CN106771928A - A kind of online pick-up method of partial discharge pulse's initial time - Google Patents
A kind of online pick-up method of partial discharge pulse's initial time Download PDFInfo
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- CN106771928A CN106771928A CN201710015497.8A CN201710015497A CN106771928A CN 106771928 A CN106771928 A CN 106771928A CN 201710015497 A CN201710015497 A CN 201710015497A CN 106771928 A CN106771928 A CN 106771928A
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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
- G01R31/1227—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
- G01R31/1263—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 of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
- G01R31/1272—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 of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation of cable, line or wire insulation, e.g. using partial discharge measurements
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- Testing Relating To Insulation (AREA)
Abstract
The present invention discloses a kind of online pickup technology of partial discharge pulse's initial time based on wavelet packet kurtosis, and the online high accuracy for being particularly well-suited to high-tension cable partial discharge pulse initial time is picked up, and belongs to field of signal processing；Specially, calculate monitoring data sequent it is front and rear when window energy ratio R, and window energy ratio curve determines the when window that shelf depreciation occurs when utilizing, then the when window that pair partial discharge pulse for determining occurs carries out the Scale Decomposition of wavelet packet three with reconstruct, partial discharge pulse is extracted, the online pickup of high-precision local discharge pulse initial time is finally realized using kurtosis algorithm.Compared to single kurtosis method and the Peak Intensity Method that there is currently, small echo module maximum method etc., the present invention has stronger adaptability to noise, with important engineering application value.
Description
Technical field
The present invention relates to a kind of online pick-up method of the partial discharge pulse's initial time based on wavelet packet kurtosis algorithm,
It is particularly well-suited to the online pickup of high-tension cable partial discharge pulse initial time.Belong to field of signal processing.
Background technology
With the requirement developed rapidly with urban planning of China's large- and-medium size cities construction, the power cable of underground is layed in
Conventional outskirts of a town overhead transmission line will gradually be replaced.Buried cable have take up an area less, maintenance work reliable to personal safety, power supply
Many advantages, such as measuring small, but buried cable once breaks down, and ten minutes difficulties of trouble-shooting point will not only waste a large amount of manpower things
Power, but also the loss of outage for being difficult to estimate will be brought.Therefore, how accurately, quickly, economically detect cable insulation failure
Point is the focus studied about engineers and technicians both at home and abroad for many years.And the shelf depreciation of buried cable is examined online
What is surveyed and position is to diagnose the cable insulation trouble point most directly perceived, most preferable, most efficient method.The cable part commonly used at present
Discharge pulse tuning on-line method mainly has single-ended traveling wave method (TDR) and a both-end traveling wave method (ATA), and the positioning of the two methods
Precision is highly dependent on the pickup precision of partial discharge pulse's initial time.
In the pick-up method of the partial discharge pulse's initial time for having developed at present, prior art [1] is (referring to Zheng Wen
, Yang Ning, Qian Yong wait experimental study of the multisensors associated detection technique in XLPE cable annex shelf depreciation positioning
[J] electric power system protection and controls, 2011,39 (20):84-88.) using the first arrival of AIC information criterions pickup partial discharge pulse
Moment, but AIC methods are only used for the pickup of partial discharge pulse's signal initial time, can not carry out partial discharge pulse's thing
The identification of part, i.e. AIC methods are only used for determining the when window of partial discharge pulse, it is impossible to realize online pickup.
Prior art [2] (builds some key technology research [D] of cable survey length that brightness is based on Time Domain Reflectometry principle referring to Song
Harbin Institute of Technology, 2010.) threshold method, Peak Intensity Method based on Time Domain Reflectometry principle are utilized to cable local discharge clock
Positioned.But its positioning precision is influenceed larger by noise and wave distortion, is difficult to ensure that in actual applications.
Prior art [3] (referring to Gao Shuguo, Liu Hechen, Fan Hui, waits to consider the wavelet modulus maxima of velocity of wave characteristic
Power cable shelf depreciation Position Research [J] electric power network techniques of method, 2016,40 (7):2244-2250.) utilize WAVELET TRANSFORM MODULUS
Maximum Approach realizes the online pickup of partial discharge pulse's initial time.But the method is easily affected by noise to produce multiple puppet extreme values
Point, pickup precision is difficult to ensure that.
Therefore, existing partial discharge pulse's initial time pickup technology is present on-line automatic can not pick up and easily receive noise shadow
Ring two problems.
The content of the invention
The present invention proposes a kind of online pick-up method of partial discharge pulse's initial time based on wavelet packet kurtosis, the method
The on-line automatic pickup of initial time can be realized and there is very strong adaptability to noise.
