Grid Equipment Fault Monitoring Method Based on Non-Contact High-Voltage Current Transformer

Abstract

The present invention discloses a method for monitoring grid equipment faults based on non-contact high-voltage transformers, which relates to the technical field of non-contact high-voltage transformers and includes the following steps: obtaining transformer nodes in the area to be measured, labeling the transformer nodes, and obtaining grid fault data of the nodes to be measured through the transformers; analyzing the influence of electrical noise sources on the transformers based on linear regression and correcting the grid fault data; constructing a grid fault coefficient model based on the grid fault data using a machine learning algorithm; dividing the area to be measured into multiple sub-areas, calculating the average grid fault coefficient of each sub-area based on the grid fault coefficient model; correcting the coefficient of the sub-area to be measured through the sub-areas connected to the sub-area to be measured to obtain the corrected grid fault coefficient; The present application constructs a grid fault coefficient model to solve the problem of being unable to comprehensively and accurately identify the types and causes of equipment faults.

Description

Technical Field

[0001] The present invention relates to the technical field of non-contact high-voltage transformers. More specifically, the present invention relates to a method for monitoring grid equipment faults based on non-contact high-voltage transformers. Background Art

[0002] Non-contact high-voltage transformers are widely used in power systems for the measurement and monitoring of current and voltage. Their core function is to convert high-voltage current or voltage signals into low-voltage signals for subsequent use by control, monitoring, and protection equipment. With the continuous expansion of the scale of the power system, the operating environment of grid equipment has become increasingly complex, and the monitoring and diagnosis of equipment faults have become key issues for ensuring the safe and stable operation of the power grid.

[0003] In recent years, the application of non-contact technologies has gradually emerged, especially in the fields of power equipment monitoring and power grid stability optimization. As an innovative sensor, non-contact high-voltage transformers have the characteristics of non-destructive measurement, high precision, and high reliability. Non-contact high-voltage transformers obtain voltage and current information in the power system through the principle of electromagnetic induction, which can not only effectively reduce the maintenance cost of traditional contact transformers but also improve the safety and real-time performance of power grid operation. Its working principle is mainly based on the changes in induced current and induced voltage, and precisely measures the electrical parameters of transmission lines in the power grid through non-contact means, providing data support for the dispatching, control, and optimization of the power grid.

[0004] In the above disclosed technical solutions, at least the following technical problems exist:

[0005] Traditional fault diagnosis mainly relies on human experience and lacks intelligent and automated analysis means, resulting in poor accuracy and timeliness of fault diagnosis, and it is easy to miss potential fault hazards. In addition, the existing monitoring systems have limited ability to analyze the cross-influence of multiple power parameters in complex power grid environments, resulting in the inability to comprehensively and accurately identify the types and causes of equipment faults. In view of the above problems, the present invention proposes a solution. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for monitoring grid equipment faults based on non-contact high-voltage transformers, by constructing a grid fault coefficient model to solve the problem of being unable to comprehensively and accurately identify the types and causes of equipment faults.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A power grid equipment fault monitoring method based on a non-contact high-voltage transformer includes: obtaining transformer nodes in the area to be measured, labeling the transformer nodes, and obtaining power grid fault data of the nodes to be measured through the transformers; analyzing the influence of electrical noise sources on the transformers based on linear regression and correcting the power grid fault data; constructing a power grid fault coefficient model based on a machine learning algorithm according to the power grid fault data; dividing the area to be measured into multiple sub-areas, calculating the average power grid fault coefficient of each sub-area based on the power grid fault coefficient model; correcting the coefficient of the sub-area to be measured through the sub-areas connected to the sub-area to be measured to obtain the corrected power grid fault coefficient; sorting the corrected power grid fault coefficients in descending order to form a sorting form, and performing maintenance according to the sorting form and a preset power grid equipment fault database.

