CN114779028B - Generator partial discharge online monitoring device and monitoring method - Google Patents
Generator partial discharge online monitoring device and monitoring method Download PDFInfo
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- CN114779028B CN114779028B CN202210659517.6A CN202210659517A CN114779028B CN 114779028 B CN114779028 B CN 114779028B CN 202210659517 A CN202210659517 A CN 202210659517A CN 114779028 B CN114779028 B CN 114779028B
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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
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
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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
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
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- G—PHYSICS
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- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/148—Wavelet transforms
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Abstract
The invention provides a partial discharge online monitoring device and a partial discharge online monitoring method for a generator, wherein the online monitoring device comprises a main detection line, a correction line and an online monitor, the main detection line and the correction line are arranged in parallel, and the online monitor is connected with the generator through the main detection line and is used for acquiring partial discharge data of the generator in real time; the online monitor is connected with the generator through a correction circuit and is used for acquiring the actual generator terminal voltage U of the generator in real time and correcting the threshold value of the partial discharge data by using the U; compared with the prior art adopting a fixed threshold, the method provided by the invention has the advantages that the threshold is corrected through the U obtained in real time, and the size of the threshold can be adjusted according to the actual operation condition of the generator, so that the threshold adopted in the threshold processing process is more fit with the actual operation condition of the generator, the accurate determination of the threshold is ensured, the partial discharge noise can be more accurately removed, and the identification accuracy of the partial discharge signal of the generator is favorably improved.
Description
Technical Field
The invention relates to the field of insulation online monitoring of electrical equipment, in particular to a partial discharge online monitoring device and a partial discharge online monitoring method for a generator.
Background
Partial Discharge (PD) monitoring of a genset is an important means of detecting degradation in insulation performance of the genset. Because partial discharge is an important cause of insulation degradation of the generator set and is a main characteristic reflecting the insulation degradation, the partial discharge capacity of the generator set can effectively represent the insulation health condition of the generator set.
The method has the advantages that the partial discharge condition of the generator set under the operation condition is measured on line, so that the insulation health condition of the generator set can be timely mastered, insulation accidents can be effectively prevented, reference is provided for state maintenance, the influence characteristics of various operation stresses on insulation health can be identified, various insulation damage events can be captured, and a basis is provided for fault diagnosis. The generator partial discharge online monitoring technology has been studied for a long time at home and abroad, and a lot of equipment is put into operation on the engineering site, so that good practical effects are achieved.
In the prior art, a generator partial discharge online monitoring device (as shown in fig. 1) acquires partial discharge signals at a generator end in real time through a coupling capacitor 3 arranged on a closed bus 2 at the generator end, inputs the partial discharge signals into partial discharge online monitoring equipment through a coaxial cable 4 for analysis and processing, calculates parameters such as discharge capacity, discharge frequency and discharge phase, and finally displays the parameters through a human-computer interface HMI. In the prior art, although the current generator partial discharge online monitoring equipment and monitoring technology are widely applied, the accurate measurement of a partial discharge signal is greatly challenged because of serious noise and interference in online measurement and the interference is larger when the generator terminal voltage is higher. Therefore, the elimination of noise and interference is a key problem in the online measurement of partial discharge of the generator and is also the basis for the subsequent identification and determination of the discharge type and the corresponding insulation defect.
Aiming at eliminating noise and interference of partial discharge signals, wavelet transformation is often used as a main time-frequency domain tool for denoising of partial discharge of a generator in the prior art, wherein a threshold method is most widely applied, mainly aiming at white noise and discrete spectrum interference, and noise elimination is generally realized through three steps of decomposition, threshold processing and reconstruction. For example, the prior patents CN106324502A, CN111521916A, CN102540028A, etc. describe wavelet transformation and threshold denoising methods.
However, in the threshold processing stage in actual engineering, a fixed threshold is often adopted for processing in the prior art, which easily causes that the numerical accuracy of the adopted fixed threshold is poor and cannot be matched with the actual operation condition of the generator; if the value of the fixed threshold is selected to be larger, a useful part in the partial discharge signal can be lost, and if the value of the fixed threshold is selected to be smaller, part of noise can not be effectively eliminated, so that the accuracy of final partial discharge data is undoubtedly affected, and the identification accuracy of the partial discharge signal of the generator is lower.
Therefore, in the process of analyzing the partial discharge signal by using the wavelet, how to accurately determine the threshold value in the threshold processing stage becomes a difficult problem to be solved urgently in the field.
Disclosure of Invention
In view of the above, the present invention is directed to provide an on-line monitoring device and a monitoring method for a generator partial discharge, so as to solve the problems that in the prior art, in a process of analyzing a partial discharge signal by using a wavelet, a fixed threshold is often used for processing in a threshold processing stage, so that it is difficult to accurately determine a threshold, and the recognition accuracy of the generator partial discharge signal is low.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a partial discharge online monitoring device of a generator comprises a main detection circuit, a correction circuit and an online monitor, wherein the main detection circuit and the correction circuit are arranged in parallel, and the online monitor is connected with the generator through the main detection circuit and is used for acquiring partial discharge data of the generator in real time; the online monitor is connected with the generator through a correction circuit and used for acquiring the actual generator terminal voltage U of the generator in real time and performing threshold correction on the partial discharge data by using the U.
Further, a voltage transformer is arranged in the correction circuit.
Furthermore, a coupling capacitor and a coaxial cable are sequentially arranged in the main detection circuit, and the main detection circuit is connected with the online monitor through the coaxial cable.
Preferably, the coupling capacitance is 80pF, and the coaxial cable is 50 Ω.
A monitoring method of a generator partial discharge online monitoring device is applied to the generator partial discharge online monitoring device, and comprises the following steps: s1, acquiring partial discharge data of the generator in real time through the main detection line to form a partial discharge data waveform; s2, determining wavelet function and decomposition layer number j, performing wavelet transform on partial discharge data waveform, and calculating wavelet coefficient of each layer
(ii) a S3, acquiring the actual terminal voltage U of the generator in real time through a correction circuit; s4, carrying out threshold correction according to U to obtain the threshold of each layer
(ii) a S5, converting the wavelet coefficient
Binding threshold
Calculating to obtain estimated wavelet coefficient
(ii) a S6, reconstructing the wavelet through each layer coefficient of wavelet decomposition to obtain a partial discharge signal after noise signals are eliminated, and analyzing the partial discharge signal to obtain final partial discharge data.
Further, in step S4, the threshold correction calculation formula is
，
Is the threshold value of the j layer, Ue is the terminal rated voltage,
for signal-to-noise ratio, N is the number of signal data.
Further, in step S5, wavelet coefficients are estimated
Is calculated as
。
Further, in step S1, the on-line monitor continuously records the partial discharge data of the generator through the main detection line for a recording time period T.
Compared with the prior art, the partial discharge online monitoring device and the monitoring method for the generator have the following advantages:
according to the generator partial discharge online monitoring device and the monitoring method, only the correction circuit is additionally arranged in the existing generator partial discharge online monitoring device and is connected with the main detection circuit in parallel, the existing online monitoring device can be conveniently modified, the existing device does not need to be greatly disassembled and modified, and the modification cost is favorably reduced.
Meanwhile, in the process of processing the partial discharge signals, acquisition of partial discharge data cannot be influenced, the actual voltage U of a machine end is additionally acquired through a correction circuit, the U is used for carrying out threshold correction on the partial discharge data, compared with the prior art adopting a fixed threshold, the threshold correction is carried out through the U acquired in real time, the size of the threshold can be adjusted according to the actual running condition of the generator, the threshold adopted in the threshold processing process is more fit with the actual running condition of the generator, accurate determination of the threshold is ensured, partial discharge noise can be removed more accurately, and the method is favorable for improving the identification accuracy of the partial discharge signals of the generator.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic structural diagram of a generator partial discharge online monitoring device in the prior art;
fig. 2 is a schematic structural diagram of a generator partial discharge online monitoring device according to an embodiment of the present invention;
fig. 3 is a data waveform diagram of an original partial discharge signal when the terminal voltage is 23.38kV in embodiment 1 of the present invention;
FIG. 4 is a diagram of a de-noised reconstructed signal after the waveform data in FIG. 3 is processed by a conventional fixed threshold according to the present invention;
FIG. 5 is a diagram of a de-noised reconstructed signal after the waveform data in FIG. 3 is subjected to the threshold correction processing proposed in the present application;
fig. 6 is a data waveform diagram of an original partial discharge signal when the terminal voltage is 24.72kV in embodiment 2 of the present invention;
FIG. 7 is a diagram of a de-noised reconstructed signal after the waveform data in FIG. 6 is processed by a conventional fixed threshold according to the present invention;
fig. 8 is a diagram of a de-noised reconstructed signal obtained by performing threshold correction processing on the waveform data in fig. 6 according to the present invention.
Description of reference numerals:
1. a generator; 11. a first ground line; 2. sealing the bus; 3. a coupling capacitor; 4. a coaxial cable; 5. a main detection line; 6. correcting the circuit; 61. a voltage transformer; 7. a protection circuit; 71. a voltage stabilizing tube; 8. and a second ground line.
Detailed Description
The inventive concepts of the present disclosure will be described hereinafter using terms commonly employed by those skilled in the art to convey the substance of their work to others skilled in the art. These inventive concepts may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. Meanwhile, the term "partial discharge" in the present application is simply referred to as "partial discharge".
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
In the prior art, a generator partial discharge online monitoring device (as shown in fig. 1) acquires a generator end partial discharge signal in real time through a coupling capacitor 3 mounted on a closed bus 2 at a generator end, inputs the partial discharge signal into partial discharge online monitoring equipment through a coaxial cable 4 for analysis, calculates parameters such as discharge capacity, discharge frequency and discharge phase, and then displays the parameters through a human-machine interface HMI (human machine interface). Due to the existence of serious noise and interference in online measurement, wavelet transformation is often used as a main time-frequency domain tool for generator partial discharge denoising in the prior art, wherein a threshold method is most widely applied and mainly aims at white noise and discrete spectrum interference, noise elimination is generally realized by three steps of decomposition, threshold processing and reconstruction in the prior art, but in the process of adopting wavelet analysis partial discharge signals in the prior art, a fixed threshold is often adopted for processing in a threshold processing stage, so that the numerical accuracy of the adopted fixed threshold is poor, the fixed threshold cannot be matched with the actual operation condition of a generator, and the identification accuracy of the generator partial discharge signals is low.
In order to solve the problems that in the prior art, in the process of analyzing partial discharge signals by using wavelets, a fixed threshold is often used for processing at a threshold processing stage, which results in difficulty in accurately determining the threshold, low accuracy in identifying partial discharge signals of a generator, and the like, in this embodiment, a generator partial discharge online monitoring device is provided, as shown in fig. 2, the online monitoring device is connected with a generator 1, and includes a main detection line 5, a correction line 6, and an online monitor, wherein the main detection line 5 and the correction line 6 are arranged in parallel, and the online monitor is connected with the generator 1 through the main detection line 5 and is used for acquiring partial discharge data of the generator 1 in real time; the online monitor is connected with the generator 1 through a correction circuit 6 and used for acquiring the actual generator terminal voltage U of the generator 1 in real time and performing threshold correction on partial discharge data by using the U.
It should be noted that the partial discharge data refers to a partial discharge data waveform obtained by continuous detection, which is the same as that in the prior art and is not described in detail. The online monitor in the application can be only data acquisition equipment, can acquire partial discharge data and U, can process the partial discharge data through U by manpower or other data processing tools in the process of carrying out threshold correction on the partial discharge data, and obtains final partial discharge data. Of course, the online monitor may also be an automated data acquisition and analysis instrument, and after the partial discharge data and the U are acquired, the partial discharge data can be automatically subjected to threshold correction through the U until the final partial discharge data is obtained.
Thereby the on-line monitoring device of this application simple structure only additionally increases correction circuit 6 in current generator partial discharge on-line monitoring device to parallelly connected with main detection circuitry 5, can realize the transformation to current on-line monitoring device conveniently, need not to tear open greatly to change current device greatly, be favorable to reducing and reform transform the cost. Meanwhile, in the process of processing the partial discharge signal, acquisition of partial discharge data cannot be influenced, the actual terminal voltage U is additionally acquired through the correction circuit 6, the U is used for correcting the partial discharge data to carry out threshold correction, compared with the prior art adopting a fixed threshold, the threshold correction is carried out through the U acquired in real time, the size of the threshold can be adjusted according to the actual running condition of the generator, the threshold adopted in the threshold processing process is more fit with the actual running condition of the generator, accurate determination of the threshold is ensured, partial discharge noise can be removed more accurately, and the identification accuracy of the partial discharge signal of the generator is improved.
For the generator 1, the generator 1 comprises a closed bus 2, and the generator 1 is connected with a main detection line 5 and a correction line 6 through the closed bus 2. In addition, the generator 1 further comprises a first grounding wire 11, one end of the first grounding wire 11 is connected with the generator 1, and the other end of the first grounding wire 11 is grounded, so that the electrical safety of the generator 1 is guaranteed.
For a main detection line 5, a coupling capacitor 3 and a coaxial cable 4 are sequentially arranged in the main detection line 5, and the main detection line 5 is connected with an online monitor through the coaxial cable 4. Preferably, the coupling capacitor 3 is 80pF, and the coaxial cable 4 is 50 Ω. In order to ensure the stability of data acquired by the online monitor through the main detection circuit 5 and ensure corresponding electrical safety, the online monitoring device comprises a protection circuit 7, one end of the protection circuit 7 is connected with the main detection circuit 5, the other end of the protection circuit is grounded, and a voltage regulator tube 71 is arranged in the protection circuit 7 and used for preventing surge impact. Preferably, the connection point of the protection line 7 and the main detection line 5 is located between the coupling capacitor 3 and the coaxial cable 4. In addition, the online monitor is provided with a second grounding wire 8, one end of the second grounding wire 8 is connected with the online monitor, and the other end of the second grounding wire 8 is grounded, so that the electrical safety of the online monitor is ensured.
For the correction circuit 6, a voltage transformer 61 is arranged in the correction circuit 6 and is used for transforming the terminal voltage of the generator 1 and transforming the high voltage value of the terminal voltage into the low voltage so as to meet the requirement of the online monitor on the safe voltage when receiving the voltage signal, avoid the direct impact of the overhigh terminal voltage on the online monitor and ensure the safe and effective data acquisition of the online monitor.
Preferably, the on-line monitor is an automated data acquisition and analysis instrument, and includes a conventional central processing unit in addition to a conventional data acquisition module, such as a voltage detector, a current detector, and the like, for performing automated wavelet analysis on the partial discharge signal. In addition, the online monitoring device further comprises a human-computer interface, wherein the human-computer interface is connected with the online monitor and used for an engineer to perform operations such as manual intervention, manual calculation, parameter presetting and the like on the partial discharge signal processing process. The human-computer interface and the online monitor may be connected via a data line or wirelessly, for example, via WIFI, ethernet, etc., which are not repeated herein in view of the prior art.
On the basis of the on-line monitoring device, the application also provides a generator partial discharge on-line monitoring method, which comprises the following steps:
s1, acquiring partial discharge data of the generator 1 in real time through the main detection line 5 to form a partial discharge data waveform;
in step S1, under the recording duration T, the on-line monitor continuously records the partial discharge data of the generator 1 through the main detection line 5, and integrates the partial discharge data with the recording duration T, as shown in fig. 3 and 6 of the present application, a partial discharge data waveform is formed with the recording time as a horizontal axis and the partial discharge data amplitude corresponding to the recording time as a vertical axis, and the partial discharge data waveform can be used as an original partial discharge signal diagram;
in view of the recording, drawing and the like of the signal waveform diagrams, which are conventional in the art, further description is omitted here.
In the present application, T may be a length of time, such as 1 minute to 1 day or any other length of time. However, considering the actual continuous operation of the generator 1, the online monitoring device in the present application is preferably capable of continuously recording the partial discharge data of the generator 1 for a long time, storing the sampled partial discharge data for 1 to 7 days, deleting old data exceeding the data storage life, continuously storing newly acquired data, and repeating the steps in sequence to maintain the continuous sampling of the data.
For the waveform lengths in fig. 3-8 of the present application, which are only a small fraction of the cut-out from the continuously recorded signal, the numbers on the horizontal axis in fig. 3-8 represent the number of partial discharge data points (dimensionless), but depending on the sampling rate of the on-line monitoring device, the numbers on the horizontal axis may also be equivalent to the recording time, for example: suppose that the on-line monitoring device of the present application samples 10 samples per second 7 A partial discharge data point, a number 500 on the horizontal axis in fig. 3 to 8 of the present application indicates a 500 th data point, which may also be equivalent to a recording time length of 50 microseconds; if the on-line monitoring device samples 10 samples per second 6 For each partial discharge data point, the number 500 on the horizontal axis is equivalent to a recording time length of 500 microseconds.
The vertical axis in fig. 3-8 again represents the magnitude of the partial discharge data points in mV.
S2, determining wavelet function and decomposition layer number j, performing wavelet transform on partial discharge data waveform, and calculating wavelet coefficient of each layer
；
Step S2 is a conventional wavelet transform technique in the prior art, and an engineer selects a proper wavelet function and decomposition layer number j according to the characteristics of the original partial discharge signal and the noise characteristics thereof to perform wavelet transform. The wavelet function may be any one of a plurality of functions from db2 wavelet to db8 wavelet, and the decomposition layer number j may be any one of 3 to 8. Since the wavelet transform technology is a conventional technology, it is not described in detail.
S3, acquiring the actual terminal voltage U of the generator 1 in real time through the correction circuit 6;
s4, carrying out threshold correction according to U to obtain the threshold of each layer
；
Fixed thresholds are often used for thresholding in conventional wavelet transform techniques, e.g., the prior art is often based on
To calculate the threshold value, wherein,
is the threshold value for the j-th layer,
for signal-to-noise ratio, N is the number of signal data. Therefore, the threshold value in the prior art is a fixed value and cannot be adapted to the actual operation condition of the generator, which easily causes poor numerical precision of the threshold value and low identification accuracy of the partial discharge signal of the generator.
In step S4 of the present application, the threshold correction calculation formula is
，
Is the threshold value of the j layer, Ue is the terminal rated voltage, in particular the rated working voltage value in the nameplate of the generator 1,
for signal-to-noise ratio, N is the number of signal data.
Compared with the prior art, the threshold value is corrected by the U in the step S4, the size of the threshold value can be automatically adjusted according to the actual operation condition of the generator, so that the threshold value adopted in the threshold value processing process is more attached to the actual operation condition of the generator, the accurate determination of the threshold value is ensured, the partial discharge noise can be more accurately removed, and the identification accuracy of the partial discharge signal of the generator is favorably improved.
S5, wavelet coefficient
Binding threshold
Calculating to obtain estimated wavelet coefficient
；
Wherein wavelet coefficients are estimated
Is calculated as
Therefore, after the threshold value is corrected by using U, the estimated wavelet coefficient more suitable for the actual operation condition of the generator can be directly obtained by the calculation formula for estimating the wavelet coefficient
The method is favorable for improving the accuracy of removing partial discharge noise and improving the identification accuracy of the partial discharge signal of the generator.
S6, reconstructing the wavelet through each layer coefficient of wavelet decomposition to obtain a partial discharge signal after the noise signal is eliminated, and analyzing the partial discharge signal to obtain final partial discharge data.
In step S6, conventional data analysis processing techniques such as wavelet reconstruction and signal analysis in the existing wavelet transform technique can be directly used, and are not described in detail in view of their existing techniques.
On the basis of the online monitoring device and the online monitoring method, two embodiments are continuously provided for further introduction of the application.
Example 1
The generator parameters for a certain power plant are as follows: capacity: 388.2MVA, model number: QFSN-330-2-24, rated voltage 24kV, rated current 9339A.
The partial discharge data of the generator 1 is continuously recorded through the step S1, a small segment of continuous sampling points of the partial discharge data at the receiver end when the actual voltage at the receiver end is 23.38kV contains about 500 continuous partial discharge data points, and the online monitoring device of the present application samples 10 partial discharge data points per second 7 On the basis of the partial discharge data points, the recording time length is about 50 microseconds, and a partial discharge data waveform is formed, as shown in fig. 3, obviously, only a large amount of noise can be seen from the figure, and a useful partial discharge signal cannot be seen.
Performing wavelet analysis processing on the partial discharge data waveform, selecting a db3 wavelet, selecting 3 layers as decomposition layer numbers,
=1，N=512。
firstly, according to the prior art, the conventional wavelet transform technology and the fixed threshold are adopted for calculation, and the calculation formula of the fixed threshold is
After conventional calculation and wavelet reconstruction in the prior art, the waveform of the final partial discharge data is obtained as shown in fig. 4, and as can be seen from fig. 4, when the actual voltage of the machine end is 23.38kV, because the fixed threshold in the prior art is set to be higher, noise is not effectively filtered, and a signal is causedIs drowned out by noise and no useful partial discharge signal is detected.
By adopting the on-line monitoring device and the monitoring method, on the basis of the conventional wavelet transformation technology, the actual voltage U at the machine end is additionally detected, the U is utilized to correct the threshold value, and the calculation formula of the threshold value correction is
Wherein, U =23.38kV, and Ue =24 kV. The final partial discharge data waveform obtained by the processing in steps S5 and S6 is shown in fig. 5.
By comparing the waveform data of fig. 4 and 5, it can be clearly seen that: in the prior art, after wavelet processing is carried out by adopting a fixed threshold, noise is not effectively filtered, so that signals are submerged by the noise, and useful partial discharge signals cannot be detected; on the basis of a conventional wavelet transformation technology, the threshold value can be automatically adjusted according to the actual running condition of the generator by additionally detecting the actual voltage U of the generator end and utilizing the U to correct the threshold value, so that the threshold value adopted in the threshold value processing process is more attached to the actual running condition of the generator, the accurate determination of the threshold value is ensured, the partial discharge noise can be more accurately removed, the partial discharge signal can be effectively detected, and the identification accuracy of the partial discharge signal of the generator can be favorably improved.
Example 2
The generator parameters for a certain power plant are as follows: capacity: 388.2MVA, model number: QFSN-330-2-24, rated voltage 24kV, rated current 9339A.
The partial discharge data of the generator 1 is continuously recorded through the step S1, a small continuous sampling point of the partial discharge data when the actual voltage at the receiver end is 24.72kV is intercepted, the small continuous sampling point comprises about 500 continuous partial discharge data points, and the online monitoring device of the present application samples 10 samples per second 7 On the basis of the partial discharge data points, the recording time length is about 50 microseconds, and a partial discharge data waveform is formed, as shown in fig. 6, obviously, only a large amount of noise can be seen from the figure, and a useful partial discharge signal cannot be seen.
Wavelet analysis processing for partial discharge data waveformIn other words, db3 wavelet is selected, 3 layers are selected for the number of decomposition layers,
=1，N=512。
firstly, according to the prior art, the conventional wavelet transformation technology and the fixed threshold are adopted for calculation, and the calculation formula of the fixed threshold is
After conventional calculation and wavelet reconstruction in the prior art, the waveform of the final partial discharge data is shown in fig. 7, and it can be seen from fig. 7 that when the actual voltage of the machine end is 24.72kV, a fixed threshold in the prior art is set to be relatively low, a part of useful signals are lost, so that the reconstructed signals are distorted, and no useful partial discharge signals are detected.
By adopting the on-line monitoring device and the monitoring method, on the basis of the conventional wavelet transformation technology, the actual voltage U at the machine end is additionally detected, the U is utilized to correct the threshold value, and the calculation formula of the threshold value correction is
Wherein, U =24.72kV, Ue =24 kV. The final partial discharge data waveform obtained by the processing in steps S5 and S6 is shown in fig. 8.
By comparing the waveform data of fig. 7 and 8, it can be clearly seen that: in the prior art, after wavelet processing is carried out by adopting a fixed threshold, part of useful signals are lost, so that reconstructed signals are distorted, and useful partial discharge signals are not detected; on the basis of a conventional wavelet transformation technology, the threshold value can be automatically adjusted according to the actual running condition of the generator by additionally detecting the actual voltage U of the generator end and utilizing the U to correct the threshold value, so that the threshold value adopted in the threshold value processing process is more attached to the actual running condition of the generator, the accurate determination of the threshold value is ensured, the partial discharge noise can be more accurately removed, the partial discharge signal can be effectively detected, and the identification accuracy of the partial discharge signal of the generator can be favorably improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (5)
1. The monitoring method of the generator partial discharge online monitoring device is characterized by comprising a main detection line (5), a correction line (6) and an online monitor, wherein the main detection line (5) and the correction line (6) are arranged in parallel, and the online monitor is connected with a generator (1) through the main detection line (5) and is used for acquiring partial discharge data of the generator (1) in real time; the online monitor is connected with the generator (1) through a correction circuit (6) and is used for acquiring the actual terminal voltage U of the generator (1) in real time and correcting the threshold value of the partial discharge data by using the U;
the monitoring method comprises the following steps:
s1, acquiring partial discharge data of the generator (1) in real time through the main detection line (5) to form a partial discharge data waveform;
s2, determining wavelet function and decomposition layer number j, performing wavelet transform on partial discharge data waveform, and calculating wavelet coefficient of each layer
；
S3, acquiring the actual terminal voltage U of the generator (1) in real time through the correction circuit (6);
s4, carrying out threshold correction according to U to obtain the threshold of each layer
；
S5, wavelet coefficient
Binding threshold
Performing calculation processing to obtainTo estimate wavelet coefficients
；
S6, reconstructing the wavelet through each layer coefficient of wavelet decomposition to obtain a partial discharge signal after noise signals are eliminated, and analyzing the partial discharge signal to obtain final partial discharge data;
in step S4, the threshold correction formula is
，
Is the threshold of the j layer, Ue is the terminal rated voltage,
the signal-to-noise ratio is N, and the number of the signal data is N;
in step S5, wavelet coefficients are estimated
Is calculated as
。
2. The monitoring method of the generator partial discharge online monitoring device according to claim 1, characterized in that a voltage transformer (61) is arranged in the correction line (6).
3. The monitoring method of the generator partial discharge online monitoring device according to claim 1, wherein a coupling capacitor (3) and a coaxial cable (4) are sequentially arranged in the main detection line (5), and the main detection line (5) is connected with the online monitor through the coaxial cable (4).
4. The monitoring method of the generator partial discharge on-line monitoring device according to claim 3, wherein the coupling capacitor (3) is 80pF, and the coaxial cable (4) is 50 Ω.
5. The monitoring method of the generator partial discharge online monitoring device according to claim 1, wherein in step S1, the online monitor continuously records the partial discharge data of the generator (1) through the main detection line (5) for a recording time period T.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210659517.6A CN114779028B (en) | 2022-06-13 | 2022-06-13 | Generator partial discharge online monitoring device and monitoring method |
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| CN202210659517.6A CN114779028B (en) | 2022-06-13 | 2022-06-13 | Generator partial discharge online monitoring device and monitoring method |
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| CN114779028A CN114779028A (en) | 2022-07-22 |
| CN114779028B true CN114779028B (en) | 2022-09-06 |
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