CN109239554A - A kind of denoising of power cable partial discharge signal and useful signal extracting method and system - Google Patents
A kind of denoising of power cable partial discharge signal and useful signal extracting method and system Download PDFInfo
- Publication number
- CN109239554A CN109239554A CN201811140600.2A CN201811140600A CN109239554A CN 109239554 A CN109239554 A CN 109239554A CN 201811140600 A CN201811140600 A CN 201811140600A CN 109239554 A CN109239554 A CN 109239554A
- Authority
- CN
- China
- Prior art keywords
- wavelet
- discharge signal
- signal
- coefficient
- threshold
- 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
- G01R31/1227—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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Testing Relating To Insulation (AREA)
Abstract
This application discloses a kind of denoising of power cable partial discharge signal and useful signal extracting methods and system, it proposes new threshold function table and threshold process is carried out to the wavelet coefficient after wavelet decomposition, it can overcome the problems, such as exist when existing hard threshold method and Soft thresholding processing signal, may be implemented to be laid in cable duct or directly be embedded in underground cable operation data carry out denoising, extract useful signal, realize the accurate positionin to cable fault, it timely and effectively finds fault point, ensures the safe and effective operation of electric power facility.
Description
Technical field
This disclosure relates to power cable partial discharge signal processing method, in particular to a kind of power cable office
The denoising of portion's discharge signal and useful signal extracting method and system.
Background technique
In recent years, with the continuous transformation of China's urban distribution network, main product of the XLPE power cable as power cable
It has been widely used in transmission line of electricity and power distribution network.According to incompletely statistics, the high-voltage electricity of the 110KV or more to have put into operation
Cable road reaches several hundred kilometers, and up to as many as 500,000 kilometers of 35KV and following voltage class, highest voltage level has reached 500KV.
It is generally acknowledged that service life of the XLPE power cable in normal environment is 20 to 30 years, however due to cable laying in cable duct or directly
It connects and is embedded in underground, laying environment will greatly affect the service life of cable with use state.Long-term same soil, moisture, moisture contact,
It insulate vulnerable to corrosion penetration, local defect when along with cables manufacturing or installation all may cause failure.Buried cable one
Denier breaks down.Find get up it is very difficult, not only to waste a large amount of manpower and material resources, but also the power failure for being difficult to estimate will be brought
Loss.If failure cannot exclude in time, it will cause serious economic loss and social influence.
In the on-line monitoring of local discharge signal, the signal data of acquisition includes a large amount of noise, such as white noise,
The interference signals such as PERIODIC INTERFERENCE noise and impulsive noise.During actual test, local discharge signal can be submerged in and make an uproar
In sound, for the detection and positioning for realizing local discharge signal, discharge fault is excluded in time, need to the signal of acquisition into
Row denoising extracts useful information.
The existing processing to local discharge signal is after local discharge signal is carried out wavelet transformation, to carry out threshold denoising
Processing, common thresholding method have hard threshold method and Soft thresholding.Hard threshold method be exactly by the absolute value of wavelet coefficient with
Threshold value is compared, and when being greater than threshold value, is remained unchanged, and when being less than or equal to threshold value, is set to 0.Although hard threshold method can
Some mutagenic components in stick signal, but new discontinuity point may also be generated simultaneously, and to data reacting condition cross for
It is sensitive, it will appear oscillation in signal reconstruction.Wavelet coefficient and threshold value are exactly compared by Soft thresholding, when greater than threshold value
When, be punctured into the difference of wavelet coefficient and threshold value, when wavelet coefficient is less than threshold value, be set as wavelet coefficient and threshold value and,
Wavelet coefficient is set to 0 by remaining the case where.Treated that wavelet coefficient is shunk for Soft thresholding, because of meeting when signal reconstruction
Some useful high-frequency informations are lost, cause the noise of signal relatively low, in addition, the derivative of soft-threshold function is discontinuous, and
Often first derivative is handled in practical application, so Soft thresholding has certain limitation.
