CN114034990A - High-voltage electrical equipment online diagnosis system and method - Google Patents
High-voltage electrical equipment online diagnosis system and method Download PDFInfo
- Publication number
- CN114034990A CN114034990A CN202111234137.XA CN202111234137A CN114034990A CN 114034990 A CN114034990 A CN 114034990A CN 202111234137 A CN202111234137 A CN 202111234137A CN 114034990 A CN114034990 A CN 114034990A
- Authority
- CN
- China
- Prior art keywords
- electrical equipment
- voltage electrical
- partial discharge
- voltage
- signal
- 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
- 238000003745 diagnosis Methods 0.000 title claims abstract description 22
- 238000000034 method Methods 0.000 title claims abstract description 13
- 238000009413 insulation Methods 0.000 claims abstract description 67
- 238000011156 evaluation Methods 0.000 claims abstract description 35
- 238000012545 processing Methods 0.000 claims abstract description 20
- 230000036541 health Effects 0.000 claims abstract description 17
- 238000001514 detection method Methods 0.000 claims abstract description 8
- 238000012544 monitoring process Methods 0.000 claims abstract description 8
- 208000028659 discharge Diseases 0.000 claims description 145
- 239000012774 insulation material Substances 0.000 claims description 10
- 239000000523 sample Substances 0.000 claims description 10
- 239000003990 capacitor Substances 0.000 claims description 9
- 230000008878 coupling Effects 0.000 claims description 9
- 238000010168 coupling process Methods 0.000 claims description 9
- 238000005859 coupling reaction Methods 0.000 claims description 9
- 230000003862 health status Effects 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 4
- 238000013473 artificial intelligence Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 claims description 3
- 238000013135 deep learning Methods 0.000 claims description 3
- 238000010183 spectrum analysis Methods 0.000 claims description 3
- 230000026676 system process Effects 0.000 claims description 3
- 238000004804 winding Methods 0.000 claims description 3
- 230000008033 biological extinction Effects 0.000 claims description 2
- 238000012360 testing method Methods 0.000 description 15
- 230000015556 catabolic process Effects 0.000 description 10
- 230000032683 aging Effects 0.000 description 6
- 239000011810 insulating material Substances 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000010292 electrical insulation Methods 0.000 description 4
- 238000006731 degradation reaction Methods 0.000 description 3
- 230000006866 deterioration Effects 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- 230000007423 decrease Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 230000005684 electric field Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 238000004171 remote diagnosis Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 230000000638 stimulation Effects 0.000 description 1
- 238000003878 thermal aging Methods 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
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
- G01R31/12—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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Testing Relating To Insulation (AREA)
Abstract
The invention relates to a high-voltage electrical equipment on-line diagnosis system and a method, comprising a signal acquisition system, a signal processing system and a signal evaluation system; the signal acquisition system is used for acquiring partial discharge signals of the high-voltage electrical equipment in real time and forming a signal package file; the signal processing system is used for identifying, reading and processing fault characteristic signal files in the signal package file to form a data file; the signal evaluation system is used for further analyzing and calculating the data file to obtain the partial discharge parameters of the high-voltage electrical equipment, comparing the partial discharge parameters of the high-voltage electrical equipment with historical partial discharge parameters of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment and obtaining an evaluation result. The online diagnosis system and method for the high-voltage electrical equipment realize sensitive and effective insulation detection and real-time monitoring of the health state of the equipment.
Description
Technical Field
The invention relates to the technical field of high-voltage electrical insulation performance operation and maintenance, in particular to an online diagnosis system and method for high-voltage electrical equipment.
Background
The insulation material of the high-voltage electrical equipment is subjected to electrical aging, thermal aging, mechanical aging and environmental aging, so that the insulation strength of the insulation material is gradually reduced and finally broken down, and the insulation material is subjected to short-circuit fault after being treated in time, seriously damages the equipment and even expands into a serious accident. For this reason, the industry has attracted a high level of attention to electrical insulation. The traditional method is mainly used for detecting the insulation performance of high-voltage electrical equipment through a test. At present, the mature applications are off-line tests and detections, such as: insulation test, dielectric loss test, direct current withstand voltage test, alternating current withstand voltage test, off-line partial discharge test and the like. There are also some power supply devices, in order to realize insulation fault protection for on-line devices as much as possible, the insulation fault of the device is protected as much as possible by measuring leakage current or installing leakage current protection, grounding protection, short-circuit protection and the like, but the protection and measurement are macroscopic and stable serious insulation faults for electrical insulation faults and cannot have any response to early-stage abnormity of insulation aging. Until the insulation is damaged to the extent of the protective action, with the result that the equipment is severely damaged and cannot continue to operate by simple treatment, the production system develops basically into an accident.
Disclosure of Invention
Therefore, it is necessary to provide a system and a method for online diagnosis of high-voltage electrical equipment, which can implement sensitive and effective insulation detection and real-time monitoring of the health status of the equipment, in order to solve the problems that the insulation protection of the existing online high-voltage electrical equipment cannot implement sensitive and effective insulation detection and the offline test cannot real-time monitor the health status of the equipment.
In order to achieve the above purpose, the invention provides the following technical scheme:
an online diagnosis system for high-voltage electrical equipment comprises a signal acquisition system, a signal processing system and a signal evaluation system;
the signal acquisition system is used for acquiring partial discharge signals of the high-voltage electrical equipment in real time and forming a signal package file; the signal processing system is used for identifying, reading and processing fault characteristic signal files in the signal package file to form a data file;
the signal evaluation system is used for further analyzing and calculating the data file to obtain the partial discharge parameters of the high-voltage electrical equipment, comparing the partial discharge parameters of the high-voltage electrical equipment with historical partial discharge parameters of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment and obtaining an evaluation result.
Further, the partial discharge signal of the high-voltage electrical equipment is an insulation characteristic waveform of the high-voltage electrical equipment.
Further, the high-voltage electrical equipment insulation characteristic waveform is a superposition of a fundamental wave waveform and an partial discharge pulse waveform of the high-voltage electrical equipment voltage.
Further, the partial discharge pulse waveform of the high-voltage electrical equipment comprises a partial discharge voltage waveform measured by a coupling capacitor, a partial discharge current waveform measured by a current transformer or a partial discharge vibration waveform measured by a vibration probe, and the coupling capacitor, the current transformer and the vibration probe are all arranged at an inlet terminal, a bus or a switch of the high-voltage electrical equipment.
Further, the signal processing system processes the fault characteristic signal file in the signal package file and comprises digital display, waveform display, FFT analysis, wavelet analysis, fundamental wave spectrum analysis, decibel analysis, storage and sampling rate adjustment.
Further, the signal processing system obtains a purified partial discharge pulse waveform by calling Matlab software to perform wavelet analysis on the partial discharge pulse waveform of the high-voltage electrical equipment; and superposing the purified partial discharge pulse waveform with the fundamental wave waveform of the voltage of the high-voltage electrical equipment as a comparison reference.
Further, the fault characteristic signal of the high-voltage electrical equipment comprises a partial discharge pulse signal of the high-voltage electrical equipment, the phase of a power supply base voltage of the high-voltage electrical equipment and the break time of the pulse signal of the high-voltage electrical equipment.
Further, the signal evaluation system is used for comparing the initial voltage Ui and the extinguishing voltage Ue of the partial discharge of the high-voltage electrical equipment with historical parameters of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment, and obtaining an evaluation result.
Further, the evaluation result evaluates the health condition grade of the insulation according to the percentage of the phase interruption time t of the initial voltage Ui and the extinguishing voltage Ue of the partial discharge of the high-voltage electrical equipment to the voltage cycle time.
Further, the health state of the insulation performance of the high-voltage electrical equipment comprises an initial stage, a stable stage, a starting partial discharge stage, an obvious partial discharge stage and an insulation failure stage, wherein the partial discharge quantity of the obvious partial discharge stage is set to be different insulation failure alarm intervals according to different insulation materials.
Further, the starting voltage Ui and the extinguishing voltage Ue of the partial discharge pulse waveform of the high-voltage electrical equipment are obtained by monitoring the time of the pulse on a winding power frequency voltage curve to calculate the extinguishing time of the partial discharge pulse at each cycle.
Further, for parameters with ready-made metrics, the parameters are based on ready-made evaluation criteria; for parameters without the existing measurement standard, a reference database is determined according to the corresponding historical parameter change trend of the equipment during evaluation, the basic recommended alarm value and the shutdown overhaul value are set by using an offline detection result during first commissioning, and then the recommended alarm value and the shutdown overhaul value can be improved and improved by using artificial intelligence deep learning.
