CN108919068B - Intermittent defect signal identification method for power equipment - Google Patents
Intermittent defect signal identification method for power equipment Download PDFInfo
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- CN108919068B CN108919068B CN201810579726.3A CN201810579726A CN108919068B CN 108919068 B CN108919068 B CN 108919068B CN 201810579726 A CN201810579726 A CN 201810579726A CN 108919068 B CN108919068 B CN 108919068B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1209—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 using acoustic measurements
Abstract
The invention relates to an intermittent defect signal identification method for power equipment. The method is characterized by comprising the following steps: installing a plurality of partial discharge sensors on the power equipment, and receiving partial discharge signals generated inside the power equipment and detected by the partial discharge sensors by using a power equipment partial discharge detection instrument; installing a plurality of noise sensors in the external space of the power equipment, and receiving a noise signal transmitted from the external space and detected by the noise sensors by using a local discharge detection instrument of the power equipment; for each partial discharge sensor, the following steps 1 to 4 are sequentially used for judgment and identification; step 1, analyzing a signal characteristic map; step 2, intermittent analysis; step 3, analyzing the noise sensor; and 4, pulse positioning analysis. The method can comprehensively judge the source of the intermittent signal, effectively distinguish the intermittent defect signal from the external interference signal and improve the reliability of the defect diagnosis of the power equipment.
Description
Technical Field
The invention relates to an intermittent defect signal identification method for power equipment.
Background
The main power transformation equipment such as transformers, GIS and mutual inductors are influenced by factors such as power equipment structures, operation states and external environments, and intermittent defects often occur. Due to the uncertainty of the occurrence time of the defect signal and the uncertainty of the feature representation of the defect in the intermittent defect, it is generally impossible to effectively judge whether the detected signal is from the intermittent defect or from the external disturbance.
Disclosure of Invention
The invention aims to provide a method for identifying intermittent defect signals of power equipment, which can effectively distinguish the intermittent defect signals from external interference signals and improve the reliability of defect diagnosis of the power equipment.
An intermittent defect signal identification method for power equipment is characterized by comprising the following steps:
installing a plurality of partial discharge sensors on the power equipment, and receiving partial discharge signals generated inside the power equipment and detected by the partial discharge sensors by using a power equipment partial discharge detection instrument; installing a plurality of noise sensors in the external space of the power equipment, and receiving a noise signal transmitted from the external space and detected by the noise sensors by using a local discharge detection instrument of the power equipment; for each partial discharge sensor, the following steps 1 to 4 are sequentially used for judgment and identification;
step 1, analyzing a signal characteristic map;
step 2, intermittent analysis;
step 3, analyzing the noise sensor;
and 4, pulse positioning analysis.
Step 1, detecting intermittent signals of the power equipment provided by a partial discharge sensor by using a partial discharge detector of the power equipment to obtain a partial discharge characteristic map; observing the partial discharge characteristic map, and finishing identification if the partial discharge characteristic map is judged to be an interference signal; and if the signal is judged to be a suspected partial discharge signal, continuing to the next step.
Step 2, counting the signal trend of the partial discharge sensor; if the total number of the suspected partial discharge signals is less than M or the average daily number of the suspected partial discharge signals is less than N, judging that the signals detected by the sensor are accidental interference, and finishing identification; otherwise, the next step is continued.
Step 3, calculating the correlation coefficient of the discharge fingerprints of the partial discharge sensor and the adjacent noise sensor, and judging the similarity of signals; if the signal detected by the partial discharge sensor is similar to the signal of the adjacent noise sensor and the signal amplitude is small, judging that the signal detected by the sensor is external interference, and finishing identification; otherwise, continuing the next step;
wherein the discharge fingerprint comprises signal skewness, prominence, asymmetry, correlation coefficient, pulse concentration and dispersion;
the correlation coefficient of the discharge fingerprint is calculated as follows:
wherein n represents n parameters of the discharge fingerprint, i represents 0 to n-1, xiI-th discharge fingerprint parameter, y, representing a partial discharge sensor xiThe ith discharge fingerprint parameter representing the neighboring noise sensor y.
Step 4, specifically, taking the signal of the partial discharge sensor as a trigger signal, collecting high-speed pulse signals of all partial discharge sensors, and observing time domain waveforms of all partial discharge sensors; if the signal of the partial discharge sensor leads other sensors, the signal detected by the sensor is judged to be an intermittent partial discharge signal generated inside the power equipment, otherwise, the signal is judged to be an interference signal.
Step 1 the external space is a place 0.5-5 m away from the outer wall of the equipment.
Taking N as 12, and collecting at least once every 2 hours; taking M as 24, and judging according to the judgment standard of 2 days.
The method can comprehensively judge the source of the intermittent signal by carrying out various analyses on the local discharge signal, effectively distinguish the intermittent defect signal from the external interference signal, improve the reliability of the defect diagnosis of the power equipment and provide guarantee for the safe operation of the power equipment.
Drawings
FIG. 1 is a flow chart of the invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
The invention provides a method for identifying intermittent defect signals of power equipment, which comprises the following steps:
step 1, analyzing a signal characteristic map;
step 2, intermittent analysis;
step 3, analyzing the noise sensor;
and 4, pulse positioning analysis.
According to the identification method of the intermittent defect signals of the power equipment, provided by the invention, a power equipment partial discharge detection instrument is used, and a plurality of partial discharge sensors are mounted on the power equipment and used for receiving partial discharge signals generated from the inside of the power equipment; the method comprises the following steps that a plurality of noise sensors are arranged in the external space of the power equipment and used for receiving noise signals transmitted from the external space; for each partial discharge sensor, the judgment from step 1 to step 4 is used in sequence.
Step 1, analyzing a signal characteristic map: detecting intermittent signals of the power equipment to obtain a partial discharge characteristic map; observing a partial discharge characteristic map, and finishing identification if the signal is judged to be an interference signal (the method aims to identify whether the signal is an interference signal or an interference signal, so that if the signal can be judged to be the interference signal or the partial discharge signal, the method belongs to the following steps of finishing identification, namely identifying that the input signal is the interference signal, is not suspected partial discharge or partial discharge, and does not need further processing); if the signal is judged to be a suspected partial discharge signal, the next step is continued.
The Partial Discharge characteristic map refers to a Partial Discharge PRPS (Phase Resolved Pulse Sequence)/PRPD (Phase Resolved Partial Discharge) map.
The signal judgment of the partial discharge characteristic map refers to judging the signal type of the partial discharge characteristic map by using a partial discharge type diagnosis method, and dividing the signal into an interference signal and a suspected partial discharge signal.
Step 2, intermittent analysis: counting the signal trend of the partial discharge sensor (namely the currently analyzed partial discharge sensor, 4 steps in the process are all partial discharge sensors for a certain research); if the total number of the suspected partial discharge signals is less than M or the average daily number of the suspected partial discharge signals is less than N, judging that the signals detected by the sensor are accidental interference, and finishing identification; otherwise, the next step is continued. (the above identified target is "intermittent partial discharge", that is, the partial discharge occurs irregularly, not sporadically, and no further occurrence, specifically, N is 12, and at least once is collected every 2 hours, M is 24, and the judgment standard is 2 days)
Step 3, noise sensor analysis: calculating the correlation coefficient of the discharge fingerprints of the partial discharge sensor and the adjacent noise sensor, and judging the similarity of signals; if the signal detected by the partial discharge sensor is similar to the signal of the adjacent noise sensor and the signal amplitude is small, the signal detected by the sensor is judged to be interference, and the identification is completed; otherwise, the next step is continued.
The discharge fingerprint comprises signal skewness, prominence, asymmetry, correlation coefficient, pulse concentration and dispersion degree.
The correlation coefficient is calculated as follows:
wherein n represents n parameters of the discharge fingerprint, i represents 0 to n-1, xiI-th discharge fingerprint parameter, y, representing a partial discharge sensor xiThe ith discharge fingerprint parameter representing the neighboring noise sensor y.
Xi in the formula represents the ith fingerprint parameter. N represents the number of parameters of the discharge fingerprint, such as the "skewness" described above, and is 6 here. Together, "Xi" represents the ith parameter of sensor x. Assuming 2 partial discharge sensors, when judging the 1 st partial discharge sensor, X1 represents the value of the first fingerprint parameter "skewness" of this sensor. So X represents the first one only and is not a serial number. The same applies to Y.
Step 4, pulse positioning analysis: taking the signal of the partial discharge sensor as a trigger signal, collecting a high-speed pulse signal, and observing time domain waveforms of all the sensors; if the signal of the partial discharge sensor leads other sensors, the signal detected by the sensor is judged to be an intermittent partial discharge signal generated inside the power equipment, otherwise, the signal is judged to be an interference signal.
The invention discloses a method for identifying intermittent defect signals of power equipment, which is mainly technically characterized by comprising the following steps of: analyzing a signal characteristic map, and judging the type of the signal to be a suspected partial discharge signal or an interference signal; analyzing the intermittence, and judging whether the signal is accidental interference; analyzing by a noise sensor, and judging whether the signal is from external interference; and pulse positioning analysis is carried out, the sequence of the signals is judged, and identification of intermittent defect signals and external interference of the power equipment is realized.
The invention can comprehensively judge the source of the intermittent signal by carrying out various analyses on the local discharge signal, effectively distinguish the intermittent defect signal from the external interference signal, improve the reliability of the defect diagnosis of the power equipment and provide guarantee for the safe operation of the power equipment.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (3)
1. An intermittent defect signal identification method for power equipment is characterized by comprising the following steps:
installing a plurality of partial discharge sensors on the power equipment, and receiving partial discharge signals generated inside the power equipment and detected by the partial discharge sensors by using a power equipment partial discharge detection instrument; installing a plurality of noise sensors in the external space of the power equipment, and receiving a noise signal transmitted from the external space and detected by the noise sensors by using a local discharge detection instrument of the power equipment; for each partial discharge sensor, the following steps 1 to 4 are sequentially used for judgment and identification;
step 1, analyzing a signal characteristic map: detecting intermittent signals of the power equipment provided by a partial discharge sensor by using a power equipment partial discharge detection instrument to obtain a partial discharge characteristic map; observing the partial discharge characteristic map, and finishing identification if the partial discharge characteristic map is judged to be an interference signal; if the suspected partial discharge signal is judged, continuing the next step;
step 2, intermittent analysis: counting the signal trend of the partial discharge sensor; if the total number of the suspected partial discharge signals is less than M or the average daily number of the suspected partial discharge signals is less than N, judging that the signals detected by the partial discharge sensor are accidental interference, and finishing identification; otherwise, continuing the next step;
step 3, analyzing the noise sensor: calculating the correlation coefficient of the discharge fingerprints of the partial discharge sensor and the adjacent noise sensor, and judging the similarity of signals; if the signal detected by the partial discharge sensor is similar to the signal of the adjacent noise sensor and the signal amplitude is small, judging that the signal detected by the partial discharge sensor is external interference, and finishing identification; otherwise, continuing the next step; wherein the discharge fingerprint comprises signal skewness, prominence, asymmetry, correlation coefficient, pulse concentration and dispersion; the correlation coefficient of the discharge fingerprint is calculated as follows:
wherein n represents n parameters of the discharge fingerprints, xi represents the ith discharge fingerprint parameter of the partial discharge sensor x, and yi represents the ith discharge fingerprint parameter of the adjacent noise sensor y;
step 4, pulse positioning analysis: taking the intermittent defect signals of the suspected partial discharge signals, which are dissimilar to the adjacent noise sensor signals, of which the total number is more than M or the daily average number is more than N as trigger signals, collecting high-speed pulse signals of all partial discharge sensors, and observing time domain waveforms of all the partial discharge sensors; if the total number of the suspected partial discharge signals which are dissimilar to the adjacent noise sensor signals is higher than M, or the intermittent defect signals of the suspected partial discharge signals with the daily average number of the suspected partial discharge signals higher than N are ahead of other partial discharge sensors, the signals detected by the partial discharge sensors are judged to be intermittent partial discharge signals generated in the power equipment, and otherwise, the signals are judged to be interference signals.
2. The power equipment intermittent defect signal identification method as claimed in claim 1, wherein: step 1 the external space is a place 0.5-5 m away from the outer wall of the equipment.
3. The power equipment intermittent defect signal identification method as claimed in claim 1, wherein: taking N as 12, and collecting at least once every 2 hours; taking M as 24, and judging according to the judgment standard of 2 days.
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| CN112710928B (en) * | 2020-12-10 | 2023-02-21 | 国网宁夏电力有限公司电力科学研究院 | Direct-current partial discharge waveform interference removing method and system based on autocorrelation analysis |
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