Summary of the invention
The disclosure to solve the above-mentioned problems, proposes a kind of denoising of power cable partial discharge signal and useful signal mentions
Method and system are taken, by the new threshold function table of proposition, existing hard threshold method and Soft thresholding can be overcome to deposit when handling
The problem of, may be implemented to be laid in cable duct or directly be embedded in underground cable operation data carry out denoising, extract
Useful signal realizes the accurate positionin to cable fault, timely and effectively finds fault point, ensure the safe and effective of electric power facility
Operation.
To achieve the goals above, the disclosure adopts the following technical scheme that
A kind of denoising of power cable partial discharge signal and useful signal extracting method, include the following steps:
Step 1, the local discharge signal x (t) for acquiring cable；
Step 2 is decomposed, the wavelet coefficient after obtaining wavelet decomposition using discharge signal of the db6 wavelet basis to acquisition
Including approximation coefficient C0And wavelet details coefficient wj,k；
Step 3 carries out hard -threshold processing to wavelet coefficient, specially by the wavelet approximation coefficients C0Retain, to small echo
Detail coefficients wj,kThreshold process is carried out, the threshold function table for carrying out threshold process use is as follows:
Wherein wj,kFor the wavelet details coefficient after wavelet decomposition,For treated wavelet details coefficient, β be adjust because
Son, and β is positive number, λ is threshold value.Wherein j indicates that the scale of wavelet decomposition, k indicate the wavelet details coefficient decomposed with scale for j
Length.
Step 4, according to approximation coefficient C0With hard -threshold treated wavelet details coefficientSignal is reconstructed, is obtained
Local discharge signal y (t) to after removal white noise.
Step 5 carries out median filtering to y (t), obtains effective local discharge signal z (t).
Further, decomposed using discharge signal of the db6 wavelet basis to acquisition specifically: to local discharge signal into
9 one-dimensional decomposition of scale of row small echo db6, and calculate the one-dimensional decomposition low frequency coefficient C that scale is 90With scale be 9 to 1 it is each
Scale high frequency wavelet detail coefficients wj,k。
Further, threshold value λ selection method is using fixed threshold method:Wherein, σ is with ruler
Degree is the standard deviation for the wavelet details coefficient that j is decomposed, and k is with the length for the wavelet details coefficient that scale is j decomposition.
Further, the step 5 is 30 to y (t) the filter window width for carrying out median filtering.
The system that a kind of denoising of power cable partial discharge signal and useful signal extract, including sequentially connected acquisition are electric
The module of the local discharge signal of cable, the module decomposed using discharge signal of the db6 wavelet basis to acquisition, to wavelet coefficient
It carries out the module of hard -threshold processing, signal is reconstructed after obtaining removal white noise according to hard -threshold treated wavelet coefficient
Local discharge signal y (t) reconstructed module and median filtering carried out to local discharge signal y (t) obtain effective shelf depreciation
The processing module of signal z (t).
A kind of computer readable storage medium, is stored thereon with computer program, comprising: when the program is executed by processor
The step of executing the above-mentioned a kind of denoising of power cable partial discharge signal and useful signal extracting method.
A kind of denoising of power cable partial discharge signal and useful signal extraction system, including server, the server
Including memory, processor and the computer program that can be run on a memory and on a processor is stored, the processor is held
The step of above-mentioned a kind of denoising of power cable partial discharge signal and useful signal extracting method is realized when row described program.
Compared with prior art, the disclosure has the beneficial effect that
(1) disclosed method cuts down acquisition using the part of white noise and pulsive noise and the characteristics of being approximately zero
The amplitude of the noise of discharge signal effectively inhibits white noise and pulsive noise, while preferable must extract local discharge signal
Wave character.Oscillation problem of the thresholding functions that the disclosure uses when can effectively reduce signal reconstruction and overcome existing
Hard -threshold handle discontinuous problem.The thresholding functions that the disclosure uses also can effectively solve the problem that using soft-threshold function
There are problems that constant deviation between wavelet coefficient and the wavelet coefficient of signals and associated noises, reduces high-frequency information loss.