An online diagnosis method for high-voltage electrical equipment comprises the following steps:
1. collecting partial discharge signals of high-voltage electrical equipment and forming a signal package file;
2. identifying, reading and processing fault characteristic signal files in the signal package file to form a data file and establish a database;
3. and further analyzing and calculating the database file to obtain the partial discharge parameters of the high-voltage electrical equipment, comparing the partial discharge parameters of the high-voltage electrical equipment with historical partial discharge parameters of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment, and obtaining an evaluation result.
The high-voltage electrical equipment on-line diagnosis system and method provided by the invention are based on the on-line partial discharge monitoring and diagnosis of the high-voltage electrical equipment, and based on the premise of not influencing the structures of the existing system and equipment, the purposes of remote diagnosis and predictive maintenance of the insulation performance of the high-voltage electrical equipment are realized, and the problem that the existing off-line test and on-line protection cannot solve is well solved, so that the insulation state of the equipment is ensured to be known and controllable.
Drawings
FIG. 1 is an equivalent circuit diagram of an insulation partial discharge;
FIG. 2 is a graph of partial discharge voltage versus maximum charge;
FIG. 3 is a schematic diagram of a partial discharge pulse waveform acquisition mode of the high-voltage electrical equipment;
fig. 4 is a schematic diagram of a partial discharge pulse waveform of the high-voltage electrical equipment after Matlab software wavelet analysis;
fig. 5 is a partial discharge trend diagram of the high-voltage electrical equipment.
In fig. 1, C1 is the equivalent capacitance of a normal insulated vertical plane; CV is the equivalent capacitance to the vertical plane of the air bubble and Ca is the capacitance of the air bubble.
In fig. 3, the solid line indicates the loop of the partial discharge voltage waveform measured by the coupling capacitor, the dotted line indicates the loop of the partial discharge vibration waveform measured by the vibration probe, and the chain line indicates the loop of the partial discharge current waveform measured by the current transformer.
In fig. 4, t is a time interval between the partial discharge extinction voltage Ue and the initial voltage Ui in the phase of the fundamental voltage waveform.
In fig. 5, 1 is an initial stage; 2 is a stabilization stage; 3, starting a partial discharge stage; 4 is an obvious partial discharge stage; and 5, an insulation failure stage.
Detailed Description
The invention is described in further detail below with reference to the figures and the detailed description.
Referring to fig. 1, if air bubbles exist in the insulating material inside the high-voltage electrical equipment, the air bubbles are broken down at first as the voltage increases, because the insulating strength of air is lower than that of vacuum, resulting in discharge inside the high-voltage electrical equipment. With the stimulation of various aging factors, the insulation strength of the insulation material is gradually reduced, the discharge part is gradually enlarged, and finally, insulation breakdown is developed. Therefore, the partial discharge amount and the discharge position of the high-voltage electrical equipment are monitored early, and the high-voltage electrical equipment is maintained and processed in time, so that accidents are avoided. However, when the discharge starts, the discharge amount is small, and the measurement and positioning are difficult.
In actual production, the dielectric constants and the insulating strengths of different insulating media are different. For the same vertical line, voltage breakdown can not occur under normal insulation strength, once a material with lower insulation strength is mixed, the overall insulation strength of the same vertical line is reduced due to the reduction of the voltage shared by the material, and therefore the voltage breakdown phenomenon, namely partial discharge, occurs at the weak part of the insulation strength.
In addition, because the amplitude of the alternating voltage is changed in a waveform manner, under the condition that the reduction of the insulation strength is not serious, a process that partial discharge is intermittent pulse discharge occurs, the partial discharge occurs firstly near the wave crest and the wave trough of the voltage, and the partial discharge returns to the vicinity of the zero point and stops.
The insulation state of a high-voltage electrical system is generally expressed by the following characteristic variables: firstly, local discharge amount and discharge position; ② dielectric loss factor (tg δ); leakage current; and fourthly, the capacitance variation of the equipment.
The partial discharge of solid insulating material for electric equipment is usually at the position of dielectric insulation unevenness. Breakdown occurs due to overlarge local electric field intensity, and the breakdown is expressed as local breakdown at the early stage of the fault, so that the breakdown of the whole insulation structure cannot be caused. This discharge is represented by a pulse having a duration of less than 1 mus, and typically the frequency of the partial discharge is around 30Mz (the specific frequency is related to the insulating material). The weaker the dielectric strength, the earlier and more severe the discharge at the same operating voltage.