[0009] In a preferred embodiment, the power grid fault data includes a voltage fluctuation coefficient, and the specific steps for obtaining the voltage fluctuation coefficient are as follows: obtaining the electrical signal data of the transformer node to be measured, and amplifying the collected electrical signal through an amplifier; transmitting the signal amplified by the amplifier to a signal processing unit, where the signal processing unit includes a filter, a signal conditioning circuit, and a digital converter; processing the signal data through the filter in the signal processing unit to remove noise and interference and retain the effective signal; converting the processed signal data into voltage fluctuation data through the digital converter in the signal processing unit, adding and averaging the voltage fluctuation data to obtain the average value of the voltage; calculating the standard deviation of the voltage fluctuation based on the voltage fluctuation data and the average value of the voltage according to the standard deviation formula; calculating the voltage fluctuation coefficient based on the standard deviation of the voltage fluctuation and the average value of the voltage according to a preset voltage fluctuation formula.

[0010] In a preferred embodiment, the power grid fault data includes a harmonic intensity, and the specific steps for obtaining the harmonic intensity are as follows: obtaining the current signal of the transformer node to be measured, and transmitting the current signal to a signal processing unit to process the signal to remove noise and interference; uploading the processed current signal to an FFT analysis tool, performing Fourier transform on the current signal through the FFT analysis tool to convert the time-domain signal into a frequency signal, and extracting the frequency and amplitude from the frequency signal; according to the frequency, finding the frequency point with the maximum amplitude in the frequency as the fundamental frequency; performing FFT conversion on the time-domain signal to obtain a set of amplitude and phase data, calculating the amplitude output by the amplitude and phase data based on a preset amplitude spectrum formula to obtain the amplitude spectrum; analyzing the frequency points near the fundamental frequency in the amplitude spectrum, obtaining the harmonic frequency according to the principle that the harmonic frequency is an integer multiple of the fundamental frequency, and obtaining the harmonic amplitude and the fundamental amplitude according to the harmonic frequency and the fundamental frequency; calculating the harmonic intensity based on the harmonic amplitude and the fundamental amplitude according to a preset harmonic intensity formula.

[0011] In a preferred embodiment, the power grid fault data includes electromagnetic compatibility, and the specific acquisition steps of the electromagnetic compatibility are as follows: Obtain the device voltage data monitored by the to-be-tested mutual inductor node, add and average the peak value and the valley value of the voltage data respectively to obtain the average voltage peak value and the average voltage valley value; Delete the data higher than the average voltage peak value and lower than the average voltage valley value according to the average voltage peak value and the average voltage valley value, add and average the remaining voltage data after deletion to obtain the average voltage; Obtain the distance from the electric field source of the to-be-tested mutual inductor node to the receiving point, and calculate based on the electric field strength formula according to the average voltage and the distance from the electric field source to the receiving point to obtain the electric field strength; Obtain the device current data monitored by the to-be-tested mutual inductor node, add and average the peak value and the valley value of the current data respectively to obtain the average current peak value and the average current valley value; Delete the data higher than the average current peak value and lower than the average current valley value according to the average current peak value and the average current valley value, add and average the remaining current data after deletion to obtain the average current; Calculate based on the magnetic field strength formula according to the average current and the distance from the electric field source to the receiving point to obtain the magnetic field strength; Obtain the power supply impedance and the circuit impedance of the to-be-tested device, and calculate based on the preset electromagnetic radiation power formula according to the average current, the power supply impedance and the circuit impedance to obtain the electromagnetic radiation power; Calculate based on the preset electromagnetic compatibility formula according to the electromagnetic radiation power, the magnetic field strength and the electric field strength to obtain the electromagnetic compatibility.

[0012] In a preferred embodiment, the influence of the electrical noise source on the mutual inductor is analyzed based on linear regression analysis, and the power grid fault data is corrected. The specific steps are as follows: Obtain the to-be-tested mutual inductor node, isolate the noise source by using high-efficiency electromagnetic shielding materials, and record the signal power and the noise power without being affected by the noise source; Calculate based on the signal-to-noise ratio formula according to the signal power and the noise power to obtain the signal-to-noise ratio without the noise source; Turn on the noise source radiation device and adjust the power of the device, record the signal power and the noise power at different powers, and calculate based on the signal-to-noise ratio formula to obtain the signal-to-noise ratios under multiple different noise sources; Based on linear regression analysis according to the signal-to-noise ratios under different noise sources and the signal-to-noise ratio without being affected by the noise source, obtain the accuracy influence coefficient of the electrical noise source, and correct the voltage fluctuation coefficient, the harmonic intensity and the electromagnetic compatibility parameters through the accuracy influence coefficient of the electrical noise source.

