to detect the apparent tendency from the φ-q distribution. For example, the tendency of the maximum discharge charge q nax to depend on the normalized voltage η
Various variations are possible, such as dq nax /dη>0, or 0, or <0, which can also be used for diagnosis.
以上の説明から明らかなように、本発明におい
ては印加電圧の複数サイクルにおける平均φ−ｑ
分布を求め、これを迅速に処理して数サイクル毎
に診断結果を得ることができるので、本発明によ
る診断装置を設置することにより、常に機器を監
視してボイド欠陥の種類と発生箇所の診断と劣化
の予知診断を迅速かつ確実に行うことができる。
従つて従来の劣化の有無のみを知るものに比べ
て、絶縁性能の評価の精度を飛躍的に向上させる
ことができる。また更に本発明は絶縁劣化の予知
に当つても、従来の部分放電パルスのレベルから
最大放電々荷を求め、その量から判定するものの
ように、部分放電パルスの絶対値によるものでは
なく、印加電圧に対する部分放電パルスの発生頻
度ｎおよびその発生位相即φ−ｎ分布から放電々
荷ｑの印加電圧に対する発生位相の分布即φ−ｑ
分布パターンを求め、そのパターンと既知パター
ンとの比較により診断するものであるので、精度
を向上できるすぐれた利点が得られる。 As is clear from the above explanation, in the present invention, the average φ-q in multiple cycles of applied voltage
Since the distribution can be obtained and quickly processed to obtain diagnostic results every few cycles, by installing the diagnostic device according to the present invention, it is possible to constantly monitor the equipment and diagnose the type and location of void defects. and predictive diagnosis of deterioration can be performed quickly and reliably.
Therefore, compared to conventional methods that only determine the presence or absence of deterioration, the accuracy of insulation performance evaluation can be dramatically improved. Furthermore, in predicting insulation deterioration, the present invention does not rely on the absolute value of the partial discharge pulse, as in the conventional method of determining the maximum discharge load from the level of the partial discharge pulse, and making judgments based on the amount. From the frequency of occurrence n of partial discharge pulses with respect to voltage and the distribution of their occurrence phase, i.e. φ-n, the distribution of the generation phase of discharge charge q with respect to the applied voltage, i.e. φ-q.
Since the diagnosis is made by finding a distribution pattern and comparing that pattern with a known pattern, it has the advantage of improving accuracy.
第１図はボイド欠陥の種類などによつてφ−ｑ
分布パターンが変る例を示す波形図、第２図は本
発明の一実施装置例を示すブロツク系統図、第３
図はφ−ｑ分布の演算過程を示す波形図、第４図
ａ，ｂはφ−ｑ分布の実測例図、第５図および第
６図は本発明の他の実施装置例を示すブロツク系
統図である。
１……被測定機器、２……その接地線、３……
電流検出器、４，５……極性弁別器、６，７……
φ−ｎ分布パターン検出器、８，９……φ−ｑ分
布パターン演算器、１０，１１……診断用基準φ
−ｑ分布パターン記憶器、１２，１３……比較器
類似パターン検出器、１４……表示器、１５，１
６……歪度演算器、１７，１８……歪度と尖度演
算器。
Figure 1 shows φ−q depending on the type of void defect, etc.
FIG. 2 is a waveform diagram showing an example in which the distribution pattern changes; FIG. 2 is a block system diagram showing an example of an apparatus for implementing the present invention;
The figure is a waveform diagram showing the calculation process of the φ-q distribution, FIGS. 4a and 4b are actual measurement examples of the φ-q distribution, and FIGS. 5 and 6 are block systems showing other embodiments of the present invention. It is a diagram. 1...Device under test, 2...The grounding wire, 3...
Current detector, 4, 5... Polarity discriminator, 6, 7...
φ-n distribution pattern detector, 8, 9...φ-q distribution pattern calculator, 10, 11...Diagnostic standard φ
-q distribution pattern storage, 12, 13... Comparator similar pattern detector, 14... Display, 15, 1
6... Skewness calculator, 17, 18... Skewness and kurtosis calculator.
Claims (1)
ルスの正極性および負極性パルスについて、部分
放電パルス発生頻度の印加電圧位相角特性を求め
た後、印加電圧に対する部分放電位相特性である
被診断φ−ｑ分布パターンを演算し、この被診断
φ−ｑ分布パターンが、予めボイド欠陥の種類、
発生箇所、劣化の程度を変えて求めた複数の診断
用基準部分放電位相特性である診断用基準φ−ｑ
分布パターンと比較し、その類似度の高い診断用
基準φ−ｑ分布パターンを得ることにより、当該
電気機器のボイド欠陥の種類、その発生箇所など
を診断することを特徴とする部分放電位相特性に
よる電気機器のボイド欠陥診断方法。 ２ 前記各φ−ｑ分布パターンが、サイクル平均
φ−ｑ分布パターンであることを特徴とする特許
請求の範囲第１項記載の部分放電位相特性による
電気機器のボイド欠陥診断方法。 ３ 前記各φ−ｑ分布パターンが、パルス平均φ
−ｑ分布パターンであることを特徴とする特許請
求の範囲第１項記載の部分放電位相特性による電
気機器のボイド欠陥診断方法。[Claims] 1. After determining the applied voltage phase angle characteristics of the partial discharge pulse occurrence frequency for the positive and negative polarity pulses of the partial discharge pulses detected from the electrical equipment to be diagnosed, the partial discharge phase with respect to the applied voltage is determined. A diagnostic φ-q distribution pattern, which is a characteristic, is calculated, and this diagnosed φ-q distribution pattern is determined in advance by the type of void defect,
Diagnostic standard φ-q which is multiple diagnostic reference partial discharge phase characteristics obtained by changing the occurrence location and degree of deterioration.
Based on partial discharge phase characteristics, the type of void defect in the electrical equipment, the location of its occurrence, etc. can be diagnosed by comparing it with the distribution pattern and obtaining a diagnostic standard φ-q distribution pattern with a high degree of similarity. A method for diagnosing void defects in electrical equipment. 2. The method for diagnosing void defects in electrical equipment using partial discharge phase characteristics according to claim 1, wherein each of the φ-q distribution patterns is a cycle average φ-q distribution pattern. 3 Each of the above φ-q distribution patterns has a pulse average φ
2. A method for diagnosing void defects in electrical equipment using partial discharge phase characteristics according to claim 1, characterized in that the -q distribution pattern is used.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP6174784A JPS60203866A (en) | 1984-03-29 | 1984-03-29 | Diagnozing method of void defect of electric apparatus on the basis of partial discharging phase characteristics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP6174784A JPS60203866A (en) | 1984-03-29 | 1984-03-29 | Diagnozing method of void defect of electric apparatus on the basis of partial discharging phase characteristics |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPS60203866A JPS60203866A (en) | 1985-10-15 |
| JPH0580630B2 true JPH0580630B2 (en) | 1993-11-09 |
Family
ID=13180067
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP6174784A Granted JPS60203866A (en) | 1984-03-29 | 1984-03-29 | Diagnozing method of void defect of electric apparatus on the basis of partial discharging phase characteristics |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPS60203866A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101864639B1 (en) * | 2016-12-23 | 2018-06-08 | 산일전기 주식회사 | Method of Insulation Risk in GIS |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB9021484D0 (en) * | 1990-10-03 | 1990-11-14 | Univ Strathclyde | Gas insulated substations |
| JP3106884B2 (en) * | 1994-12-12 | 2000-11-06 | 日立電線株式会社 | Partial discharge measurement method |
| JP2018059848A (en) * | 2016-10-06 | 2018-04-12 | 株式会社日立パワーソリューションズ | Rotary machine diagnosis system and data processing method thereof |
| JP7107632B2 (en) * | 2016-11-04 | 2022-07-27 | 株式会社日立パワーソリューションズ | Rotating machine diagnostic system and rotating machine diagnostic method |
| JP7326038B2 (en) * | 2019-06-18 | 2023-08-15 | 株式会社東芝 | Partial discharge diagnosis device, partial discharge diagnosis method, and partial discharge diagnosis system |
| CN111679159B (en) * | 2020-08-14 | 2020-11-24 | 四川大学 | Method for judging impedance change type in frequency domain reflection method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5555269A (en) * | 1978-10-20 | 1980-04-23 | Hitachi Ltd | Internal insulation diagnosis device of power apparatus |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS56109025U (en) * | 1980-01-23 | 1981-08-24 |
-
1984
- 1984-03-29 JP JP6174784A patent/JPS60203866A/en active Granted
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5555269A (en) * | 1978-10-20 | 1980-04-23 | Hitachi Ltd | Internal insulation diagnosis device of power apparatus |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101864639B1 (en) * | 2016-12-23 | 2018-06-08 | 산일전기 주식회사 | Method of Insulation Risk in GIS |
Also Published As
| Publication number | Publication date |
|---|---|
| JPS60203866A (en) | 1985-10-15 |
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