CN113109705B - GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points - Google Patents
GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points Download PDFInfo
- Publication number
- CN113109705B CN113109705B CN202110402210.3A CN202110402210A CN113109705B CN 113109705 B CN113109705 B CN 113109705B CN 202110402210 A CN202110402210 A CN 202110402210A CN 113109705 B CN113109705 B CN 113109705B
- Authority
- CN
- China
- Prior art keywords
- microphone
- frequency
- resonance spectrum
- amplitude
- noise
- 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.)
- Active
Links
Images
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
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
Abstract
The invention discloses a GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points, belonging to the technical field of GIS fault detection, and the method comprises the method of claims 1-7; the GIS mechanical resonance spectrum analysis method based on different resonance point sensitivity analyses combines the quality factor and the sensitivity analysis method of the microphone and analyzes the sound source characteristics by using the generated resonance spectrum, thereby not only quantifying the detection result and avoiding the defects of roughness and low precision of the traditional methods such as hand touch, ear smell and the like of operation maintenance personnel, but also improving the scientificity of the test result and being beneficial to the maintenance and safe operation of GIS equipment.
Description
Technical Field
The invention belongs to the technical field of GIS fault detection, and particularly relates to a GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points.
Background
Along with the rapid development of national social economy, the power demand is continuously increased, the voltage level is continuously improved, and GIS (Gas-Insulated Switchgear) has remarkable advantages in the aspects of reliability, safety, miniaturization, occupied area and the like, so that the GIS is rapidly popularized and applied. And (4) a mechanical structure barrier inside the GIS.
GIS equipment is when carrying out mechanical motion, because there is the defect in the equipment inside can produce except the vibration of normal behavior, GIS equipment adopts totally closed structure moreover, and the structure is complicated, in case break down, can not in time fix a position the trouble, also be difficult to make correct processing, will be complicated, contain numerous electrical equipment, in equipment capital construction, operation, maintenance in-process, partial equipment has the condition of vibration abnormal sound, noise increase, the reason that produces the noise probably is that the vibration event of discharge nature trouble and some mechanicals leads to the trouble further to enlarge. Therefore, it is very important to analyze the mechanical resonance of the GIS device.
At present, no clear analysis method for mechanical resonance of GIS equipment in a transformer substation exists. The mechanical vibration and noise of the GIS equipment are sensed roughly by a first-line operation maintenance personnel through a touch and ear-smell method, and accurate analysis cannot be carried out, which is a leak of safe operation of the equipment and influences the operation safety of the equipment.
Disclosure of Invention
The invention aims to provide a GIS mechanical resonance spectrum analysis method based on different resonance point sensitivity analysis, which can accurately analyze the acquired data, provide systematic and scientific test results for operation and maintenance personnel, discover various defects of equipment in time, ensure the safe and stable operation of GIS equipment, realize high-efficiency maintenance and effectively solve the problems in the background technology.
The method comprises the steps of firstly fitting signals collected by each microphone unit into a single output signal, processing the single output signal to obtain the relation between the amplitude and the frequency in a frequency domain, combining the sensitivity analysis of a quality factor, arranging the sensitivity and the serial number of the frequency points of the microphone and generating a three-dimensional resonance spectrum according to the change rule along with time, and then analyzing the noise and sound source characteristics of the GIS equipment, including the sound source frequency, the sound source number and the sound source azimuth angle by using the spectrum.
In order to achieve the purpose, the invention provides the following technical scheme: a GIS mechanical resonance spectrum analysis method based on different resonance point sensitivity analysis comprises the following steps:
the method comprises the following steps:
collecting GIS equipment noise signals by using a microphone array, fitting the signals collected by each microphone unit into a single output signal, and converting the output signal from a time domain to a frequency domain to obtain a relation between a signal amplitude and a frequency;
constructing quality factor functions related to different resonant frequencies by using a quality factor formula based on the frequency curve;
carrying out sensitivity analysis on the constructed function, and investigating the influence of the resonance frequency change of the microphone on the quality factor;
and generating a three-dimensional resonance spectrum by using the result obtained by sensitivity analysis in combination with the microphone frequency point sequence number and the change rule along with time, and analyzing the noise source characteristics of the GIS equipment by using the resonance spectrum, thereby discovering the defects of the GIS equipment.