The specific reality of the online pick-up method of partial discharge pulse's initial time based on wavelet packet kurtosis of the present invention
Existing step is as follows:
Step one：On-line monitoring of cable time series x is obtained by High Frequency Current Sensor (HFCT)n(n=1,2,
...N)；Wherein N is the sequential sampling point number；
Step 2：The when window energy ratio R of the sequence is calculated, it is determined that the on-line monitoring changed with the sampled point
Time series xnWhen window energy ratio curve R (i)；
The energy ratio of window constructs the on-line monitoring time sequence when using length being 2M, forward and backward centered on sampled point i
Row xnIt is described when window energy ratio curve R (i),
Wherein, λ is stable factor, the energy value of window when its value should be much smaller than preceding
Step 3：According to it is described when window energy ratio curve determine the when window that the partial discharge pulse occurs；
Whether window energy ratio R is more than given threshold value C during by judging described, and whether window has shelf depreciation arteries and veins when determining this
Punching occurs；Subsequent time is recycled to if qualified energy ratio is not detected by, if detecting partial discharge pulse's event,
Then can determine that centered on partial discharge pulse's case point, length is the when window x of 2Mm(m=i-M, i-M+1 ... i+
M-1)。
Step 4：The Scale Decomposition of wavelet packet three and reconstruct are carried out to the when window that the partial discharge pulse of the determination occurs,
Extract the partial discharge pulse；
Frequency band contained by cable local discharge pulse (the up to GHz orders of magnitude) higher and mainly divide in the frequency spectrum of noise jamming
Amount focuses mostly in≤1MHz.Pair determine when window carry out the Scale Decomposition of wavelet packet three with reconstruct, signal is divided into 8 frequency bands, it is small
Ripple packet transform can carry out Time-Frequency Localization analysis to the signal comprising a large amount of medium, high frequency information, by partial discharge pulse's information
Decomposed in different frequency bands from noise information, noise signal is mainly distributed on lower band, and partial discharge pulse is present in higher
Frequency band, removes at least a portion noise jamming frequency band, selection partial discharge pulse content highest frequency band, and extract the part
Pulse signal in discharge pulse content highest frequency band is used as partial discharge pulse.
Step 5：The online pickup of high-precision local discharge pulse initial time is realized using kurtosis algorithm；
Kurtosis is asymmetric and non-gaussian distribution time series important measure parameter, reflects the collection intermediate range of signal distributions
Degree, the kurtosis value K of frequency band characterizes the steep of signal probability distribution,
Wherein, It is [xn] average value；
Using the frequency band of the selection time-varying kurtosis change rate curve K is constructed in the waveform steep of moment it(i),
When time-varying kurtosis rate of change is maximum, waveform steep is the most obvious, and the point is the shelf depreciation
Pulse initial time；
Wherein, K is the kurtosis value of the frequency band of the selection；K (i) is partial discharge pulse's content highest of the selection
Period of the day from 11 p.m. to 1 a.m window kurtosis value in frequency band, the window center when period of the day from 11 p.m. to 1 a.m window is with i, length is L.
Beneficial effect：
The present invention first by when window energy ratio determine partial discharge pulse generation when window, overcome kurtosis algorithm not
The defect that initial time is picked up online can be used for.
Secondly, the present invention extracts pulse signal using the Scale Decomposition of wavelet packet three with reconstruct, than directly using kurtosis algorithm
Pickup high precision, and with very strong noise adaptation ability, with engineering application value higher.
Brief description of the drawings
Fig. 1 is the method for the invention flow chart.
Fig. 2 be different signal to noise ratios under Peak Intensity Method, kurtosis method, small echo module maximum method and the method for the invention initial time pick up
Take design sketch.
Specific embodiment
In order to the purpose of the present invention and advantage is better described, below the present invention will be further described.
When cable local discharge on-line checking is carried out with positioning using many High Frequency Current Sensors, for shelf depreciation arteries and veins
The problem of signal initial time pickup precision influence positioning precision not high is rushed, a kind of shelf depreciation based on wavelet packet kurtosis is proposed
The on-line automatic pick-up method of pulse initial time.The anti-noise jamming ability and pickup precision of kurtosis algorithm are the method increase,
Compared to individually using kurtosis method and Peak Intensity Method, the small echo module maximum method that there is currently, the method has stronger fitting to noise
Should be able to power.
