CN108445364A - Power plant's partial discharge of switchgear fault diagnosis method and system based on vibration signal - Google Patents
Power plant's partial discharge of switchgear fault diagnosis method and system based on vibration signal Download PDFInfo
- Publication number
- CN108445364A CN108445364A CN201810357886.3A CN201810357886A CN108445364A CN 108445364 A CN108445364 A CN 108445364A CN 201810357886 A CN201810357886 A CN 201810357886A CN 108445364 A CN108445364 A CN 108445364A
- Authority
- CN
- China
- Prior art keywords
- vibration signal
- switchgear
- power plant
- partial discharge
- phase space
- 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.)
- Pending
Links
Classifications
-
- 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
-
- 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
- G01R31/1227—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 of components, parts or materials
Abstract
Power plant's partial discharge of switchgear fault diagnosis method and system based on vibration signal, are first depending on phase space reconfiguration, and vibration signal higher-dimension phase space matrix is constructed in the case where not destroying signal dynamic characteristic itself；Recycling independent component analysis method carries out SNR estimation and compensation, extraction estimation source information component to vibration signal, and estimation source information component is reconstructed, and constructs the hot-tempered vibration signal that disappears；Finally offset it is hot-tempered after vibration signal carry out wavelet-packet energy spectrum analysis, judge partial discharge of switchgear malfunction according to analysis result.The present invention to collected power plant's partial discharge of switchgear vibration signal disappear hot-tempered first, solve the problems, such as that power station environment interference is stronger, again by disappear it is hot-tempered after vibration signal carry out wavelet-packet energy spectrum analysis, calculate each sub-band energy accounting, the generation of switchgear partial discharges fault and its fault severity level are judged according to each sub-band energy accounting, improve the reliability and precision of fault verification.
Description
Technical field
Power plant's partial discharge of switchgear fault diagnosis method and system based on vibration signal that the present invention relates to a kind of, belong to
Maintenance of electrical equipment technical field.
Background technology
Whether reliably power plant's switchgear is directly related to the peace of power plant as control device important in power plant, operation
Entirely.Long-term operation and maintenance experience have shown that, the insulation fault of inside switch cabinet be cause one of its operation troubles it is main former
Cause.And inside switch cabinet shelf depreciation is to lead to its built-in electrical insulation aging, occur insulation fault an important factor for.Therefore, accurate
Really extract partial discharge of switchgear fault-signal, diagnosis partial discharges fault has important meaning to the reliability service of entire power plant
Justice.Since power plant's switchgear running environment is complicated, when shelf depreciation occurs for switchgear, signal is very faint, is often buried in strong
In strong interference noise, the accuracy of partial discharge of switchgear testing result is influenced.So eliminating partial discharge of switchgear signal
Noise is the key that improve testing result accuracy.
It is introduced according to power plant staff, interference source can be divided into according to partial discharge detection method by two classes：First, vibration interference：
Vibration interference is mainly derived from each switchgear output source distal end (motor) with the vibration of power cable transmission and switchgear institute
Locate background vibration two parts of overall situation；Second is that electromagnetic interference：Electromagnetic interference is divided into survey of the pulse electromagnetic wave to vibrating sensor
Amount interference, external electromagnetic field are to transient state voltage-to-ground (Transient Earth Voltage：TEV) measure interference and open
Cabinet internal interference is closed, the interference of the Electromagnetic Interference and the source of trouble of coil class equipment is subdivided into.Therefore, vibration signal work has been selected
For a kind of method of detection power plant partial discharge of switchgear failure.On the one hand, vibration signal is often buried in strong vibration interference
In noise, partial discharge of switchgear testing result is influenced；On the other hand, it in order to analyze CHARACTERISTICS OF OSCILLATORY DISTURBANCE, needs to retain and vibrate
Interference signal, so, select independent analysis analysis method (independent component analysis：ICA it) extracts
Switch cabinet partial discharge vibration signal, while retaining vibration interference signal.
Independent component analysis method, which can be realized, effectively divides the signal component with statistical independence in mixed signal
From.But traditional ICA methods require the number in observation channel to be more than or equal to the number for vibrating source signal in the application.In reality
In engineering, observation signal is difficult this assumed condition for meeting ICA methods, limits the application range of ICA methods.And phase space
Reconstruct can construct the coordinate components of one group of characterization original system kinetic characteristics by single system output time series, more
The deficiency of traditional IC A methods is mended.Therefore, the advantage in conjunction with ICA methods and phase space reconfiguration respectively, it is proposed that one kind being based on phase
The ICA noise-reduction methods of Space Reconstruction, and this method is applied in the noise reduction of power plant's partial discharge of switchgear vibration signal.Finally
Wavelet-packet energy spectrum analysis is carried out to the switchgear vibration signal of the elimination noise of acquisition, whether diagnosis switchgear, which occurs part, puts
Electric fault realizes that vibratory drilling method (vibration signal) diagnoses partial discharge of switchgear failure.