Optionally, the specific process of converting the noise signal collected by each microphone unit into a single output signal is as follows:
assuming that a microphone array comprises n microphone units, D sound source signals exist in a space, and a noise signal acquired by each microphone unit is as follows:
wherein，XkRepresenting GIS equipment noise signals collected by a microphone unit with the sequence number k, j representing the number of GIS equipment noise sources, gkjThe amplitude attenuation factor, s, of the jth noise source signal collected by the microphone unit with the sequence number kjRepresenting the jth noise source signal, τkjRepresenting the time difference between the arrival of the jth noise source signal at the microphone element with sequence number k and the arrival at the reference element, nk(t) represents invalid noise collected by a microphone unit with the serial number k; and at time t, the signal collected by the microphone array composed of n microphone units can be represented as:
fitting the signals collected by the next n-1 microphone units to the signals collected by the reference microphone unit to obtain output signals X (t):
X(t)＝α2X2(t)+…+αnXn(t) (3)
wherein alpha isiIs the weight of the ith microphone.
Optionally, the specific process of solving the quality factor is as follows:
processing and analyzing the original time domain output signals of the microphone array to obtain an amplitude-frequency characteristic curve of a frequency domain, and solving the quality factors of different resonance points of each microphone by using the obtained amplitude-frequency characteristic curve, wherein the calculation formula of the quality factors is as follows:
wherein, ω is0Is the resonant frequency, omega1And omega2Respectively on the curves representing the amplitude-frequency characteristics
Two frequency values at amplitude, where A0Representing the amplitude at the resonant frequency;
(1) the microphone array is composed of a plurality of microphone units, and the microphones comprise different resonant frequencies;
(2) converting the noise signal collected by the microphone array to obtain an amplitude-frequency characteristic curve, and setting the resonant frequency of the ith microphone as omega0And reading the amplitude A at the resonant frequency point on the amplitude-frequency characteristic curve0；
(3) Reading omega0Around a point and corresponding to an amplitude of
At two frequency values omega1And ω2And calculating the absolute value | ω of the two frequency differences1-ω2|；
(4) Substituting the parameters into a calculation formula of the quality factor to obtain the resonance frequency omega0Quality factor Q of microphonei。
Optionally, the specific process of performing sensitivity analysis on the quality factor is as follows:
s1: fitting the previously obtained quality factor data to a continuous quality factor curve Q (omega)0)；
S2: using the quality factor curve Q (ω) of step S10) Performing sensitivity analysis and generating sensitivity curve
Namely:
optionally, the generating a three-dimensional resonance spectrum by using the result obtained by the sensitivity analysis in combination with the microphone frequency point sequence number and the change rule along with time, and analyzing the noise source characteristics of the GIS equipment by using the three-dimensional resonance spectrum includes:
generating a resonance spectrum according to the sensitivity analysis result and the change of the microphone frequency point serial numbers, and selecting a three-dimensional resonance spectrum consisting of time, sensitivity and the microphone frequency point serial numbers as an optimal analysis resonance spectrum;
analyzing the noise source characteristics of the GIS equipment by using the resonance spectrum;
the sound source characteristics comprise sound source frequency, the number of sound sources and sound source azimuth angles.