[0013] In a preferred embodiment, the method of dividing the area to be measured into multiple sub - regions and calculating the average grid fault coefficient of each sub - region based on the grid fault coefficient model is as follows: Obtain the coverage area range of the measuring transformer node to be measured, and divide it into N sub - regions of the same size according to the coverage area range of the measuring transformer node; Obtain the grid fault coefficients of all transformer nodes in the sub - region, and add and average the grid fault coefficients of all transformer nodes in the sub - region to obtain the grid fault coefficient of the sub - region.

[0014] In a preferred embodiment, the method of sorting the corrected grid fault coefficients in descending order and performing maintenance according to the sorted form and the preset grid equipment fault database is as follows: Obtain the corrected grid fault coefficients of the sub - regions, sort them in descending order according to the magnitude of the corrected grid fault coefficients. If the grid fault coefficient exceeds the threshold, an alarm will be issued to remind the administrator to perform maintenance; The administrator maintains the grid equipment according to the sorted form and the grid equipment fault database. During the maintenance of each node, compare the waveforms and fault causes in the grid equipment fault database, and correct the waveforms and fault causes in the grid equipment fault database; After N times of maintenance, if the equipment is still in a fault state, check the transformers around the equipment. If the transformers are not faulty, scrap the equipment and replace it with a new one.

[0015] In a preferred embodiment, the grid equipment fault database is specifically as follows: Obtain the measuring transformer node to be measured, and collect the voltage signal and current signal of the equipment to be measured in real - time through the transformer, and convert the collected voltage signal and current signal into a low - voltage signal that can be processed; Filter the collected voltage data and current data, and reconstruct the voltage data and current data into complete voltage waveforms and current waveforms through DSP technology. At the same time, correct the voltage waveforms and current waveforms through the electrical noise source accuracy influence coefficient; Obtain the voltage waveforms and current waveforms under normal operating conditions as standard waveforms; By comparing the standard waveforms with the real - time voltage and current waveforms, find the places where the voltage and current waveforms deviate and are unstable, analyze the reasons for the deviation and instability of the voltage waveforms and current waveforms, and record the waveforms and reasons for the deviation and instability of the voltage waveforms and current waveforms in the database.

[0016] The technical effects and advantages of a grid equipment fault monitoring method based on a non - contact high - voltage transformer of the present invention:

[0017] 1. The present invention collects power grid fault data in real time through a non-contact high-voltage transformer, including various parameters such as voltage fluctuation coefficient, harmonic intensity, and electromagnetic compatibility. By precisely analyzing these data, it can more comprehensively reflect the operating state of power grid equipment, providing higher fault detection accuracy than traditional methods. By real-time monitoring and comparing the voltage waveform and current waveform of the equipment, abnormal operating conditions of the equipment can be detected in a timely manner, fault modes of the equipment can be identified, and these fault data can be entered into the database for long-term tracking and analysis, thereby realizing the health management and precise maintenance of power grid equipment.

[0018] 2. Based on the corrected power grid fault coefficient and power grid fault coefficient, the method of the present invention can automatically generate a descending order form to guide the maintenance personnel to give priority to dealing with areas with greater fault risks. By combining with the power grid equipment fault database to form a data-driven decision support system, the fault source can be more accurately located and repaired in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic structural diagram of a power grid equipment fault monitoring method based on a non-contact high-voltage transformer according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0021] Embodiment 1, Figure 1 A power grid equipment fault monitoring method based on a non-contact high-voltage transformer according to the present invention is given, including:

[0022] S1. Obtain the transformer nodes in the area to be measured, label the transformer nodes, and obtain the power grid fault data of the nodes to be measured through the transformer. The power grid fault data includes voltage fluctuation coefficient, harmonic intensity, and electromagnetic compatibility.

[0023] In this embodiment, the steps of obtaining the transformer nodes in the area to be measured, labeling the transformer nodes, and obtaining the power grid fault data of the nodes to be measured through the transformer, where the power grid fault data includes voltage fluctuation coefficient, harmonics, and electromagnetic compatibility, are as follows:

[0024] Voltage fluctuation coefficient. The voltage fluctuation coefficient is an index used to measure voltage fluctuation or voltage change. It represents the degree of voltage change relative to its average value. Usually, it is used to evaluate the voltage stability in the power system, especially in the case of large load fluctuations.

[0025] The power grid fault data includes a voltage fluctuation coefficient, and the specific steps for obtaining the voltage fluctuation coefficient are as follows:

[0026] Obtain the electrical signal data of the current transformer node to be measured, and amplify the collected electrical signal through an amplifier;

[0027] Transmit the signal amplified by the amplifier to the signal processing unit, and the signal processing unit includes a filter, a signal conditioning circuit, and a digital converter;

[0028] Process the signal data through the filter in the signal processing unit to remove noise and interference and retain the effective signal;

[0029] Convert the processed signal data into voltage fluctuation data through the digital converter in the signal processing unit, and add and average the voltage fluctuation data to obtain the average value of the voltage;

[0030] Calculate the standard deviation of the voltage fluctuation based on the standard deviation formula according to the voltage fluctuation data and the average value of the voltage;

[0031] Calculate the voltage fluctuation coefficient based on the preset voltage fluctuation formula according to the standard deviation of the voltage fluctuation and the average value of the voltage.

[0032] The specific calculation formula of the voltage fluctuation coefficient is as follows:

[0033]

[0034] The specific calculation formula of the average value of the voltage is as follows:

[0035]

[0036] The specific calculation formula of the standard deviation of the voltage fluctuation is as follows:

[0037]

[0038] In the formula, is the voltage fluctuation coefficient, is the standard deviation of the voltage fluctuation, is the average value of the voltage, is the total number of data points, is the voltage at the i-th time point, i = 1, 2, 3 ····· N.

[0039] It should be noted that the voltage fluctuation coefficient reflects the relative amplitude of voltage change. If the voltage fluctuation coefficient is small, it means that the voltage fluctuation is small and the power system is relatively stable. If the voltage fluctuation coefficient is large, it indicates that the voltage fluctuation is large and there may be problems with voltage instability in the system.

[0040] Harmonic intensity. Harmonic intensity refers to the frequency components in a periodic signal other than the fundamental frequency. These components are usually integer multiples of the fundamental frequency. Harmonic analysis is commonly used in the fields of power systems, audio processing, and vibration analysis.

[0041] The power grid fault data includes harmonic intensity. The specific steps for obtaining the harmonic intensity are as follows:

[0042] Obtain the current signal of the node of the transformer under test and transmit the current signal to the signal processing unit. The signal processing unit processes the signal to remove noise and interference.

[0043] Upload the processed current signal to the FFT (Fast Fourier Transform) analysis tool. The FFT (Fast Fourier Transform) analysis tool performs Fourier transform on the current signal to convert the time-domain signal into a frequency-domain signal, and extracts the frequency and amplitude from the frequency-domain signal.

[0044] According to the frequency, find the frequency point with the maximum amplitude in the frequency, and use the frequency point with the maximum amplitude as the fundamental frequency.

[0045] Perform FFT (Fast Fourier Transform) conversion on the time-domain signal to obtain a set of amplitude and phase data. Calculate the amplitude output from the amplitude and phase data based on a preset amplitude spectrum formula to obtain the amplitude spectrum.

[0046] Analyze the frequency points near the fundamental frequency in the amplitude spectrum. Obtain the harmonic frequency according to the principle that the harmonic frequency is an integer multiple of the fundamental frequency. Obtain the harmonic amplitude and the fundamental amplitude based on the harmonic frequency and the fundamental frequency.

[0047] Calculate based on the harmonic amplitude and the fundamental amplitude according to a preset harmonic intensity formula to obtain the harmonic intensity.

[0048] The specific calculation formula for the harmonic intensity is as follows:

[0049]

[0050] The specific calculation formula for the amplitude spectrum is as follows:

[0051]

[0052] In the formula, is the harmonic intensity, represents the amplitude of the nth harmonic, represents the fundamental amplitude, is the amplitude output from the amplitude and phase data, is the real part of the frequency point of the amplitude and phase data, is the imaginary part of the frequency point of the amplitude and phase data.

[0053] Electromagnetic compatibility. Electromagnetic compatibility (EMC) is an important aspect to ensure the normal operation of equipment in power systems, especially in smart grids. For the electromagnetic interference (EMI) generated by high-voltage currents in the grid, the intensity and impact of the electromagnetic field are detected through non-contact high-voltage transformers to help evaluate and solve electromagnetic compatibility problems.

[0054] The grid fault data includes electromagnetic compatibility, and the specific steps for obtaining the electromagnetic compatibility are as follows:

[0055] Obtain the device voltage data monitored by the transformer node to be measured, and respectively add and average the peak and valley values of the voltage data to obtain the average voltage peak value and the average voltage valley value;

[0056] Delete the data higher than the average voltage peak value and lower than the average voltage valley value according to the average voltage peak value and the average voltage valley value, and add and average the remaining voltage data after deletion to obtain the average voltage;

[0057] Obtain the distance from the electric field source to the receiving point of the transformer node to be measured, and calculate based on the electric field strength formula according to the average voltage and the distance from the electric field source to the receiving point to obtain the electric field strength;

[0058] Obtain the device current data monitored by the transformer node to be measured, and respectively add and average the peak and valley values of the current data to obtain the average current peak value and the average current valley value;

[0059] Delete the data higher than the average current peak value and lower than the average current valley value according to the average current peak value and the average current valley value, and add and average the remaining current data after deletion to obtain the average current;

[0060] Calculate based on the magnetic field strength formula according to the average current and the distance from the electric field source to the receiving point to obtain the magnetic field strength;

[0061] Obtain the power impedance and circuit impedance of the device to be measured, and calculate based on a preset electromagnetic radiation power formula according to the average current, power impedance, and circuit impedance to obtain the electromagnetic radiation power;

[0062] Calculate based on a preset electromagnetic compatibility formula according to the electromagnetic radiation power, magnetic field strength, and electric field strength to obtain the electromagnetic compatibility.

[0063] The specific calculation formula for the electromagnetic compatibility is as follows:

[0064]

[0065] The specific calculation formula for the electromagnetic compatibility is as follows:

[0066]

[0067] In the formula, is electromagnetic compatibility, is the electromagnetic radiation power, is the electromagnetic radiation power under normal conditions, is the electric field strength, is the electric field strength under normal conditions, is the magnetic field strength, is the magnetic field strength under normal conditions, is the free space wave impedance, , , and are adjustment coefficients used to weigh the different contributions of the electric field, magnetic field, and radiation power to electromagnetic compatibility, is the impedance of the circuit, is the impedance of the power supply, is the current.

[0068] S2. Based on linear regression analysis, analyze the influence of electrical noise sources on the transformer and correct the power grid fault data.

[0069] In this embodiment, the steps of analyzing the influence of electrical noise sources on the transformer based on linear regression analysis and correcting the power grid fault data are as follows:

[0070] Obtain the node of the transformer to be measured, isolate the noise source using high-efficiency electromagnetic shielding materials, and record the signal power and noise power without being affected by the noise source;

[0071] Based on the signal power and noise power, calculate according to the signal-to-noise ratio formula to obtain the signal-to-noise ratio without the influence of the noise source;

[0072] Turn on the noise source radiation device and adjust the power of the device. Record the signal power and noise power at different powers, and calculate based on the signal-to-noise ratio formula to obtain multiple groups of signal-to-noise ratios under different noise sources;

[0073] Based on linear regression analysis of the signal-to-noise ratios under different groups of noise sources and the signal-to-noise ratio without being affected by the noise source, obtain the influence coefficient of the electrical noise source accuracy, and correct the voltage fluctuation coefficient, harmonic intensity, and electromagnetic compatibility parameters through the influence coefficient of the electrical noise source accuracy.

[0074] S3. Construct a power grid fault coefficient model based on the power grid fault data using a machine learning algorithm.