The on-line diagnosis of insulation faults is to diagnose the insulation health degree by monitoring the intensity of partial discharge.
Referring to fig. 2, the degradation of the insulation layer internal aging can be detected by a conventional off-line partial discharge test (corona test). The evaluation criteria are: maximum discharge QmThe curve increases slowly with increasing voltage. For the same electrical equipment, under the same power supply voltage and in the same time interval, the more the number of partial discharge pulses is, the larger the amplitude of the discharge pulses is, and the discharge electric quantity Q ismThe larger. Starting voltage V of partial dischargeiDirect reflection insulationDielectric strength of the material, slope K of the curveiMaximum discharge Q, depending on the degree of deterioration of the insulating materialmRelated to the capacitance of the insulating material.
Is the local maximum discharge QmThe corresponding voltage. However, this method is easy to implement in an off-line partial discharge test, and is not suitable for an on-line partial discharge detection technique.
In the online partial discharge test, the typical partial discharge fault characteristics are as follows: starting voltage UiThe magnitude of the extinguishing voltage Ue decreases with the severity of the insulation degradation, and the magnitude of the extinguishing voltage Ue also decreases with the severity of the insulation degradation. However, since the partial discharge signal is a small signal of an ultra high frequency, it is easily interfered by external noise, and it is difficult to detect and identify the partial discharge signal. Therefore, although the theory of the insulation off-line diagnosis is mature, the insulation on-line diagnosis is difficult to popularize and apply.
The invention provides an on-line diagnosis system for high-voltage electrical equipment, which comprises a signal acquisition system, a fault characteristic signal lifting and analyzing system and a state evaluation and prediction system, wherein the signal acquisition system is used for acquiring a fault characteristic signal;
the signal acquisition system is used for acquiring partial discharge signals of the high-voltage electrical equipment in real time and forming a signal package file; the signal processing system is used for identifying, reading and processing fault characteristic signal files in the signal package file to form a data file and establish a database;
the signal evaluation system is used for further analyzing and calculating the database file to obtain the partial discharge parameters of the high-voltage electrical equipment, comparing the partial discharge parameters of the high-voltage electrical equipment with historical partial discharge parameters of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment and obtaining an evaluation result.
Further, the partial discharge signal of the high-voltage electrical equipment is an insulation characteristic waveform of the high-voltage electrical equipment.
Further, the high-voltage electrical equipment insulation characteristic waveform is a superposition of a fundamental wave waveform and an partial discharge pulse waveform of the high-voltage electrical equipment voltage.
In view of the particularity of the partial discharge signal, the partial discharge signal of the high-voltage electrical equipment is acquired by a sensor with high frequency, high saturation response capability, high resolution and high sensitivity.
Further, referring to fig. 3, the partial discharge pulse waveform of the high voltage electrical equipment includes a partial discharge voltage waveform measured by the coupling capacitor, a partial discharge current waveform measured by the current transformer, or a partial discharge vibration waveform measured by the vibration probe. The circuit entering the signal acquisition system comprises the following three circuits: the solid line indicates the loop of the partial discharge voltage waveform measured by the coupling capacitor, the dotted line indicates the loop of the partial discharge vibration waveform measured by the vibration probe, and the chain line indicates the loop of the partial discharge current waveform measured by the current transformer.
The partial discharge voltage waveform measured by the coupling capacitor, the partial discharge current waveform measured by the current transformer and the partial discharge vibration waveform measured by the vibration probe are directly filtered without wavelet analysis, and the obtained partial discharge pulse waveform is disordered due to the existence of white noise and contains a waveform with certain regular characteristics. The partial discharge voltage waveform measured by the coupling capacitor is directly filtered without wavelet analysis, and the obtained partial discharge pulse waveform is disordered due to the existence of white noise and contains a waveform with certain regular characteristics.
Further, the signal processing system processes the fault characteristic signal file in the signal package file and comprises digital display, waveform display, FFT analysis, wavelet analysis, fundamental wave spectrum analysis, decibel analysis, storage and sampling rate adjustment.
Further, referring to fig. 4, the signal processing system obtains a cleaner and more regular waveform by calling Matlab software to perform wavelet analysis on the partial discharge pulse waveform of the high-voltage electrical device; and superposing the purified partial discharge pulse waveform with the fundamental wave waveform of the voltage of the high-voltage electrical equipment as a comparison reference.
Further, the fault characteristic signal of the high-voltage electrical equipment comprises a partial discharge pulse signal of the high-voltage electrical equipment, the phase of a power supply base voltage of the high-voltage electrical equipment and the break time of the pulse signal of the high-voltage electrical equipment.
In combination with the above theoretical analysis, it is known that an electrical insulation fault starts to generate a partial discharge when the applied voltage rises to a certain value, and the partial discharge is increased and the discharge power is increased as the voltage rises or the insulation deteriorates. The discharge power formula is as follows:
in the formula, TrefIs a reference time interval; q. q.siIs a single apparent charge; p is at a selected reference time interval TrefWithin a single apparent charge qiFeeding average pulse power between two ends of the test sample; u. ofiFor a single apparent charge qiCorresponding discharge transient tiThe instantaneous value of the test voltage of (1); i is a natural number.
The general insulation comprehensive judgment standard of the high-voltage alternating-current motor is as follows in the following table 1:
TABLE 1 insulation comprehensive judgment standard for common high-voltage AC motor
In actual production operation, the discharge power is not easy to be measured on line, and the deterioration degree of the insulation strength can be identified according to the components or positions of the pulse waveform of the fundamental wave and the partial discharge for the partial discharge characteristic of the insulation.
Further, the signal evaluation system is used for comparing the pulse position of the partial discharge of the high-voltage electrical equipment with the historical parameters of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment and obtaining an evaluation result.
For example, in the case where the power supply voltage is stable and the partial discharge is not broken down seriously, the relationship between the number of pulses and the time of the power supply fundamental partial discharge is determined, so that the severity of the partial discharge can be monitored by monitoring the starting voltage Ui and the extinguishing voltage Ue of the partial discharge pulse. The diagnosis result can more accurately evaluate the serious degree of the insulation deterioration of the equipment. The dielectric strength given here is only a relative value and must be given an accurate evaluation based on the relevant historical parameters of the equipment.
Further, the starting voltage Ui and the extinguishing voltage Ue of the partial discharge pulse waveform of the high-voltage electrical equipment are obtained by monitoring the time of the pulse on a winding power frequency voltage curve to calculate the extinguishing time of the partial discharge pulse at each cycle.
Further, for parameters with ready-made metrics, the parameters are based on ready-made evaluation criteria; for parameters without ready-made measuring standards, the parameters can be basically defined as equipment characteristic parameters, when evaluation is carried out, a reference database is required to be determined according to the corresponding historical parameter change trend of the equipment, when the equipment is put into operation for the first time, the basic suggested alarm value and the shutdown overhaul value are set by fully utilizing an offline detection result, and subsequently, the key sensitive parameters of the suggested alarm value and the shutdown overhaul value can be perfected and improved by applying artificial intelligence deep learning, so that the evaluation on the health state of the motor is more accurate and effective.
Further, the evaluation result evaluates the health condition grade of the insulation according to the percentage of the phase interruption time t of the initial voltage Ui and the extinguishing voltage Ue of the partial discharge of the high-voltage electrical equipment to the voltage cycle time. Because the insulation materials are different, the evaluation standard is weak and different, the evaluation standard is generally required to be compared with a pressure parameter, the percentage of the insulation materials is generally controlled according to 25% -30%, and the insulation materials with the percentage higher than 25% -30% are qualified.
Referring to fig. 5, the state of health of the insulation performance of the high-voltage electrical equipment is divided into 5 stages, namely, an initial stage 1, a stable stage 2, a starting partial discharge stage 3, an obvious partial discharge stage 4 and an insulation failure stage 5, by the amount of generated partial discharge. Wherein, obviously, the partial discharge number in the partial discharge stage is set to different insulation failure alarm intervals due to different insulation materials.
The invention also provides an online diagnosis method of the high-voltage electrical equipment, which comprises the following steps:
1. collecting partial discharge signals of high-voltage electrical equipment and forming a signal package file;
2. identifying, reading and processing fault characteristic signal files in the signal package file to form a data file and establish a database;
3. and further analyzing and calculating the database file to obtain the partial discharge parameters of the high-voltage electrical equipment, comparing the partial discharge parameters of the high-voltage electrical equipment with historical partial discharge parameters of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment, and obtaining an evaluation result.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (13)
1. The on-line diagnosis system for the high-voltage electrical equipment is characterized by comprising a signal acquisition system, a signal processing system and a signal evaluation system; the signal acquisition system is used for acquiring partial discharge signals of the high-voltage electrical equipment in real time on line and forming a signal package file; the signal processing system is used for identifying, reading and processing fault characteristic signal files in the signal package file to form a data file; the signal evaluation system is used for further analyzing and calculating the data file to obtain the partial discharge parameters of the high-voltage electrical equipment, comparing the partial discharge parameters of the high-voltage electrical equipment with historical partial discharge parameters of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment and obtaining an evaluation result.
