CN105334435A - Adaptive partial discharge ultrasonic monitoring method based on any array - Google Patents
Adaptive partial discharge ultrasonic monitoring method based on any array Download PDFInfo
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- CN105334435A CN105334435A CN201510688957.4A CN201510688957A CN105334435A CN 105334435 A CN105334435 A CN 105334435A CN 201510688957 A CN201510688957 A CN 201510688957A CN 105334435 A CN105334435 A CN 105334435A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1209—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing using acoustic measurements
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Abstract
The invention discloses an adaptive partial discharge ultrasonic monitoring method based on any array, comprising steps of utilizing a sensor array of any array to receive spatial signals, processing the received spatial signals to obtain characteristic value decomposition matrix of an array covariance matrix, performing modeling on each scanning point in the space to obtain an expected guidance vector of any array, looking for the optimal guidance vector according to the obtained expected guidance vector and the characteristic decomposition matrix, wherein the optimal guidance vector is obtained from the expected guidance vector through the principle formed by the adaptive wave beams, forming an optimal weight vector according to the optimal guidance vector and obtaining the evaluation result of the sound source position according to the optimal weight vector. The invention can maximally inhibit the noise and interference, can reduce the output sidelobe of the processor, and can guarantee the output signal to noise ratio, has higher resolution, guarantees the monitoring performance under the interference condition, has the wide application range and strong interference resistance.
Description
Technical field:
The present invention relates to a kind of method for Partial Discharge Online Monitoring of Transformers, particularly relate to a kind of adaptive local based on arbitrary arrays electric discharge ultrasonic monitoring method, belong to monitoring technical field.
Background technology:
Power transformer is the important component part of electric system.Shelf depreciation is the important sign that the transformer insulated performance of reflection reduces.Physics and the chemical phenomenons such as shelf depreciation can generate electromagnetic waves, sound, light, heat, according to the position that can obtain Partial Discharge Sources to these quantitative analysis process, the monitoring method formed thus mainly contains pulse current method, vapor-phase chromatography, supercritical ultrasonics technology, ultrahigh frequency method and flash spotting.Wherein, adopt the supercritical ultrasonics technology of sensor array because having the advantages such as impact, the location that can avoid electromagnetic interference (EMI) be convenient and being widely applied.
Comparatively conventional is rectangle, cruciform, L shape array at present, and such as patent 201110182613.8 proposes a kind of L shape ultrasound array sensor for partial discharge of transformer location and method thereof; Patent 201110182614.2 proposes a kind of cruciform ultrasound array sensor for partial discharge of transformer location and method.Said method is fixed due to formation, requires higher to installation site, is difficult to adapt to changeable installation environment.In real work, due to the change of monitoring location, occur that above-mentioned ultrasonic sensor array is difficult to the situation of installing sometimes.
When transformer runs there is multiple disturbed sources of noise in scene, comprises PERIODIC INTERFERENCE, white noise interference and impulse disturbances etc.Local discharge signal is weaker than undesired signal usually, so adopt interference suppression algorithm to be necessary.Existing patent focuses mostly in the raising of measuring accuracy, as patent 201410235567.7 adopts the form of virtual array to improve the positioning precision of discharge source.Said method is only applicable to specific several formation, very flexible, and jamproof poor-performing.
Summary of the invention:
The object of the invention is to overcome the deficiency of above-mentioned prior art and one farthest restraint speckle and interference is provided, reduce the output secondary lobe of processor, ensure output signal-to-noise ratio, there is higher resolving power, ensure that the Monitoring Performance under disturbed condition, applied range, the electric discharge of the adaptive local based on the arbitrary arrays ultrasonic monitoring method that antijamming capability is strong.
Object of the present invention can be reached by following measure: a kind of electric discharge of the adaptive local based on arbitrary arrays ultrasonic monitoring method, is characterized in that it comprises the steps:
1) with the array received signal comprising N number of sonac array element;
2) accumulation obtains the time-domain signal of N number of array element L snap;
3) Fast Fourier Transform (FFT) is done to L time domain snap signal of N number of array element, obtain the frequency-domain data matrix X of a N*L;
4) the snap data estimation array covariance matrix R after Fourier transform is used
（1）
In formula,
efor getting expectation,
hfor conjugate transpose;
5) Eigenvalues Decomposition carries out to R as follows
（2）
In formula, U is feature matrix, and Σ is the diagonal matrix be made up of eigenwert, and expression formula is as follows:
（3）
Wherein, N is the total number receiving array element,
represent i-th eigenwert of array covariance matrix R, i representation feature value sequence number, its span is 1 ~ N;
6) according to the element position of sonac, obtain expecting steering vector to each analyzing spot modeling in space, principle is as Fig. 2, if the position coordinates of No. n-th array element is
, then analyzing spot
expectation steering vector
for:
（4）
Wherein,
ffor signal frequency,
cfor the velocity of sound;
7) according to the steering vector expected
, find optimum steering vector
, the resolution principle of optimum steering vector is as Fig. 3, and computing formula is:
（5）
Wherein,
ifor unit matrix,
for Lagrange multiplier, R is array covariance matrix;
Above formula is substituted into constraint
, can obtain
meet following nonlinear equation:
（6）
Wherein,
for getting second order norm,
for steering vector error margin, its accurate value is determined by the disturbance of practical application, and experience value is
; Application Newton-Raphson method or dichotomy solve (6) formula, by what try to achieve
(5) formula of substitution, can obtain optimum steering vector
;
8) according to the steering vector of optimum
, obtain weight vector
w;
（7）
9) following formula is adopted to obtain the output valve of each analyzing spot according to weight vector
pas shown in the formula
（8）。
The present invention can produce following good effect compared with the prior art: the present invention, by introducing Adaptive beamformer technology, can realize the monitoring to faint local discharge signal under interference environment.Adaptive beamformer technology is widely used in radar, sonar, radio communication, medical imaging, the fields such as radioastronomy, has output signal-to-noise ratio and resolving power well.The weight coefficient of Adaptive Signal Processing technology is associated with the data, automatically weight coefficient is adjusted to every batch data, array response is made to have optimum detection perform in target azimuth, when interference is present, sunken zero can be formed at interference radiating way, farthest restraint speckle and interference, reduce the output secondary lobe of processor, ensure output signal-to-noise ratio, there is higher resolving power simultaneously.
The present invention is based on the supersonic array of arbitrary shape, be applicable to arbitrary arrays, utilize the adaptive beam-forming algorithm proposed in document " J.Li, P.Stoica; andZ.Wang; " OnrobustCaponbeamforminganddiagonalloading, " IEEETrans.SignalProcessing, vol.51; no.7; pp.1702 – 1715, July2003 " to carry out Signal estimation, ensure that the Monitoring Performance under disturbed condition.The present invention has:
1. applied range.By adopting the steering vector modeling method of arbitrary arrays, in actual applications according to concrete mounting condition array of designs form, the service condition restriction of the method can be greatly reduced;
2. antijamming capability is strong.Introduce the Adaptive beamformer technology in signal transacting, form zero at jamming bearing and fall into, reduce the impact of interference on weak signal, ensure that the method has the Monitoring Performance in strongly disturbing actual application environment.
Accompanying drawing illustrates:
Fig. 1 is algorithm flow chart of the present invention;
Fig. 2 is that the arbitrary arrays steering vector in the present invention estimates schematic diagram;
Fig. 3 is the Adaptive beamformer schematic diagram in the present invention.
Embodiment:
Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail:
Essence of the present invention is the sensor array modeling to arbitrary arrays, and introduces Adaptive beamformer technology, thus improves range of application and the interference free performance of the method.Described method comprises following steps:
1) 101 in corresponding diagram 1, with the array received signal comprising N number of sonac array element;
2) 102 in corresponding diagram 1, accumulation obtains the time-domain signal of N number of array element L snap;
3) 103 in corresponding diagram 1, does Fast Fourier Transform (FFT) to L time domain snap signal of N number of array element, obtains the frequency-domain data matrix X of a N*L;
4) 104 in corresponding diagram 1, uses the snap data estimation array covariance matrix R after Fourier transform
（1）
In formula,
efor getting expectation,
hfor conjugate transpose;
5) 105 in corresponding diagram 1, carries out Eigenvalues Decomposition to R as follows
（2）
In formula, U is feature matrix, and Σ is the diagonal matrix be made up of eigenwert, and expression formula is as follows:
（3）
Wherein, N is the total number receiving array element,
represent i-th eigenwert of array covariance matrix R, i representation feature value sequence number, its span is 1 ~ N;
6) 106 in corresponding diagram 1, according to the element position of sonac, obtain expecting steering vector to each analyzing spot modeling in space, principle is as Fig. 2, if the position coordinates of No. n-th array element is
, then analyzing spot
expectation steering vector
for:
（4）
Wherein,
ffor signal frequency,
cfor the velocity of sound.
