CN114167240A - Built-in wireless self-energy-taking ultrahigh frequency partial discharge detection method - Google Patents
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Abstract
The invention discloses a built-in wireless self-energy-taking ultrahigh frequency partial discharge detection method, relates to the technical field of GIS (geographic information System) live detection, and solves the technical problems that in the prior art, when ultrahigh frequency partial discharge of GIS equipment is detected, the workload is large, and long-term uninterrupted detection on the partial discharge cannot be ensured; the energy acquisition module is internally provided with the rechargeable battery and the super capacitor, the super capacitor and the rechargeable battery are charged in a capacitive voltage division mode integrated by the built-in ultrahigh frequency sensor, and then the single module in the detection unit is powered by the energy acquisition module, so that long-term uninterrupted work of the detection unit is guaranteed; the invention combines the partial discharge detection unit with the 5G technology, completes data interaction by the advantages of high bandwidth, high capacity, high reliability, low time delay and low power consumption of the 5G technology, and displays the partial discharge detection result by the visual platform, thereby solving the problem of large workload of the current wired laying.
Description
Technical Field
The invention belongs to the field of GIS (geographic information system) live detection, relates to a built-in wireless self-energy-taking technology in GIS live detection, and particularly relates to a built-in wireless self-energy-taking ultrahigh frequency partial discharge detection method.
Background
GIS is the English abbreviation of gas-insulated totally closed combined electrical apparatus, and GIS can produce partial discharge because of various reasons in the operation process, and partial discharge time overlength can lead to GIS inside flashover trouble, and GIS's full seal structure makes fault location and maintenance more difficult, and detection work is complicated, and the maintenance time is long.
Currently, ultrahigh frequency partial discharge detection of GIS equipment is mainly carried out in two modes of ultrahigh frequency partial discharge live detection and ultrahigh frequency partial discharge online detection; the ultrahigh frequency partial discharge live detection needs professional personnel to carry out, and has the defects of large workload, long period, low sensitivity and incapability of real-time detection; the ultrahigh frequency partial discharge online detection comprises a wired mode and a wireless mode, wherein the wired mode has the problems of complicated field wiring, external signal interference and transmission attenuation, and the wireless mode has the problems of long detection period, low sensitivity and incapability of effectively detecting partial intermittent discharge; therefore, a detection method capable of efficiently detecting the ultrahigh frequency partial discharge of the GIS equipment in real time is needed.
Disclosure of Invention
The invention provides a built-in wireless self-energy-taking ultrahigh frequency partial discharge detection method, which is used for solving the technical problems that the workload is large and the long-term uninterrupted detection of partial discharge cannot be ensured when detecting ultrahigh frequency partial discharge of GIS equipment in the prior art.
The purpose of the invention can be realized by the following technical scheme: a built-in wireless self-powered ultrahigh frequency partial discharge detection method comprises the following steps:
the energy acquisition module is used for inducing energy storage through capacitance voltage division integrated with the built-in ultrahigh frequency sensor and supplying power to a detection unit in the built-in ultrahigh frequency sensor system; the detection unit comprises a data acquisition module, a wireless transmission module and a data processing module;
the data acquisition module acquires the partial discharge signal through a built-in ultrahigh frequency sensor connected with the data acquisition module, and processes and stores the partial discharge signal by combining with the data processing module.
Preferably, the energy-taking module is internally provided with a rechargeable battery and a super capacitor, and the super capacitor and the rechargeable battery are charged in a capacitive voltage division mode integrated by the built-in ultrahigh frequency sensor.
Preferably, the energy obtaining module is electrically connected with the data acquisition module, the data processing module and the wireless transmission module respectively, and the data processing module is electrically connected with the data acquisition module and the wireless transmission module respectively.
Preferably, the built-in ultrahigh frequency sensor samples the partial discharge signal and then sends the partial discharge signal to the data acquisition module;
the data acquisition module converts the partial discharge signal into target data and sends the target data to the data processing module through the wireless transmission module; wherein the target data is a digital signal;
and the data processing module is in communication connection with the partial discharge visualization platform.
Preferably, the partial discharge visualization platform acquires the data in the data processing module in real time or at regular time and performs visualization display.
Preferably, the partial discharge visualization platform is in communication connection with the data processing module through a 5G technology, and data transmission is completed by adopting a unified authentication framework and an encryption transmission mode.
Preferably, before the data processing module processes the target data, denoising processing is performed on the target data; the denoising processing is realized by combining a wavelet denoising algorithm and a spectral subtraction method.
Preferably, the data processing module processes the target data, and includes:
converting target data into a partial discharge detection map, and extracting numerical values and coordinates of data points in the detection data to generate a PRPD data matrix;
and analyzing the PRPD data matrix to obtain a detection result, sending the detection result to the partial discharge visualization platform, and storing the detection result.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is provided with an energy taking module, a rechargeable battery and a super capacitor are arranged in the energy taking module, the super capacitor and the rechargeable battery are charged in a capacitive voltage division mode integrated by a built-in ultrahigh frequency sensor, and then a single module in a detection unit is powered by the energy taking module; the energy-taking module is charged in an induction energy-taking mode, so that a power supply is provided for the work of the detection unit, and the long-term uninterrupted work of the detection unit is guaranteed.
2. The invention combines the partial discharge detection unit with the 5G technology, completes data interaction by the advantages of high bandwidth, high capacity, high reliability, low time delay and low power consumption of the 5G technology, and displays the partial discharge detection result by the visual platform, thereby solving the problem of large workload of the current wired laying.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram illustrating an energy-extracting principle of an energy-extracting module according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an energy obtaining unit structure of an energy obtaining module according to an embodiment of the present invention;
fig. 3 is a schematic diagram illustrating a principle of connection between a detection unit and an energy-obtaining module according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used herein is for the purpose of describing embodiments and is not intended to be limiting and/or limiting of the present disclosure; it should be noted that the singular forms "a," "an," and "the" include the plural forms as well, unless the context clearly indicates otherwise; also, although the terms first, second, etc. may be used herein to describe various elements, the elements are not limited by these terms, which are only used to distinguish one element from another.
When the electric equipment generates partial discharge, the breakdown time is very short, a steep pulse current is generated, the rise time is generally less than 1ns, and electromagnetic waves of several GHz are emitted to the periphery. The ultrahigh frequency method is to install a UHF sensor (with a typical frequency band of 0.4GHz-1.5GHz) at a non-shielding part such as a basin-type insulator of the GIS device by using the characteristic of partial discharge, and to collect, analyze and judge the type of a fault for an ultrahigh frequency signal (0.3GHz-3 GHz). The ultrahigh frequency electromagnetic wave is less attenuated in the GIS equipment and is easy to generate resonance in a cavity of the GIS equipment, so that the ultrahigh frequency method has very high sensitivity for detecting defects in the GIS equipment and wide effective detection range; the frequency band of the on-site corona discharge is below 0.3GHz, so the method has stronger anti-air interference capability and is not influenced by noise, mechanical vibration and the like; the ultrahigh frequency electromagnetic wave is transmitted in the GIS equipment at approximate light speed, and the time of the ultrahigh frequency electromagnetic wave reaching each UHF sensor is in direct proportion to the distance, so that the method is also suitable for positioning defects; in addition, the characteristics of different types of partial discharge ultrahigh frequency signals are obvious, and the defect type identification is facilitated.
Referring to fig. 1-3, the ultrahigh frequency partial discharge online monitoring includes a wired mode and a wireless mode:
1) the wired approach has two problems: a. the field wiring is complicated, the sensor is installed in a built-in mode, the power supply and the signal transmission of a power supply need wiring, the workload of early installation, debugging and later-stage modification operation and maintenance is large, and the cost is high; b. the sensor and the concentrator adopt coaxial cables for wire transmission, and the problems of external signal interference and transmission attenuation exist.
2) There are two problems with the current wireless approach: a. because the battery is adopted for supplying power, in order to ensure long-term work, the existing ultrahigh frequency partial discharge monitoring sensor only collects one group of data every day, the detection period is long, and partial intermittent discharge cannot be effectively monitored; b. the sensor is mainly installed at an external insulation basin of the GIS equipment for detection, and the local discharge signal in the GIS equipment is greatly attenuated and has low sensitivity.
Although the hardware can be designed with low power consumption, real-time monitoring and long service life are required, and an active power supply method is the best choice; however, in consideration of the fact that active power supply involves the work of on-site power taking and paying off in the installation process, the invention provides a method for solving the self-energy taking problem of the sensor by using a sensor to sense energy taking mode, and provides a new possibility for the on-site application of the subsequent sensor.
In order to solve the problems, the invention provides a built-in wireless self-energy-taking ultrahigh frequency partial discharge detection method, which solves the bottleneck that the current wired laying workload is large and a wireless power supply cannot be guaranteed.
The invention provides a built-in type wireless self-energy-taking ultrahigh frequency partial discharge detection method, which comprises the following steps:
the energy acquisition module is used for inducing energy storage through capacitance voltage division integrated with the built-in ultrahigh frequency sensor and supplying power to a detection unit in the built-in ultrahigh frequency sensor system;
the data acquisition module acquires the partial discharge signal through a built-in ultrahigh frequency sensor connected with the data acquisition module, and processes and stores the partial discharge signal by combining with the data processing module.
The built-in ultrahigh frequency sensor system in the application is an integrated system actually and comprises an energy acquisition module, a detection unit and a built-in ultrahigh frequency sensor, namely the energy acquisition module and the detection unit are integrated in the built-in ultrahigh frequency sensor system; therefore, the energy-taking module supplies power for the built-in ultrahigh frequency sensor and the internal detection unit; the energy-taking module is arranged inside the GIS equipment, and the built-in ultrahigh frequency sensor is arranged inside or outside the GIS equipment and is connected with the energy-taking module in a wireless communication mode.
In one embodiment, the detection unit comprises a data acquisition module, a wireless transmission module and a data processing module; the energy taking module is electrically connected with the data acquisition module, the data processing module and the wireless transmission module respectively, and the data processing module is electrically connected with the data acquisition module and the wireless transmission module respectively.
In one embodiment, the existing GIS built-in sensor is generally connected in a capacitance voltage division mode, and discharges electromagnetic wave signals in a coupling manner from a GIS, so that the detection, diagnosis and positioning of local discharge signals are realized; therefore, the energy taking module is additionally arranged, a rechargeable battery and a super capacitor are arranged in the energy taking module, and the super capacitor and the battery are charged by dividing the pressure of the built-in sensor capacitor to drive the data acquisition module, the data processing module and the wireless transmission module.
Referring to fig. 3, according to the formula U1 ═ Um × C2/(C1+ C2), it can be known that, as long as different energy-taking capacitor plates are arranged according to GIS of different voltage classes, so that the capacitance to ground C1 is much larger than the capacitance to ground C2(C1/C2> >5000), the voltage obtained by induction inside the GIS is within the period of 20V to 200V, and then the functions of the data acquisition module and the communication module of the uhf sensor can be realized through rectification by the rectifier circuit.
The electric capacity of typical capacitanc board and the inside conducting rod of GIS is about pF level, sets up the electric capacity of capacitanc board to ground and can satisfy its size requirement for uF (be 106pF) level. Typical values are given in the following table:
| voltage class (kV) | Capacitance C2(pF) | Capacitance C1(uF) |
| 1000 | 10 | 10 |
| 500 | 20 | 10 |
| 220 | 20 | 10 |
In one embodiment, after the built-in ultrahigh frequency sensor samples the partial discharge signal, the partial discharge signal is sent to the data acquisition module;
the data acquisition module converts the partial discharge signal into target data and sends the target data to the data processing module through the wireless transmission module;
the data processing module is in communication connection with the partial discharge visualization platform.
In a specific embodiment, the data acquisition module performs amplification, filtering and analog-to-digital conversion on the acquired partial discharge signal (analog signal) to acquire target data (digital signal).
In a specific embodiment, the partial discharge visualization platform is in communication connection with the data processing module through a 5G technology, and data transmission is completed by adopting a unified authentication framework and an encryption transmission mode.
In consideration of the fact that all service subsystems of the power system have a perfect data transmission system, the information transmission backbone network is built. The power system 5G safe access scheme can be divided into two steps: a. the information security access of the power terminal equipment-5G base station is realized by utilizing the technologies of encryption, authentication, network slice isolation, slice authentication, management interface protection, differentiation configuration, slice intelligent protection strategies and the like; and b, the MEC server is deployed in a transformer substation in a sinking way to form a 5G wireless local area network in a local area of the power system, so that local shunt access of data information of the power system to a power communication private network is realized, and the information security access in the data transmission process of the power system is ensured by matching with necessary protection measures.
In one embodiment, the data processing module performs denoising processing on the target data before processing the target data; the denoising processing in the embodiment is realized by combining a wavelet denoising algorithm and spectral subtraction.
The essence of wavelet de-noising is to find the signal under test to contain the component most correlated to the wavelet mother function. Wavelet analysis is widely applied in the fields of image signal processing, rolling bearing vibration signal processing and feature extraction, power system fault signal processing, power system signal denoising, signal denoising and data compression, partial discharge signal extraction and denoising and the like.
The wavelet transform has a higher frequency resolution and a lower time resolution in the low frequency part and a higher time resolution and a lower frequency resolution in the high frequency part. Wavelet transformation involves several steps of mother wavelet selection, threshold function determination, decomposition scale selection, etc. The mother wavelet is selected by calculating the cross-correlation coefficient rho of the discharge pulse and the mother wavelet, so that the wavelet with the maximum rho value is the optimal mother wavelet. The threshold function comprises a hard threshold and a soft threshold, a hard threshold method is adopted for the low-scale decomposition signal, and a soft threshold processing method is adopted for the high-scale decomposition signal.
The decomposition scale is related to the interference characteristic, the energy of the narrow-band interference is concentrated, the energy is only distributed on the limited scale after wavelet transformation, and the wavelet coefficient of each layer is uniform. However, the frequency range of the discharge signal is large, and the energy after wavelet transformation exists in a mode maximum value in all scales. If the frequency bands of the two are obviously differentiated, the purpose can be achieved only by selecting reasonable decomposition scales and setting a plurality of scales with concentrated narrow-band interference to be zero.
However, when the frequency bands of the two are overlapped in scale, a special method is needed to filter the frequency bands. In addition, although the wavelet transform has good noise suppression capability, the waveform distortion after denoising is serious.
The principle of the wavelet threshold denoising concept is that a threshold is set for wavelet coefficients of acquired signals on various scales, if the coefficient on a certain scale is larger than the threshold, the coefficient is considered to correspond to a discharge signal, and if the coefficient is smaller than the threshold, the coefficient corresponds to a noise signal. And finally, reconstructing a new wavelet coefficient obtained by threshold processing by utilizing wavelet inverse transformation so as to obtain a denoised signal.
The wavelet threshold denoising process comprises three steps:
a. wavelet decomposition: selecting wavelet base and decomposition layer number, carrying out wavelet decomposition on the noisy signal to obtain high-frequency detail coefficient and low-frequency similarity coefficient,
b. threshold processing: and processing the wavelet coefficient obtained by wavelet decomposition by adopting a soft threshold function.
c. And (3) reconstruction: and performing wavelet reconstruction on the wavelet coefficient subjected to threshold processing to obtain a denoised signal.
The spectral subtraction method is widely applied in the field of voice enhancement, noise is assumed to be additive noise of stable transformation, and a noise spectrum is subtracted from a signal spectrum to obtain a partial discharge signal spectrum. However, in practice, ideal stationary noise hardly exists, noise and signal are always superimposed, and if only the statistical average of the section of the signal without discharge signal is used as noise for power spectrum subtraction, some spectrum peaks will remain. These spectral peaks remaining in the frequency domain appear as a superposition of sinusoidal signals in the time domain, which is "musical noise". Although the spectral subtraction method can ensure that the denoised waveform is consistent with the original waveform, the interference suppression capability is limited, discharge pulses are filtered out when the noise estimation is too large, and music noise remains when the noise estimation is smaller.
The selection of the threshold in the wavelet denoising method has a close relation to the distortion of the denoised signal. Therefore, in the embodiment, the advantages of the wavelet denoising algorithm and the spectral subtraction are combined, the partial discharge signal is denoised, then the wavefront time of the partial discharge pulse is extracted from the signal subjected to denoising pretreatment, and the denoising effect and the positioning accuracy improvement condition are researched.
In one embodiment, the data processing module processes the target data, including:
converting target data into a partial discharge detection map, and extracting numerical values and coordinates of data points in the detection data to generate a PRPD data matrix;
and analyzing the PRPD data matrix to obtain a detection result, sending the detection result to the partial discharge visualization platform, and storing the detection result.
In the embodiment, the generation method of the PRPD data matrix refers to the invention patent with application number 2017108666211, and the accurate and sustainable detection of the ultrahigh frequency partial discharge can be realized by combining the existing partial discharge detection analysis method.
The working principle of the invention is as follows:
the energy acquisition module continuously stores energy in a capacitance voltage division mode of the built-in ultrahigh frequency sensor and supplies power to the data acquisition module, the data processing module and the wireless transmission module in the detection unit.
After the built-in ultrahigh frequency sensor samples the partial discharge signal, the partial discharge signal is sent to a data acquisition module; the data acquisition module converts the partial discharge signal into target data and sends the target data to the data processing module through the wireless transmission module.
The data processing module converts the target data into a partial discharge detection map, extracts the numerical values and coordinates of data points in the detection data and generates a PRPD data matrix; and analyzing the PRPD data matrix to obtain a detection result, sending the detection result to the partial discharge visualization platform, and storing the detection result.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the accompanying claims.
Claims (8)
1. A built-in wireless self-powered ultrahigh frequency partial discharge detection method is characterized by comprising the following steps:
the energy acquisition module is used for inducing energy storage through capacitance voltage division integrated with the built-in ultrahigh frequency sensor and supplying power to a detection unit in the built-in ultrahigh frequency sensor system; the detection unit comprises a data acquisition module, a wireless transmission module and a data processing module;
the data acquisition module acquires the partial discharge signal through a built-in ultrahigh frequency sensor connected with the data acquisition module, and processes and stores the partial discharge signal by combining with the data processing module.
2. The method for detecting the ultrahigh frequency partial discharge of the built-in wireless self-energy-taking module according to claim 1, wherein a rechargeable battery and a super capacitor are built in the energy-taking module, and the super capacitor and the rechargeable battery are charged in a capacitive voltage division manner integrated by a built-in ultrahigh frequency sensor.
3. The method for detecting the UHF partial discharge of claim 1, wherein the energy-taking module is connected to a data acquisition module, a data processing module and a wireless transmission module respectively, and the data processing module is connected to the data acquisition module and the wireless transmission module respectively.
4. The method for detecting the built-in wireless self-powered ultrahigh frequency partial discharge according to claim 1, wherein the built-in ultrahigh frequency sensor samples a partial discharge signal and sends the partial discharge signal to a data acquisition module;
the data acquisition module converts the partial discharge signal into target data and sends the target data to the data processing module through the wireless transmission module; wherein the target data is a digital signal;
and the data processing module is in communication connection with the partial discharge visualization platform.
5. The method for detecting the built-in wireless self-powered ultrahigh frequency partial discharge according to claim 4, wherein the partial discharge visualization platform acquires data in the data processing module in real time or at regular time and performs visualization display.
6. The method for detecting the built-in wireless self-energizing UHF partial discharge according to claim 4, characterized in that the partial discharge visualization platform is in communication connection with the data processing module through 5G technology, and data transmission is completed by adopting a unified authentication framework and an encryption transmission mode.
7. The method for detecting the UHF partial discharge of the built-in wireless self-energy taking device as claimed in claim 4, wherein the de-noising process is performed on the target data before the data processing module processes the target data; the denoising processing is realized by combining a wavelet denoising algorithm and a spectral subtraction method.
8. The method for detecting the UHF partial discharge of the built-in wireless self-powered device according to claim 4, wherein the data processing module processes target data, comprising:
converting target data into a partial discharge detection map, and extracting numerical values and coordinates of data points in the detection data to generate a PRPD data matrix;
and analyzing the PRPD data matrix to obtain a detection result, sending the detection result to the partial discharge visualization platform, and storing the detection result.
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| CN115980528A (en) * | 2023-02-14 | 2023-04-18 | 湖南湘能智能配电设备有限公司 | Ring main unit noise signal rapid diagnosis and elimination method and device |
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