2. The system of claim 1, wherein the partial discharge signal of the high-voltage electrical equipment is an insulation characteristic waveform of the high-voltage electrical equipment.
3. The system of claim 2, wherein the high-voltage electrical equipment insulation characteristic waveform is a superposition of a fundamental waveform and a partial discharge pulse waveform of the high-voltage electrical equipment voltage.
4. The system of claim 3, wherein the partial discharge pulse waveform of the high-voltage electrical equipment comprises a partial discharge voltage waveform measured by a coupling capacitor, a partial discharge current waveform measured by a current transformer, or a partial discharge vibration waveform measured by a vibration probe, and the coupling capacitor, the current transformer, and the vibration probe are all disposed at an incoming line terminal, a bus, or a switch of the high-voltage electrical equipment.
5. The system of claim 1, wherein the signal processing system processes the fault signature file in the signal package file including digital display, waveform display, FFT analysis, wavelet analysis, fundamental spectrum analysis, decibel analysis, phase analysis, storage, and sample rate adjustment.
6. The on-line diagnosis system for high-voltage electrical equipment of claim 5, wherein the signal processing system obtains a purified partial discharge pulse waveform by calling Matlab software to perform wavelet analysis on the partial discharge pulse waveform of the high-voltage electrical equipment; and superposing the purified partial discharge pulse waveform with the fundamental wave waveform of the voltage of the high-voltage electrical equipment as a comparison reference.
7. The system of claim 1, wherein the fault signature signal of the high voltage electrical device comprises a partial discharge pulse signal of the high voltage electrical device, a phase of a power supply base voltage of the high voltage electrical device, and a break time of the pulse signal of the high voltage electrical device.
8. The system for online diagnosis of high-voltage electrical equipment according to claim 1, wherein the signal evaluation system is configured to compare the phase of the start voltage Ui and the extinction voltage Ue of the partial discharge of the high-voltage electrical equipment in the fundamental voltage loop with the historical corresponding parameters of the high-voltage electrical equipment, determine the health status of the insulation performance of the high-voltage electrical equipment, and obtain the evaluation result.
9. The system of claim 8, wherein the evaluation result evaluates the insulation health level according to the percentage of the phase interruption time t of the initial voltage Ui and the extinguishing voltage Ue of the partial discharge of the high-voltage electrical equipment to the voltage cycle time.
10. The system of claim 9, wherein the health status of the insulation performance of the high-voltage electrical equipment comprises an initial stage, a stable stage, a starting partial discharge stage, an obvious partial discharge stage and an insulation failure stage, and the partial discharge amount of the obvious partial discharge stage is set to different insulation failure alarm intervals according to different insulation materials.
11. The system for on-line diagnosis of high-voltage electrical equipment according to any one of claims 8 to 10, wherein the starting voltage Ui and the extinguishing voltage Ue of the partial discharge pulse waveform of the high-voltage electrical equipment are obtained by monitoring the phase time of the pulse on the winding power frequency voltage curve to calculate the extinguishing time of the partial discharge pulse at each cycle.
12. The system for on-line diagnosis of high-voltage electrical equipment according to any of claims 8 to 10, characterized in that the parameters for which there are existing metrics are based on existing evaluation criteria; for parameters without the existing measurement standards, a reference database is determined according to the corresponding historical parameter change trend of the equipment during evaluation, a basic recommended alarm value and a shutdown overhaul value are set by using an offline detection result during first operation, and the recommended alarm value and the shutdown overhaul value are improved and improved by subsequently applying artificial intelligence deep learning.
