CN104765971A - Crosslinked polyethylene high-voltage cable partial discharge feature extraction method - Google Patents
Crosslinked polyethylene high-voltage cable partial discharge feature extraction method Download PDFInfo
- Publication number
- CN104765971A CN104765971A CN201510193461.XA CN201510193461A CN104765971A CN 104765971 A CN104765971 A CN 104765971A CN 201510193461 A CN201510193461 A CN 201510193461A CN 104765971 A CN104765971 A CN 104765971A
- Authority
- CN
- China
- Prior art keywords
- wavelet
- wavelet packet
- partial discharge
- packet
- coefficient
- 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.)
- Granted
Links
- 238000000605 extraction Methods 0.000 title claims abstract description 23
- 229920003020 cross-linked polyethylene Polymers 0.000 title claims abstract description 10
- 239000004703 cross-linked polyethylene Substances 0.000 title claims abstract description 10
- 238000000034 method Methods 0.000 claims abstract description 30
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 15
- 238000001514 detection method Methods 0.000 claims abstract description 6
- 239000011159 matrix material Substances 0.000 claims description 9
- 238000001914 filtration Methods 0.000 claims description 7
- 239000002184 metal Substances 0.000 abstract 1
- 238000009413 insulation Methods 0.000 description 4
- 206010038743 Restlessness Diseases 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 230000013011 mating Effects 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Landscapes
- Testing Relating To Insulation (AREA)
Abstract
The invention provides a crosslinked polyethylene high-voltage cable partial discharge feature extraction method, and belongs to the technical field of high-voltage cables. The high-voltage cable partial discharge feature extraction method aims to solve the problem that partial discharge feature extraction is inaccurate in an existing high-voltage cable partial detection method. According to the method, firstly, metal sheath grounding current signals generated when crosslinked polyethylene high-voltage cable partial discharge happens is acquired through a high-frequency current mutual inductor; then, current signals are converted into digital signals; next, wavelet packet decomposition is conducted on the digital signals, modulus maxima extraction and singularity detection are sequentially conducted on decomposed wavelet packet node coefficients or reconstructed signals, and wavelet packet energy index entropy calculation is conducted; finally, a discharge feature curve is drawn according to the operation result, and crosslinked polyethylene high-voltage cable partial discharge feature extraction is achieved. By means of the crosslinked polyethylene high-voltage cable partial discharge feature extraction method, the cable partial discharge feature extraction accuracy can be improved, and technical support is provided for next high-voltage cable partial discharge.
Description
Technical field
The invention belongs to high-tension cable technical field.
Background technology
Shelf depreciation (the partial discharge that crosslinked polyethylene high voltage power cable (under be called for short cable) is inner, PD) electric discharge phenomena occurred in certain region in cable insulation structure are referred to, this electric discharge can cause damage to the insulation system of this district cable, if shelf depreciation (lower abbreviation office puts) long-term existence, just may cause the decline of cable major insulation electrical strength under certain condition, time serious, cause cable major insulation penetrability to puncture.At present for the online acquisition method mainly broadband Electromagnetic coupling method of high-tension cable Partial discharge signal, cable cover(ing) pulse current over the ground when utilizing HF current transformer (HFCT) collection office to put generation.But research shows, because cable tunnel inner cable One's name is legion exists strong electromagnetic, in addition not the mating of HF current transformer and apparatus measures interface impedance, the pulsed current signal feature that cable partial discharge is formed often is submerged in ground unrest, even if it is still not obvious to put feature by its office of software and hardware filtering, if rely on merely doubtful Partial discharge signal and judge whether its discharge parameter is positioned at specialized range and decides it and whether belong to cable partial discharge, just may cause the generation of failing to judge and judging by accident.
Summary of the invention
The object of the invention is to solve current high-tension cable office to put the office existed in detection method and put the inaccurate problem of feature extraction, provide and a kind of the method that feature extracts is put to high-tension cable office.
Step of the present invention is:
A, signal are changed: utilize HFCT sensor gather cable cover(ing) ground current signal and be converted to voltage signal, utilize analog to digital converter that voltage signal is converted to 16 position digital signals;
B, filtering: utilize digital band-pass filter to carry out filtering to 16 position digital signals obtained, obtain 16 position digital signals of frequency range at 0.5 ~ 20MHz;
C, DB4 WAVELET PACKET DECOMPOSITION is carried out to 16 position digital signals, the different frequency component of 16 position digital signals is correspondingly distributed in different wavelet packet yardsticks, then the wavelet packet node coefficient obtained WAVELET PACKET DECOMPOSITION or reconstruction signal carry out office and put feature information extraction;
The process that feature information extraction is put in office is:
1. modulus maximum extraction and Singularity Detection are carried out to wavelet packet node coefficient or reconstruction signal: the maximum value each wavelet packet node coefficient or reconstruction signal being asked for mould, modulus maximum point in each wavelet scale converges as singular point, utilizes threshold method to filter out wavelet packet node coefficient or the reconstruction signal of Singularity Degree exception;
2. the computing of energy index entropy is carried out to the wavelet packet coefficient of Singularity Degree exception or reconstruction signal:
Discrete wavelet packet node coefficient or reconstruction signal matrix are
,
for measured signal raw data length,
dupper definition slip data window, window width is
, slippage factor is
, this slip data window is expressed as:
In above formula,
,
,
d i,j (k)for wavelet packet node (
i, j) the
kindividual discrete wavelet packet coefficient or reconstruction signal,
kfor element position variable in discrete wavelet packet coefficient or reconstruction signal matrix,
nfor the Decomposition order upper limit,
mfor wavelet-packet energy Exponential Entropy length; Then the process of wavelet-packet energy Exponential Entropy computing is:
e(
m)=
for signal with
centered by moment, window width is
slip data window in yardstick
ion
the energy of individual wavelet packet coefficient group or reconstruction signal and, wherein
for
moment time slip-window
interior yardstick
iupper
jthe energy of individual node wavelet packet coefficient or reconstruction signal and; Order
and
, then
the wavelet-packet energy Exponential Entropy in moment is:
In above formula,
efor the truth of a matter of right logarithmic function
D, make slippage factor
, at discrete wavelet packet node coefficient or reconstruction signal matrix be
upper mobile time slip-window
, repeat step 3, until
, finally obtain a wavelet-packet energy Exponential Entropy array
, take time as horizontal ordinate, wavelet-packet energy Exponential Entropy is ordinate, draws cable partial discharge characteristic curve.
The present invention in the calculating process of wavelet-packet energy Exponential Entropy, the WAVELET PACKET DECOMPOSITION number of plies
iselection range be [2,4].
Slip data window width of the present invention
wand slippage factor
concrete establishing method be: pulse width is put to typical cable office and adds up, order
w maxrepresent cable partial discharge pulse width maximal value, order
w mincharacteristic pulse width minimum is put in expression office, then slip data window width
walternative condition be
; Slippage factor
alternative condition is
.
The present invention proposes a kind of high-tension cable office based on wavelet-packet energy Exponential Entropy theory and puts feature extracting method, utilizes the method can improve the extraction accuracy of cable partial discharge feature, and the identification of putting for next step high-tension cable office provides technical support.Good effect of the present invention:
(1) the wavelet-packet energy Exponential Entropy that the present invention proposes possesses the dual characteristics of the multiple dimensioned resolved analysis of wavelet packet and Exponential Entropy statistics, organically blending to Wavelet Analysis Theory and entropy statistical theory, the temporal variations that the computing of energy index entropy can portray sheath ground current signal frequency when cable partial discharge occurs further is carried out to wavelet packet node coefficient or reconstruction signal, improves the extraction accuracy to cable partial discharge feature.
(2) the wavelet-packet energy Exponential Entropy that the present invention proposes carries out the computing of energy index entropy to wavelet packet node coefficient or reconstruction signal, thus effectively evaded the problem with the undefined value in logarithm definition information entropy and null value, overcomes the deficiency of Shannon entropy.