Invention content
The present invention is directed to deficiency in the prior art, provides a kind of power plant's partial discharge of switchgear event based on vibration signal
Hinder diagnostic method and system, is especially in the partial discharges fault diagnosis of power plant's switchgear in strong interference environment, in conjunction with
The advantage of ICA methods and phase space reconfiguration respectively, the noise-reduction method of proposition are simultaneously applied to power plant's partial discharge of switchgear and shake
In dynamic signal, Wavelet Packet Energy Spectrum algorithm is recycled to analyze the power plant's switchgear vibration signal for eliminating noise, diagnosis is opened
Close cabinet malfunction.
To achieve the above object, the present invention uses following technical scheme：
A kind of power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal, which is characterized in that including following
Step：
Step 1: acquisition switchgear vibration signal, and signal is pre-processed；
Step 2: calculate switchgear vibration signal time delay and smallest embedding dimension number, and according to be calculated when
Between delay and smallest embedding dimension number, by the one-dimensional vibration signal collected pass through phase space reconfiguration construct higher-dimension phase space square
Battle array；
Step 3: using the higher-dimension phase space matrix of acquisition as the input of independent component analysis method, to higher-dimension phase space
SNR estimation and compensation is carried out, exports a series of isolated component, and a series of isolated component is classified, obtains estimation source information
Component and noise information component；
Step 4: giving up the noise information component in isolated component, the estimation source information component in isolated component is selected, it is right
Switchgear vibration signal is rebuild, and the noise in switchgear vibration signal is eliminated；
Step 5: the switchgear vibration signal progress wavelet-packet energy spectrum analysis of the elimination noise obtained to step 4, is examined
Whether disconnected switchgear occurs partial discharges fault.
To optimize above-mentioned technical proposal, the concrete measure taken further includes：
In the step 1, the frequency that is sampled to switchgear vibration signal is 16kHz, when sampling a length of 1s.
In the step 2, mutual information method is selected to determine time delay, in the case where time delay determines, as
Priori conditions select cao methods to determine smallest embedding dimension number.
In the step 2, construction higher-dimension phase space matrix is specially：
Give a time series xn, the phase space matrix of n=1,2 ..., N, Embedded dimensions and time delay passes through row
Vector defines：
X=[xi, xi+τ..., xi+(m-1)τ]
Wherein：I=1,2 ..., L, L=N- (m-1) τ, x is the phase space vector after reconstruct, and τ is time delay, and m is embedding
Enter dimension, N counts for original time series, and L is phase space vector number after reconstruct, and X is phase space matrix.
In the step 3, independent component analysis method selects maximum likelihood ICA blind separation algorithms.
In the step 4, the noise eliminated in switchgear vibration signal is specially：
First by one estimation source information component space of estimation source information component construction in isolated component, then it will estimate source
Each estimation source information components in information component space are multiplied by the respective column of hybrid matrix, construct higher-dimension phase space
A phase subspace：
Su=auyu
Wherein, SuFor a phase subspace of higher-dimension phase space, yuTo estimate source information component space, auFor hybrid matrix
Correspondence column space；
Therefore, the vibration signal after noise reductionFor：
Wherein,For j-th of vector of phase subspace, l is phase subspace vector number.
In the step 5, analyzed specially using Wavelet Packet Energy Spectrum algorithm：
1) selection sym5 wavelet basis carries out 5 layers of WAVELET PACKET DECOMPOSITION to switchgear vibration signal, obtains 32 sub-bands；
2) Wavelet Packet Energy Spectrum algorithm is used to carry out energy to the vibration signal under the different frequency bands after 5 layers of decomposition of wavelet packet
Statistical analysis is measured, calculates the energy and global vibration signal gross energy of each sub-band of switchgear vibration signal, and by 32
Sub-band energy forms 32 dimensional vectors；
3) energy accounting analysis is carried out to the energy of each sub-band, calculates the percentage that each sub-band energy accounts for gross energy
Example analyzes partial discharge of switchgear failure according to each sub-band energy accounting.
