Intelligent GIS defect detection method, controller, power grid management system and medium

Abstract

The embodiment of the present invention provides an intelligent GIS defect detection method, a controller, a power grid management system and a medium. The intelligent GIS defect detection method includes: when the power grid management system detects at least one partial discharge position of the gas-insulated metal-enclosed switchgear, obtaining the partial discharge level of the partial discharge position; determining the processing sequence table of the partial discharge position according to the partial discharge level; obtaining the detection data and simulation data of the partial discharge position in sequence according to the processing sequence table; determining the defect type of the partial discharge position according to the detection data and the simulation data; generating corresponding intelligent decision-making information according to the defect type. GIS defect detection has high efficiency and low detection cost. By displaying the partial discharge position and defect type on the digital twin model, the visualization is good, and the defects of the partial discharge position with high partial discharge level are processed first, thereby minimizing the loss caused by partial discharge.

Description

Technical Field

[0001] The present invention relates to the field of, but is not limited to, electric power detection technology, and in particular to an intelligent GIS defect detection method, a controller, a power grid management system and a medium. Background Art

[0002] Gas Insulated Switchgear (GIS) has the characteristics of stable operation, small footprint, and maintenance-free, and is suitable for use in high-voltage substations in urban centers or marginal areas. However, gas-insulated power equipment such as gas-insulated switches and gas transmission pipelines will inevitably produce insulation defects such as conductor tips, scratches, and floating potentials during production, transportation, assembly, and operation. Such insulation defects will cause partial discharge or even insulation breakdown under the action of strong electric fields. Serious safety accidents. Therefore, timely detection and diagnosis of fault types in the early stage of GIS faults are of great significance to ensure the safe and reliable operation of equipment.

[0003] At present, the partial discharge detection of GIS is usually carried out using the ultra-high frequency method. After the location of the partial discharge is detected, it is necessary to manually disassemble the GIS on site to determine the specific defects and then perform corresponding maintenance. The defect detection efficiency is low and the detection cost is high. Summary of the invention

[0004] The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

[0005] The main purpose of the embodiments of the present invention is to propose an intelligent GIS defect detection method, controller, power grid management system and medium, which can improve the efficiency of GIS defect detection and reduce the detection cost.

[0006] In a first aspect, an embodiment of the present invention provides an intelligent GIS defect detection method, which is applied to a power grid management system provided with a digital twin model of a gas-insulated metal-enclosed switchgear, and the method comprises:

[0007] When the power grid management system detects at least one partial discharge location of the gas-insulated metal-enclosed switchgear, obtaining a partial discharge level of the partial discharge location;

[0008] Determine a processing sequence table of the partial discharge position according to the partial discharge level;

[0009] Acquire detection data and simulation data of the partial discharge position in sequence according to the processing sequence table, wherein the detection data represents sonar data, gas data, temperature and humidity data, and abnormal event data of the partial discharge position, and the simulation data represents simulation data of the partial discharge signal generated at the partial discharge position;

[0010] Determining a defect type at the partial discharge location according to the detection data and the simulation data, and displaying the partial discharge location and the defect type on the digital twin model;

[0011] Generate corresponding intelligent decision-making information according to the defect type.

[0012] In some optional embodiments, obtaining the partial discharge level of the partial discharge position includes:

[0013] Acquiring the partial discharge signal at the partial discharge position;

[0014] Determine the discharge amount, discharge time and discharge frequency of the local discharge position according to the partial discharge signal, wherein the discharge amount represents the discharge intensity of the local discharge position, the discharge time represents the discharge duration of the local discharge position, and the discharge frequency represents the number of discharges at the local discharge position within a preset time;

[0015] The partial discharge level is obtained by weighted calculation of the discharge amount, the discharge time and the discharge frequency.

[0016] In some optional embodiments, the partial discharge level is obtained by weighted calculation of the discharge amount, the discharge time and the discharge frequency, including:

[0017] respectively calculating a first level corresponding to the discharge amount, a second level corresponding to the discharge time, and a third level corresponding to the discharge frequency;

[0018] Obtaining a first weighting coefficient of the first level, a second weighting coefficient of the second level, and a third weighting coefficient of the third level;

[0019] The partial discharge level is calculated according to the first level, the first weighting coefficient, the second level, the second weighting coefficient, the third level and the third weighting coefficient.

[0020] In some optional embodiments, determining the defect type of the partial discharge position according to the detection data and the simulation data includes:

[0021] When the simulation data indicates that the pulse current amplitude of the partial discharge signal is less than a first threshold, the pulse repetition rate is greater than a second threshold, the pulse rise time and the pulse fall time are greater than a third threshold, the duration of the ultrasonic signal in the partial discharge signal is greater than a fourth threshold, and the spectrum peak of the partial discharge signal is greater than a fifth threshold, the discharge type of the partial discharge position is configured as corona discharge;

[0022] When the discharge type is corona discharge, the sonar data of the local discharge position is obtained, and the surface data of the local discharge position is reconstructed according to the sonar data. When the surface data indicates that there is a pointed protrusion at the local discharge position, the defect at the local discharge position is configured as an inherent defect. When the surface data indicates that there is no pointed protrusion at the local discharge position, the negative half-wave of the spectrum diagram of the partial discharge signal has a double-peak structure, and a preset amplitude and a preset waveform appear at a phase of 245-255 degrees of the spectrum diagram, the defect at the local discharge position is configured as suspended metal particles.

[0023] In some optional embodiments, the method further includes:

[0024] When the simulation data indicates that the pulse current amplitude of the partial discharge signal is greater than a sixth threshold, the pulse repetition rate is less than a seventh threshold, the pulse rise time and the fall time are less than an eighth threshold, the duration of the ultrasonic signal in the partial discharge signal is less than a ninth threshold, and the spectrum peak of the partial discharge signal is less than a tenth threshold, the discharge type of the partial discharge position is configured as electric spark discharge;

[0025] When the discharge type is the spark discharge, the temperature and humidity data of the partial discharge position are obtained, and when the temperature and humidity data indicate that the humidity of the partial discharge position is greater than a preset humidity, the defect of the partial discharge position is configured as insulator moisture, and when the temperature and humidity data indicate that the temperature of the partial discharge position is greater than a preset temperature, the defect of the partial discharge position is configured as insulator ablation;

[0026] When the temperature and humidity data indicates that the temperature and humidity at the partial discharge position are less than a preset temperature and humidity, acquiring the gas data at the partial discharge position, and when the gas data indicates that the decomposition gas content of SF6 at the partial discharge position is greater than a preset content, configuring the defect at the partial discharge position as SF6 gas decomposition;

[0027] When the gas data indicates that the decomposition gas content of SF6 at the local discharge location is less than a preset content, the abnormal event data of the local discharge location is obtained; when the abnormal event data indicates that the local discharge location has an operation event and / or a lightning event, the defect of the local discharge location is configured as an overvoltage effect.

[0028] In some optional embodiments, the sonar data is collected by a sonar device arranged inside and / or outside the gas-insulated metal-enclosed switchgear, and the ultrasonic waves emitted by the sonar device are also used to vibrate the gas-insulated metal-enclosed switchgear, so that the gas-insulated metal-enclosed switchgear generates vibration wave data, and the method further includes:

[0029] Acquiring the vibration wave data of the partial discharge position;

[0030] generating a vibration spectrum according to the vibration wave data;

[0031] When the correlation between the waveform of the vibration spectrum and the waveform of the preset defect spectrum reaches a correlation threshold, and the vibration frequency of the vibration spectrum is greater than the preset vibration frequency, the defect at the partial discharge position is configured as an aging crack.

[0032] In some optional embodiments, the method further includes:

[0033] When the simulation data indicates that the pulse current amplitude of the partial discharge signal is greater than a sixth threshold, and the frequency of the ultrasonic signal in the partial discharge signal is less than a preset frequency and the amplitude value is greater than a preset amplitude value, the defect at the partial discharge position is configured as an internal air gap.

[0034] In some optional embodiments, the gas-insulated metal-enclosed switchgear is provided with at least one first vibration sensor and at least one second vibration sensor, and before the power grid management system detects at least one partial discharge position of the gas-insulated metal-enclosed switchgear, the method for determining the partial discharge position includes:

[0035] Acquire a first vibration signal of the first vibration sensor;

[0036] Acquire a second vibration signal from the second vibration sensor;

[0037] The partial discharge position is determined according to the first vibration signal, the second vibration signal and position information.

[0038] In some optional embodiments, the gas-insulated metal-enclosed switchgear is further provided with a third vibration sensor, and the determining the partial discharge position according to the first vibration signal, the second vibration signal and the position information comprises:

[0039] Determine a difference in transmission distances from the partial discharge position to the first vibration sensor and the second vibration sensor according to a first reception time of the first vibration signal, a second reception time of the second vibration signal, and a transmission speed of a preset vibration wave;

[0040] One or more target location points are obtained according to the location information and the transmission distance difference, wherein the target location point represents a location point on the GIS where the distance difference to the first vibration sensor and the second vibration sensor is equal to the transmission distance difference, and the location information represents the spatial location information of each point on the gas-insulated metal-enclosed switchgear;

[0041] When there is only one target location point, configuring the target location point as the partial discharge location;

[0042] In the case where there are multiple target position points, a third vibration signal of the third vibration sensor is obtained, and a difference in transmission distances between the local discharge position and the first vibration sensor, the second vibration sensor and the third vibration sensor is determined according to a third receiving time of the third vibration signal, a first receiving time of the first vibration signal, a second receiving time of the second vibration signal and a transmission speed of a preset vibration wave;

[0043] The partial discharge position is obtained according to the position information and the difference between the two transmission distances.

[0044] In a second aspect, an embodiment of the present invention provides a controller comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the intelligent GIS defect detection method described in the first aspect is implemented.

[0045] In a third aspect, an embodiment of the present invention provides a power grid management system, including the controller involved in the second aspect above.

[0046] In a fourth aspect, a computer storage medium stores computer executable instructions, wherein the computer executable instructions are used to execute the intelligent GIS defect detection method described in the first aspect.

[0047] The beneficial effects of the present invention include: when the power grid management system detects at least one partial discharge location of the gas-insulated metal-enclosed switchgear, the present invention obtains the partial discharge level of the partial discharge location; determines the processing sequence table of the partial discharge location according to the partial discharge level; obtains detection data and simulation data of the partial discharge location in sequence according to the processing sequence table, the detection data represents the sonar data, gas data, temperature and humidity data and abnormal event data of the partial discharge location, and the simulation data represents the simulation data of the partial discharge signal generated by the partial discharge location; determines the defect type of the partial discharge location according to the detection data and the simulation data, and displays the partial discharge location and the defect type on the digital twin model; generates corresponding intelligent decision-making information according to the defect type. The detection data and simulation data of the partial discharge position are obtained in turn according to the partial discharge level, and the defect type of the partial discharge position is determined, so that the defects at the partial discharge position with a high partial discharge level are dealt with first, thereby minimizing the losses caused by partial discharge; and the defect type of the partial discharge position can be quickly determined through the detection data and simulation data, and the corresponding intelligent decision-making information can be made according to the defect type, which is convenient for the processing personnel to quickly handle it. The GIS defect detection efficiency is high and the detection cost is low; the partial discharge position and defect type are displayed on the digital twin model, and the visualization is good.

[0048] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a flowchart of the steps of an intelligent GIS defect detection method provided by an embodiment of the present invention;

[0050] Figure 2 is a detection schematic diagram of a vibration sensor provided by an embodiment of the present invention;

[0051] Figure 3 It is a schematic diagram of a controller provided by an embodiment of the present invention.

[0052] Reference numerals: controller 1000, processor 1100, memory 1200;

[0053] A first vibration sensor 210 , a second vibration sensor 220 , a third vibration sensor 230 , and a partial discharge location 240 . DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0055] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims or the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0056] The UHF method is usually used to detect partial discharges on GIS in operation. The UHF method monitors the equipment continuously over a long period of time, and requires the manufacturer to build in sensor couplers when manufacturing the equipment to ensure measurement accuracy. However, it is difficult to detect damage to the sensor couplers in time, which can easily lead to errors in locating the partial discharge source. If the sensor couplers are installed outside the equipment, they are easily interfered by various electromagnetic signals from the outside world, affecting the detection accuracy, and the positioning accuracy of the partial discharge source is poor.

[0057] In order to solve the above-mentioned problems, the present application provides an intelligent GIS defect detection method, controller, power grid management system and medium.

[0058] In the present application, an intelligent GIS defect detection method, a controller, a power grid management system and a medium are provided, which are described in detail one by one in the following embodiments.

[0059] like Figure 1 As shown, the embodiment of the present invention provides an intelligent GIS defect detection method, including:

[0060] S100: When a power grid management system detects at least one partial discharge location of a gas-insulated metal-enclosed switchgear, obtain a partial discharge level of the partial discharge location.

[0061] It should be noted that the intelligent GIS defect detection method of the present application is applied to a power grid management system equipped with a digital twin model of a gas-insulated metal-enclosed switchgear. The digital twin model of the gas-insulated metal-enclosed switchgear is provided with multiple vibration wave sensors, temperature and humidity sensors, gas sensors, partial discharge signal sensors, etc., that is, corresponding vibration wave sensors, temperature and humidity sensors, gas sensors, partial discharge signal sensors, etc. are also provided on the corresponding gas-insulated metal-enclosed switchgear, so that the position and specific working status of each sensor can be intuitively viewed through the digital twin model.

[0062] Specifically, when partial discharge occurs inside the GIS, the partial discharge signal sensor obtains the high-frequency electromagnetic signal and / or pulse current signal of the partial discharge. The high-frequency electromagnetic signal received by the partial discharge signal sensor is in the preset electromagnetic signal frequency band, triggering the partial discharge signal sensor, and the partial discharge signal sensor receives the high-frequency electromagnetic signal. The partial discharge signal (high-frequency electromagnetic signal and / or pulse current signal) received by the partial discharge signal sensor is transmitted to the upper level for simulation to obtain the corresponding simulation data. After detecting that a partial discharge occurs in the GIS and detecting the specific partial discharge location, it is necessary to determine the defect type of the partial discharge location and perform corresponding processing to eliminate the impact of the partial discharge. When at least one partial discharge location is obtained, it is necessary to first divide the priority of the partial discharge location to determine the processing priority of the partial discharge location, that is, to determine the partial discharge level.

[0063] In some optional embodiments, obtaining the partial discharge level of a local discharge location includes: obtaining a partial discharge signal of the local discharge location; determining a discharge amount, a discharge time, and a discharge frequency of the local discharge location according to the partial discharge signal, wherein the discharge amount represents the discharge intensity of the local discharge location, the discharge time represents the discharge duration of the local discharge location, and the discharge frequency represents the number of discharges at the local discharge location within a preset time; and obtaining the partial discharge level after weighted calculation of the discharge amount, the discharge time, and the discharge frequency.

[0064] Specifically, the partial discharge level is determined according to the partial discharge signal at the partial discharge position. That is, by analyzing the signal waveform of the partial discharge signal, the discharge intensity corresponding to the partial discharge signal is determined according to the amplitude value of the signal, and the discharge duration corresponding to the partial discharge signal is determined by the signal period of the partial discharge signal, that is, the discharge duration is determined by the waveform continuity time of the partial discharge signal. Similarly, the discharge time interval is determined by the time interval between the waveforms in the signal waveform diagram, thereby obtaining the discharge frequency. The partial discharge level is obtained by weighted calculation of the discharge amount, discharge time and discharge frequency, so that the processing priority of the partial discharge position can be determined according to the partial discharge level.

[0065] In some optional embodiments, the partial discharge level is obtained after weighted calculation of the discharge amount, discharge time and discharge frequency, including: respectively calculating a first level corresponding to the discharge amount, a second level corresponding to the discharge time and a third level corresponding to the discharge frequency; obtaining a first weighting coefficient of the first level, a second weighting coefficient of the second level and a third weighting coefficient of the third level; and calculating the partial discharge level according to the first level, the first weighting coefficient, the second level, the second weighting coefficient, the third level and the third weighting coefficient.

[0066] Specifically, the discharge amount, discharge time and discharge frequency correspond to different weighting coefficients respectively, and the specific coefficients are determined according to the influence of the discharge intensity, discharge time and discharge frequency on the GIS; that is, if the discharge intensity has a significant influence on the GIS, the first weighting coefficient corresponding to the discharge intensity (discharge amount / discharge per unit time) is increased accordingly; if the discharge time has no significant influence on the GIS, the second weighting coefficient corresponding to the discharge time is reduced accordingly. For example, at the first partial discharge position, the first level of the discharge amount is level 7, the first weighting coefficient corresponding to the discharge amount is 0.4, the second level of the discharge time is level 4, the second weighting coefficient corresponding to the discharge time is 0.2, the third level of the discharge frequency is level 6, and the third weighting coefficient corresponding to the discharge frequency is 0.4. Then the partial discharge level can be expressed as 7*0.4+4*0.2+6*0.4=6, that is, the partial discharge level of the first partial discharge position obtained by weighted calculation is 6; at the second partial discharge position, the first level of the discharge amount is level 6, the first weighting coefficient corresponding to the discharge amount is 0.4, the second level of the discharge time is level 8, the second weighting coefficient corresponding to the discharge time is 0.2, the third level of the discharge frequency is level 4, and the third weighting coefficient corresponding to the discharge frequency is 0.4. Then the partial discharge level can be expressed as 6*0.4+8*0.2+4*0.4=5.6, that is, the partial discharge level of the second partial discharge position obtained by weighted calculation is 5.6, that is, the partial discharge level of the first partial discharge position is greater than that of the second partial discharge position.

[0067] S200, determining a processing sequence table of partial discharge positions according to the partial discharge levels.

[0068] Specifically, the higher the PD level, the higher the processing priority and the higher the position in the processing sequence table. The processing sequence table can intuitively show the PD levels of different PD locations and the processing priority, so that the PD location with the greatest impact on GIS can be processed according to the processing sequence table, thereby minimizing the impact of PD on GIS.

[0069] S300, acquiring detection data and simulation data of the partial discharge position in sequence according to the processing sequence table, wherein the detection data represents sonar data, gas data, temperature and humidity data and abnormal event data of the partial discharge position, and the simulation data represents simulation data of the partial discharge signal generated at the partial discharge position.

[0070] Specifically, sonar data is data collected by sonar installed in GIS. Since GIS is a metal device, other electromagnetic data will be interfered by GIS, which makes the accuracy of electromagnetic data low. However, this application collects sonar data from GIS by installing sonar, which is not interfered by metal and GIS's own electromagnetic signals or external electromagnetic signals, and can accurately obtain sonar data inside or outside GIS, thereby improving the accuracy of determining the type of GIS defects. Gas data is obtained by detecting a gas detection device installed inside GIS. The gas detection device can detect the gas pressure, gas composition and content of different gas components at different locations inside GIS, that is, the gas data includes gas pressure, gas composition and content of different gas components. The gas detection device uploads the gas data to the power grid management system, and generates corresponding detection result information after processing by the processor of the power grid management system, and can display the corresponding detection result information on the digital twin model, thereby intuitively displaying the gas data of different parts on GIS. Similarly, sonar data can also be selectively displayed in the digital twin model. That is, when the internal image of the GIS constructed by sonar data needs to be displayed, click the display mode of the digital twin model to display it accordingly, and then intuitively display the internal structure of the GIS. Temperature and humidity data are collected by temperature and humidity sensors installed inside the GIS. The collected temperature and humidity data can also be displayed on the digital twin model, so that the temperature and humidity of different parts of the GIS can be intuitively seen. Abnormal event data is obtained and stored through the event model of the power grid management system. The event model is specifically connected to the climate platform and can obtain corresponding meteorological data and meteorological events occurring in different regions, such as thunder, hail, rain, etc., which are not specifically limited here. The event model is also connected to the operation platform to obtain GIS operation data, such as maintenance and installation operation data of a GIS in a certain area. The simulation data is obtained by acquiring the partial discharge signal at the partial discharge position and then performing simulation display, wherein the partial discharge signal includes a pulse electric signal and an ultrasonic signal. The specific type of the partial discharge signal is determined according to the sensor used for collection, such as an ultrasonic sensor collecting ultrasonic signals in the partial discharge signal, a pulse current sensor collecting pulse electric signals in the partial discharge signal, and an electromagnetic sensor collecting electromagnetic signals in the partial discharge signal. The specific type is not limited here.

[0071] S400. Determine the defect type of the partial discharge position according to the detection data and the simulation data, and display the partial discharge position and the defect type on the digital twin model.

[0072] Specifically, the signal characteristics of the partial discharge signal can be identified through simulation data, different types of discharges can be identified based on the specific signal characteristics, and corresponding detection data can be obtained based on the different types of discharges. The defect type at the partial discharge location can be quickly determined through the detection data.

[0073] In some optional embodiments, determining the defect type of the partial discharge position according to the detection data and the simulation data includes:

[0074] When the simulation data indicates that the pulse current amplitude of the partial discharge signal is less than the first threshold, the pulse repetition rate is greater than the second threshold, the pulse rise time and the pulse fall time are greater than the third threshold, the duration of the ultrasonic signal in the partial discharge signal is greater than the fourth threshold, and the spectrum peak of the partial discharge signal is greater than the fifth threshold, the discharge type of the partial discharge position is configured as corona discharge;

[0075] When the discharge type is corona discharge, sonar data of the local discharge position is obtained, and surface data of the local discharge position is reconstructed according to the sonar data. When the surface data indicates that there is a sharp protrusion at the local discharge position, the defect at the local discharge position is configured as an inherent defect; when the surface data indicates that there is no sharp protrusion at the local discharge position, the negative half-wave of the spectrum diagram of the partial discharge signal has a double-peak structure, and a preset amplitude and a preset waveform appear at a phase of 245-255 degrees of the spectrum diagram, the defect at the local discharge position is configured as suspended metal particles;

[0076] When the simulation data indicates that the pulse current amplitude of the partial discharge signal is greater than the sixth threshold, the pulse repetition rate is less than the seventh threshold, the pulse rise time and the fall time are less than the eighth threshold, the duration of the ultrasonic signal in the partial discharge signal is less than the ninth threshold, and the spectrum peak of the partial discharge signal is less than the tenth threshold, the discharge type of the partial discharge position is configured as electric spark discharge;

[0077] When the discharge type is electric spark discharge, the temperature and humidity data of the local discharge position are obtained. When the temperature and humidity data indicate that the humidity of the local discharge position is greater than the preset humidity, the defect of the local discharge position is configured as insulator moisture. When the temperature and humidity data indicate that the temperature of the local discharge position is greater than the preset temperature, the defect of the local discharge position is configured as insulator ablation. When the temperature and humidity data indicate that the temperature and humidity of the local discharge position are less than the preset temperature and humidity, the gas data of the local discharge position are obtained. When the gas data indicate that the decomposition gas content of SF6 at the local discharge position is greater than the preset content, the defect of the local discharge position is configured as SF6 gas decomposition. When the gas data indicate that the decomposition gas content of SF6 at the local discharge position is less than the preset content, the abnormal event data of the local discharge position are obtained. When the abnormal event data indicate that the local discharge position has an operation event and / or a lightning event, the defect of the local discharge position is configured as an overvoltage effect.

[0078] Specifically, the pulse current signal in the partial discharge signal is displayed through the simulation waveform, and the pulse current amplitudes generated by different discharge types are different. For example, the pulse current amplitude of corona discharge is relatively small, generally below the milliampere (mA) level (the first threshold is set to a value below the milliampere level according to demand, such as 0.9 mA, and there is no specific limit); while the pulse current amplitude of spark discharge is larger, generally reaching tens of mA or even higher (the sixth threshold is set to a value above the milliampere level according to demand, such as 100 mA, and there is no specific limit). By analyzing the magnitude of the detected pulse current amplitude, the severity of the discharge can be preliminarily judged. If the amplitude is low and relatively stable, it may be a corona discharge; if the amplitude is high and there is a sudden increase, it may be a spark discharge or an arc discharge. The type of discharge can be preliminarily judged by the pulse current amplitude. The frequency of discharge is reflected by the pulse repetition rate. For corona discharge, due to its relatively stable discharge process, the pulse repetition rate is relatively high (such as the second threshold value can be set to 50%, the specific second threshold value is determined according to the actual test environment and data, and is not limited here), that is, the pulse current graph is relatively stable, and the pulse waveform changes in different cycles are relatively small. For intermittent discharge faults (such as spark discharge), the pulse repetition rate (the pulse repetition rate corresponding to spark discharge is less than 30%, that is, the seventh threshold value can be set to 30%, the specific third threshold value is determined according to the actual test environment and data, and is not limited here) may change irregularly, and the pulse waveform changes in different cycles are large. By monitoring the change pattern of the pulse repetition rate, clues can be provided for judging the discharge type. Therefore, the pulse repetition rate is used to further judge the discharge type based on the preliminary judgment of the discharge type. The rise time and fall time of the pulse can also reflect the characteristics of the discharge type. The pulse rise time and fall time of the corona discharge are relatively long. The rise time of the corona discharge is usually at the nanosecond (ns) level, and the rise time is 2-7 nanoseconds. The general positive corona pulse stage is mainly divided into the initial pulse stage, the streamer pulse stage and the brush pulse stage, while the negative polarity corona pulse stage is mainly divided into the streamer pulse increase stage, the streamer pulse decrease stage and the brush pulse stage. Therefore, the specific rise time and fall time are analyzed according to different stages. Generally, the fall time of corona discharge is longer than the rise time, generally in the order of tens of nanoseconds (ns), and the fall time is 10-20 nanoseconds. This shows that the fall process of corona discharge is relatively slow, in contrast to the rapid rise of the rise process. Therefore, it is possible to judge whether the local discharge position has the characteristics of corona discharge based on the rise and fall characteristics of corona discharge. Therefore, the third threshold can be set to 13 nanoseconds, and the specific third threshold is not limited here. The pulse rise time of spark discharge is shorter, and the fall time may vary depending on the characteristics of the discharge channel. The eighth threshold can be set to 10 nanoseconds, which is not specifically limited. Measuring these time parameters of the pulse can assist in distinguishing the discharge type.The duration and intermittency of ultrasonic signals are also one of the bases for judging the type of discharge. The ultrasonic signal generated by corona discharge is an intermittent signal with a long duration (the fourth threshold can be set to 2 milliseconds, or set according to actual test data and historical test data, which is not limited here), while the electric spark discharge will produce an ultrasonic signal with a short duration (the ninth threshold can be set to 50 microseconds). By observing the time domain characteristics of the ultrasonic signal, it can be used as one of the conditions for judging the type of discharge. By performing fast Fourier transform (FFT) on the detected partial discharge signal (pulse current signal, ultrasonic signal), the time domain signal is converted into a frequency domain signal. Different discharge types have different characteristics in the frequency domain; corona discharge will have a relatively obvious spectrum peak in the high frequency band, and its frequency range may be above several hundred megahertz (MHz) (the fifth threshold can be set to 400 MHz, which is not limited here); while the spectrum peak of surface discharge may be concentrated in a lower frequency band, such as around tens of megahertz (MHz) (the tenth threshold can be set to 60 MHz, which is not limited here). By analyzing the spectrum distribution of the signal and comparing the spectrum characteristics of the known discharge type, the actual detected discharge type can be determined. After simulation analysis, if the simulation graph of the partial discharge signal satisfies that the pulse current amplitude of the partial discharge signal is less than the first threshold, the pulse repetition rate is greater than the second threshold, the pulse rise time and fall time are greater than the third threshold, and the duration of the ultrasonic signal in the partial discharge signal is greater than the fourth threshold, and the spectrum peak of the partial discharge signal is greater than the fifth threshold, and it indicates that the partial discharge signal meets all the characteristics of corona discharge, the discharge type of the partial discharge position is configured as corona discharge, and the judgment result is more accurate than judging the discharge type by a single condition. Similarly, if the simulation graph of the partial discharge signal satisfies that the pulse current amplitude is greater than the sixth threshold, the pulse repetition rate is less than the seventh threshold, the pulse rise time and fall time are less than the eighth threshold, and the duration of the ultrasonic signal in the partial discharge signal is less than the ninth threshold, and the spectrum peak of the partial discharge signal is less than the tenth threshold, and it indicates that the partial discharge signal meets all the characteristics of spark discharge, the discharge type of the partial discharge position is configured as spark discharge.

[0079] After the discharge type at the partial discharge position is determined as corona discharge, it is necessary to determine the type of defect that causes the corona discharge in the GIS. At this time, by obtaining the sonar data at the partial discharge position and reconstructing the surface data of the discharge position with the sonar data, a specific surface image inside the GIS is obtained; the surface data is used to identify whether there are sharp protrusions inside the GIS. If a sharp protrusion is identified at the partial discharge position, the defect at the partial discharge position is configured as an inherent defect (that is, there are metal protrusions on the inner surface of the GIS shell due to improper installation of the conductor, scratches and burrs, and protruding particles on the surface of the solid insulation). If the surface data does not identify the presence of sharp protrusions at the partial discharge position, through the simulation graph of the partial discharge signal, if it is identified that the negative half-wave of the spectrum diagram of the partial discharge signal has a double-peak structure, and a preset amplitude and preset waveform appear at the phase of 245-255 degrees of the spectrum diagram, the defect at the partial discharge position is configured as suspended metal particles, that is, there are freely movable metal particles or conductive suspensions at the partial discharge position of the GIS.

[0080] After the discharge type of the local discharge position is determined to be electric spark discharge, the temperature and humidity data of the local discharge position is obtained through the temperature and humidity sensor set inside the GIS. When the humidity of the local discharge position is greater than the preset humidity (specifically obtained based on historical data and experiments, not limited here, the preset humidity of this application is set), the defect of the local discharge position is configured as damp insulator, that is, the humidity inside the GIS is too high, resulting in local discharge. When the temperature and humidity data identify that the temperature of the local discharge position is greater than the preset temperature (which can be set to 100 degrees Celsius, the specific preset temperature is not limited here), the defect of the local discharge position is configured as insulator ablation, that is, the insulator inside the GIS is ablated, resulting in local discharge, and the insulator ablation causes the temperature of the local discharge position to rise, so whether the insulator ablation occurs can be determined based on the temperature.

[0081] When the temperature and humidity data are normal, the gas data at the partial discharge location is analyzed. When the partial discharge location is identified to contain SF6 decomposition gas through the gas data, and the content of the decomposition gas is greater than the preset content, the defect at the partial discharge location is configured as SF6 gas decomposition. That is, during the GIS operation, due to the effects of arc, corona, spark discharge, partial discharge, high temperature, etc., SF6 gas will decompose, and its decomposition products will become corrosive electrolytes when encountering moisture. These decomposition products will affect the insulation performance inside the GIS, thereby causing electric spark discharge.

[0082] If the decomposed gas content of SF6 at the partial discharge location is less than the preset content, the abnormal event data of the partial discharge location is obtained. Through the abnormal event data recorded by the system, if the partial discharge location is identified to have an operation event and / or lightning event, the defect of the partial discharge location is configured as an overvoltage effect. When GIS is subjected to lightning overvoltage, operation overvoltage, etc. during operation, the lightning overvoltage often causes flashover or discharge inside the components with low insulation level; the high-frequency transient overvoltage (i.e., operation overvoltage) caused by the disconnector switching on the small capacitance current may cause the GIS to flash over to the ground (housing).

[0083] In some optional embodiments, sonar data is collected by sonar equipment arranged inside and / or outside GIS (gas-insulated metal-enclosed switchgear), and the ultrasonic waves emitted by the sonar equipment are also used to vibrate the GIS, so that the GIS generates vibration wave data. The method also includes: obtaining vibration wave data of the local discharge position; generating a vibration spectrum according to the vibration wave data; when the correlation between the waveform of the vibration spectrum and the waveform of the preset defect spectrum reaches a correlation threshold, and the vibration frequency of the vibration spectrum is greater than the preset vibration frequency, configuring the defect at the local discharge position as an aging crack.

[0084] Specifically, the ultrasonic waves emitted by the sonar equipment can cause the GIS to vibrate accordingly. By collecting specific vibration wave information, it is possible to identify whether there are cracks and gaps on the GIS. The frequency of the vibration wave of a GIS with cracks is high. Therefore, by identifying the frequency of the vibration wave after processing, it is possible to determine whether there are cracks. First, the vibration wave data of the local discharge position is obtained. The system generates a corresponding vibration spectrum based on the vibration wave data. After the waveform of the vibration spectrum has a correlation threshold with the waveform of the preset defect spectrum, the vibration spectrum is determined as the vibration frequency waveform of the GIS equipment, and the vibration frequency of the vibration spectrum is identified. If there is a vibration frequency greater than the preset vibration frequency (the preset vibration frequency can be set to 2kHz, which is not specifically limited here), the defect at the local discharge position is configured as an aging crack.

[0085] In some optional embodiments, the method also includes: when the pulse current amplitude of the partial discharge signal represented by simulation data is greater than a sixth threshold, the frequency of the ultrasonic signal in the partial discharge signal is less than a preset frequency, and the amplitude value is greater than a preset amplitude value, configuring the defect at the partial discharge position as an internal air gap.

[0086] Specifically, in ultrasonic testing, the amplitude and frequency of ultrasonic signals generated by different discharge types are different. The frequency of ultrasonic signals generated by internal discharge of solid insulation is relatively low, between 20kHz and 100kHz, but the pulse current amplitude is greater than the sixth threshold. Based on the frequency and pulse current amplitude range of the ultrasonic signal, it can be preliminarily determined that the discharge occurs inside the solid insulation, and the discharge inside the insulator can be considered as partial discharge caused by air gaps.

[0087] In some optional embodiments, at least one first vibration sensor 210 and at least one second vibration sensor 220 are provided on the GIS. Before the power grid management system detects at least one local discharge position of the gas-insulated metal-enclosed switchgear, a method for determining the local discharge position includes: obtaining a first vibration signal of the first vibration sensor 210; obtaining a second vibration signal of the second vibration sensor 220; and determining the local discharge position 240 according to the first vibration signal, the second vibration signal and the position information.

[0088] Specifically, refer to Figure 2 When partial discharge occurs, the GIS shell, insulator, etc. can vibrate accordingly, that is, vibration waves are generated and transmitted in the GIS. The first vibration sensor 210 and the second vibration sensor 220 set at different positions receive the vibration waves. After receiving the vibration waves, the first vibration sensor 210 generates a corresponding first vibration signal, and after receiving the vibration waves, the second vibration sensor 220 generates a corresponding second vibration signal. The first time point when the first vibration sensor 210 receives the vibration wave is obtained through the first vibration signal, and the second time point when the second vibration sensor 220 receives the vibration wave is obtained through the second vibration signal, so as to obtain the distance difference between the first distance from the partial discharge position 240 to the first vibration sensor 210 and the second distance from the partial discharge position 240 to the second vibration sensor 220, and determine the corresponding partial discharge position 240 through the spatial points of each GIS on the position information.

[0089] In some optional embodiments, a third vibration sensor 230 is further provided on the GIS, and a local discharge position 240 is determined according to the first vibration signal, the second vibration signal and the position information, including: determining the transmission distance difference between the local discharge position 240 and the first vibration sensor 210 and the second vibration sensor 220 according to the first reception time of the first vibration signal, the second reception time of the second vibration signal and the transmission speed of the preset vibration wave; obtaining one or more target position points according to the position information and the transmission distance difference, the target position point representing the position point on the GIS where the distance difference to the first vibration sensor 210 and the second vibration sensor 220 is equal to the transmission distance difference, and the position The location information represents the spatial location information of each point on the GIS; when there is only one target location point, the target location point is configured as the local discharge location 240; when there are multiple target location points, the third vibration signal of the third vibration sensor 230 is obtained, and the difference in transmission distances between the local discharge location 240 and the first vibration sensor 210, the second vibration sensor 220 and the third vibration sensor 230 is determined according to the third receiving time of the third vibration signal, the first receiving time of the first vibration signal, the second receiving time of the second vibration signal and the transmission speed of the preset vibration wave; the local discharge location 240 is obtained according to the GIS location information and the difference in transmission distances between the two locations.

[0090] Specifically, refer to Figure 2, the first vibration sensor 210 can receive the vibration wave and record the corresponding receiving time point, which is the first receiving time of the first vibration signal. Similarly, the second vibration sensor 220 can receive the vibration wave and record the corresponding receiving time point, which is the second receiving time of the second vibration signal. The first distance from the local discharge position 240 to the first vibration sensor 210 is determined according to the first receiving time and the transmission speed of the preset vibration wave. The second distance from the local discharge position 240 to the second vibration sensor 220 is determined according to the second receiving time and the transmission speed of the preset vibration wave. The transmission distance difference between the local discharge position 240 to the first vibration sensor 210 and the second vibration sensor 220 is the transmission distance difference between the first distance and the second distance. By substituting the position point in the position information into the calculation, the position point whose distance difference between the first vibration sensor 210 and the first vibration sensor 210 is the transmission distance difference is saved as the target position point. When there is only one target position point, the target position point is used as the local discharge position 240. When there are multiple target position points, the third vibration signal of the third vibration sensor 230 is obtained. The third vibration sensor 230 and the first vibration sensor 210 and the second vibration sensor 220 are at different positions on the GIS, so that the distance differences between each point on the GIS and the first vibration sensor 210, the second vibration sensor 220 and the third vibration sensor 230 are different. According to the third receiving time of the third vibration signal, the first receiving time of the first vibration signal, the second receiving time of the second vibration signal and the transmission speed of the preset vibration wave, a first distance difference between the local discharge position 240 and the first vibration sensor 210 and the third vibration sensor 230 and a second distance difference between the local discharge position 240 and the second vibration sensor 220 and the third vibration sensor 230 are determined, so as to find a position point on the GIS through the GIS position information that satisfies the conditions that the distance difference between the first vibration sensor 210 and the second vibration sensor 220 is the transmission distance difference, the distance difference between the first vibration sensor 210 and the third vibration sensor 230 is the first distance difference, and the distance difference between the second vibration sensor 220 and the third vibration sensor 230 is the second distance difference, and use the position point as the local discharge position 240.

[0091] S500. Generate corresponding intelligent decision-making information according to the defect type.

[0092] Specifically, after determining the defect type at the local discharge location, smart decision information is generated based on the specific defect type, and the smart decision information is displayed on the digital twin model of GIS, which is convenient for viewing and quickly performing corresponding repairs based on the smart decision information. For example, when the defect type is detected as an inherent defect, the generated smart decision information is "partial discharge at the local discharge position A is caused by an inherent defect, please replace the GIS shell or eliminate the tip protrusion"; when the defect type is detected as suspended metal particles, the generated smart decision information is "partial discharge at the local discharge position A is caused by suspended metal particles, please replace the GIS shell or eliminate the suspended metal particles"; when the defect type is detected as insulator ablation, the generated smart decision information is "partial discharge at the local discharge position A is caused by insulator ablation, please replace the insulator"; when the defect type is detected as SF6 gas decomposition, the generated smart decision information is "partial discharge at the local discharge position A is caused by SF6 gas decomposition, please replace the gas inside the GIS and refill the SF6 gas"; when the defect type is detected as overvoltage, the generated smart decision information is "partial discharge at the local discharge position A is caused by overvoltage, please stop operation or pay attention to the weather and take lightning protection measures". Through the smart decision information, the local discharge situation of the GIS and the specific maintenance operations can be quickly identified, which can facilitate maintenance personnel to quickly complete maintenance and eliminate the impact of local discharge.

[0093] In some optional embodiments, after the intelligent decision information is generated, the partial discharge fault of the GIS is distributed to the corresponding engineers or maintenance personnel for processing through dispatching. First, the partial discharge fault of the local discharge position with a high priority is dispatched for processing, and the task order of the partial discharge fault is sent to different engineers and / or maintenance personnel for processing according to the specific defect type and priority, so that the partial discharge fault can be handled in a timely and effective manner. When the corresponding engineer and / or maintenance personnel have no spare time, the task order of the partial discharge fault is distributed to the engineer and / or maintenance personnel who handles the upper or lower level partial discharge fault. The upper level is the previous priority level, and similarly, the lower level is the next priority level. By performing corresponding upgrades or downgrades on the matching engineers and / or maintenance personnel, the task order of the partial discharge fault is distributed and processed in time, thereby handling the partial discharge fault in time. When the task order of the partial discharge fault is dispatched, the intelligent decision information and the tools, operating steps, precautions, and quality inspection after installation that need to be carried are also packaged and sent to the corresponding engineers and / or maintenance personnel for easy viewing and standardized operation. Within the preset time period after the task order of the partial discharge fault is distributed, if the engineer and / or maintenance personnel who received the task order does not handle it, a corresponding message will be sent to remind the relevant engineers and / or maintenance personnel. After the engineers and / or maintenance personnel determine that they do not have time to handle it, the task order will be reassigned to other engineers and / or maintenance personnel who are free and can handle it immediately, so as to avoid increasing the losses and harm caused by the partial discharge fault after a long time; wherein, the preset time period is determined according to the specific priority, that is, the partial discharge fault with a higher priority has a shorter preset time period than the partial discharge fault with a lower priority. The specific time is determined according to the actual situation and is not limited here.

[0094] After the engineer and / or maintenance personnel have handled the partial discharge fault at the partial discharge location, the maintenance records of the engineer and / or maintenance personnel and the test results after the maintenance are uploaded to the system for storage, so that they can be viewed when problems occur later.

[0095] Specifically, when dispatching orders to engineers and / or maintenance personnel, the current number of tasks, estimated processing time, and distance to the partial discharge location of the engineers and / or maintenance personnel who will handle the corresponding partial discharge fault are obtained, and engineers and / or maintenance personnel are selected according to the preset time period corresponding to the priority level of the partial discharge fault, so that the engineers and / or maintenance personnel can reach the partial discharge location within the preset time period to perform maintenance.

[0096] The specific estimated processing time is obtained based on the type of task, the task processing status and the historical processing speed of the engineer and / or maintenance personnel to which it belongs, so that a relatively accurate estimated processing time can be obtained, so that the task orders for partial discharge faults are reasonably assigned and the partial discharge faults can be handled in a timely manner.

[0097] The beneficial effects of implementing the embodiments of the present invention include: the present invention obtains the partial discharge level of the partial discharge position when at least one partial discharge position of the gas-insulated metal-enclosed switchgear is detected in the power grid management system; determines the processing sequence table of the partial discharge position according to the partial discharge level; obtains the detection data and simulation data of the partial discharge position in sequence according to the processing sequence table, the detection data represents the sonar data, gas data, temperature and humidity data and abnormal event data of the partial discharge position, and the simulation data represents the simulation data of the partial discharge signal generated by the partial discharge position; determines the defect type of the partial discharge position according to the detection data and simulation data, and displays the partial discharge position and defect type on the digital twin model; generates corresponding intelligent decision information according to the defect type. The detection data and simulation data of the partial discharge position are obtained in sequence according to the partial discharge level to determine the defect type of the partial discharge position, so as to give priority to the defects of the partial discharge position with a high partial discharge level, thereby minimizing the losses caused by partial discharge; and the defect type of the partial discharge position can be quickly determined by the detection data and simulation data, and the corresponding intelligent decision information is made according to the defect type, which is convenient for the processing personnel to quickly process, and the GIS defect detection efficiency is high and the detection cost is low; the partial discharge position and defect type are displayed on the digital twin model, and the visualization is good.

[0098] like Figure 3 As shown, Figure 3 The structure block diagram of a controller 1000 provided according to an embodiment of the present application is shown. The components of the controller 1000 include but are not limited to a memory 1200 and a processor 1100. The processor 1100 is connected to the memory 1200 via a bus, and the memory 1200 is used to store data.

[0099] The controller 1000 also includes an access device that enables the controller 1000 to communicate via one or more networks. Examples of these networks include a combination of a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a communication network such as the Internet. The access device 340 may include one or more of any type of network interface (e.g., a network interface card (NIC)) of wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a global interconnection for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, a near field communication (NFC) interface, and the like.

[0100] The controller 1000 may be any type of stationary or mobile electronic device, including a mobile computer or mobile electronic device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable electronic device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary electronic device such as a desktop computer or a PC. The controller 1000 of the smart seat may also be a mobile or stationary server.

[0101] The processor 1100 is used to execute computer executable instructions of the intelligent GIS defect detection method.

[0102] The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the above-mentioned intelligent GIS defect detection method belong to the same concept, and the details not described in detail in the technical scheme of the computing device can be referred to the description of the technical scheme of the above-mentioned intelligent GIS defect detection method.

[0103] According to an embodiment of the present application, a power grid management system is also provided. The power grid management system is installed with a controller 1000, or the power grid management system is connected to the controller 1000 through communication, so that the power grid management system can locate the partial discharge source through the controller 1000. It should be noted that the technical solution of the computing device and the technical solution of the above-mentioned intelligent GIS defect detection method belong to the same concept, and the details of the technical solution of the computing device that are not described in detail can be found in the description of the technical solution of the above-mentioned intelligent GIS defect detection method.

[0104] An embodiment of the present application also provides a storage medium, which is a computer-readable storage medium. The storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned intelligent GIS defect detection method is implemented.

[0105] As a non-transient computer-readable storage medium, the memory can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage devices. In some embodiments, the memory may include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and are implemented to be located in one place, or may also be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0106] It will be appreciated by those skilled in the art that all or some of the steps and systems in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or transient medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically include computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0107] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the above implementation mode. Technical personnel familiar with the field can also make various equivalent modifications or substitutions under the shared conditions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. Intelligent GIS defect detection method, characterized in that: A method for a power grid management system provided with a digital twin model of a gas-insulated metal-enclosed switchgear comprises: When the power grid management system detects at least one partial discharge location of the gas-insulated metal-enclosed switchgear, obtaining a partial discharge level of the partial discharge location; Determine a processing sequence table of the partial discharge position according to the partial discharge level; Acquire detection data and simulation data of the partial discharge position in sequence according to the processing sequence table, wherein the detection data represents sonar data, gas data, temperature and humidity data, and abnormal event data of the partial discharge position, and the simulation data represents simulation data of the partial discharge signal generated at the partial discharge position; determining a defect type at the partial discharge location according to the detection data and the simulation data, and displaying the partial discharge location and the defect type on a digital twin model, wherein the digital twin model represents a digital twin model of the gas-insulated metal-enclosed switchgear; Determining the defect type at the partial discharge position according to the detection data and the simulation data includes: identifying the signal characteristics of the partial discharge signal through the simulation data, identifying different types of discharge according to the signal characteristics, acquiring the corresponding detection data according to the different types of discharge, and determining the defect type at the partial discharge position through the detection data; Generate corresponding intelligent decision-making information according to the defect type.

2. The intelligent GIS defect detection method according to claim 1 is characterized in that: The obtaining of the partial discharge level of the partial discharge position includes: Acquiring the partial discharge signal at the partial discharge position; Determine the discharge amount, discharge time and discharge frequency of the local discharge position according to the partial discharge signal, wherein the discharge amount represents the discharge intensity of the local discharge position, the discharge time represents the discharge duration of the local discharge position, and the discharge frequency represents the number of discharges at the local discharge position within a preset time; respectively calculating a first level corresponding to the discharge amount, a second level corresponding to the discharge time, and a third level corresponding to the discharge frequency; Obtaining a first weighting coefficient of the first level, a second weighting coefficient of the second level, and a third weighting coefficient of the third level; The partial discharge level is calculated according to the first level, the first weighting coefficient, the second level, the second weighting coefficient, the third level and the third weighting coefficient.

3. The intelligent GIS defect detection method according to claim 1 is characterized in that: The step of determining the defect type of the partial discharge position according to the detection data and the simulation data comprises: When the simulation data indicates that the pulse current amplitude of the partial discharge signal is less than a first threshold, the pulse repetition rate is greater than a second threshold, the pulse rise time and the pulse fall time are greater than a third threshold, the duration of the ultrasonic signal in the partial discharge signal is greater than a fourth threshold, and the spectrum peak of the partial discharge signal is greater than a fifth threshold, the discharge type of the partial discharge position is configured as corona discharge; When the discharge type is corona discharge, the sonar data of the local discharge position is obtained, and the surface data of the local discharge position is reconstructed according to the sonar data. When the surface data indicates that there is a pointed protrusion at the local discharge position, the defect at the local discharge position is configured as an inherent defect. When the surface data indicates that there is no pointed protrusion at the local discharge position, the negative half-wave of the spectrum diagram of the partial discharge signal has a double-peak structure, and a preset amplitude and a preset waveform appear at a phase of 245-255 degrees of the spectrum diagram, the defect at the local discharge position is configured as suspended metal particles.

4. The intelligent GIS defect detection method according to claim 3 is characterized in that: The method further comprises: When the simulation data indicates that the pulse current amplitude of the partial discharge signal is greater than a sixth threshold, the pulse repetition rate is less than a seventh threshold, the pulse rise time and the fall time are less than an eighth threshold, the duration of the ultrasonic signal in the partial discharge signal is less than a ninth threshold, and the spectrum peak of the partial discharge signal is less than a tenth threshold, the discharge type of the partial discharge position is configured as electric spark discharge; When the discharge type is the spark discharge, the temperature and humidity data of the partial discharge position are obtained, and when the temperature and humidity data indicate that the humidity of the partial discharge position is greater than a preset humidity, the defect of the partial discharge position is configured as insulator moisture, and when the temperature and humidity data indicate that the temperature of the partial discharge position is greater than a preset temperature, the defect of the partial discharge position is configured as insulator ablation; When the temperature and humidity data indicates that the temperature and humidity at the partial discharge position are less than a preset temperature and humidity, acquiring the gas data at the partial discharge position, and when the gas data indicates that the decomposition gas content of SF6 at the partial discharge position is greater than a preset content, configuring the defect at the partial discharge position as SF6 gas decomposition; When the gas data indicates that the decomposition gas content of SF6 at the local discharge location is less than a preset content, the abnormal event data of the local discharge location is obtained; when the abnormal event data indicates that the local discharge location has an operation event and / or a lightning event, the defect of the local discharge location is configured as an overvoltage effect.

5. The intelligent GIS defect detection method according to claim 3 is characterized in that: The sonar data is collected by a sonar device arranged inside and / or outside the gas-insulated metal-enclosed switchgear, and the ultrasonic waves emitted by the sonar device are also used to vibrate the gas-insulated metal-enclosed switchgear, so that the gas-insulated metal-enclosed switchgear generates vibration wave data. The method also includes: Acquiring the vibration wave data of the partial discharge position; generating a vibration spectrum according to the vibration wave data; When the correlation between the waveform of the vibration spectrum and the waveform of the preset defect spectrum reaches a correlation threshold, and the vibration frequency of the vibration spectrum is greater than the preset vibration frequency, the defect at the partial discharge position is configured as an aging crack.

6. The intelligent GIS defect detection method according to claim 3 is characterized in that: The method further comprises: When the simulation data indicates that the pulse current amplitude of the partial discharge signal is greater than a sixth threshold, and the frequency of the ultrasonic signal in the partial discharge signal is less than a preset frequency and the amplitude value is greater than a preset amplitude value, the defect at the partial discharge position is configured as an internal air gap.

7. The intelligent GIS defect detection method according to claim 1 is characterized in that: The gas-insulated metal-enclosed switchgear is provided with at least one first vibration sensor and at least one second vibration sensor. Before the power grid management system detects at least one partial discharge position of the gas-insulated metal-enclosed switchgear, the method for determining the partial discharge position includes: Acquire a first vibration signal of the first vibration sensor; Acquire a second vibration signal from the second vibration sensor; The partial discharge position is determined according to the first vibration signal, the second vibration signal and position information.

8. The intelligent GIS defect detection method according to claim 7 is characterized in that: The gas-insulated metal-enclosed switchgear is further provided with a third vibration sensor, and the determining of the partial discharge position according to the first vibration signal, the second vibration signal and the position information comprises: Determine a difference in transmission distances from the partial discharge position to the first vibration sensor and the second vibration sensor according to a first reception time of the first vibration signal, a second reception time of the second vibration signal, and a transmission speed of a preset vibration wave; One or more target position points are obtained according to the position information and the transmission distance difference, wherein the target position points represent positions on the gas-insulated metal-enclosed switchgear where the distance difference between the first vibration sensor and the second vibration sensor is equal to the transmission distance difference, and the position information represents the spatial position information of each point on the gas-insulated metal-enclosed switchgear; When there is only one target location point, configuring the target location point as the partial discharge location; In the case where there are multiple target position points, a third vibration signal of the third vibration sensor is obtained, and a difference in transmission distances between the local discharge position and the first vibration sensor, the second vibration sensor and the third vibration sensor is determined according to a third receiving time of the third vibration signal, a first receiving time of the first vibration signal, a second receiving time of the second vibration signal and a transmission speed of a preset vibration wave; The partial discharge position is obtained according to the position information and the difference between the two transmission distances.

9. A controller, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the intelligent GIS defect detection method described in any one of claims 1 to 8 when executing the computer program.

10. A power grid management system, characterized in that: include: The controller of claim 9.

11. A computer storage medium, characterized in that: The computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the intelligent GIS defect detection method described in any one of claims 1-8.

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