7) 107 in corresponding diagram 1, according to the steering vector expected
, find optimum steering vector
, the resolution principle of optimum steering vector is as Fig. 3, and computing formula is:
（5）
Wherein,
ifor unit matrix,
for Lagrange multiplier, R is array covariance matrix.
Above formula is substituted into constraint
, can obtain
meet following nonlinear equation:
（6）
Wherein,
for getting second order norm,
for steering vector error margin, its accurate value is determined by the disturbance of practical application, and experience value is
.Application Newton-Raphson method or dichotomy solve (14) formula, by what try to achieve
(13) formula of substitution, can obtain optimum steering vector
.
8) 108 in corresponding diagram 1, according to the steering vector of optimum
, obtain weight vector
w;
（7）
9) 109 in corresponding diagram 1, adopts following formula to obtain the output valve of each analyzing spot according to weight vector
pas shown in the formula:
（8）。
Claims (1)
1., based on an adaptive local electric discharge ultrasonic monitoring method for arbitrary arrays, it is characterized in that it comprises the steps:
1) with the array received signal comprising N number of sonac array element;
2) accumulation obtains the time-domain signal of N number of array element L snap;
3) Fast Fourier Transform (FFT) is done to L time domain snap signal of N number of array element, obtain the frequency-domain data matrix X of a N*L;
4) the snap data estimation array covariance matrix R after Fourier transform is used
（1）
In formula,
efor getting expectation,
hfor conjugate transpose;
5) Eigenvalues Decomposition carries out to R as follows
（2）
In formula, U is feature matrix, and Σ is the diagonal matrix be made up of eigenwert, and expression formula is as follows:
（3）
Wherein, N is the total number receiving array element,
represent i-th eigenwert of array covariance matrix R, i representation feature value sequence number, its span is 1 ~ N;
6) according to the element position of sonac, obtain expecting steering vector to each analyzing spot modeling in space, principle is as Fig. 2, if the position coordinates of No. n-th array element is
, then analyzing spot
expectation steering vector
for:
（4）
Wherein,
ffor signal frequency,
cfor the velocity of sound;
7) according to the steering vector expected
, find optimum steering vector
, the resolution principle of optimum steering vector is as Fig. 3, and computing formula is:
（5）
Wherein,
ifor unit matrix,
for Lagrange multiplier, R is array covariance matrix;
Above formula is substituted into constraint
, can obtain
meet following nonlinear equation:
（6）
Wherein,
for getting second order norm,
for steering vector error margin, its accurate value is determined by the disturbance of practical application, and experience value is
; Application Newton-Raphson method or dichotomy solve (6) formula, by what try to achieve
(5) formula of substitution, can obtain optimum steering vector
;
8) according to the steering vector of optimum
, obtain weight vector
w;
（7）
9) following formula is adopted to obtain the output valve of each analyzing spot according to weight vector
pas shown in the formula
（8）。
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108008262A (en) * | 2017-11-29 | 2018-05-08 | 国网上海市电力公司 | A kind of shelf depreciation quick determination method |
| CN109829416A (en) * | 2019-01-28 | 2019-05-31 | 国网山东省电力公司日照供电公司 | A kind of method and system detecting ultrahigh frequency partial discharge signal from random noise |
| CN110470956A (en) * | 2019-08-05 | 2019-11-19 | 上海电机学院 | A kind of power equipment shelf depreciation ultrasound locating method |
| CN110673075A (en) * | 2019-09-03 | 2020-01-10 | 国网江西省电力有限公司电力科学研究院 | Method for evaluating electromagnetic interference resistance of ultrahigh frequency partial discharge detector |
| CN111736050A (en) * | 2020-08-28 | 2020-10-02 | 杭州兆华电子有限公司 | Partial discharge fault monitoring and evaluating device and method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0815367A (en) * | 1994-06-29 | 1996-01-19 | Chubu Electric Power Co Inc | Partial discharge measuring method |
| CN102508124A (en) * | 2011-10-18 | 2012-06-20 | 广西电网公司电力科学研究院 | Detection method of partial discharge of electrical equipment and device thereof |
| CN203037802U (en) * | 2012-12-12 | 2013-07-03 | 山西省电力公司电力科学研究院 | Data measuring storage system achieving transformer high-frequency and ultrahigh-frequency partial discharge monitoring |
| CN103336231A (en) * | 2013-07-01 | 2013-10-02 | 杭州电子科技大学 | Neural network method for detecting AE position of partial discharge |
| CN103969560A (en) * | 2014-05-28 | 2014-08-06 | 北达正视(北京)科技有限公司 | Visual ultrasonic detection system for partial discharge failure detection |
-
2015
- 2015-10-23 CN CN201510688957.4A patent/CN105334435B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0815367A (en) * | 1994-06-29 | 1996-01-19 | Chubu Electric Power Co Inc | Partial discharge measuring method |
| CN102508124A (en) * | 2011-10-18 | 2012-06-20 | 广西电网公司电力科学研究院 | Detection method of partial discharge of electrical equipment and device thereof |
| CN203037802U (en) * | 2012-12-12 | 2013-07-03 | 山西省电力公司电力科学研究院 | Data measuring storage system achieving transformer high-frequency and ultrahigh-frequency partial discharge monitoring |
| CN103336231A (en) * | 2013-07-01 | 2013-10-02 | 杭州电子科技大学 | Neural network method for detecting AE position of partial discharge |
| CN103969560A (en) * | 2014-05-28 | 2014-08-06 | 北达正视(北京)科技有限公司 | Visual ultrasonic detection system for partial discharge failure detection |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108008262A (en) * | 2017-11-29 | 2018-05-08 | 国网上海市电力公司 | A kind of shelf depreciation quick determination method |
| CN108008262B (en) * | 2017-11-29 | 2020-07-07 | 国网上海市电力公司 | Rapid partial discharge detection method |
| CN109829416A (en) * | 2019-01-28 | 2019-05-31 | 国网山东省电力公司日照供电公司 | A kind of method and system detecting ultrahigh frequency partial discharge signal from random noise |
| CN110470956A (en) * | 2019-08-05 | 2019-11-19 | 上海电机学院 | A kind of power equipment shelf depreciation ultrasound locating method |
| CN110673075A (en) * | 2019-09-03 | 2020-01-10 | 国网江西省电力有限公司电力科学研究院 | Method for evaluating electromagnetic interference resistance of ultrahigh frequency partial discharge detector |
| CN111736050A (en) * | 2020-08-28 | 2020-10-02 | 杭州兆华电子有限公司 | Partial discharge fault monitoring and evaluating device and method |
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| CN105334435B (en) | 2018-04-13 |
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Inventor after: Guo Zhiyuan Inventor after: Ma Lili Inventor after: Zhou Bin Inventor after: Wang Yanhong Inventor after: Yi Xin Inventor after: Xu Zhiqiang Inventor after: Tian Chuanming Inventor after: Jiao Dafeng Inventor after: Peng Yuntao Inventor after: Wang Bo Inventor after: Wang Yanlong Inventor after: Sunny Inventor after: Xin Xiangjun Inventor before: Guo Zhiyuan Inventor before: Liu Dong Inventor before: Liu Yongmei Inventor before: Xu Yingtao Inventor before: Cai Hong Inventor before: Sun Hongmei Inventor before: Xu Zhiqiang Inventor before: Sun Wanli Inventor before: Sun Xuelei Inventor before: Wang Zhichao Inventor before: Wang Bo |
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