(2) disclosure carries out threshold using the thresholding functions that this announcement proposes to the signal of acquisition by wavelet decomposition
Value processing, the white noise of removal acquisition signal remain the useful of signal using the impulsive noise in median filtering removal signal
Information.
Detailed description of the invention
The accompanying drawings constituting a part of this application is used to provide further understanding of the present application, and the application's shows
Meaning property embodiment and its explanation do not constitute the restriction to the application for explaining the application.
Fig. 1 is the flow chart of the denoising method of cable local discharge signal；
Fig. 2 is the signal graph of the original local discharge signal of acquisition；
Fig. 3 is the local discharge signal part figure of the original Partial discharge signal acquired in Fig. 2；
Fig. 4 is the signal graph of the local discharge signal y (t) after small echo processing removal white noise；
Fig. 5 is the signal graph of local discharge signal z (t) after median filtering removal pulsive noise.
Specific embodiment:
The disclosure is described further with embodiment with reference to the accompanying drawing.
It is noted that described further below be all exemplary, it is intended to provide further instruction to the application.Unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
Following embodiments are a kind of typical embodiment of the application, as shown, a kind of power cable shelf depreciation
Signal denoising and useful signal extracting method, include the following steps:
Step 1, the local discharge signal x (t) for acquiring cable；
Step 2 is decomposed, the wavelet coefficient after obtaining wavelet decomposition using discharge signal of the db6 wavelet basis to acquisition
Including approximation coefficient C0And wavelet details coefficient wj,k；
The scale of wavelet decomposition can be to be multiple dimensioned, and the scale number that the present embodiment determines is 9, and 9 scales are respectively
Scale 9, scale 8, scale 7 ... scale 1.
The present embodiment decomposes the discharge signal of acquisition using db6 wavelet basis specifically: to local discharge signal into
9 one-dimensional decomposition of scale of row small echo db6 carry out the one-dimensional decomposition that scale is 9 to signal, obtain the one-dimensional decomposition that scale is 9
Low frequency coefficient C0It is 9 high frequency wavelet detail coefficients w with scale9,k, k expression is with the length for the wavelet details coefficients that scale is 9 decomposition
Degree；The one-dimensional decomposition that scale is 8 to 1 is carried out to signal, obtaining scale is 8 to 1 high frequency wavelet detail coefficients w8,kTo w1,k；Scale
W can be expressed as 9 to 1 each scale high frequency wavelet detail coefficientsj,k, j indicates the scale of wavelet decomposition, k indicate with scale be
The length for the high frequency wavelet detail coefficients that j is decomposed.
Step 3 carries out hard -threshold processing to wavelet coefficient, specially by the wavelet approximation coefficients C0Retain, to small echo
Detail coefficients wj,kThreshold process is carried out, the threshold function table for carrying out threshold process use is as follows:
Wherein, wj,kFor the wavelet details coefficient after wavelet decomposition,For treated wavelet details coefficient, β is to adjust
The factor, and β is positive number, λ is threshold value.Wherein j indicates that the scale of wavelet decomposition, k indicate the wavelet details system decomposed with scale for j
Several length.
Preferably, threshold value λ selection method calculates the threshold value λ on 9 to 1 each scale using fixed threshold method,Wherein, σ be with scale be j decompose wavelet details coefficient wj,kStandard deviation, it is j point that k, which is with scale,
The wavelet details coefficient w of solutionj,kLength.
The detailed process of the threshold process are as follows:
It calculates the threshold value λ that scale is 9 to 1 each scale: being respectively the high frequency wavelet detail coefficients of 9-1 decomposition with each scale
w9,k, w8,k……w1,kFixed threshold method is used to calculate scale as the threshold value λ on 9 to 1 each scale, respectively λ9, λ8……λ1。
Wavelet details coefficient, which is handled, according to threshold function table, that is, formula (1) obtains wavelet coefficientAnd retain approximation coefficient
C0。
Step 4, according to approximation coefficient C0With hard -threshold treated wavelet details coefficientSignal is reconstructed, is gone
Local discharge signal y (t) except white noise existing for local discharge signal, after obtaining removal white noise.
Step 5 carries out median filtering to y (t), and window width is selected as 30, removes the pulse letter in shelf depreciation time domain
Number interference, obtain required for local discharge signal z (t).
This announcement carries out the one-dimensional decomposition of 9 scales of db6 to the power cable local signal of acquisition first, and calculating scale is 9
One-dimensional decomposition low frequency coefficient C0, retain low frequency coefficient C0.Each scale high frequency wavelet detail coefficients that scale is 9 to 1 are calculated, and
The threshold value λ on 9 to 1 each scale is calculated, threshold process is carried out to the high frequency wavelet detail coefficients.Finally according to threshold process after
Wavelet details coefficient, signal is reconstructed.White noise removal is carried out first, and power cable is then completed by median filtering
The denoising and extraction of local signal can overcome hard threshold method in the prior art and soft by the new threshold function table of proposition
When threshold method handles signal there are the problem of, may be implemented cable duct or to be directly embedded in the cable operation data of underground to being laid in
Denoising is carried out, useful signal is extracted, the accurate positionin to cable fault is realized, timely and effectively finds fault point, is ensured
The safe and effective operation of electric power facility.
The signal graph of Fig. 2-Fig. 4 illustrates the denoising reached by the method for this announcement and extracts the effect of useful signal.
Fig. 2 is local discharge signal original sampling data, and noise is spread in entire time domain.For the verifying denoising effect being more clear
Fruit, Fig. 3 choose shelf depreciation original sampling data of the time domain 2000 to 4000.Fig. 4 is to use threshold value letter using Wavelet Denoising Method
Number handles wavelet coefficient, then the signal graph of reconstruction signal, it can be seen from the figure that the thresholding method of this announcement is to white noise
The denoising effect of sound is obvious, but in entire time domain, still there is apparent impulsive noise.Fig. 5 is after removing white noise
Effect of the signal after median filtering, it can be seen from the figure that the data-signal figure after median filtering, denoising effect
Fruit clearly, can be as the type of subsequent shelf depreciation and the valid data of positioning.
Although traditional hard threshold method can some mutagenic components in stick signal, may also generate simultaneously it is new not
Continuity point, and data reacting condition is crossed to be sensitive, it will appear oscillation in signal reconstruction.The threshold process letter that the disclosure uses
Oscillation problem when number can effectively reduce signal reconstruction and it is corrected without successional problem.
Using Soft thresholding, treated that wavelet coefficient is shunk in the prior art, because can lose when signal reconstruction
Some useful high-frequency informations, cause the noise of signal relatively low, in addition, the derivative of soft-threshold function is discontinuous, and in reality
Often first derivative is handled in, so soft-threshold function has certain limitation.The threshold that the disclosure uses
Value processing function also can effectively solve the problem that there are problems that constant deviation between wavelet coefficient and the wavelet coefficient of signals and associated noises, drop
Low high-frequency information loss.The disclosure utilizes the arteries and veins in median filtering removal signal after wavelet decomposition threshold method removes white noise
Noise is rushed, the useful information of signal can be effectively retained.
The foregoing is merely preferred embodiment of the present application, are not intended to limit this application, for the skill of this field
For art personnel, various changes and changes are possible in this application.Within the spirit and principles of this application, made any to repair
Change, equivalent replacement, improvement etc., should be included within the scope of protection of this application.
Although above-mentioned be described in conjunction with specific embodiment of the attached drawing to the disclosure, model not is protected to the disclosure
The limitation enclosed, those skilled in the art should understand that, on the basis of the technical solution of the disclosure, those skilled in the art are not
Need to make the creative labor the various modifications or changes that can be made still within the protection scope of the disclosure.
Claims (7)
1. a kind of power cable partial discharge signal denoising and useful signal extracting method, which comprises the following steps:
Step 1, the local discharge signal x (t) for acquiring cable；
Step 2 is decomposed using discharge signal of the db6 wavelet basis to acquisition, and the wavelet coefficient after obtaining wavelet decomposition includes
Approximation coefficient C0And wavelet details coefficient wj,k；
Step 3 carries out hard -threshold processing to wavelet coefficient, specially by the wavelet approximation coefficients C0Retain, to wavelet details system
Number wj,kThreshold process is carried out, the threshold function table for carrying out threshold process use is as follows:
Wherein, wj,kFor the wavelet details coefficient after wavelet decomposition,For treated wavelet details coefficient, β is regulatory factor,
And β is positive number, λ is threshold value, and wherein j indicates that the scale of wavelet decomposition, k are indicated with scale as the j wavelet details coefficient decomposed
Length；
Step 4, according to approximation coefficient C0With hard -threshold treated wavelet details coefficientSignal is reconstructed, is removed
Local discharge signal y (t) after white noise；
Step 5 carries out median filtering to y (t), obtains effective local discharge signal z (t).
2. a kind of power cable partial discharge signal denoising as described in claim 1 and useful signal extracting method, feature
It is: is decomposed using discharge signal of the db6 wavelet basis to acquisition specifically: the 9 of small echo db6 is carried out to local discharge signal
A one-dimensional decomposition of scale, and calculate the one-dimensional decomposition low frequency coefficient C that scale is 90Each scale high frequency wavelet for being 9 to 1 with scale
Detail coefficients wj,k。
3. a kind of power cable partial discharge signal denoising as described in claim 1 and useful signal extracting method, feature
Be: threshold value λ selection method is using fixed threshold method:Wherein, it is the small of j decomposition that σ, which is with scale,
The standard deviation of wave detail coefficients, k is with the length for the wavelet details coefficient that scale is j decomposition.
4. a kind of power cable partial discharge signal denoising as described in claim 1 and useful signal extracting method, feature
Be: the step 5 is 30 to y (t) the filter window width for carrying out median filtering.
5. what it is based on a kind of power cable partial discharge signal denoising described in claim 1 and useful signal extracting method is
System, it is characterised in that: including it is sequentially connected acquisition cable local discharge signal module, using db6 wavelet basis to acquisition
Discharge signal decomposed module, hard -threshold processing is carried out to wavelet coefficient module, according to hard -threshold, that treated is small
Wave system number is reconstructed to obtain the reconstructed module of the local discharge signal y (t) after removing white noise, believe shelf depreciation to signal
Number y (t) carries out the processing module that median filtering obtains effective local discharge signal z (t).
6. a kind of computer readable storage medium, is stored thereon with computer program characterized by comprising the program is located
Perform claim requires a kind of described in any item power cable partial discharge signal denoisings of 1-4 and useful signal to mention when reason device executes
The step of taking method.
7. a kind of power cable partial discharge signal denoising and useful signal extraction system, which is characterized in that including server, institute
Server is stated to include memory, processor and store the computer program that can be run on a memory and on a processor, it is described
Processor realized when executing described program a kind of described in any item power cable partial discharge signal denoisings of claim 1-4 and
The step of useful signal extracting method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811140600.2A CN109239554A (en) | 2018-09-28 | 2018-09-28 | A kind of denoising of power cable partial discharge signal and useful signal extracting method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811140600.2A CN109239554A (en) | 2018-09-28 | 2018-09-28 | A kind of denoising of power cable partial discharge signal and useful signal extracting method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109239554A true CN109239554A (en) | 2019-01-18 |
Family
ID=65057678
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811140600.2A Pending CN109239554A (en) | 2018-09-28 | 2018-09-28 | A kind of denoising of power cable partial discharge signal and useful signal extracting method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109239554A (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110108936A (en) * | 2019-04-30 | 2019-08-09 | 西安西拓电气股份有限公司 | Signal processing method and device |
| CN110118919A (en) * | 2019-06-25 | 2019-08-13 | 武汉伏佳安达电气技术有限公司 | A kind of denoising of high voltage power cable local discharge signal and extracting 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 |
| CN111551832A (en) * | 2020-06-01 | 2020-08-18 | 广西电网有限责任公司南宁供电局 | Method and device for high-precision positioning and noise removal of partial discharge of cable |
| CN111781439A (en) * | 2020-05-28 | 2020-10-16 | 广西电网有限责任公司梧州供电局 | Power cable partial discharge signal detection method and device |
| CN112307997A (en) * | 2020-11-06 | 2021-02-02 | 华北电力大学 | Power signal reconstruction method and system by using main mode decomposition |
| CN112485616A (en) * | 2020-11-27 | 2021-03-12 | 国网北京市电力公司 | Cable insulation aging detection method and device, storage medium and processor |
| CN112924823A (en) * | 2021-01-28 | 2021-06-08 | 国网山东省电力公司淄博供电公司 | Power cable partial discharge quantity measuring method and system |
| CN113517877A (en) * | 2021-04-30 | 2021-10-19 | 华中科技大学 | Steel wire rope online detection signal noise reduction method and system based on generalized morphological filtering |
| CN115389888A (en) * | 2022-10-28 | 2022-11-25 | 山东科华电力技术有限公司 | Partial discharge real-time monitoring system based on high-voltage cable |
| CN115569341A (en) * | 2022-10-20 | 2023-01-06 | 河北盛世博业科技有限公司 | Multi-person collaborative fire-fighting training method and system based on virtual reality |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090012727A1 (en) * | 2005-03-04 | 2009-01-08 | Wah Hoon Siew | Detecting Partial Discharge in High Voltage Cables |
| CN102508076A (en) * | 2011-11-09 | 2012-06-20 | 东北大学 | Fault diagnosis device and method based on multi-agent system and wavelet analysis |
| CN102590716A (en) * | 2012-02-11 | 2012-07-18 | 广东电网公司电力科学研究院 | Power cable partial discharge signal denoising method based on wavelet analysis |
| CN103268630A (en) * | 2013-05-22 | 2013-08-28 | 北京工业大学 | Vessel three-dimensional visualized method based on ultrasonic image in vessel |
| CN103886558A (en) * | 2014-04-02 | 2014-06-25 | 福州大学 | Improved adaptive threshold wavelet denoising algorithm based on LoG operator |
| CN104020402A (en) * | 2014-06-18 | 2014-09-03 | 国网上海市电力公司 | Method for reducing noise of transformer substation partial discharging pulse signals collected through pulse triggering |
| CN104367316A (en) * | 2014-11-13 | 2015-02-25 | 重庆邮电大学 | Electrocardiosignal denoising method based on morphological filtering and lifting wavelet transformation |
| CN105677035A (en) * | 2016-01-26 | 2016-06-15 | 杭州电子科技大学 | EEMD (Ensemble Empirical Mode Decomposition) and wavelet threshold based motor imagery electroencephalogram signal denoising method |
| CN106127154A (en) * | 2016-06-23 | 2016-11-16 | 西安西热节能技术有限公司 | The Wavelet Package Denoising Method of partial discharge radio-frequency signal is extracted from white noise |
| CN106353649A (en) * | 2016-09-18 | 2017-01-25 | 广东电网有限责任公司珠海供电局 | Method for denoising partial discharge signals on basis of lifting wavelet transformation |
| CN107241243A (en) * | 2017-06-07 | 2017-10-10 | 梧州市兴能农业科技有限公司 | Smart home safety monitoring system |
| CN107272066A (en) * | 2017-06-22 | 2017-10-20 | 东华理工大学 | A kind of noisy seismic signal first-arrival traveltime pick-up method and device |
| CN107302230A (en) * | 2017-08-28 | 2017-10-27 | 苏州思创源博电子科技有限公司 | A kind of photovoltaic power generation equipment is incorporated into the power networks optimization method |
-
2018
- 2018-09-28 CN CN201811140600.2A patent/CN109239554A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090012727A1 (en) * | 2005-03-04 | 2009-01-08 | Wah Hoon Siew | Detecting Partial Discharge in High Voltage Cables |
| CN102508076A (en) * | 2011-11-09 | 2012-06-20 | 东北大学 | Fault diagnosis device and method based on multi-agent system and wavelet analysis |
| CN102590716A (en) * | 2012-02-11 | 2012-07-18 | 广东电网公司电力科学研究院 | Power cable partial discharge signal denoising method based on wavelet analysis |
| CN103268630A (en) * | 2013-05-22 | 2013-08-28 | 北京工业大学 | Vessel three-dimensional visualized method based on ultrasonic image in vessel |
| CN103886558A (en) * | 2014-04-02 | 2014-06-25 | 福州大学 | Improved adaptive threshold wavelet denoising algorithm based on LoG operator |
| CN104020402A (en) * | 2014-06-18 | 2014-09-03 | 国网上海市电力公司 | Method for reducing noise of transformer substation partial discharging pulse signals collected through pulse triggering |
| CN104367316A (en) * | 2014-11-13 | 2015-02-25 | 重庆邮电大学 | Electrocardiosignal denoising method based on morphological filtering and lifting wavelet transformation |
| CN105677035A (en) * | 2016-01-26 | 2016-06-15 | 杭州电子科技大学 | EEMD (Ensemble Empirical Mode Decomposition) and wavelet threshold based motor imagery electroencephalogram signal denoising method |
| CN106127154A (en) * | 2016-06-23 | 2016-11-16 | 西安西热节能技术有限公司 | The Wavelet Package Denoising Method of partial discharge radio-frequency signal is extracted from white noise |
| CN106353649A (en) * | 2016-09-18 | 2017-01-25 | 广东电网有限责任公司珠海供电局 | Method for denoising partial discharge signals on basis of lifting wavelet transformation |
| CN107241243A (en) * | 2017-06-07 | 2017-10-10 | 梧州市兴能农业科技有限公司 | Smart home safety monitoring system |
| CN107272066A (en) * | 2017-06-22 | 2017-10-20 | 东华理工大学 | A kind of noisy seismic signal first-arrival traveltime pick-up method and device |
| CN107302230A (en) * | 2017-08-28 | 2017-10-27 | 苏州思创源博电子科技有限公司 | A kind of photovoltaic power generation equipment is incorporated into the power networks optimization method |
Non-Patent Citations (2)
| Title |
|---|
| HAI-JIAN XUE 等: "Gyro Signal De-noising Based on a New Wavelet Threshold Function", 《2012 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND SERVICE SYSTEM》 * |
| 王志立 等: "基于优化小波阈值函数的高压电缆局放信号消噪研究", 《软件导刊》 * |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110108936A (en) * | 2019-04-30 | 2019-08-09 | 西安西拓电气股份有限公司 | Signal processing method and device |
| CN110118919A (en) * | 2019-06-25 | 2019-08-13 | 武汉伏佳安达电气技术有限公司 | A kind of denoising of high voltage power cable local discharge signal and extracting 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 |
| CN111781439A (en) * | 2020-05-28 | 2020-10-16 | 广西电网有限责任公司梧州供电局 | Power cable partial discharge signal detection method and device |
| CN111551832B (en) * | 2020-06-01 | 2023-06-02 | 广西电网有限责任公司南宁供电局 | Cable partial discharge high-precision positioning and noise removing method and device |
| CN111551832A (en) * | 2020-06-01 | 2020-08-18 | 广西电网有限责任公司南宁供电局 | Method and device for high-precision positioning and noise removal of partial discharge of cable |
| CN112307997A (en) * | 2020-11-06 | 2021-02-02 | 华北电力大学 | Power signal reconstruction method and system by using main mode decomposition |
| CN112485616A (en) * | 2020-11-27 | 2021-03-12 | 国网北京市电力公司 | Cable insulation aging detection method and device, storage medium and processor |
| CN112924823B (en) * | 2021-01-28 | 2022-06-17 | 国网山东省电力公司淄博供电公司 | Power cable partial discharge quantity measuring method and system |
| CN112924823A (en) * | 2021-01-28 | 2021-06-08 | 国网山东省电力公司淄博供电公司 | Power cable partial discharge quantity measuring method and system |
| CN113517877A (en) * | 2021-04-30 | 2021-10-19 | 华中科技大学 | Steel wire rope online detection signal noise reduction method and system based on generalized morphological filtering |
| CN115569341A (en) * | 2022-10-20 | 2023-01-06 | 河北盛世博业科技有限公司 | Multi-person collaborative fire-fighting training method and system based on virtual reality |
| CN115569341B (en) * | 2022-10-20 | 2023-08-25 | 河北盛世博业科技有限公司 | Multi-person collaborative fire-fighting training method and system based on virtual reality |
| CN115389888A (en) * | 2022-10-28 | 2022-11-25 | 山东科华电力技术有限公司 | Partial discharge real-time monitoring system based on high-voltage cable |
| CN115389888B (en) * | 2022-10-28 | 2023-01-31 | 山东科华电力技术有限公司 | Partial discharge real-time monitoring system based on high-voltage cable |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109239554A (en) | A kind of denoising of power cable partial discharge signal and useful signal extracting method and system | |
| WO2023216553A1 (en) | Multi-fault diagnosis method for power distribution network, and system | |
| CN103630808B (en) | A kind of partial discharge signal denoising method based on lifting wavelet transform | |
| Wu et al. | Ultra-high-speed directional protection of transmission lines using mathematical morphology | |
| CN103675617A (en) | Anti-interference method for high-frequency partial discharge signal detection | |
| CN113253046B (en) | Cable water tree fault positioning method based on impedance spectroscopy technology | |
| Chang et al. | Denoising of partial discharge signals in wavelet packets domain | |
| CN105116273A (en) | Insulator on-line monitoring system | |
| CN104020402A (en) | Method for reducing noise of transformer substation partial discharging pulse signals collected through pulse triggering | |
| CN113642417B (en) | Denoising method for partial discharge signal of insulated overhead conductor based on improved wavelet algorithm | |
| CN110912091A (en) | Single-ended traveling wave ultra-high speed protection system and method for flexible direct current transmission line | |
| CN113466634B (en) | Ground fault waveform identification method based on fault indicator | |
| CN105205736A (en) | Rapid detection method for power load abnormal data based on empirical mode decomposition | |
| Cao et al. | Speeded‐up robust features based single‐ended travelling wave fault location: a practical case study in Yunnan power grid of China | |
| CN108802175A (en) | A kind of Pulsed eddy current testing signal de-noising method based on EMD | |
| CN115469179A (en) | Submarine cable defect positioning method, device, storage medium and system | |
| CN110609088A (en) | Post insulator fault identification method and device | |
| CN111323681B (en) | Cable insulation monitoring method and system based on high-voltage power frequency and low-voltage ultralow frequency | |
| Wang et al. | A Denoising Method for Cable Partial Discharge Signals Based on Image Information Entropy and Multivariate Variational Mode Decomposition | |
| CN109635781B (en) | Digital signal coarse data detection and correction method and system based on wavelet transformation | |
| CN117949782A (en) | Multi-sensor-based intelligent positioning method and system for power transmission line faults | |
| Madhu et al. | A novel algorithm for denoising of simulated partial discharge signals using adaptive wavelet thresholding methods | |
| Hassen et al. | Power cable network topology reconstruction using multi-carrier reflectometry for fault detection and location in live smart grids | |
| CN113419139B (en) | High-resistance grounding fault positioning method and related device for small-resistance grounding system | |
| CN112034253B (en) | MOA online monitoring method |
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 | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 250101 f1-a203, Qilu Software Park, Jinan hi tech Development Zone, Shandong Province Applicant after: Conway Communication Technology Co.,Ltd. Address before: 250101 f1-a203, Qilu Software Park, Jinan hi tech Development Zone, Shandong Province Applicant before: SHANDONG KANGWEI COMMUNICATION TECHNOLOGY Co.,Ltd. |
|
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190118 |