CN108446632A - It a kind of partial discharge pulse edge finds and shelf depreciation confirmation method - Google Patents
It a kind of partial discharge pulse edge finds and shelf depreciation confirmation method Download PDFInfo
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- CN108446632A CN108446632A CN201810228658.6A CN201810228658A CN108446632A CN 108446632 A CN108446632 A CN 108446632A CN 201810228658 A CN201810228658 A CN 201810228658A CN 108446632 A CN108446632 A CN 108446632A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
- G06F2218/06—Denoising by applying a scale-space analysis, e.g. using wavelet analysis
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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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
- G06F2218/10—Feature extraction by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
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Abstract
The present invention disclose a kind of partial discharge pulse edge find with shelf depreciation confirmation method, belong to electric power transformer insulated detection technique and its application field, method includes：Wavelet de-noising is carried out to partial discharge pulse's sample sequence；Extract the signal sequence of ambient noise；Calculate Background Noise Power；Find the edge placement of the impulse waveform of the partial discharge pulse；Confirm and extracts discharge pulse；The present invention has efficiently separated the ambient noise of partial discharge pulse's sample sequence using the method for Wavelet Denoising Method, adjusts the setting of threshold value in real time according to noise power calculation threshold value and according to sampling environment, ambient noise, avoids the limitation of empirical value；The accuracy of porch searching is also improved simultaneously for the filtering exclusion of noise so that the present invention is suitable for the partial discharge monitoring under varying environment and data analysis.
Description
【Technical field】
The invention belongs to electric power transformer insulated detection technique and its application field, more particularly to a kind of partial discharge pulse
It finds and shelf depreciation confirmation method at edge.
【Background technology】
Power transformer is one of most important equipment in electric system, power plant, substation's large high voltage transformer
Safe operation is to ensure that the key of large area normal power supply.Transformer insulating system is the important component of power transformer,
Its system largely determines the reliability and economy of transformer station high-voltage side bus.Fortune of the power transformer under operating voltage
It is closely related that whether there is or not shelf depreciations during the row service life is insulated from, and shelf depreciation is weaker, then the normal operation service life is longer.Shelf depreciation
Not only result in turn insulation breakdown, in some instances it may even be possible to lead to turn-to-turn and layer short circuit, this accident high-power transformer intermediate frequency at home
Numerous appearance.Phenomena such as electricity that is generated when Partial Discharge Detection is so that shelf depreciation occurs, light as foundation, by the way that the phenomenon can be stated
Physical quantity characterize the state of shelf depreciation.But due to the presence of ambient noise, Partial Discharge in Power Transformer is examined online
It surveys acquired signal and contains a large amount of noise, the very unobvious for making the edge of single partial discharge pulse signal become；In addition partial discharge is examined
There is a large amount of disturbing pulse at survey scene, to partial discharge pulse's signal characteristic analyzing in later stage, identification and discharge time statistics
Bring certain difficulty.Accordingly, it is determined that the marginal position of partial discharge pulse's signal, accurately from ambient noise and interference
Partial discharge pulse's waveform is accurately found in pulse has become one of Partial Discharge in Power Transformer detection technique critical issue.It seeks
Committed step of the edge of partial discharge pulse's signal as the measurement of partial discharge Signal Pretreatment stage is looked for, is to shelf depreciation
The basis that signal is analysed in depth.
The method of existing partial discharge pulse's extraction is based on one is a threshold value is arranged based on experience value using threshold value
Sliding window extracts starting and the end position of pulse.The setting of this method threshold value relies primarily on empirical value, and threshold value is chosen not
Appropriately, then the discharge pulse of mistake can be caused to judge that limitation is bigger.It is also smooth one is FIR is carried out to pulse train
Then filtering detects pulse width and turn-off time, set down-sampling scale, again smothing filtering, and then by detecting transition
Point segmentation pulse, and corrected errors according to segmentation result and adjust filter scale, divide again, until segmentation is correct, but wherein pulse
The calculating process of width and turn-off time use Density Distribution statistical average method, and histogram is carried out on calibration graph paper to pulse
Figure is drawn, and process calculating is excessively complicated and cumbersome, is not suitable for analyzing the on-line monitoring of shelf depreciation.Its publication No. is
A kind of patent " fast automatic extracting method of train pulse signal " of CN103487788A adopts this method to realize.Patent
《Method for extracting radar pulse based on adaptive threshold》(publication No.：CN101762808A the envelope width of radar signal) is first extracted
Value, smothing filtering is carried out to radar envelope range value, is carried out K mean cluster algorithm to filtered envelope range value, is calculated radar arteries and veins
It purges with and takes threshold value.The algorithm have both sides limitation, first, first have to be each using the process of K mean cluster algorithm
Cluster determines an initial cluster centre.The performance of cluster is related with the selection of initial cluster center.Initial cluster center
It determines to cluster result, influence when clustering convergence is very big, and inappropriate initial value can usually make result converge to one not wish
The minimal point of prestige, and influence convergence rate；Second, K mean algorithm in the calculating process of the mean value of lower aprons and borderline region,
Object is all only added the object number again divided by corresponding region by algorithm, that is, assert that the weight of each data object is identical
's.Practical to adjust weight according to the density of each data point region in the calculating process to cluster mean value, what is obtained is equal
Value point can preferably represent this cluster.Cluster is a dynamic process, with cluster process early period to later stage upper approximation and under
The characteristics of approximate variation, fixed experience weight can not adapt to cluster early period and later stage very well, while the algorithm is easy by different
The interference of normal noise spot, such a small amount of data can generate strong influence to average value.Patent《One kind being based on sliding window
Shelf depreciation pulse extracting method》(publication No.：CN104635126) pass through the background in the no pulse region to sample sequence
Signal is counted to obtain the mean value of ambient noise and variance, the threshold value that setting discharge pulse extracts.It was counted in background signal
Cheng Zhong needs to intercept sufficiently long sample sequence, and interception sequence is longer, and the ambient noise mean value and variance counted is more smart
Really.This processing procedure needs count a large amount of shelf depreciation time serieses, increase calculation amount；Secondly, different defects
The specific location that occurs of shelf depreciation it is different, need to re-start interception statistics to background signal, this procedure reduces arteries and veins
Rush extraction rate.Method proposed by the present invention utilizes noise work(using wavelet de-noising techniques separation discharge signal and ambient noise
Threshold value is arranged in rate, adjusts the setting of threshold value in real time according to sampling environment, ambient noise, meets the detection of shelf depreciation real-time online
Data processing, and do not limited by discharge defect and detection mode.
【Invention content】
A kind of partial discharge pulse edge of present invention proposition is found and shelf depreciation confirmation method, utilizes the side of Wavelet Denoising Method
Method has efficiently separated the ambient noise of partial discharge pulse's sample sequence, can be according to noise power calculation threshold value and according to adopting
Sample environment, ambient noise adjust the setting of threshold value in real time, avoid the limitation of empirical value；Meet the part under varying environment
On-line Discharge monitors and data analysis.Specific technical solution is as follows.
A kind of partial discharge pulse edge is found includes with shelf depreciation confirmation method, key step：
(1)：Wavelet de-noising is carried out to partial discharge pulse's sample sequence；
(2)：Extract the signal sequence of ambient noise；
(3)：Calculate Background Noise Power；
(4)：Find the edge placement of the impulse waveform of the partial discharge pulse；
(5)：Confirm and extracts discharge pulse.
Specifically, the step (1) includes：Wavelet transformation is carried out to the partial discharge pulse sample sequence X (i), is adopted
True discharge signal is detached with ambient noise with the method for threshold function table denoising, obtains denoising postamble sequence Y (i).
Specifically, the step (2) includes：By signal after the partial discharge pulse sample sequence X (i) and the denoising
Sequence Y (i) obtains the signal sequence n (i) of the ambient noise as difference, i.e.,：N (i)=X (i)-Y (i).
Specifically, the step (3) includes：According to the signal sequence n (i) of the ambient noise, using formula Pn=sum
The Background Noise Power Pn is calculated in (abs (n (i)) .^2)/N.
Specifically, the step (4) includes：
Step (41)：Using threshold values slip window sampling, and according to the Background Noise Power Pn given thresholds thr1 and window
Mouth width degree M；
Step (42)：Since first point of the denoising postamble sequence Y (i), believe after gradually moving the denoising
Number sequence Y (i), the absolute value of sequence amplitude is more than threshold value thr1 in the window when reaching A points, then using the A points described in
The starting point of impulse waveform, record A points are as index A；
Step (43)：The denoising postamble sequence Y (i) is continued to move to, the sequence amplitude in window when reaching B points
Absolute value is respectively less than threshold value thr1, i.e., using the B points as the end point of the impulse waveform, record B points are as index B；
Step (44)：Simultaneously using the signal sequence between the index A and index B as the primary complete impulse waveform
It preserves；
Step (45)：Step (42) and (43) is repeated, the terminal until reaching the denoising postamble sequence Y (i) then stops
Only move.
Specifically, the step (5) includes：According to the Background Noise Power Pn, discharge pulse amplitude thresholds are set
Thr2 judges the impulse waveform preserved, if the maximum value of the pulse signal of the impulse waveform is big
In threshold value thr2, then the impulse waveform is the pulse signal of primary true shelf depreciation, output and the pulse
Waveform corresponds to the discharge pulse；It, should if the maximum value of the pulse signal of the impulse waveform is less than threshold value thr2
The impulse waveform is disturbing pulse and removes.
A kind of partial discharge pulse edge proposed by the present invention is found and shelf depreciation confirmation method, utilizes Wavelet Denoising Method side
Method effectively separates discharge signal from ambient noise, and carries out porch searching and electric discharge arteries and veins according to ambient noise
The threshold value setting that punching confirms, avoids the limitation of empirical value, while filtering out for noise also improves the edge of a pulse in this way
The accuracy of extraction meets the partial discharge monitoring under varying environment and data analysis；In addition, the setting of two layers of threshold value,
On the one hand be not in fail to judge to the judgement of discharge pulse, on the other hand efficiently separated pseudo- discharge pulse.
【Description of the drawings】
Fig. 1 is the flow chart of partial discharge pulse edge searching and shelf depreciation confirmation method of the present invention.
Fig. 2 is partial discharge pulse's time domain waveform of certain collected defect type in the embodiment of the present invention.
Fig. 3, which is the embodiment of the present invention, primary completely to be put using the method for the present invention to what the embodiment of Fig. 2 extracted
Electric pulse waveform.
【Specific implementation mode】
A kind of partial discharge pulse edge proposed by the present invention is found and shelf depreciation confirmation method, can be fast and accurately
The edge placement of single discharge pulse is found from the pulse train for being continuously contaminated with ambient noise and carries out discharge pulse confirmation,
The setting of threshold value adjusts in real time according to the Background Noise Power after wavelet de-noising during porch position is found, avoid through
It tests the limitation of threshold value and is not limited to by noise.
A kind of present invention partial discharge pulse edge is elaborated with reference to Fig. 1 to find and discharge pulse confirmation method
Key step：
(1) wavelet de-noising is carried out to partial discharge pulse's sample sequence；
Wavelet transformation is carried out to the partial discharge pulse sample sequence X (i), it will be true using the method for threshold function table denoising
Real discharge signal is detached with ambient noise, obtains denoising postamble sequence Y (i).
(2) signal sequence of ambient noise is extracted；
The step (2) includes：By the partial discharge pulse sample sequence X (i) and the denoising postamble sequence Y
(i) the signal sequence n (i) of the ambient noise is obtained as difference, i.e.,：N (i)=X (i)-Y (i).
(3) Background Noise Power is calculated；
The step (3) includes：According to the signal sequence n (i) of the ambient noise, using formula Pn=sum (abs (n
(i)) .^2) the Background Noise Power Pn is calculated in/N.
(4) edge placement of the impulse waveform of the partial discharge pulse is found, including：
Step (41)：Using threshold values slip window sampling, and according to the Background Noise Power Pn given thresholds thr1 and window
Mouth width degree M；
Step (42)：Since first point of the denoising postamble sequence Y (i), believe after gradually moving the denoising
Number sequence Y (i), the absolute value of sequence amplitude is more than threshold value thr1 in the window when reaching A points, then using the A points described in
The starting point of impulse waveform, record A points are as index A；
Step (43)：The denoising postamble sequence Y (i) is continued to move to, the sequence amplitude in window when reaching B points
Absolute value is respectively less than threshold value thr1, i.e., using the B points as the end point of the impulse waveform, record B points are as index B；
Step (44)：Simultaneously using the signal sequence between the index A and index B as the primary complete impulse waveform
It preserves；
Step (45)：Step (42) and (43) is repeated, the terminal until reaching the denoising postamble sequence Y (i) then stops
Only move.
(5) confirm and extract discharge pulse
Discharge pulse amplitude thresholds thr2 is set according to the Background Noise Power Pn, to the impulse waveform preserved
Judged, if the maximum value of the pulse signal of the impulse waveform is more than threshold value thr2, the impulse waveform
For the pulse signal of primary true shelf depreciation, discharge pulse corresponding with impulse waveform described in this is exported；If institute
The maximum value for stating the pulse signal of impulse waveform is less than threshold value thr2, then the impulse waveform is disturbing pulse and goes
It removes.
As shown in Figure 2,3, method using the present invention of the embodiment of the present invention finds the edge of pulse to the electric discharge sample sequence of Fig. 2
Confirm along position and discharge pulse, obtained primary complete Discharge pulse waveform such as Fig. 3, wherein determining discharge time is 9
It is secondary.
A kind of partial discharge pulse edge proposed by the present invention is found and shelf depreciation confirmation method, utilizes Wavelet Denoising Method side
Method effectively separates discharge signal from ambient noise, and carries out porch searching and electric discharge arteries and veins according to ambient noise
The threshold value setting that punching confirms, avoids the limitation of empirical value, while filtering out for noise also improves the edge of a pulse in this way
The accuracy of extraction meets the partial discharge monitoring under varying environment and data analysis；In addition, the setting of two layers of threshold value,
On the one hand be not in fail to judge to the judgement of discharge pulse, on the other hand efficiently separated pseudo- discharge pulse.
The above is only the preferable case study on implementation of invention, is not intended to limit the invention, all spirit in invention
With within principle made by all any modification, equivalent and improvement etc., should all be included in the protection scope of the present invention.
Claims (6)
1. a kind of partial discharge pulse edge is found and shelf depreciation confirmation method, which is characterized in that key step includes：
(1)：Wavelet de-noising is carried out to partial discharge pulse's sample sequence；
(2)：Extract the signal sequence of ambient noise；
(3)：Calculate Background Noise Power；
(4)：Find the edge placement of the impulse waveform of the partial discharge pulse；
(5)：Confirm and extracts discharge pulse.
2. partial discharge pulse edge according to claim 1 is found and shelf depreciation confirmation method, which is characterized in that institute
Stating step (1) includes：Wavelet transformation is carried out to the partial discharge pulse sample sequence X (i), using the side of threshold function table denoising
Method detaches true discharge signal with ambient noise, obtains denoising postamble sequence Y (i).
3. partial discharge pulse edge according to claim 2 is found and shelf depreciation confirmation method, which is characterized in that institute
Stating step (2) includes：The partial discharge pulse sample sequence X (i) and the denoising postamble sequence Y (i) are obtained as difference
To the signal sequence n (i) of the ambient noise, i.e.,：N (i)=X (i)-Y (i).
4. partial discharge pulse edge according to claim 3 is found and shelf depreciation confirmation method, which is characterized in that institute
Stating step (3) includes：According to the signal sequence n (i) of the ambient noise, using formula Pn=sum (abs (n (i)) .^2)/N
The Background Noise Power Pn is calculated.
5. partial discharge pulse edge according to claim 4 is found and shelf depreciation confirmation method, which is characterized in that institute
Stating step (4) includes：
Step (41)：Using threshold values slip window sampling, and it is wide according to the Background Noise Power Pn given thresholds thr1 and window
Spend M；
Step (42)：Since first point of the denoising postamble sequence Y (i), signal sequence after the denoising is gradually moved
Y (i) is arranged, the absolute value of sequence amplitude is more than threshold value thr1 in the window when reaching A points, then using the A points as the pulse
The starting point of waveform, record A points are as index A；
Step (43)：Continue to move to the denoising postamble sequence Y (i), when reaching B points in window sequence amplitude it is absolute
Value is respectively less than threshold value thr1, i.e., using the B points as the end point of the impulse waveform, record B points are as index B；
Step (44)：Signal sequence between the index A and index B as the primary complete impulse waveform and is protected
It deposits；
Step (45)：Step (42) and (43) is repeated, the terminal until reaching the denoising postamble sequence Y (i) then stops moving
It is dynamic.
6. partial discharge pulse edge according to claim 5 is found and shelf depreciation confirmation method, which is characterized in that institute
Stating step (5) includes：Discharge pulse amplitude thresholds thr2 is set according to the Background Noise Power Pn, to the arteries and veins preserved
It rushes waveform to be judged, if the maximum value of the pulse signal of the impulse waveform is more than threshold value thr2, the arteries and veins
The pulse signal that waveform is primary true shelf depreciation is rushed, discharge pulse corresponding with impulse waveform described in this is exported；
If the maximum value of the pulse signal of the impulse waveform is less than threshold value thr2, which is disturbing pulse
And it removes.
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109085477A (en) * | 2018-09-28 | 2018-12-25 | 国网山东省电力公司济南供电公司 | Signal identification and localization method for power cable distribution partial discharge monitoring system |
| CN109212391A (en) * | 2018-09-15 | 2019-01-15 | 四川大学 | Take into account the signal processing of partial discharge method and power cable partial discharge positioning method of DISCHARGE PULSES EXTRACTION and signal denoising |
| CN109901031A (en) * | 2019-02-27 | 2019-06-18 | 西安电子科技大学 | Signal De-noising Method, information data processing terminal for local discharge signal |
| CN109991520A (en) * | 2019-03-19 | 2019-07-09 | 中国电力科学研究院有限公司 | A kind of cable oscillation wave partial discharge detecting system velocity of wave New calculating method |
| CN110596544A (en) * | 2019-09-04 | 2019-12-20 | 国网四川省电力公司电力科学研究院 | Partial discharge test platform under power cable frequency conversion series resonance |
| CN111046836A (en) * | 2019-12-24 | 2020-04-21 | 杭州电力设备制造有限公司 | Method, system, equipment and storage medium for filtering, denoising and analyzing partial discharge signal |
| CN111308281A (en) * | 2019-12-12 | 2020-06-19 | 云南电网有限责任公司临沧供电局 | Partial discharge pulse extraction method |
| CN111999620A (en) * | 2020-09-22 | 2020-11-27 | 珠海华网科技有限责任公司 | Multi-channel joint positioning method for partial discharge of power equipment |
| CN112130037A (en) * | 2020-09-16 | 2020-12-25 | 杭州西湖电子研究所 | Method for identifying local discharge and pulse interference based on pulse form |
| CN112710928A (en) * | 2020-12-10 | 2021-04-27 | 国网宁夏电力有限公司电力科学研究院 | Direct-current partial discharge waveform interference removing method and system based on autocorrelation analysis |
| CN113433437A (en) * | 2021-06-28 | 2021-09-24 | 华北电力大学 | Method and system for extracting discharge current pulse |
| CN117406046A (en) * | 2023-12-14 | 2024-01-16 | 凯恩茨(福州)工业有限公司 | Partial discharge detection device |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109212391A (en) * | 2018-09-15 | 2019-01-15 | 四川大学 | Take into account the signal processing of partial discharge method and power cable partial discharge positioning method of DISCHARGE PULSES EXTRACTION and signal denoising |
| CN109085477A (en) * | 2018-09-28 | 2018-12-25 | 国网山东省电力公司济南供电公司 | Signal identification and localization method for power cable distribution partial discharge monitoring system |
| CN109085477B (en) * | 2018-09-28 | 2021-06-25 | 国家电网有限公司 | Signal identification and positioning method for power cable distributed partial discharge monitoring system |
| CN109901031B (en) * | 2019-02-27 | 2021-06-11 | 西安电子科技大学 | Signal-to-noise separation method for partial discharge signal and information data processing terminal |
| CN109901031A (en) * | 2019-02-27 | 2019-06-18 | 西安电子科技大学 | Signal De-noising Method, information data processing terminal for local discharge signal |
| CN109991520A (en) * | 2019-03-19 | 2019-07-09 | 中国电力科学研究院有限公司 | A kind of cable oscillation wave partial discharge detecting system velocity of wave New calculating method |
| CN110596544A (en) * | 2019-09-04 | 2019-12-20 | 国网四川省电力公司电力科学研究院 | Partial discharge test platform under power cable frequency conversion series resonance |
| CN110596544B (en) * | 2019-09-04 | 2022-02-11 | 国网四川省电力公司电力科学研究院 | Partial discharge test platform under power cable frequency conversion series resonance |
| CN111308281A (en) * | 2019-12-12 | 2020-06-19 | 云南电网有限责任公司临沧供电局 | Partial discharge pulse extraction method |
| CN111046836A (en) * | 2019-12-24 | 2020-04-21 | 杭州电力设备制造有限公司 | Method, system, equipment and storage medium for filtering, denoising and analyzing partial discharge signal |
| CN112130037A (en) * | 2020-09-16 | 2020-12-25 | 杭州西湖电子研究所 | Method for identifying local discharge and pulse interference based on pulse form |
| CN111999620A (en) * | 2020-09-22 | 2020-11-27 | 珠海华网科技有限责任公司 | Multi-channel joint positioning method for partial discharge of power equipment |
| CN112710928A (en) * | 2020-12-10 | 2021-04-27 | 国网宁夏电力有限公司电力科学研究院 | Direct-current partial discharge waveform interference removing method and system based on autocorrelation analysis |
| CN112710928B (en) * | 2020-12-10 | 2023-02-21 | 国网宁夏电力有限公司电力科学研究院 | Direct-current partial discharge waveform interference removing method and system based on autocorrelation analysis |
| CN113433437A (en) * | 2021-06-28 | 2021-09-24 | 华北电力大学 | Method and system for extracting discharge current pulse |
| CN117406046A (en) * | 2023-12-14 | 2024-01-16 | 凯恩茨(福州)工业有限公司 | Partial discharge detection device |
| CN117406046B (en) * | 2023-12-14 | 2024-03-08 | 凯恩茨(福州)工业有限公司 | Partial discharge detection device |
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