[0075] In this embodiment, constructing a power grid fault coefficient model based on the power grid fault data using a machine learning algorithm is as follows:

[0076] The specific calculation formula of the power grid fault coefficient model is as follows:

[0077]

[0078] Wherein, is the power grid fault coefficient, is the voltage fluctuation coefficient, is the harmonic intensity, is the electromagnetic compatibility, is the influence coefficient of the accuracy of the electrical noise source, is the natural base.

[0079] S4. Divide the area to be measured into multiple sub-areas, and calculate the average power grid fault coefficient of each sub-area based on the power grid fault coefficient model.

[0080] In this embodiment, the steps of dividing the area to be measured into multiple sub-areas and calculating the average power grid fault coefficient of each sub-area based on the power grid fault coefficient model are as follows:

[0081] Obtain the coverage area range of the current transformer node to be measured, and divide it into N sub-areas of the same size according to the coverage area range of the current transformer node to be measured;

[0082] Obtain the power grid fault coefficients of all current transformer nodes in the sub-area, and add and average the power grid fault coefficients of all current transformer nodes in the sub-area to obtain the power grid fault coefficient of the sub-area.

[0083] S5. Perform coefficient correction on the sub-area to be measured through the sub-areas connected to the sub-area to be measured, and obtain the corrected power grid fault coefficient.

[0084] In this embodiment, the steps of performing coefficient correction on the sub-area to be measured through the sub-areas connected to the sub-area to be measured and obtaining the corrected power grid fault coefficient are as follows:

[0085] The calculation formula of the corrected power grid fault coefficient is as follows:

[0086]

[0087] Wherein, is the corrected power grid fault coefficient, is the power grid fault coefficient, is the weight coefficient, is the number of sub-areas connected to the sub-area to be measured, represents the weight coefficient of the i-th sub-area connected to the sub-area to be measured.

[0088] S6. Sort the corrected power grid fault coefficients in descending order to form a sorted list, and perform maintenance according to the sorted list and the preset power grid equipment fault database.

[0089] In this embodiment, for the form of sorting the corrected grid fault coefficients in descending order, maintenance is performed according to the sorting form and a preset grid equipment fault database, as follows:

[0090] Obtain the corrected grid fault coefficients of the sub-region, sort them in descending order according to the magnitudes of the corrected grid fault coefficients. If the grid fault coefficient exceeds the threshold, an alarm will be issued to remind the administrator to perform maintenance;

[0091] The administrator maintains the grid equipment according to the sorting form and the grid equipment fault database. During the repair of each node, the waveforms and fault causes in the grid equipment fault database are compared, and the waveforms and fault causes in the grid equipment fault database are corrected;

[0092] After N repairs, if the equipment is still in a fault state, the transformers around the equipment will be inspected. If the transformers are not faulty, the equipment will be scrapped and replaced with new equipment.

[0093] In this embodiment, the grid equipment fault database is specifically:

[0094] Obtain the nodes of the transformers to be measured, collect the voltage signal and current signal of the equipment to be measured in real time through the transformers, and convert the collected voltage signal and current signal into a low-voltage signal that can be processed;

[0095] Perform filtering processing on the collected voltage data and current data, reconstruct the voltage data and current data into complete voltage waveforms and current waveforms through DSP (Digital Signal Processor) technology, and at the same time correct the voltage waveforms and current waveforms through the accuracy influence coefficient of the electrical noise source;

[0096] Obtain the voltage waveforms and current waveforms under normal working conditions as standard waveforms;

[0097] By comparing the standard waveforms with the real-time voltage and current waveforms, find the places where the voltage and current waveforms deviate and are unstable, analyze the reasons for the deviation and instability of the voltage waveforms and current waveforms, and record the waveforms and reasons for the deviation and instability of the voltage waveforms and current waveforms in the database.

[0098] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by software simulation of a large amount of collected data to get a formula closest to the real situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0099] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0100] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0101] In addition, in each embodiment of this application, the functional modules can be integrated into a processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0102] As described above, this is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0103] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for monitoring faults of power grid equipment based on a non-contact high-voltage transformer, characterized in that Including: Obtain the transformer nodes in the area to be measured, label the transformer nodes, and obtain the power grid fault data of the nodes to be measured through the transformer. The power grid fault data includes voltage fluctuation coefficient, harmonic intensity, and electromagnetic compatibility; Based on linear regression analysis, analyze the influence of electrical noise sources on the transformer and correct the power grid fault data; Construct a power grid fault coefficient model based on the machine learning algorithm according to the power grid fault data; Divide the area to be measured into multiple sub-areas, and calculate the average power grid fault coefficient of each sub-area based on the power grid fault coefficient model; Perform coefficient correction on the sub-area to be measured through the sub-areas connected to the sub-area to be measured to obtain the corrected power grid fault coefficient; Sort the corrected power grid fault coefficients in descending order to obtain a sorted form, and perform maintenance according to the sorted form and the preset power grid equipment fault database; The specific acquisition steps of electromagnetic compatibility are as follows: Obtain and filter the voltage data to calculate the average value, and combine the distance from the electric field source to the receiving point to calculate the electric field strength; Obtain and filter the current data to calculate the average value, and combine the distance from the electric field source to the receiving point to calculate the magnetic field strength; Obtain the electromagnetic radiation power, and output the electromagnetic compatibility based on the preset electromagnetic compatibility formula in combination with the electric field strength and the magnetic field strength; The power grid fault coefficient model is as follows: The electromagnetic compatibility formula is as follows: Wherein, is the power grid fault coefficient, is the voltage fluctuation coefficient, is the harmonic intensity, is the electromagnetic compatibility, is the influencing coefficient of the electrical noise source accuracy, is the natural base, is the electromagnetic compatibility, is the electromagnetic radiation power, is the electromagnetic radiation power under normal conditions, is the electric field strength, is the electric field strength under normal conditions, is the magnetic field strength, is the magnetic field strength under normal conditions, is the free space wave impedance, , , and are the adjustment coefficients.

2. The power grid equipment fault monitoring method based on a non-contact high-voltage transformer according to claim 1, wherein The power grid fault data includes a voltage fluctuation coefficient. The specific acquisition steps of the voltage fluctuation coefficient are as follows: Obtain the electrical signal data of the transformer node to be measured, and amplify the collected electrical signal through an amplifier; Transmit the signal amplified by the amplifier to the signal processing unit, and the signal processing unit includes a filter, a signal conditioning circuit, and a digital converter; Process the signal data through the filter in the signal processing unit to remove noise and interference and retain the effective signal; Convert the processed signal data into voltage fluctuation data through the digital converter in the signal processing unit, add and average the voltage fluctuation data to calculate the average value of the voltage; Calculate based on the voltage fluctuation data and the average value of the voltage according to the standard deviation formula to obtain the standard deviation of the voltage fluctuation; Calculate based on the standard deviation of the voltage fluctuation and the average value of the voltage according to the preset voltage fluctuation formula to obtain the voltage fluctuation coefficient.

3. The power grid equipment fault monitoring method based on a non-contact high-voltage transformer according to claim 2, wherein The power grid fault data includes harmonic intensity. The specific acquisition steps of the harmonic intensity are as follows: Obtain the current signal of the transformer node to be measured, transmit the current signal to the signal processing unit, and process the signal through the signal processing unit to remove noise and interference; Upload the processed current signal to the FFT analysis tool, perform Fourier transform on the current signal through the FFT analysis tool, convert the time-domain signal into a frequency signal, and extract the frequency and amplitude from the frequency signal; According to the frequency, find the frequency point with the maximum amplitude in the frequency, and use the frequency point with the maximum amplitude as the fundamental frequency; Perform FFT conversion on the time-domain signal to obtain a set of amplitude and phase data, calculate the amplitude output by the amplitude and phase data based on the preset amplitude spectrum formula to obtain the amplitude spectrum; Analyze the frequency points near the fundamental frequency in the amplitude spectrum, obtain the harmonic frequencies according to the principle that the harmonic frequencies are integer multiples of the fundamental frequency, and obtain the harmonic amplitudes and the fundamental amplitude based on the harmonic frequencies and the fundamental frequency; Calculate based on the harmonic amplitudes and the fundamental amplitude according to a preset harmonic intensity formula to obtain the harmonic intensity.

4. The method for monitoring faults of power grid equipment based on a non-contact high-voltage transformer according to claim 3, wherein, The influence of the electrical noise source on the mutual inductor is analyzed based on linear regression analysis, and the power grid fault data is corrected. The specific steps are as follows: Obtain the mutual inductor node to be measured, isolate the noise source using high-efficiency electromagnetic shielding materials, and record the signal power and noise power without being affected by the noise source; Calculate based on the signal power and the noise power according to the signal-to-noise ratio formula to obtain the signal-to-noise ratio without the noise source; Turn on the noise source radiation device, adjust the power of the device, record the signal power and noise power at different powers, and calculate based on the signal-to-noise ratio formula to obtain multiple groups of signal-to-noise ratios under different noise sources; Based on linear regression analysis of the signal-to-noise ratios under different groups of noise sources and the signal-to-noise ratio without being affected by the noise source, obtain the electrical noise source accuracy influence coefficient, and correct the voltage fluctuation coefficient, harmonic intensity, and electromagnetic compatibility parameters through the electrical noise source accuracy influence coefficient.

5. The method for monitoring grid equipment faults based on a non-contact high-voltage transformer according to claim 4, characterized in that, The area to be measured is divided into multiple sub-areas, and the average power grid fault coefficient of each sub-area is calculated based on the power grid fault coefficient model. Specifically as follows: Obtain the coverage area range of the mutual inductor node to be measured, and divide it into N sub-areas of the same size according to the coverage area range of the mutual inductor node to be measured; Obtain the power grid fault coefficients of all the mutual inductor nodes in the sub-area, and add and average the power grid fault coefficients of all the mutual inductor nodes in the sub-area to obtain the power grid fault coefficient of the sub-area.

6. The method for monitoring grid equipment faults based on a non-contact high-voltage transformer according to claim 5, characterized in that, Sort the corrected power grid fault coefficients in descending order to obtain a sorted list, and perform maintenance according to the sorted list and a preset power grid equipment fault database. Specifically as follows: Obtain the corrected power grid fault coefficients of the sub-areas, sort them in descending order according to the magnitudes of the corrected power grid fault coefficients. If the power grid fault coefficient exceeds the threshold, an alarm will be issued to remind the administrator to perform maintenance; The administrator maintains the power grid equipment according to the sorted list and the power grid equipment fault database. During the maintenance of each node, compare the waveforms and fault causes in the power grid equipment fault database, and correct the waveforms and fault causes in the power grid equipment fault database; After N repairs, if the equipment is still in a faulty state, check the mutual inductors around the equipment. If the mutual inductors are not faulty, scrap the equipment and replace it with a new one.

7. The method for monitoring grid equipment faults based on a non-contact high-voltage transformer according to claim 6, wherein, The power grid equipment fault database is specifically as follows: Obtain the mutual inductor node to be measured, collect the voltage signal and current signal of the equipment to be measured in real time through the mutual inductor, and convert the collected voltage signal and current signal into a low-voltage signal that can be processed; Perform filtering processing on the collected voltage data and current data, reconstruct the voltage data and current data into a complete voltage waveform and current waveform through DSP technology, and at the same time correct the voltage waveform and current waveform through the electrical noise source accuracy influence coefficient; Obtain the voltage waveform and current waveform under normal operating conditions as the standard waveform; By comparing the standard waveform with the real-time voltage and current waveforms, find the places where the voltage and current waveforms deviate and become unstable, analyze the reasons for the deviation and instability of the voltage and current waveforms, and record the waveforms and reasons for the deviation and instability of the voltage and current waveforms in the database.

8. The method for monitoring grid equipment faults based on a non-contact high-voltage transformer according to claim 7, characterized in that, The sub-region connected to the sub-region to be measured is used to correct the coefficient of the sub-region to be measured, and the corrected power grid fault coefficient is obtained as follows: The calculation formula of the corrected power grid fault coefficient is as follows: In the formula, is the corrected power grid fault coefficient, is the power grid fault coefficient, is the weight coefficient, is the number of sub-regions connected to the sub-region to be measured, represents the weight coefficient of the sub-region connected to the i-th sub-region to be measured.

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