Accompanying drawing explanation
Fig. 1 adopts method of the present invention, the raw voltage signals oscillogram comprising cable partial discharge feature collected when sample frequency is 100MHz;
Fig. 2 is that signature waveform figure is put in the office utilizing the inventive method to extract from Fig. 1 raw voltage signals;
Fig. 3 is the raw voltage signals oscillogram not comprising cable partial discharge feature collected when sample frequency is 100MHz;
Fig. 4 utilizes the inventive method to carry out to Fig. 3 original signal the oscillogram that the computing of wavelet-packet energy Exponential Entropy obtains.
Embodiment
Step of the present invention is:
A, signal are changed: utilize HFCT sensor gather cable cover(ing) ground current signal and be converted to voltage signal, utilize analog to digital converter that voltage signal is converted to 16 position digital signals;
B, filtering: utilize digital band-pass filter to carry out filtering to 16 position digital signals obtained, obtain 16 position digital signals of frequency range at 0.5 ~ 20MHz;
C, DB4 WAVELET PACKET DECOMPOSITION (WAVELET PACKET DECOMPOSITION number of plies selection range see in claims 2) is carried out to described 16 position digital signals, the different frequency component of 16 position digital signals is made correspondingly to be distributed in different wavelet packet yardsticks (such as, through 4 layers of WAVELET PACKET DECOMPOSITION, original signal is assigned to corresponding 16 frequency bands: (0 ~ 1.25MHz), (1.25 ~ 2.50 MHz), (2.50 ~ 3.75 MHz), (3.75 ~ 5.00 MHz), (5.00 ~ 6.25 MHz), (6.25 ~ 7.50 MHz), (7.50 ~ 8.75 MHz), (8.75 ~ 10.00 MHz), (10.00 ~ 11.25 MHz), (11.25 ~ 12.50 MHz), (12.50 ~ 13.75 MHz), (13.75 ~ 15.00 MHz), (15.00 ~ 16.25 MHz), (16.25 ~ 17.50 MHz), (17.50 ~ 18.75 MHz), (18.75 ~ 20.00 MHz)), the wavelet packet node coefficient obtained WAVELET PACKET DECOMPOSITION again or reconstruction signal carry out office puts feature information extraction,
The process that feature information extraction is put in office is:
1. modulus maximum extraction and Singularity Detection are carried out to wavelet packet node coefficient or reconstruction signal: the maximum value each wavelet packet node coefficient or reconstruction signal being asked for mould, modulus maximum point in each wavelet scale converges as singular point, utilizes threshold method to filter out wavelet packet node coefficient or the reconstruction signal of Singularity Degree exception;
2. the computing of energy index entropy is carried out to the wavelet packet coefficient of Singularity Degree exception or reconstruction signal:
Discrete wavelet packet node coefficient or reconstruction signal matrix are
,
for measured signal raw data length,
dupper definition slip data window, window width is
, slippage factor is
, this slip data window is expressed as:
In above formula,
,
,
d i,j (k)for wavelet packet node (
i, j) the
kindividual discrete wavelet packet coefficient or reconstruction signal,
kfor element position variable in discrete wavelet packet coefficient or reconstruction signal matrix,
nfor the Decomposition order upper limit,
mfor wavelet-packet energy Exponential Entropy length; Then the process of wavelet-packet energy Exponential Entropy computing is:
e(
m)=
for signal with
centered by moment, window width is
slip data window in yardstick
ion
the energy of individual wavelet packet coefficient group or reconstruction signal and, wherein
for
moment time slip-window
interior yardstick
iupper
jthe energy of individual node wavelet packet coefficient or reconstruction signal and; Order
and
, then
the wavelet-packet energy Exponential Entropy in moment is:
In above formula,
efor the truth of a matter of right logarithmic function
D, make slippage factor
, at discrete wavelet packet node coefficient or reconstruction signal matrix be
upper mobile time slip-window
, repeat step 3, until
, finally obtain a wavelet-packet energy Exponential Entropy array
, take time as horizontal ordinate, wavelet-packet energy Exponential Entropy is ordinate, draws cable partial discharge characteristic curve.
The present invention in the calculating process of wavelet-packet energy Exponential Entropy, the WAVELET PACKET DECOMPOSITION number of plies
iselection range be [2,4].
Slip data window width of the present invention
wand slippage factor
concrete establishing method be: pulse width is put to typical cable office and adds up, order
w maxrepresent cable partial discharge pulse width maximal value, order
w mincharacteristic pulse width minimum is put in expression office, then slip data window width
walternative condition be
; Slippage factor
alternative condition is
.
Utilize office provided by the invention to put feature extracting method and cable partial discharge feature extraction is carried out to the raw voltage signals comprising cable partial discharge feature in Fig. 1, the cable partial discharge feature extracted as shown in Figure 2, as shown in Figure 2: at moment 11.5ms, wavelet-packet energy Exponential Entropy has occurred that amplitude is the pulse (concrete waveform is shown in ' M ' type ripple of arrow indication in Fig. 2) of 0.0065pu, and cable partial discharge event occurs moment 11.5ms really, so prove that office provided by the invention puts feature extracting method and not only can the office of extraction put signature waveform but also can indicate its generation moment.
Utilize office provided by the invention to put feature extracting method and cable partial discharge feature extraction is carried out to the raw voltage signals not comprising cable partial discharge feature in Fig. 3, obtain operation result as shown in Figure 4, as shown in Figure 4: owing to not comprising cable partial discharge feature in raw voltage signals, so in Fig. 4 there is not obvious pulse waveform in wavelet packet energy index entropy, wavelet-packet energy Exponential Entropy numerical value is constant=0.4169pu substantially, proving that in Fig. 3, raw voltage signals does not exist cable partial discharge feature, there is not cable partial discharge event in this period.
Claims (3)
1. a crosslinked polyethylene high-tension cable local discharge characteristic extracting method, is characterized in that:
A, signal are changed: utilize HFCT sensor gather cable cover(ing) ground current signal and be converted to voltage signal, utilize analog to digital converter that voltage signal is converted to 16 position digital signals;
B, filtering: utilize digital band-pass filter to carry out filtering to 16 position digital signals obtained, obtain 16 position digital signals of frequency range at 0.5 ~ 20MHz;
C, DB4 WAVELET PACKET DECOMPOSITION is carried out to 16 position digital signals, the different frequency component of 16 position digital signals is correspondingly distributed in different wavelet packet yardsticks, then the wavelet packet node coefficient obtained WAVELET PACKET DECOMPOSITION or reconstruction signal carry out office and put feature information extraction;
The process that feature information extraction is put in office is:
1. modulus maximum extraction and Singularity Detection are carried out to wavelet packet node coefficient or reconstruction signal: the maximum value each wavelet packet node coefficient or reconstruction signal being asked for mould, modulus maximum point in each wavelet scale converges as singular point, utilizes threshold method to filter out wavelet packet node coefficient or the reconstruction signal of Singularity Degree exception;
2. the computing of energy index entropy is carried out to the wavelet packet coefficient of Singularity Degree exception or reconstruction signal:
Discrete wavelet packet node coefficient or reconstruction signal matrix are
,
for measured signal raw data length,
dupper definition slip data window, window width is
, slippage factor is
, this slip data window is expressed as:
In above formula,
,
,
d i,j (k)for wavelet packet node (
i, j) the
kindividual discrete wavelet packet coefficient or reconstruction signal,
kfor element position variable in discrete wavelet packet coefficient or reconstruction signal matrix,
nfor the Decomposition order upper limit,
mfor wavelet-packet energy Exponential Entropy length; Then the process of wavelet-packet energy Exponential Entropy computing is:
e(
m)=
for signal with
centered by moment, window width is
slip data window in yardstick
ion
the energy of individual wavelet packet coefficient group or reconstruction signal and, wherein
for
moment time slip-window
interior yardstick
iupper
jthe energy of individual node wavelet packet coefficient or reconstruction signal and; Order
and
, then
the wavelet-packet energy Exponential Entropy in moment is:
In above formula,
efor the truth of a matter of right logarithmic function
D, make slippage factor
, at discrete wavelet packet node coefficient or reconstruction signal matrix be
upper mobile time slip-window
, repeat step 3, until
, finally obtain a wavelet-packet energy Exponential Entropy array
, take time as horizontal ordinate, wavelet-packet energy Exponential Entropy is ordinate, draws cable partial discharge characteristic curve.
2. crosslinked polyethylene high-tension cable local discharge characteristic extracting method according to claim 1, is characterized in that: in the calculating process of wavelet-packet energy Exponential Entropy, the WAVELET PACKET DECOMPOSITION number of plies
iselection range be [2,4].
3. crosslinked polyethylene high-tension cable local discharge characteristic extracting method according to claim 1, is characterized in that: described slip data window width
wand slippage factor
concrete establishing method be: pulse width is put to typical cable office and adds up, order
w maxrepresent cable partial discharge pulse width maximal value, order
w mincharacteristic pulse width minimum is put in expression office, then slip data window width
walternative condition be
; Slippage factor
alternative condition is
.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510193461.XA CN104765971B (en) | 2015-04-23 | 2015-04-23 | A kind of crosslinked polyethylene high-tension cable local discharge characteristic extracting method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510193461.XA CN104765971B (en) | 2015-04-23 | 2015-04-23 | A kind of crosslinked polyethylene high-tension cable local discharge characteristic extracting method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104765971A true CN104765971A (en) | 2015-07-08 |
| CN104765971B CN104765971B (en) | 2017-11-10 |
Family
ID=53647796
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510193461.XA Expired - Fee Related CN104765971B (en) | 2015-04-23 | 2015-04-23 | A kind of crosslinked polyethylene high-tension cable local discharge characteristic extracting method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104765971B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105203937A (en) * | 2015-10-28 | 2015-12-30 | 国网江西省电力公司南昌供电分公司 | Internal discharge mode recognition method and fault diagnosis system for transformer |
| CN105676079A (en) * | 2015-12-18 | 2016-06-15 | 长沙理工大学 | Cable partial discharge source positioning method based on online decision rule |
| 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 |
| CN105974283A (en) * | 2016-05-18 | 2016-09-28 | 东北电力大学 | Cable partial discharge feature extraction method based on wavelet packet survival index singular entropy |
| CN106771928A (en) * | 2017-01-10 | 2017-05-31 | 河南理工大学 | A kind of online pick-up method of partial discharge pulse's initial time |
| CN107632240A (en) * | 2017-09-08 | 2018-01-26 | 河北金能电力科技股份有限公司 | Aerial cable current data analysis method, health status monitoring method and system |
| CN107942214A (en) * | 2017-12-04 | 2018-04-20 | 囯网河北省电力有限公司电力科学研究院 | A kind of feature extracting method of transformer partial discharge signal, device |
| CN110945370A (en) * | 2017-07-24 | 2020-03-31 | 赖茵豪森机械制造公司 | Method and test device for measuring partial discharge pulses of shielded cable |
-
2015
- 2015-04-23 CN CN201510193461.XA patent/CN104765971B/en not_active Expired - Fee Related
Non-Patent Citations (6)
| Title |
|---|
| M.JEEVAN等: ""GAIT RECOGNITION BASED ON GAIT PAL AND PAL ENTROPY IMAGE"", 《2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING(ICIP)》 * |
| NIKHIL R. PAL等: ""Entropy: A New Definition and its Applications"", 《IEEE TRANSACTIONS ON SYSTEMS,MAN,AND CYBERNETICS》 * |
| 唐炬等: ""基于最优小波包变换与核主分量分析的局部放电信号特征提取"", 《电工技术学报》 * |
| 李辉峰等: "《地震勘探新技术》", 31 December 2009, 石油工业出版社 * |
| 罗新等: ""基于小波包分解的XLPE配电电缆局部放电波形特征提取与识别"", 《高压电器》 * |
| 陈继开: ""基于小波熵电力系统暂态信号特征提取及识别方法研究"", 《万方数据企业知识服务平台》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105203937A (en) * | 2015-10-28 | 2015-12-30 | 国网江西省电力公司南昌供电分公司 | Internal discharge mode recognition method and fault diagnosis system for transformer |
| CN105676079A (en) * | 2015-12-18 | 2016-06-15 | 长沙理工大学 | Cable partial discharge source positioning method based on online decision rule |
| CN105676079B (en) * | 2015-12-18 | 2019-02-01 | 长沙理工大学 | Cable local discharge source positioning based on on-line decision rule |