13. An online diagnosis method for high-voltage electrical equipment is characterized by comprising the following steps:
step 1, collecting partial discharge signals of high-voltage electrical equipment and forming a signal package file;
step 2, identifying, reading and processing fault characteristic signal files in the signal package file to form data files and establish a database;
and 3, further analyzing and calculating the database file to obtain a partial discharge parameter of the high-voltage electrical equipment, comparing the partial discharge parameter of the high-voltage electrical equipment with a historical partial discharge parameter of the high-voltage electrical equipment, judging the health state of the insulation performance of the high-voltage electrical equipment, and obtaining an evaluation result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111234137.XA CN114034990A (en) | 2021-10-22 | 2021-10-22 | High-voltage electrical equipment online diagnosis system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111234137.XA CN114034990A (en) | 2021-10-22 | 2021-10-22 | High-voltage electrical equipment online diagnosis system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114034990A true CN114034990A (en) | 2022-02-11 |
Family
ID=80135239
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111234137.XA Pending CN114034990A (en) | 2021-10-22 | 2021-10-22 | High-voltage electrical equipment online diagnosis system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114034990A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116298722A (en) * | 2023-02-07 | 2023-06-23 | 深圳新立图智能科技有限公司 | Aluminum electrolysis cell short-circuit port insulation on-line monitoring method and system based on partial discharge signals |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005156452A (en) * | 2003-11-27 | 2005-06-16 | Tm T & D Kk | Partial discharge diagnosis method for gas insulation electric device |
| JP2011095036A (en) * | 2009-10-28 | 2011-05-12 | Mitsubishi Electric Corp | Partial discharge measuring apparatus |
| CN102221665A (en) * | 2011-03-21 | 2011-10-19 | 江苏省电力公司无锡供电公司 | Power cable partial discharge detection contrast method |
| CN102508135A (en) * | 2011-11-23 | 2012-06-20 | 华南理工大学 | Cable oscillation wave local discharge measuring and positioning system based on cloud computing |
| CN102841296A (en) * | 2012-09-10 | 2012-12-26 | 江苏科技大学 | Online monitoring system and method for partial discharge of intelligent switch cabinet based on ultra-high frequency detection |
| CN103197206A (en) * | 2013-03-12 | 2013-07-10 | 重庆市电力公司电力科学研究院 | Electrical level scanning type ultrahigh frequency partial discharge on-line monitoring system and monitoring method |
| KR101317476B1 (en) * | 2012-05-17 | 2013-10-10 | 한국전기안전공사 | Online system and method for diagnosis of partial discharge on cable |
| CN105486987A (en) * | 2014-09-19 | 2016-04-13 | 国家电网公司 | Partial discharge detection system |
| CN105548844A (en) * | 2016-01-26 | 2016-05-04 | 北京市劳动保护科学研究所 | Partial discharge detection system and method |
| CN105606977A (en) * | 2016-03-11 | 2016-05-25 | 华乘电气科技（上海）股份有限公司 | Partial discharge PRPS atlas identification method and system based on hierarchy rule inference |
| JP2018112452A (en) * | 2017-01-11 | 2018-07-19 | 三菱電機プラントエンジニアリング株式会社 | Device and method for partial discharge monitoring |
| CN108931712A (en) * | 2018-08-07 | 2018-12-04 | 国网河南省电力公司电力科学研究院 | A kind of solid-state insulated switchgear insulation performance appraisal procedure |
| CN109164362A (en) * | 2018-09-25 | 2019-01-08 | 上海交通大学 | A kind of recognition methods and system of direct current cables shelf depreciation defect failure |
| JP2020046202A (en) * | 2018-09-14 | 2020-03-26 | 株式会社東芝 | Partial discharge detection device, partial discharge detection method, partial discharge detection system, and computer program product |
-
2021
- 2021-10-22 CN CN202111234137.XA patent/CN114034990A/en active Pending
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005156452A (en) * | 2003-11-27 | 2005-06-16 | Tm T & D Kk | Partial discharge diagnosis method for gas insulation electric device |
| JP2011095036A (en) * | 2009-10-28 | 2011-05-12 | Mitsubishi Electric Corp | Partial discharge measuring apparatus |
| CN102221665A (en) * | 2011-03-21 | 2011-10-19 | 江苏省电力公司无锡供电公司 | Power cable partial discharge detection contrast method |
| CN102508135A (en) * | 2011-11-23 | 2012-06-20 | 华南理工大学 | Cable oscillation wave local discharge measuring and positioning system based on cloud computing |
| KR101317476B1 (en) * | 2012-05-17 | 2013-10-10 | 한국전기안전공사 | Online system and method for diagnosis of partial discharge on cable |
| CN102841296A (en) * | 2012-09-10 | 2012-12-26 | 江苏科技大学 | Online monitoring system and method for partial discharge of intelligent switch cabinet based on ultra-high frequency detection |
| CN103197206A (en) * | 2013-03-12 | 2013-07-10 | 重庆市电力公司电力科学研究院 | Electrical level scanning type ultrahigh frequency partial discharge on-line monitoring system and monitoring method |
| CN105486987A (en) * | 2014-09-19 | 2016-04-13 | 国家电网公司 | Partial discharge detection system |
| CN105548844A (en) * | 2016-01-26 | 2016-05-04 | 北京市劳动保护科学研究所 | Partial discharge detection system and method |
| CN105606977A (en) * | 2016-03-11 | 2016-05-25 | 华乘电气科技（上海）股份有限公司 | Partial discharge PRPS atlas identification method and system based on hierarchy rule inference |
| JP2018112452A (en) * | 2017-01-11 | 2018-07-19 | 三菱電機プラントエンジニアリング株式会社 | Device and method for partial discharge monitoring |
| CN108931712A (en) * | 2018-08-07 | 2018-12-04 | 国网河南省电力公司电力科学研究院 | A kind of solid-state insulated switchgear insulation performance appraisal procedure |
| JP2020046202A (en) * | 2018-09-14 | 2020-03-26 | 株式会社東芝 | Partial discharge detection device, partial discharge detection method, partial discharge detection system, and computer program product |
| CN109164362A (en) * | 2018-09-25 | 2019-01-08 | 上海交通大学 | A kind of recognition methods and system of direct current cables shelf depreciation defect failure |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116298722A (en) * | 2023-02-07 | 2023-06-23 | 深圳新立图智能科技有限公司 | Aluminum electrolysis cell short-circuit port insulation on-line monitoring method and system based on partial discharge signals |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Stone | A perspective on online partial discharge monitoring for assessment of the condition of rotating machine stator winding insulation | |
| CN102981062B (en) | Insulation detection method for high voltage bushing based on frequency domain dielectric spectroscopy | |
| CN104714155A (en) | Detection and evaluation device and method for partial discharge of direct current XLPE cables | |
| Kim et al. | Assessment of deterioration in epoxy/mica machine insulation | |
| CN102540029B (en) | Method for calculating partial discharge failure probability of oil paper insulating equipment | |
| CN203025310U (en) | High-voltage sleeve insulation detection device based on frequency domain dielectric spectrum | |
| CN106771895A (en) | A kind of cable degradation detecting method based on magnetic field harmonics detection | |
| US6573727B2 (en) | Method and apparatus for evaluation of insulation in variable speed motors | |
| CN114034990A (en) | High-voltage electrical equipment online diagnosis system and method | |
| CN106597148A (en) | Residual voltage monitoring based state monitoring system and method for lightning arrester without serial gap | |
| CN102540030B (en) | Method for diagnosing development speed of partial discharge defect of oil paper insulated equipment | |
| JP3590389B2 (en) | Winding rare short monitor for electrical equipment | |
| RU2744464C1 (en) | Method for determining hazardous areas in the insulation of three-core three-phase cable power lines | |
| JP6164022B2 (en) | Interlayer insulation diagnosis method for winding equipment | |
| CN102288881B (en) | Method for diagnosing severity of discharging shortcoming of oil paper insulation thorn of transformer | |
| RU2724991C1 (en) | Method for determining technical state of insulation of a digital transformer based on partial discharge parameters | |
| CN116699459A (en) | Method and system for detecting grounding state of intelligent end screen grounding device of high-voltage sleeve | |
| CN114252742A (en) | GIS equipment dynamic insulation performance test method and system | |
| Guo | Online diagnosis of power systems insulation condition in wind farms | |
| CN115291013A (en) | Power equipment detection system and method based on artificial intelligence | |
| CN112782545A (en) | Method for testing partial discharge of generator | |
| CN110531238B (en) | GIS insulation degradation detection device and method and GIS insulation degradation diagnosis system | |
| Stone et al. | Comparison of low and high frequency partial discharge measurements on stator windings | |
| Gorgan et al. | Monitoring and Diagnosis of Electrical Equipment Insulation with the Support of Combined Conventional and Alternative Partial Discharge Methods | |
| KR20160093452A (en) | Device for detecting insulation defect of mold transformer and method thereby |
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 |