Embodiment 1：
Fig. 1 gives the present invention the online pick-up method stream of partial discharge pulse's initial time based on wavelet packet kurtosis algorithm
Cheng Tu, the method is comprised the following steps：
Step one：On-line monitoring of cable time series x is obtained by High Frequency Current Sensor (HFCT)n(n=1,2,
...N)；Wherein N is the sequential sampling point number；
Step 2：The when window energy ratio R of the sequence is calculated, it is determined that the on-line monitoring changed with the sampled point
Time series xnWhen window energy ratio curve R (i)；
The energy ratio of window constructs the on-line monitoring time sequence when using length being 2M, forward and backward centered on sampled point i
Row xnIt is described when window energy ratio curve R (i),
Wherein, λ is stable factor, the energy value of window when its value should be much smaller than preceding
Step 3：According to it is described when window energy ratio curve determine the when window that the partial discharge pulse occurs；
Whether window energy ratio R is more than given threshold value C during by judging described, and whether window has shelf depreciation arteries and veins when determining this
Punching occurs；Subsequent time is recycled to if qualified energy ratio is not detected by, if detecting partial discharge pulse's event,
Can determine that centered on partial discharge pulse's case point, length is the when window x of 2Mm(m=i-M, i-M+1 ... i+M-1).
Step 4：The Scale Decomposition of wavelet packet three and reconstruct are carried out to the when window that the partial discharge pulse of the determination occurs,
Extract the partial discharge pulse；
Frequency band contained by cable local discharge pulse (the up to GHz orders of magnitude) higher and mainly divide in the frequency spectrum of noise jamming
Amount focuses mostly in≤1MHz.Pair determine when window carry out the Scale Decomposition of wavelet packet three with reconstruct, signal is divided into 8 frequency bands, it is small
Ripple packet transform can carry out Time-Frequency Localization analysis to the signal comprising a large amount of medium, high frequency information, by partial discharge pulse's information
Decomposed in different frequency bands from noise information, noise signal is mainly distributed on lower band, and partial discharge pulse is present in higher
Frequency band, removes at least a portion noise jamming frequency band, selection partial discharge pulse content highest frequency band, and extract the part
Pulse signal in discharge pulse content highest frequency band is used as partial discharge pulse.
Step 5：The online pickup of high-precision local discharge pulse initial time is realized using kurtosis algorithm；
Kurtosis is asymmetric and non-gaussian distribution time series important measure parameter, reflects the collection intermediate range of signal distributions
Degree, the kurtosis value K of frequency band characterizes the steep of signal probability distribution,
Wherein, It is [xn] average value；
Using the frequency band of the selection time-varying kurtosis change rate curve K is constructed in the waveform steep of moment it(i),
When time-varying kurtosis rate of change is maximum, waveform steep is the most obvious, and the point is the shelf depreciation
Pulse initial time；
Wherein, K is the kurtosis value of the frequency band of the selection；K (i) is partial discharge pulse's content highest of the selection
Period of the day from 11 p.m. to 1 a.m window kurtosis value in frequency band, the window center when period of the day from 11 p.m. to 1 a.m window is with i, length is L.
Embodiment 2：
Fig. 2 gives partial discharge pulse that true initial time is the 1230th sampled point under the conditions of different signal to noise ratios,
Using kurtosis method, Peak Intensity Method carries out the analogous diagram of initial time extraction with initial time pick-up method of the present invention, now incite somebody to action this
Invention is compiled in table 1 with Peak Intensity Method, the pickup result of single kurtosis method and error amount.As it can be seen from table 1 signal to noise ratio is -6dB
When, the present invention picks up partial discharge pulse's initial time in the 1229th sampled point, and 1 is differed only by with standard sample point 1230
Sampled point；And Peak Intensity Method, kurtosis method, the pickup result of small echo module maximum method are respectively 1233 sampled points, 1232 sampled points, 1235
Sampled point, its error respectively reaches 3 sampled points, 2 sampled points, 5 sampled points；When signal to noise ratio is -12dB, the present invention exists
1230th sampled point picks up partial discharge pulse's initial time, realizes 0 error；And the pickup result of Peak Intensity Method is 1233
Sampled point, error reaches 3 sampled points；Kurtosis method picks up mistake；The pickup result of small echo module maximum method is 1235 sampled points, by mistake
Difference reaches 5 sampled points；When signal to noise ratio is -14dB, the present invention is at the beginning of the 1231st sampled point picks up partial discharge pulse
To the moment, 1 sampled point is differed only by with standard sample point 1230；And the pickup result of Peak Intensity Method is 1234 sampled points, error reaches
To 4 sampled points；Kurtosis method picks up mistake；The pickup result of small echo module maximum method is 1235 sampled points, and error reaches 5 samplings
Point.It follows that using comparing Peak Intensity Method and kurtosis method, at the beginning of pick-up method of the invention realizes high-precision local discharge pulse
To the online pickup at moment, and there is stronger adaptability to noise.
Table 1：The inventive method and Peak Intensity Method, kurtosis method, the pickup results contrast of small echo module maximum method under different signal to noise ratios.
Note：False refers to wrong pickup in table 1.
Claims (6)
1. a kind of online pick-up method of partial discharge pulse's initial time based on wavelet packet kurtosis algorithm, it is characterised in that the party
Method is concretely comprised the following steps：
Step one：On-line monitoring of cable time series x is obtained by High Frequency Current Sensor (HFCT)n(n=1,2 ... N)；Its
Middle N is the sequential sampling point number；
Step 2：The when window energy ratio R of the sequence is calculated, it is determined that the on-line monitoring time changed with the sampled point
Sequence xnWhen window energy ratio curve R (i)；
Step 3：According to it is described when window energy ratio curve determine the when window that the partial discharge pulse occurs；
Step 4：The Scale Decomposition of wavelet packet three and reconstruct are carried out to the when window that the partial discharge pulse of the determination occurs, is extracted
The partial discharge pulse；
Step 5：The online pickup of high-precision local discharge pulse initial time is realized using kurtosis algorithm.
2. the online pick-up method of partial discharge pulse's initial time according to claim 1, it is characterised in that step 2
In, the when window energy ratio R of the sequence is calculated, it is determined that the on-line monitoring time series x changed with the sampled pointn's
When window energy ratio curve, specially：The energy ratio construction of window is described when using length being 2M, forward and backward centered on sampled point i
On-line monitoring time series xnIt is described when window energy ratio curve R (i),
Wherein, λ is stable factor, the energy value of window when its value should be much smaller than preceding
3. the online pick-up method of partial discharge pulse's initial time according to claim 2, it is characterised in that step 3
In, it is described according to when window energy ratio curve determine partial discharge pulse occur when window, specially：Window during by judging described
Whether energy ratio R is more than given threshold value C, and whether window has partial discharge pulse when determining this；If being not detected by meeting bar
The energy ratio of part is then recycled to subsequent time, if detecting partial discharge pulse's event, can determine that and is put with the part
Centered on electric pulse case point, length is the when window x of 2Mm(m=i-M, i-M+1 ... i+M-1).
4. the online pick-up method of partial discharge pulse's initial time according to claim 3, it is characterised in that step 4
In, the when window of described pair of partial discharge pulse's generation of determination carries out the Scale Decomposition of wavelet packet three and reconstruct, extracts shelf depreciation
Pulse, specially：Time-Frequency Localization analysis is carried out by wavelet package transforms centering/high-frequency signal, respectively by partial discharge pulse
Signal is decomposed in multiple different frequency bands from noise interferences, removes at least a portion noise jamming frequency band, and selection is local to put
Electric pulse content highest frequency band, and the pulse signal in partial discharge pulse's content highest frequency band is extracted as part
Discharge pulse.
5. the online pick-up method of partial discharge pulse's initial time according to claim 4, it is characterised in that step 5
In, the utilization kurtosis algorithm realizes the online pickup of high-precision local discharge pulse initial time, specially：The kurtosis of frequency band
Value K characterizes the steep of signal probability distribution,
Wherein, It is [xn] average value；
Using the frequency band of the selection time-varying kurtosis change rate curve K is constructed in the waveform steep of moment it(i),
At the moment of the peak value correspondence time-varying kurtosis rate of change maximum of the time-varying kurtosis change rate curve, waveform steep is the most
Substantially, the point is partial discharge pulse's initial time；
Wherein, K is the kurtosis value of the frequency band of the selection；K (i) is partial discharge pulse's content highest frequency band of the selection
In period of the day from 11 p.m. to 1 a.m window kurtosis value, the window center when period of the day from 11 p.m. to 1 a.m window is with i, length is L.
6. the online pick-up method of partial discharge pulse's initial time according to claim 4, it is characterised in that the multiple
The number of frequency band is 8.
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| CN109932624A (en) * | 2019-04-01 | 2019-06-25 | 珠海华网科技有限责任公司 | A kind of cable partial discharge periodical narrow-band interference denoising method based on Gaussian scale-space |
| CN111551827A (en) * | 2020-04-14 | 2020-08-18 | 杭州柯林电气股份有限公司 | Wave head initial time detection method and monitoring system applied to partial discharge positioning |
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