In addition, it is also proposed that a kind of system based on above-mentioned power plant's partial discharge of switchgear method for diagnosing faults, feature
It is, including：Power plant's switchgear, vibrating sensor, signal conditioning circuit, data collecting instrument, fault diagnosis center and PC
Machine；The outer surface that the vibrating sensor is mounted on power plant switchgear cable vault and bus-bar room shakes for acquiring vibration signal
Dynamic signal input data Acquisition Instrument after signal conditioning circuit improves, the data collecting instrument is for acquiring power plant's switchgear electricity
The vibration signal of cable room and busbar outdoor face, the fault diagnosis center carries out analyzing processing to the vibration signal of acquisition, real
Existing vibratory drilling method diagnoses partial discharge of switchgear failure, and judges partial discharges fault degree；The PC machine is for showing that failure is examined
The judging result at disconnected center.
The model CA-YD-103 of the vibrating sensor.
The model NI PCIe-6320 of the data collecting instrument.
The beneficial effects of the invention are as follows：The present invention is to acquire the vibration letter of switchgear cable vault of power plant and busbar outdoor face
Number the generation of switchgear partial discharges fault and its fault severity level are judged, combines ICA methods and phase space first
Respective advantage is reconstructed, propose a kind of noise-reduction method and is applied in power plant's partial discharge of switchgear vibration signal, then profit
The power plant's switchgear vibration signal for eliminating noise is analyzed with Wavelet Packet Energy Spectrum algorithm, diagnoses switchgear malfunction.
The present invention first collected power plant's partial discharge of switchgear vibration signal disappear it is hot-tempered, solve power station environment interference asks more by force
Topic, then by disappear it is hot-tempered after power plant switch cabinet partial discharge vibration signal carry out wavelet-packet energy spectrum analysis, calculate each sub-band energy
Accounting judges the generation of switchgear partial discharges fault and its fault severity level according to each sub-band energy accounting.
This method first to collected power plant's switchgear vibration signal disappear hot-tempered, then analyzes partial discharge of switchgear malfunction, can
Improve the reliability and precision of fault verification.
Description of the drawings
Fig. 1 is flow chart of the method for the present invention.
Fig. 2 is the ICA functional block diagrams of the present invention.
Fig. 3 is the system structure diagram of the present invention.
Specific implementation mode
In conjunction with the accompanying drawings, the present invention is further explained in detail.
Power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal as shown in Figure 1, includes the following steps：
One, switchgear vibration signal is acquired, and signal is pre-processed, wherein being sampled to switchgear vibration signal
Frequency be 16kHz, when sampling a length of 1s.
Two, the time delay τ and smallest embedding dimension number m of switchgear vibration signal are calculated, and according to the time being calculated
Postpone τ and smallest embedding dimension number m, the one-dimensional vibration signal collected is constructed into higher-dimension phase space matrix by phase space reconfiguration
X, specially：
Give a time series xn, the phase space matrix X of n=1,2 ..., N, Embedded dimensions m and time delay τ passes through
Row vector defines：
X=[xi, xi+τ..., xi+(m-1)τ] (1)
Wherein：I=1,2 ..., L, L=N- (m-1) τ；x：Phase space vector after reconstruct；τ：Reconstructed sample interval, immediately
Between postpone；m：Embedded dimensions；N：Original time series are counted；L：Phase space vector number after reconstruct.
And determining for time delay τ selects mutual information method, in the case where time delay τ is determined, as priori item
Part selects cao methods to determine smallest embedding dimension number.
Three, using the higher-dimension phase space matrix X of acquisition as the input of independent component analysis (ICA) method, wherein ICA methods
What is selected is maximum likelihood ICA (Infomax) blind separation algorithm, as shown in Fig. 2, SNR estimation and compensation is carried out to higher-dimension phase space, it is defeated
Go out a series of isolated component, and a series of components that independent component analysis method processing obtains later are classified, obtains
Estimate source information component (y1, y2..., yn) and noise information component (yn+1, yn+2..., ym)。
Four, give up the noise information component in isolated component, select the estimation source information component in isolated component, to switch
Cabinet vibration signal is rebuild, and the noise in switchgear vibration signal is eliminated.
In order to realize the elimination of noise, first by one estimation source information of estimation source information component construction in independent element
Component space, then will estimate that each estimation source information components in source information component space are multiplied by the correspondence of hybrid matrix
Row, construct a phase subspace of higher-dimension phase space：
Su=auyu (2)
In formula：SuFor a phase subspace of higher-dimension phase space；yuTo estimate source information component space；auFor hybrid matrix
Correspondence column space.
Therefore, the vibration signal after noise reductionFor：
In formula：J-th of vector of phase subspace；L is phase subspace vector number.
Five, wavelet-packet energy spectrum analysis is carried out to the switchgear vibration signal of the elimination noise obtained in step 4, first
It selects sym5 wavelet basis to carry out 5 layers of WAVELET PACKET DECOMPOSITION to switchgear vibration signal, obtains 32 sub-bands；Wavelet packet energy is used again
Amount spectrum algorithm carries out energy statistics analysis to the vibration signal under the different frequency bands after 5 layers of decomposition of wavelet packet, calculates switch
The energy and global vibration signal gross energy of each sub-band of cabinet vibration signal, and 32 sub-band energies are formed into one 32 dimension
Vector；Energy accounting analysis finally is carried out to the energy of each sub-band, calculates the percentage that each sub-band energy accounts for gross energy,
Partial discharge of switchgear failure is analyzed according to each sub-band energy accounting, realizes that vibratory drilling method (vibration signal) diagnoses switchgear part
Discharge fault.
System based on above-mentioned power plant's partial discharge of switchgear method for diagnosing faults as shown in Figure 3, including power plant is with opening
Close cabinet, vibrating sensor, signal conditioning circuit, data collecting instrument, fault diagnosis center and PC machine, each vibrating sensor installation
Outer surface in switchgear cable vault and bus-bar room, for acquiring vibration signal, the model CA- of selected vibrating sensor
YD-103, vibration signal input data Acquisition Instrument after signal conditioning circuit improves, data collecting instrument is for acquiring switchgear electricity
The vibration signal of cable room and busbar outdoor face, the model NI PCIe-6320 of selected data collecting instrument, fault diagnosis
Center carries out analyzing processing to the vibration signal of acquisition, realizes that vibratory drilling method (vibration signal) diagnoses partial discharge of switchgear failure,
Judge that partial discharges fault degree, PC machine are used to show the judging result of fault diagnosis center in conjunction with each sub-band energy accounting.
The above is only the preferred embodiment of the present invention, protection scope of the present invention is not limited merely to above-described embodiment,
All technical solutions belonged under thinking of the present invention all belong to the scope of protection of the present invention.It should be pointed out that for the art
For those of ordinary skill, several improvements and modifications without departing from the principles of the present invention should be regarded as the protection of the present invention
Range.
Claims (10)
1. a kind of power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal, which is characterized in that including following step
Suddenly：
Step 1: acquisition switchgear vibration signal, and signal is pre-processed；
Step 2: calculating the time delay and smallest embedding dimension number of switchgear vibration signal, and prolonged according to the time being calculated
The one-dimensional vibration signal collected is passed through phase space reconfiguration and constructs higher-dimension phase space matrix by slow and smallest embedding dimension number；
Step 3: using the higher-dimension phase space matrix of acquisition as the input of independent component analysis method, higher-dimension phase space is carried out
SNR estimation and compensation exports a series of isolated component, and a series of isolated component is classified, and obtains estimation source information component
With noise information component；
Step 4: giving up the noise information component in isolated component, the estimation source information component in isolated component is selected, to switch
Cabinet vibration signal is rebuild, and the noise in switchgear vibration signal is eliminated；
Step 5: the switchgear vibration signal progress wavelet-packet energy spectrum analysis of the elimination noise obtained to step 4, diagnosis are opened
Close whether cabinet occurs partial discharges fault.
2. a kind of power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal as described in claim 1, special
Sign is：In the step 1, the frequency that is sampled to switchgear vibration signal is 16kHz, when sampling a length of 1s.
3. a kind of power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal as described in claim 1, special
Sign is：In the step 2, mutual information method is selected to determine time delay, in the case where time delay determines, as
Priori conditions select cao methods to determine smallest embedding dimension number.
4. a kind of power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal as claimed in claim 3, special
Sign is：In the step 2, construction higher-dimension phase space matrix is specially：
Give a time series xn, n=1,2 ..., N, the phase space matrix of Embedded dimensions and time delay by row vector come
Definition：
X=[xi, xi+τ..., xi+(m-1)τ]
Wherein：I=1,2 ..., L, L=N- (m-1) τ, x is the phase space vector after reconstruct, and τ is time delay, and m is embedded ties up
Number, N count for original time series, and L is phase space vector number after reconstruct, and X is phase space matrix.
5. a kind of power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal as described in claim 1, special
Sign is：In the step 3, independent component analysis method selects maximum likelihood ICA blind separation algorithms.
6. a kind of power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal as described in claim 1, special
Sign is：In the step 4, the noise eliminated in switchgear vibration signal is specially：
First by one estimation source information component space of estimation source information component construction in isolated component, then it will estimate source information
Each estimation source information components in component space are multiplied by the respective column of hybrid matrix, construct the one of higher-dimension phase space
A phase subspace：
Su=auyu
Wherein, SuFor a phase subspace of higher-dimension phase space, yuTo estimate source information component space, auFor pair of hybrid matrix
Answer column space；
Therefore, the vibration signal after noise reductionFor：
Wherein,For j-th of vector of phase subspace, l is phase subspace vector number.
7. a kind of power plant's partial discharge of switchgear method for diagnosing faults based on vibration signal as described in claim 1, special
Sign is：In the step 5, analyzed specially using Wavelet Packet Energy Spectrum algorithm：
1) selection sym5 wavelet basis carries out 5 layers of WAVELET PACKET DECOMPOSITION to switchgear vibration signal, obtains 32 sub-bands；
2) Wavelet Packet Energy Spectrum algorithm is used to carry out energy system to the vibration signal under the different frequency bands after 5 layers of decomposition of wavelet packet
Meter analysis calculates the energy and global vibration signal gross energy of each sub-band of switchgear vibration signal, and frequently by 32 sons
Band energy forms 32 dimensional vectors；
3) energy accounting analysis is carried out to the energy of each sub-band, calculates the percentage that each sub-band energy accounts for gross energy, root
Partial discharge of switchgear failure is analyzed according to each sub-band energy accounting.
8. a kind of power plant's partial discharge of switchgear method for diagnosing faults based on as described in any one of claim 1-7 is
System, which is characterized in that including：In power plant's switchgear, vibrating sensor, signal conditioning circuit, data collecting instrument, fault diagnosis
The heart and PC machine；The vibrating sensor is mounted on the power plant outer surface of switchgear cable vault and bus-bar room, shakes for acquiring
Dynamic signal, vibration signal input data Acquisition Instrument after signal conditioning circuit improves, the data collecting instrument is for acquiring power plant
With the vibration signal of switchgear cable vault and busbar outdoor face, the fault diagnosis center divides the vibration signal of acquisition
Analysis is handled, and realizes that vibratory drilling method diagnoses partial discharge of switchgear failure, and judge partial discharges fault degree；The PC machine is for showing
Show the judging result of fault diagnosis center.
9. the system of power plant's partial discharge of switchgear method for diagnosing faults as claimed in claim 8, it is characterised in that：It is described to shake
The model CA-YD-103 of dynamic sensor.
10. the system of power plant's partial discharge of switchgear method for diagnosing faults as claimed in claim 8, it is characterised in that：It is described
The model NI PCIe-6320 of data collecting instrument.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810357886.3A CN108445364A (en) | 2018-04-19 | 2018-04-19 | Power plant's partial discharge of switchgear fault diagnosis method and system based on vibration signal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810357886.3A CN108445364A (en) | 2018-04-19 | 2018-04-19 | Power plant's partial discharge of switchgear fault diagnosis method and system based on vibration signal |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108445364A true CN108445364A (en) | 2018-08-24 |
Family
ID=63200387
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810357886.3A Pending CN108445364A (en) | 2018-04-19 | 2018-04-19 | Power plant's partial discharge of switchgear fault diagnosis method and system based on vibration signal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108445364A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102735968A (en) * | 2012-06-13 | 2012-10-17 | 江苏省电力公司南京供电公司 | GIS (Geographic Information System) fault diagnosis system and method based on vibration signal spectrum analysis |
| CN105628419A (en) * | 2015-12-18 | 2016-06-01 | 国网安徽省电力公司 | System and method of diagnosing GIS (Gas Insulated Switchgear) mechanical defects based on independent component analysis denoising |
| CN105699869A (en) * | 2016-04-07 | 2016-06-22 | 国网江苏省电力公司南京供电公司 | Vibration signal based GIS equipment partial discharge detection method |
| CN105973621A (en) * | 2016-05-02 | 2016-09-28 | 国家电网公司 | Abnormal vibration analysis-based GIS (gas insulated switchgear) mechanical fault diagnosis method and system |
| CN106644423A (en) * | 2016-09-29 | 2017-05-10 | 国网江苏省电力公司检修分公司 | GIS partial discharge type identification system and GIS partial discharge type identification method based on vibration signal |
-
2018
- 2018-04-19 CN CN201810357886.3A patent/CN108445364A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102735968A (en) * | 2012-06-13 | 2012-10-17 | 江苏省电力公司南京供电公司 | GIS (Geographic Information System) fault diagnosis system and method based on vibration signal spectrum analysis |
| CN105628419A (en) * | 2015-12-18 | 2016-06-01 | 国网安徽省电力公司 | System and method of diagnosing GIS (Gas Insulated Switchgear) mechanical defects based on independent component analysis denoising |
| CN105699869A (en) * | 2016-04-07 | 2016-06-22 | 国网江苏省电力公司南京供电公司 | Vibration signal based GIS equipment partial discharge detection method |
| CN105973621A (en) * | 2016-05-02 | 2016-09-28 | 国家电网公司 | Abnormal vibration analysis-based GIS (gas insulated switchgear) mechanical fault diagnosis method and system |
| CN106644423A (en) * | 2016-09-29 | 2017-05-10 | 国网江苏省电力公司检修分公司 | GIS partial discharge type identification system and GIS partial discharge type identification method based on vibration signal |
Non-Patent Citations (5)
| Title |
|---|
| 刘清坤等: "基于相空间重构和独立分量分析的超声信号噪声消除", 《上海交通大学学报》 * |
| 张兢等: "基于小波包频带能量检测技术的故障诊断", 《微计算机信息》 * |
| 黄大伟等: "相空间重构单通道ICA算法及其在变形监测数据去噪中的应用", 《测绘工程》 * |
| 黄浩等: "基于PCA和LMD分解的滚动轴承故障特征提取方法", 《仪表技术与传感器》 * |
| 黄艳林等: "基于相空间重构与独立分量分析的局部独立投影降噪算法", 《振动与冲击》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lee et al. | New fault diagnosis of circuit breakers | |
| CN107462614B (en) | A kind of paper oil insulation moisture content assessment method being lost based on polarization loss and conductance | |
| CN106443316A (en) | Power transformer winding deformation state multi-information detection method and device | |
| CN105547465A (en) | Transformer vibration signal winding state feature extraction method | |
| CN101907437A (en) | Wavelet difference algorithm-based cable fault localization method | |
| EP2579056A2 (en) | Novel method for real time tests and diagnosis of the sources of partial discharge in high voltage equipment and installations, which are in service or not in service, and physical system for the practical use of the method | |
| CN111504675B (en) | On-line diagnosis method for mechanical fault of gas insulated switchgear | |
| CN101086515A (en) | Dynamotor local discharge on-line monitoring method based on double sensor directional coupling | |
| CN106441547A (en) | Transformer vibration monitoring method and apparatus | |
| CN108427067A (en) | A kind of partial discharge of switchgear fault detection method, apparatus and system | |
| CN103116090A (en) | Three-phrase pulse-width modulation (PWM) rectifier fault diagnosis method based on wavelet packet analysis and support vector machine | |
| CN112083328A (en) | Fault diagnosis method, system and device for high-voltage circuit breaker | |
| CN112816838B (en) | GIS equipment defect diagnosis device and method based on FFT, VMD and LS-SVM | |
| CN109443190A (en) | Transient traveling wave-based transformer winding deformation online monitoring method and device | |
| CN110991481A (en) | High-voltage shunt reactor internal loosening fault diagnosis method based on cross wavelet transformation | |
| Chen et al. | Analysis of the partial discharge of ultrasonic signals in large motor based on Hilbert-Huang transform | |
| Hucker et al. | Requirements of automated PD diagnosis systems for fault identification in noisy conditions | |
| CN110032752A (en) | A kind of power electronic devices and module status detection monitoring system and method | |
| CN109307816A (en) | Power equipment test method based on substation's hybrid electromagnetic interference simulation | |
| CN112881879A (en) | High-voltage cable terminal partial discharge mode identification method, device and equipment | |
| CN108445364A (en) | Power plant's partial discharge of switchgear fault diagnosis method and system based on vibration signal | |
| CN112600659A (en) | Method and system for detecting side channel leakage of safety chip based on neural network | |
| CN110929673A (en) | Transformer winding vibration signal identification method based on ITD (inverse discrete cosine transformation) permutation entropy and CGWO-SVM (Carrier-support vector machine) | |
| Buzzoni et al. | Development of an indicator for the assessment of damage level in rolling element bearings based on blind deconvolution methods | |
| Yang et al. | Vibration signature extraction of high-voltage circuit breaker by frequency and chaotic analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180824 |