| 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 |
| CN105974283A (en) * | 2016-05-18 | 2016-09-28 | 东北电力大学 | Cable partial discharge feature extraction method based on wavelet packet survival index singular entropy |
| CN106771928A (en) * | 2017-01-10 | 2017-05-31 | 河南理工大学 | A kind of online pick-up method of partial discharge pulse's initial time |
| CN110945370A (en) * | 2017-07-24 | 2020-03-31 | 赖茵豪森机械制造公司 | Method and test device for measuring partial discharge pulses of shielded cable |
| CN110945370B (en) * | 2017-07-24 | 2022-05-31 | 赖茵豪森机械制造公司 | Method and test device for measuring partial discharge pulses of shielded cable |
| CN107632240A (en) * | 2017-09-08 | 2018-01-26 | 河北金能电力科技股份有限公司 | Aerial cable current data analysis method, health status monitoring method and system |
| CN107942214A (en) * | 2017-12-04 | 2018-04-20 | 囯网河北省电力有限公司电力科学研究院 | A kind of feature extracting method of transformer partial discharge signal, device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104765971B (en) | 2017-11-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104765971A (en) | Crosslinked polyethylene high-voltage cable partial discharge feature extraction method | |
| CN103257306B (en) | Method for diagnosing direct current partial discharging insulation state of converter transformer and measurement system | |
| CN202583398U (en) | Mixing technology based partial discharge signal collection apparatus | |
| CN109799434A (en) | PD Pattern Recognition system and method | |
| CN106646165B (en) | GIS internal insulation defect classification and positioning method and system | |
| CN103969556A (en) | Insulation electrified detection device for cable accessories | |
| CN106249185B (en) | Impedance matching unit, system and method for calibrating high-frequency current sensor | |
| CN105137310A (en) | GIS partial discharge on-line detection system and method | |
| CN104569764A (en) | Live detection system for creeping discharge of composite apparatus and method thereof | |
| CN204945316U (en) | The harvester of live detection electromagnetic interference (EMI) is put in office of transformer station | |
| CN102721854B (en) | Power network overvoltage signal detection method and system | |
| CN106249054B (en) | Capacitance type voltage transformer and integrated detection sensor thereof | |
| CN203732677U (en) | Insulation state detection apparatus of all-insulation tubular busbar | |
| CN204666772U (en) | A kind of shelf depreciation In-circiut tester | |
| CN105116306B (en) | The acquisition method and device of substation's partial discharge electrification detection electromagnetic interference | |
| CN103983371A (en) | Method for measuring operating temperature of transformer lead connector based on surface acoustic waves | |
| CN105486991B (en) | A kind of partial discharge pulse's extracting method | |
| CN210923880U (en) | AD (analog-to-digital) conversion circuit for cable online detection | |
| CN112198400A (en) | High-voltage switch cabinet partial discharge online detection method based on spectrum sensing characteristic | |
| CN204256113U (en) | Partial discharge pulse's detection system | |
| CN114722882B (en) | Method and system for processing pulse electric field data | |
| CN204903662U (en) | Signal enhancement type pressure wave method model cable space charge test system | |
| CN105974283B (en) | Cable partial discharge feature extraction method based on wavelet packet survival index singular entropy | |
| CN107515364A (en) | A kind of radio interference time domain measurement device and method based on conductor corona electric discharge | |
| CN113533904A (en) | Method, device, equipment and medium for detecting high-resistance grounding fault of power distribution network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| EXSB | Decision made by sipo to initiate substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20171110 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |