Fault diagnosis method and system based on mixed gas PD and decomposition characteristics

Abstract

The invention discloses a fault diagnosis method and system based on mixed gas PD and decomposition characteristics, and relates to the technical field of electrical engineering, and the method comprises the steps: building a first discharge experiment platform, and deploying a first defect model; performing a first discharge experiment on the first defect model, and counting characteristic parameters; performing first characteristic analysis according to the characteristic parameters to obtain first gas decomposition characteristics; and secondary characteristic analysis is carried out on the decomposed gas, and a diagnosis result is obtained through characteristic quantities of local decomposition under different defects. The method provided by the invention provides a widely applicable experimental platform, and can cope with diversified insulation problems. The PD behavior and decomposition product change of the insulation defect can be stably monitored for a long time, different defect types can be accurately identified, and a rapid and accurate diagnosis method is provided. The severity of the insulation defect can be effectively judged, a scientific basis is provided for early maintenance and prevention, and equipment fault expansion is avoided.

Description

Technical Field

[0001] The present invention relates to the field of electrical engineering technology, and in particular to a fault diagnosis method and system based on mixed gas PD and decomposition characteristics. Background Art

[0002] SF6 is widely used in gas-insulated equipment due to its excellent insulation performance and arc extinguishing ability. However, SF6 is a greenhouse gas that has a great impact on the atmospheric environment, while N2 is a gas with a low liquefaction temperature, low price and no pollution. The mixed gas formed with SF6 can withstand a low temperature test of -60°C, effectively solving the problem of SF6 greenhouse effect. At present, SF6 / N2 mixed gas has been widely used in power equipment such as GIS. However, when PD occurs in GIS, the SF6 / N2 mixed gas will decompose, and the decomposition products will react chemically with H2O or O2 in GIS to generate SO2F2, SOF2, SO2, NO2, NF3, CF4 and other products. The content and generation rules of these decomposition products are closely related to the type and severity of insulation defects. Therefore, the type and severity of insulation defects can be judged by the characteristics of the decomposition products of SF6 / N2 mixed gas under PD. In this way, early prediction and diagnosis of insulation defects and their severity can be made, laying the foundation for GIS fault diagnosis and ensuring the safe and reliable operation of GIS equipment. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is: how to study the PD decomposition characteristics and severity of SF6 / N2 mixed gas under different defects, and provide a scientific basis for fault prediction and maintenance of insulation systems.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a fault diagnosis method based on mixed gas PD and decomposition characteristics, comprising:

[0006] Build the first discharge experimental platform and deploy the first defect model;

[0007] Performing a first discharge experiment on the first defect model and calculating characteristic parameters;

[0008] Perform a first characteristic analysis according to the characteristic parameter to obtain a first gas decomposition characteristic;

[0009] The decomposed gas is subjected to secondary characteristic analysis, and the diagnostic results are obtained through the characteristic quantities of local decomposition under different defects.

[0010] As a preferred solution of the fault diagnosis method based on mixed gas PD and decomposition characteristics described in the present invention, wherein: the building of the first discharge experimental platform includes building the first discharge experimental platform and cleaning the experimental device.

[0011] As a preferred solution of the fault diagnosis method based on mixed gas PD and decomposition characteristics described in the present invention, wherein: the deployment of the first defect model includes setting a decomposition gas chamber in the first discharge experimental platform and deploying the first defect model in the decomposition gas chamber.

[0012] As a preferred solution of the fault diagnosis method based on mixed gas PD and decomposition characteristics described in the present invention, wherein: the first discharge experiment includes applying a test voltage to the first defect model by a step-by-step voltage increase method.

[0013] As a preferred solution of the fault diagnosis method based on mixed gas PD and decomposition characteristics described in the present invention, the first characteristic analysis includes adjusting the voltage value to obtain different discharge values ​​and exploring the gas decomposition characteristics at different discharge levels.

[0014] As a preferred solution of the fault diagnosis method based on mixed gas PD and decomposition characteristics described in the present invention, wherein: the first gas decomposition characteristics include analyzing the change rules of PD decomposition products of the decomposed gas using GC-MS and Fourier transform infrared spectrometer.

[0015] As a preferred solution of the fault diagnosis method based on mixed gas PD and decomposition characteristics described in the present invention, the secondary characteristic analysis includes judging the type of insulation defect and its severity through three decomposition characteristics: characteristic component type, characteristic component content, and average discharge amount per second.

[0016] As a preferred solution of the fault diagnosis system based on mixed gas PD and decomposition characteristics described in the present invention, it includes: a gas collection module, a voltage control and pressure module, a gas composition analysis module, and a fault diagnosis submodule;

[0017] The gas collection module collects decomposition gas samples every 12 hours during the experiment, explores the air decomposition characteristics under different discharge levels, and counts and extracts relevant characteristic parameters;

[0018] The voltage control and pressure application module is composed of an induction voltage regulator and a corona-free test transformer, which gradually applies a test voltage to the insulation defect model to control the generation of a stable partial discharge;

[0019] The gas component analysis module: performs qualitative and quantitative analysis on the decomposed gas through GC-MS and Fourier transform infrared spectrometer, and identifies and measures the decomposed gas components;

[0020] The fault diagnosis submodule determines the insulation defect type and the severity of the fault based on the decomposed gas characteristic products and PD characteristic quantities, using the characteristic gas and the discharge amount, and realizes systematic diagnosis of different types of defects.

[0021] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a fault diagnosis method based on the PD and decomposition characteristics of a mixed gas.

[0022] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a fault diagnosis method based on the PD and decomposition characteristics of a mixed gas.

[0023] Beneficial effects of the present invention: The fault diagnosis method based on the mixed gas PD and decomposition characteristics provided by the present invention provides a widely applicable experimental platform that can cope with a variety of insulation problems. It can stably monitor the PD behavior and decomposition product changes of insulation defects over a long period of time, which is conducive to a deep understanding of the partial discharge characteristics in the insulation system and its impact on the equipment. It can accurately identify different defect types and provide a fast and accurate diagnosis method. It can effectively judge the severity of insulation defects, provide a scientific basis for early maintenance and prevention, and avoid the expansion of equipment failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0025] Figure 1 An overall flow chart of a fault diagnosis method based on mixed gas PD and decomposition characteristics provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0027] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides a fault diagnosis method based on mixed gas PD and decomposition characteristics, comprising:

[0028] S1: Build the first discharge experimental platform and deploy the first defect model.

[0029] Furthermore, the building of the first discharge experimental platform may include building the first discharge experimental platform and cleaning the experimental device.

[0030] In an embodiment of the present application, the first discharge experimental platform may be based on a gas discharge experimental platform, specifically including an inductive voltage regulator, a corona-free test transformer, a protective resistor R1, a capacitive voltage divider, a protective resistor R2, a decomposition gas chamber, a gas insulation performance test device, a coupling capacitor C and a non-inductive detection impedance Z and a digital storage oscilloscope.

[0031] The deploying the first defect model includes setting a decomposition gas chamber in the first discharge experimental platform, and deploying the first defect model in the decomposition gas chamber, specifically including:

[0032] An insulation defect model is provided in the decomposition gas chamber, and the insulation defect model can adopt a metal protrusion defect model, an insulator surface metal contamination defect model, an insulator air gap defect model, and a free metal particle defect model.

[0033] In an optional embodiment, the first discharge test platform can also be a liquid insulation discharge test platform: a partial discharge experiment is performed using a specific insulating oil or liquid medium. It includes a voltage regulator, an insulating oil test container, a protective resistor, a capacitive voltage divider, a decomposition gas capture system, and a signal detection device. By generating partial discharge in the liquid, its influence on the performance of the insulating material is studied.

[0034] It should be noted that the cleaning experimental device includes first carefully cleaning the inner wall of the tank body and the artificial defect model with anhydrous ethanol before each experiment to remove impurities and dust in the air chamber.

[0035] S2: Perform a first discharge experiment on the first defect model and collect statistical characteristic parameters.

[0036] Furthermore, the performing of the first discharge experiment includes applying a test voltage to the first defect model by a step-by-step voltage increasing method.

[0037] In the embodiment of the present application, the first discharge experiment performed on the first defect model may specifically include A1 to A4:

[0038] A1. Place the insulation defect model into the discharge chamber, evacuate the tank with a vacuum pump and a rubber tube as short as possible (the length will affect the evacuation time), and repeatedly flush the tank with air to ensure that the gas reacted in the gas chamber last time is fully discharged.

[0039] A2, draw the vacuum again and fill it with air, adjust the humidity, stabilize it for several hours, make sure the humidity diffuses evenly, the gas is in a stable state, and make sure the device is airtight.

[0040] A3, use the step-by-step voltage-boosting method to apply a test voltage to the defect model so that the defect produces a stable PD within the allowable voltage threshold (i.e., the externally applied voltage is less than the inherent defect starting discharge voltage).

[0041] A4, PD statistical characteristic parameters. The PD signal of the insulation defect model is monitored by a pulse current detection unit and a Tektronix DPO7104 digital storage oscilloscope to ensure that the insulation defect produces effective and stable PD. Different discharge values ​​can be obtained by adjusting the voltage value, and the air decomposition characteristics under 5 different discharge levels are explored.

[0042] In an optional embodiment, the first discharge experiment for the first defect model may also be a voltage waveform control experiment, specifically including B1 to B4:

[0043] B1, the experiment applies voltages of different waveforms (such as AC, DC or pulse voltage) to observe the PD behavior of the defect model under different voltage stimulations and analyze the influence of different voltage forms on the discharge characteristics.

[0044] B2, during the experiment, mechanical vibration or stress of different frequencies and amplitudes are applied to disturb the defect model and observe its effect on the PD characteristics. This method helps to simulate the effect of mechanical stress or vibration on insulation defects that actual equipment may be subjected to during operation.

[0045] B3, gradually change the humidity in the gas chamber during the experiment to observe the effect of humidity change on the PD behavior of insulation defects, especially to study the generation law of decomposition gas and discharge characteristics under different humidity conditions.

[0046] B4, conduct long-term discharge experiments on the defect model, periodically collect and analyze the decomposition gas products, and observe their changes over time, so as to have a deeper understanding of the relationship between insulation material aging and PD behavior.

[0047] It should be noted that during the PD experiment, gas samples in the tank are collected regularly, and gas analysis instruments (such as gas chromatography-mass spectrometry GC-MS) or infrared spectrometers are used to monitor and analyze the changes in the composition and concentration of the decomposed gas in real time to ensure that the characteristic gas products generated by PD are captured. During the experiment, temperature control and pressure adjustment devices are used to accurately control the temperature and pressure in the gas chamber to simulate the discharge characteristics under different environmental conditions, so as to get closer to the actual operating environment and obtain more comprehensive data.

[0048] Example 2, reference Figure 1, which is an embodiment of the present invention, provides a fault diagnosis method based on mixed gas PD and decomposition characteristics, comprising:

[0049] S3: Perform a first characteristic analysis based on the characteristic parameters to obtain a first gas decomposition characteristic.

[0050] Furthermore, the first characteristic analysis includes adjusting the voltage value to obtain different discharge values ​​and exploring the gas decomposition characteristics at different discharge levels.

[0051] The first gas decomposition characteristic specifically includes sample gas collection and detection. In a 96h PD test on insulation defects, the decomposition gas is analyzed for the change rule of PD decomposition products by using GC-MS and Fourier transform infrared spectrometer every 12 hours.

[0052] In the embodiment of the present application, the first characteristic analysis may be to conduct a 96h local discharge experiment under an air gap defect. The content of NO2 is much greater than that of other gases and is the main decomposition product. NO2 can be used as a signature product for identifying air gap defects.

[0053] Under the condition of metal protrusion defect, when the average discharge per second reaches 105468pc, the mean square gas production rate of SO2F2 is much greater than that of other gases. SO2F2 can be used as a landmark product for identifying metal protrusion defects.

[0054] In an optional embodiment, the first characteristic analysis may also be a correlation analysis between the concentration of decomposition products and the discharge time, specifically including C1 to C4:

[0055] C1, Placement of insulation defect model: Place the selected insulation defect model (such as air gap defect, metal protrusion defect, etc.) into the decomposition chamber of the experimental platform, and clean, evacuate and inflate it according to the standard experimental steps to ensure that the initial state of the gas is pure and stable. Before starting the experiment, ensure that the air chamber is well sealed to avoid interference or leakage of external gas on the experimental results.

[0056] C2, partial discharge experiment applies test voltage: apply a gradually increasing test voltage to the defect model to ensure that partial discharge is stably generated under the set voltage conditions. Use a pulse current detection unit and a digital storage oscilloscope (such as Tektronix DPO7104) to continuously monitor the PD signal to confirm the stability and effectiveness of the discharge.

[0057] C3, timed sampling of decomposition products. During the 96-hour experimental period, set a fixed time interval (e.g., every 12 hours) to collect decomposition gas samples. Ensure that each sampling operation is relatively consistent and try to avoid mixing with external gases. Use a gas sampling device to draw out and collect part of the decomposition gas in the gas chamber to ensure that the sample volume is sufficient for analysis.

[0058] C4, decomposition gas component detection, using analytical instruments: the collected gas samples are sent to gas chromatography-mass spectrometry (GC-MS) and Fourier infrared spectrometer for detection. GC-MS analysis: gas chromatography is used to separate gas components, and the mass and concentration of each component are detected by mass spectrometer to obtain an accurate decomposition product spectrum. Fourier infrared spectrometer analysis: infrared absorption peaks of each component are detected by infrared spectroscopy, and the content of specific decomposition products is qualitatively and quantitatively analyzed.

[0059] It should be noted that the sampling results are recorded each time: the concentration values ​​of the decomposition products (such as SO2F2, NO2, etc.) obtained in each test are recorded to form time series data. Analysis of the concentration change trend over time is carried out: the concentration-time curve is drawn: the concentration of each specific decomposition product is drawn in the coordinate system as the experimental time changes, and its change trend is observed.

[0060] S4: Perform secondary characteristic analysis on the decomposed gas and obtain the diagnostic results through the characteristic quantities of local decomposition under different defects.

[0061] Furthermore, the secondary characteristic analysis includes judging the type of insulation defect and its severity through three decomposition characteristics: characteristic component type, characteristic component content, and average discharge amount per second.

[0062] In the embodiment of the present application, the secondary characteristic analysis of the decomposed gas may be performed by conducting a 96h partial discharge experiment, and the four defects specifically include D1 to D4:

[0063] Among them, air gap defect < metal protrusion defect < particle defect < contamination defect. SO2 content can be used as a characteristic quantity to determine the type of insulation defect.

[0064] D1, under the protrusion defect, when the average discharge per second reaches 30000pc, it is a slight PD; when the average discharge per second reaches 300000pc, it is a moderate PD; when the average discharge per second reaches 510000pc, it is a severe PD. The severity of the protrusion defect can be judged according to the size of the average discharge per second.

[0065] D2, under particle defects, when the average discharge per second reaches 96000pc, it is a slight PD; when the average discharge per second reaches 213000pc, it is a moderate PD; when the average discharge per second reaches 420000pc, it is a severe PD. The severity of the particle defect can be judged according to the size of the average discharge per second.

[0066] D3, under the condition of contamination defect, when the average discharge per second reaches 30000pc, it is a slight PD; when the average discharge per second reaches 63000pc, it is a moderate PD; when the average discharge per second reaches 123000pc, it is a severe PD. The severity of the contamination defect can be judged according to the size of the average discharge per second.

[0067] D4, under the condition of air gap defect, when the average discharge per second reaches 33000pc, it is a slight PD; when the average discharge per second reaches 93000pc, it is a moderate PD; when the average discharge per second reaches 207000pc, it is a severe PD. The severity of the air gap defect can be judged according to the size of the average discharge per second.

[0068] In an optional embodiment, the secondary characteristic analysis of the decomposition gas can also be to establish a dynamic discharge characteristic curve, including: curve analysis and characteristic extraction, trend analysis, and observation of the change trend of the discharge amount and the decomposition gas concentration over time, such as whether it is rising, stable or falling. Analyze the evolution path of the defect during the experimental time. Key point identification: Identify key points in the discharge amount and decomposition product concentration curves, such as sudden changes, stability or peaks. These key points may indicate the development stage or turning point of the defect. Correlation analysis: Combine the dynamic changes in the discharge amount with the changes in the decomposition gas concentration, analyze the relationship between the two, and find out the main factors affecting the evolution of the defect. For example, whether a high discharge amount corresponds to a concentration peak of a specific decomposition product.

[0069] It should be noted that the faults include insulation defects and fault severity. The decomposition characteristics include: characteristic component types, characteristic component contents, and average discharge capacity per second.

[0070] Example 3: The following is an embodiment of the present invention, which provides a fault diagnosis method based on the PD and decomposition characteristics of a mixed gas. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0071] First, the present embodiment builds the first discharge experimental platform based on SF6 / N2 mixed gas, and the platform includes an inductive voltage regulator, a corona-free test transformer, protective resistors R1 and R2, a capacitive voltage divider, a coupling capacitor C, a non-inductive detection impedance Z, a decomposition chamber, a digital storage oscilloscope, etc. A first defect model is provided in the decomposition chamber, which is a metal protrusion defect. Before the experiment begins, the inner wall and the defect model of the experimental platform are thoroughly cleaned with anhydrous ethanol to remove any impurities and contaminants that may affect the experimental results. Subsequently, the decomposition chamber is evacuated using a vacuum pump, and pure air is repeatedly filled and evacuated multiple times to ensure the purity of the gas in the chamber.

[0072] After the experiment started, a gradually increasing voltage was applied to the defect model through an inductive voltage regulator. The voltage was adjusted accurately and slowly until a stable partial discharge (PD) began to be generated in the defect model. A digital storage oscilloscope was used to monitor the PD signal and record the discharge current, number of pulses and amplitude. During the experiment, decomposition gas samples were collected regularly every 12 hours, and qualitative and quantitative analysis was performed using a gas chromatography-mass spectrometer (GC-MS) and a Fourier transform infrared spectrometer, recording the composition and concentration of the decomposition gas at different discharge stages.

[0073] A 96-hour continuous PD experiment was conducted for metal protrusion defects. During this period, five different voltage levels were used to test the changes in different discharge amounts, and the concentration change curves of characteristic components were analyzed to extract the generation rules and content changes of characteristic gases such as decomposition products SO2F2 and NO2. At the same time, the average discharge amount per second was recorded, and secondary characteristic analysis was carried out based on this.

[0074] Table 1 Gas concentration change data table

[0075]

[0076] It can be seen from the table data that during the 96-hour partial discharge experiment, the average discharge amount of the metal protrusion defect model continued to increase with the experimental time, gradually rising from the initial 30,000 pc / s to 510,000 pc / s after 96 hours. This shows that the discharge intensity of the defect has shown an aggravating trend with the increase of experimental time, showing a certain degradation trend. The concentrations of decomposition products SO2F2 and NO2 also gradually increase with the increase of discharge amount. In particular, the concentration of SO2F2 increased significantly within 96 hours, indicating that this gas is an important characteristic product under the metal protrusion defect, and its content change directly reflects the discharge intensity and the severity of defect evolution.

[0077] Embodiment 4, the following is an embodiment of the present invention, which provides a fault diagnosis system based on mixed gas PD and decomposition characteristics, including a gas collection module, a voltage control and pressure module, a gas composition analysis module, and a fault diagnosis submodule;

[0078] The gas collection module collects decomposition gas samples every 12 hours during the experiment, explores the air decomposition characteristics under different discharge levels, and counts and extracts relevant characteristic parameters.

[0079] The voltage regulation and pressure application module is composed of an inductive voltage regulator and a corona-free test transformer, which gradually applies a test voltage to the insulation defect model to control the generation of stable partial discharge.

[0080] The gas component analysis module performs qualitative and quantitative analysis on the decomposed gas through GC-MS and Fourier transform infrared spectrometer to identify and measure the decomposed gas components.

[0081] The fault diagnosis submodule determines the insulation defect type and the severity of the fault based on the decomposed gas characteristic products and PD characteristic quantities, using the characteristic gas and the discharge amount, and realizes systematic diagnosis of different types of defects.

[0082] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0083] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0084] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0085] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0086] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A fault diagnosis method based on mixed gas PD and decomposition characteristics, characterized in that: include: Build the first discharge experimental platform and deploy the first defect model; Performing a first discharge experiment on the first defect model and collecting statistical characteristic parameters; Perform a first characteristic analysis according to the characteristic parameter to obtain a first gas decomposition characteristic; The decomposed gas is subjected to secondary characteristic analysis, and the diagnostic results are obtained through the characteristic quantities of local decomposition under different defects.

2. The fault diagnosis method based on mixed gas PD and decomposition characteristics as claimed in claim 1, characterized in that: The building of the first discharge experiment platform includes building the first discharge experiment platform and cleaning the experiment device.

3. The fault diagnosis method based on mixed gas PD and decomposition characteristics as claimed in claim 2, characterized in that: The deploying the first defect model includes setting a decomposition gas chamber in the first discharge experimental platform and deploying the first defect model in the decomposition gas chamber.

4. The fault diagnosis method based on mixed gas PD and decomposition characteristics as claimed in claim 3, characterized in that: The first discharge experiment includes applying a test voltage to the first defect model by a step-by-step voltage increase method.

5. The fault diagnosis method based on mixed gas PD and decomposition characteristics as claimed in claim 4, characterized in that: The first characteristic analysis includes adjusting the voltage value to obtain different discharge values ​​and exploring the gas decomposition characteristics at different discharge levels.

6. The fault diagnosis method based on mixed gas PD and decomposition characteristics as claimed in claim 5, characterized in that: The first gas decomposition characteristic includes analyzing the change rules of PD decomposition products of the decomposed gas using GC-MS and Fourier transform infrared spectrometer.

7. The fault diagnosis method based on mixed gas PD and decomposition characteristics as claimed in claim 6, characterized in that: The secondary characteristic analysis includes judging the type of insulation defect and its severity through three decomposition characteristics: characteristic component type, characteristic component content, and average discharge amount per second.

8. A system using the fault diagnosis method based on mixed gas PD and decomposition characteristics as claimed in any one of claims 1 to 7, characterized in that: It includes gas collection module, voltage control and pressure module, gas composition analysis module and fault diagnosis submodule; The gas collection module collects decomposition gas samples every 12 hours during the experiment, explores the air decomposition characteristics under different discharge levels, and counts and extracts relevant characteristic parameters; The voltage control and pressure application module is composed of an induction voltage regulator and a corona-free test transformer, which gradually applies a test voltage to the insulation defect model to control the generation of a stable partial discharge; The gas component analysis module: performs qualitative and quantitative analysis on the decomposed gas through GC-MS and Fourier transform infrared spectrometer, and identifies and measures the decomposed gas components; The fault diagnosis submodule determines the insulation defect type and the severity of the fault based on the decomposed gas characteristic products and PD characteristic quantities, using the characteristic gas and the discharge amount, and realizes systematic diagnosis of different types of defects.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the fault diagnosis method based on the mixed gas PD and decomposition characteristics according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the fault diagnosis method based on the mixed gas PD and decomposition characteristics according to any one of claims 1 to 7 are implemented.

Images