Compared with the prior art, the invention has the beneficial effects that:
firstly, noise signals collected by microphone arrays at different resonance points are combined with a sensitivity analysis method to obtain different resonance point frequencies omega0As an element parameter, the quality factor of the microphone is analyzed, then a resonance spectrum is generated, and the sound source characteristics of the GIS equipment noise are analyzed, so that the defects of roughness and low precision of the traditional method are avoided, the systematicness and the scientificity of the test result are improved, the purpose of finding the equipment defects is achieved, and the GIS equipment maintenance and the safe operation are facilitated.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a schematic diagram of the principle of detecting GIS device noise by a microphone array;
FIG. 3 is a schematic diagram of a resonance spectrum;
fig. 4 is a schematic diagram illustrating the number of sound sources.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Firstly, a hardware facility for GIS mechanical resonance spectrum analysis is erected in a mode shown in fig. 2, and comprises a microphone array consisting of microphones with different resonance frequencies, a signal conditioning unit, a multi-channel synchronous data acquisition card and a terminal computer, wherein the microphone array is assumed to be arranged around equipment and connected with the acquisition card, and the acquisition card transmits output to the computer for storing and processing acquired noise signals.
Secondly, an analysis method for analyzing a resonance spectrum of a GIS machine based on different resonance point sensitivities, as shown in fig. 1, includes the following steps:
collecting GIS equipment noise signals by using a microphone array, fitting the signals collected by each microphone unit into a single output signal, and converting the output signal from a time domain to a frequency domain to obtain a relation between a signal amplitude and a frequency;
constructing quality factor functions related to different resonant frequencies by using a quality factor formula based on the frequency curve;
carrying out sensitivity analysis on the constructed function, and investigating the influence of the resonance frequency change of the microphone on the quality factor;
and generating a three-dimensional resonance spectrum by using the result obtained by sensitivity analysis in combination with the frequency point sequence number of the microphone and the change rule along with time, and analyzing the noise sound source characteristics of the GIS equipment by using the resonance spectrum, thereby discovering the defects of the GIS equipment.
Specifically, the specific process of converting the noise signals collected by each microphone unit into a single output signal is as follows:
assuming that a microphone array comprises n microphone units, D sound source signals exist in a space, and a noise signal acquired by each microphone unit is as follows:
wherein, XkRepresenting GIS equipment noise signals collected by a microphone unit with the sequence number k, j representing the number of GIS equipment noise sources, gkjThe amplitude attenuation factor, s, of the jth noise source signal collected by the microphone unit with the sequence number kjRepresenting the jth noise source signal, τkjRepresenting the time difference between the arrival of the jth noise source signal at the microphone element with sequence number k and the arrival at the reference element, nk(t) represents invalid noise collected by a microphone unit with the serial number k; and at time t, the signal collected by the microphone array composed of n microphone units can be represented as:
fitting the signals collected by the next n-1 microphone units to the signals collected by the reference microphone unit to obtain output signals X (t):
X(t)＝α2X2(t)+…+αnXn(t) (3)
wherein alpha isiIs the weight of the ith microphone.
Specifically, the specific process of the figure of merit calculation is as follows:
processing and analyzing the original time domain output signals of the microphone array to obtain an amplitude-frequency characteristic curve of a frequency domain, and solving the quality factors of different resonance points of each microphone by using the obtained amplitude-frequency characteristic curve, wherein the calculation formula of the quality factors is as follows:
wherein, ω is0Is the resonant frequency, omega1And omega2Respectively on the curves representing the amplitude-frequency characteristics
Two frequency values at amplitude, where A0Representing the amplitude at the resonant frequency;
(1) the microphone array is composed of a plurality of microphone units, and the microphones comprise different resonant frequencies;
(2) converting the noise signal collected by the microphone array to obtain an amplitude-frequency characteristic curve, and setting the resonant frequency of the ith microphone as omega0And reading the amplitude A at the resonant frequency point on the amplitude-frequency characteristic curve0；
(3) Reading omega0Around a point and corresponding to an amplitude of
At two frequency values omega1And ω2And calculating the absolute value | ω of the two frequency differences1-ω2|；
(4) Substituting the parameters into a calculation formula of the quality factor to obtain the resonance frequency omega0Quality factor Q of microphonei。
Specifically, the specific process of performing sensitivity analysis on the quality factor is as follows:
s1: fitting the previously obtained quality factor data to a continuous quality factor curve Q (omega)0)；
Wherein curve Q (ω)0) Establishing a plane rectangular coordinate system by taking the resonant frequency as a horizontal axis and the quality factor as a vertical axis;
s2: using the quality factor curve Q (ω) of step S10) Performing sensitivity analysis to generate sensitivity curve
The network sensitivity refers to the sensitivity of a network function to element parameters in the network, the network function in the method refers to the quality factor of the microphone, and the resonant frequency influencing the quality factor is used as the element parameters; the method selects relative sensitivity to express the quality factor to the element parameter omega0The relative sensitivity is defined as the ratio of the relative variation of the generalized network function to the relative variation of the element parameter, and the following formula is a representation of the relative sensitivity:
specifically, the method for analyzing the noise source characteristics of the GIS equipment by using the three-dimensional resonance spectrum generated by the result obtained by the sensitivity analysis in combination with the microphone frequency point serial number and the change rule along with time includes:
generating a resonance spectrum according to the sensitivity analysis result and the change of the microphone frequency point serial numbers, and selecting a three-dimensional resonance spectrum consisting of time, sensitivity and the microphone frequency point serial numbers as an optimal analysis resonance spectrum; as shown in fig. 3, a three-dimensional resonance spectrum is generated for the z-axis according to the arrangement of the microphone frequency point sequence numbers as the x-axis, the time parameter as the y-axis and the change rule of the sensitivity.
Analyzing the noise source characteristics of the GIS equipment by using the resonance spectrum;
the sound source characteristics comprise sound source frequency, the number of sound sources and sound source azimuth angles.
As shown in fig. 4, the method for determining the number of sound sources includes the following steps:
step 1: analyzing the relation between the serial numbers and the sensitivity of the microphone units with different resonant frequencies by utilizing a resonance spectrum;
step 2: setting a threshold value to judge the sensitivity, paying attention to the projection of the three-dimensional resonance spectrum on a plane formed by the sensitivity and the microphone serial number, wherein the microphone serial number corresponding to the intersection point of the threshold value on the two-dimensional spectrum is n1,n2If the sensitivity is greater than the threshold, it can be determined that the frequency is [ f ] based on the number and the resonance frequency of the microphone1，f2]GIS equipment sound source signals; if the sensitivity is less than the threshold, it is considered to be a useless noise signal.
The analysis method of the sound source azimuth angle comprises the following calculation formula:
assuming that θ is the sound source incident angle, d is the microphone element spacing, and v represents the sound velocity, the time delays of the two microphone elements are:
thus, can obtain
By Δ t ═ t/fsT represents a time delay sampling point, fsSampling frequency is represented
The azimuth of the sound source can be estimated.
According to the GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points, firstly, noise signals of equipment are collected based on the microphone array, the noise signals collected by the microphone array are processed to obtain quality factors of the resonance points, and sensitivity analysis is carried out on the quality factors, so that not only is the detection result quantized, but also the noise detection level of the equipment can be improved, the equipment state is evaluated more effectively, and the operation maintenance level is improved.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. A GIS mechanical resonance spectrum analysis method based on different resonance point sensitivity analysis is characterized by comprising the following steps:
collecting GIS equipment noise signals by using a microphone array, fitting the signals collected by each microphone unit into a single output signal, and converting the output signal from a time domain to a frequency domain to obtain a relation between a signal amplitude and a frequency;
constructing quality factor functions related to different resonant frequencies by using a quality factor formula based on the frequency curve;
carrying out sensitivity analysis on the constructed function, and investigating the influence of the resonance frequency change of the microphone on the quality factor;
generating a three-dimensional resonance spectrum by using a result obtained by sensitivity analysis in combination with the frequency point sequence number of the microphone and the change rule along with time, and analyzing the noise source characteristics of the GIS equipment by using the resonance spectrum, thereby discovering the defects of the GIS equipment;
the specific process of solving the quality factor is as follows:
processing and analyzing the original time domain output signals of the microphone array to obtain an amplitude-frequency characteristic curve of a frequency domain, and solving the quality factors of different resonance points of each microphone by using the obtained amplitude-frequency characteristic curve, wherein the calculation formula of the quality factors is as follows:
wherein, ω is0Is the resonant frequency, omega1And omega2Respectively on the curves representing the amplitude-frequency characteristics
Two frequency values at amplitude, where A0Representing the amplitude at the resonant frequency;
(1) the microphone array is composed of a plurality of microphone units, and the microphones comprise different resonance frequencies;
(2) converting the noise signal collected by the microphone array to obtain an amplitude-frequency characteristic curve, and setting the resonant frequency of the ith microphone as omega0And reading the amplitude A at the resonant frequency point on the amplitude-frequency characteristic curve0；
(3) Around the read point and corresponding amplitude of
At two frequency values omega1And ω2And calculating the absolute value | ω of the two frequency differences1-ω2|；
(4) Substituting the parameters into a calculation formula of the quality factor to obtain the resonance frequency omega0Quality factor Q of microphonei；
The specific process of sensitivity analysis of the quality factor comprises the following steps:
s1: fitting the previously obtained quality factor data to a continuous quality factor curve Q (omega)0)；
S2: using the quality factor curve Q (ω) of step S10) Performing sensitivity analysis and generating sensitivity curve
2. The GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points as claimed in claim 1, wherein the specific process of converting the noise signals collected by each microphone unit into a single output signal is as follows:
assuming that there are D sound source signals in a space including n microphone elements in the microphone array, the noise signal collected by each microphone element is:
wherein, XkRepresenting GIS equipment noise signals collected by a microphone unit with the sequence number k, j representing the number of GIS equipment noise sources, gkjThe amplitude attenuation factor, s, of the jth noise source signal collected by the microphone unit with the sequence number kjRepresenting the jth noise source signal, τkjRepresenting the time difference between the arrival of the jth noise source signal at the microphone element with sequence number k and the arrival at the reference element, nk(t) represents invalid noise collected by a microphone unit with the serial number k; and at time t, the signal collected by the microphone array composed of n microphone units can be represented as:
fitting the signals collected by the next n-1 microphone units to the signals collected by the reference microphone unit to obtain output signals X (t):
X(t)＝α2X2(t)+…+αnXn(t)
wherein alpha isiIs the weight of the ith microphone.
3. The GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points as claimed in claim 1, wherein the method for generating the three-dimensional resonance spectrum by using the result obtained by the sensitivity analysis in combination with the frequency point sequence number of the microphone and the change rule along with time and analyzing the noise source characteristics of the GIS equipment by using the three-dimensional resonance spectrum comprises the following steps:
generating a resonance spectrum according to the sensitivity analysis result and the change of the microphone frequency point serial numbers, and selecting a three-dimensional resonance spectrum consisting of time, sensitivity and the microphone frequency point serial numbers as an optimal analysis resonance spectrum;
analyzing the noise source characteristics of the GIS equipment by using the resonance spectrum;
the sound source characteristics comprise sound source frequency, the number of sound sources and sound source azimuth angles.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110402210.3A CN113109705B (en) | 2021-04-14 | 2021-04-14 | GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110402210.3A CN113109705B (en) | 2021-04-14 | 2021-04-14 | GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113109705A CN113109705A (en) | 2021-07-13 |
| CN113109705B true CN113109705B (en) | 2022-05-27 |
Family
ID=76717235
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110402210.3A Active CN113109705B (en) | 2021-04-14 | 2021-04-14 | GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113109705B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201540349U (en) * | 2009-09-01 | 2010-08-04 | 江苏省电力公司常州供电公司 | Ultra-high frequency signal sensor for partial discharge detection |
| AU2013206304A1 (en) * | 2008-07-16 | 2013-07-04 | Rosemount Measurement Limited | Detector and methods of detecting |
| CN105136280A (en) * | 2015-09-18 | 2015-12-09 | 华晨汽车集团控股有限公司 | System and method for testing single noise quality in multi-source noise environment |
| CN105445629A (en) * | 2015-11-30 | 2016-03-30 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | AC voltage withstand test method for 500kV GIS |
| CN105628419A (en) * | 2015-12-18 | 2016-06-01 | 国网安徽省电力公司 | System and method of diagnosing GIS (Gas Insulated Switchgear) mechanical defects based on independent component analysis denoising |
| CN105629100A (en) * | 2015-12-18 | 2016-06-01 | 国网安徽省电力公司合肥供电公司 | System and method of diagnosing GIS (Gas Insulated Switchgear) mechanical defects based on abnormal vibration analysis |
| CN107702908A (en) * | 2017-10-12 | 2018-02-16 | 国网山东省电力公司莱芜供电公司 | GIS mechanical oscillation signal Time-Frequency Analysis Methods based on VMD self adapting morphologies |
| CN109839263A (en) * | 2019-02-26 | 2019-06-04 | 北京航空航天大学 | A kind of GIS feature extraction and mechanical defect diagnostic method based on vibration information |
| CN109916612A (en) * | 2019-03-28 | 2019-06-21 | 国网宁夏电力有限公司电力科学研究院 | GIS mechanical breakdown electrification detection system based on acoustics imaging |
| CN111580050A (en) * | 2020-05-28 | 2020-08-25 | 国网上海市电力公司 | Device and method for identifying position of abnormal sound source of GIS (geographic information System) equipment |
| CN112540272A (en) * | 2020-11-23 | 2021-03-23 | 重庆大学 | System and method for simulating mechanical vibration abnormal sound defect of GIS (gas insulated switchgear) |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2326234B (en) * | 1997-06-12 | 2001-06-06 | British Aerospace | A vibration damper assembly for a vibrating structure gyroscope resonator |
| EP1027723B1 (en) * | 1997-10-14 | 2009-06-17 | Patterning Technologies Limited | Method of forming an electric capacitor |
-
2021
- 2021-04-14 CN CN202110402210.3A patent/CN113109705B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2013206304A1 (en) * | 2008-07-16 | 2013-07-04 | Rosemount Measurement Limited | Detector and methods of detecting |
| CN201540349U (en) * | 2009-09-01 | 2010-08-04 | 江苏省电力公司常州供电公司 | Ultra-high frequency signal sensor for partial discharge detection |
| CN105136280A (en) * | 2015-09-18 | 2015-12-09 | 华晨汽车集团控股有限公司 | System and method for testing single noise quality in multi-source noise environment |
| CN105445629A (en) * | 2015-11-30 | 2016-03-30 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | AC voltage withstand test method for 500kV GIS |
| CN105628419A (en) * | 2015-12-18 | 2016-06-01 | 国网安徽省电力公司 | System and method of diagnosing GIS (Gas Insulated Switchgear) mechanical defects based on independent component analysis denoising |
| CN105629100A (en) * | 2015-12-18 | 2016-06-01 | 国网安徽省电力公司合肥供电公司 | System and method of diagnosing GIS (Gas Insulated Switchgear) mechanical defects based on abnormal vibration analysis |
| CN107702908A (en) * | 2017-10-12 | 2018-02-16 | 国网山东省电力公司莱芜供电公司 | GIS mechanical oscillation signal Time-Frequency Analysis Methods based on VMD self adapting morphologies |
| CN109839263A (en) * | 2019-02-26 | 2019-06-04 | 北京航空航天大学 | A kind of GIS feature extraction and mechanical defect diagnostic method based on vibration information |
| CN109916612A (en) * | 2019-03-28 | 2019-06-21 | 国网宁夏电力有限公司电力科学研究院 | GIS mechanical breakdown electrification detection system based on acoustics imaging |
| CN111580050A (en) * | 2020-05-28 | 2020-08-25 | 国网上海市电力公司 | Device and method for identifying position of abnormal sound source of GIS (geographic information System) equipment |
| CN112540272A (en) * | 2020-11-23 | 2021-03-23 | 重庆大学 | System and method for simulating mechanical vibration abnormal sound defect of GIS (gas insulated switchgear) |
Non-Patent Citations (4)
| Title |
|---|
| Designs synthesis of resonant fault current limiter for voltage sag mitigation and current limitation;C.S. Chang;《2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings》;20000127;全文 * |
| Locating Switched Capacitor Using Wavelet Transform and Hybrid Principal Component Analysis Network;Ying-Yi Hong;《IEEE Transactions on Power Delivery》;20070402;全文 * |
| 基于光声光谱法的SF6气体分解组分在线监测技术;张英;《高电压技术》;20160913;全文 * |
| 基于光纤声波传感的超高灵敏度光声光谱微量气体检测;陈珂;《光学学报》;20180116;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113109705A (en) | 2021-07-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Brown et al. | Characterizing and quantifying noise in PMU data | |
| CN113267330B (en) | GIS equipment mechanical fault detection system and method based on acoustic imaging | |
| CN109872323A (en) | The defects of insulator detection method and device of transmission line of electricity | |
| CN101629995A (en) | Detection method of phasor measurement unit PMU | |
| CN109375060A (en) | A kind of distribution network failure wave-form similarity calculation method | |
| CN104914405A (en) | Detection method and device | |
| CN114325250B (en) | Partial discharge detection device and method integrating positioning detection and map detection functions | |
| You et al. | Ring-down oscillation mode identification using multivariate empirical mode decomposition | |
| Delle Femine et al. | Power-quality monitoring instrument with FPGA transducer compensation | |
| Lin et al. | Optimized denoising method for weak acoustic emission signal in partial discharge detection | |
| CN114218778A (en) | Method and device for analyzing sonic boom test data | |
| Ovcharuk et al. | Features of registration of acoustic signals in multichannel acoustic-emission systems | |
| CN113109705B (en) | GIS mechanical resonance spectrum analysis method based on sensitivity analysis of different resonance points | |
| CN104991119B (en) | A kind of coprime spectral analysis method and its device for eliminating pseudo- peak, composing leakage effect | |
| CN107132500B (en) | A kind of synchronous phasor measurement unit on-line calibration method and apparatus | |
| KR101807280B1 (en) | Apparatus and Method for detecting accidents in Power Systems using PMU signal | |
| CN102722630B (en) | Cable terminal ultrahigh frequency radiation characteristic simulation method and cable terminal ultrahigh frequency radiation characteristic simulation system | |
| Wang et al. | A method of modal parameter identification for wind turbine blade based on binocular dynamic photogrammetry | |
| CN114201991A (en) | Partial discharge signal detection method and system based on ultrasonic sensor array | |
| CN113866493A (en) | Method for measuring voltage fluctuation and flicker caused by wind power | |
| CN107121624A (en) | Partial discharge detection multi-drop arrangement and localization method based on moment method | |
| CN105520738A (en) | Finger force harmony test analysis instrument based on crossed quantitative recursive computation | |
| Koo et al. | A possible application of the PD detection technique using electro-optic Pockels cell with nonlinear characteristic analysis on the PD signals | |
| Qian et al. | Acoustic Imaging Detection Technology of Electrical Equipment Based on Passive Sound Source Ranging | |
| Lasalvia et al. | Intelligent acoustic detection of defective porcelain station post insulators |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |