Oil-immersed power transformer virtual reality simulation device and simulation method

Abstract

The invention discloses a virtual reality simulation device and method for an oil-immersed power transformer, and the device carries out the high-precision reduction and interactive simulation of the internal structure, working principle, operation and maintenance operation and fault phenomena of the transformer through a virtual reality technology, and builds a dynamic behavior model of the transformer in a power network. High-fidelity simulation of a fault evolution process is realized, and structural cognition, dismounting training, fault diagnosis and emergency disposal drilling are carried out on power engineers and operation and maintenance personnel.

Description

Technical Field

[0001] This invention relates to the field of power equipment simulation training and digital operation and maintenance technology, and in particular to a virtual reality simulation device and simulation method for an oil-immersed power transformer. Background Technology

[0002] Oil-immersed power transformers are the most critical and widely used static electricity conversion devices in power transmission and distribution systems. As a key node in the power grid, they connect grids of different voltage levels, enabling efficient, economical, and safe long-distance transmission and local distribution of electrical energy. Oil-immersed power transformers store a large amount of insulating oil (a flammable material) and powerful electromagnetic energy. When an oil-immersed power transformer malfunctions, this energy is released instantaneously, causing immense damage. Furthermore, internal faults (such as partial discharge and overheating) are often difficult to detect in their early stages but can rapidly escalate into catastrophic failures such as arc discharge and insulation breakdown. Moreover, when a fault occurs, the repair cycle for oil-immersed transformers can last for months, with extremely high replacement costs. The economic losses caused by industrial shutdowns, business disruptions, and social chaos are often tens or even hundreds of times the value of the equipment itself.

[0003] To ensure the safe and reliable operation of oil-immersed power transformers, the power industry has constructed a comprehensive defense system covering the entire lifecycle and integrating both technological and human safeguards. These efforts are systematic and continuously iterating, primarily manifested in the following aspects:

[0004] I. Source Control: Design and Manufacturing Stage

[0005] 1. High-standard design and simulation: Advanced electromagnetic field, thermal field, flow field and mechanical stress simulation calculations are used to optimize the insulation structure, cooling system and mechanical strength, eliminating weak points from the design stage.

[0006] 2. Strict material and process control: High-performance oriented silicon steel sheets, oxygen-free copper wires, high-quality insulating paperboard, and insulating oil are used. Key processes such as vacuum drying and vacuum oil injection are strictly controlled to ensure the initial integrity of the insulation system.

[0007] 3. Comprehensive factory testing: including but not limited to rigorous tests such as lightning impulse, power frequency withstand voltage, induced voltage, partial discharge, temperature rise, and short-circuit impedance, to ensure that each transformer is "certified to operate" and meets or even exceeds national standards (such as GB and IEC standards).

[0008] II. Core Defense Line: Operational Monitoring and Condition-Based Maintenance

[0009] 1. Dissolved gas analysis in oil: This is the "blood test" for monitoring latent internal faults. Regular or online monitoring of characteristic gases such as H2, CH4, and C2H2 is performed, and methods such as the three-ratio method and David's triangle are used to accurately determine the fault type (overheating, discharge) and severity.

[0010] 2. Partial discharge online monitoring: Sensitively captures early discharge signals inside the insulation and locates the discharge point, which is a cutting-edge method to prevent insulation breakdown.

[0011] 3. Comprehensive Electrical Testing: Regularly conduct winding deformation tests (frequency response method), insulation resistance, dielectric loss, core grounding current, etc., to assess the stability of the mechanical and insulation conditions. (For real-time testing, it is a cumulative process, an accumulation of experience, and cannot be achieved overnight.)

[0012] III. The Last Barrier: Protection and Fault Isolation

[0013] 1. Comprehensive primary / backup protection: Dual protection with different principles, such as differential protection (primary protection), gas protection (for internal tank faults), and overcurrent protection, to ensure that the protection "does not fail to operate and does not operate falsely".

[0014] 2. On-load tap changer: As a component prone to failure, its manufacturing process, online oil filtration, and mechanical condition monitoring have been specially strengthened.

[0015] 3. Sleeve: Adopts a capacitive structure to enhance sealing and online monitoring.

[0016] Current research on oil-immersed transformer faults is limited to certain types of faults. Research on other faults is hampered by technical limitations or excessively high costs, hindering the safer and more reliable operation of oil-immersed transformers. While the power industry has implemented various measures to ensure the safe and reliable operation of oil-immersed power transformers, these measures still have some shortcomings.

[0017] 1. Unsafe: During fault testing, oil-immersed power transformers contain a large amount of insulating oil (flammable material) and powerful electromagnetic energy. Internal faults (such as partial discharge and overheating) are not easily detected in the early stages, but may quickly evolve into catastrophic faults such as arc discharge and insulation breakdown. At this time, there is a risk to life for the personnel present.

[0018] 2. High cost: A brand new 110kV transformer may cost millions, while a 500kV ultra-high voltage transformer can cost tens of millions of yuan. Conducting destructive experiments on a large ultra-high voltage transformer would be prohibitively expensive.

[0019] 3. Poor Results: Numerical simulations are used to recreate real-world scenarios in fault-related research, but the simulation results are often unrealistic and differ significantly from actual results. Using decommissioned transformers could significantly reduce costs, but the uncertainty of their initial state might affect the generalizability of the experimental results.

[0020] 4. Poor Intelligence: The safe operation of traditional oil-immersed transformers largely relies on pre-set procedures, periodic inspections, and reactive responses, exhibiting significant shortcomings in "intelligence." Therefore, this lack of intelligence is primarily reflected in deficiencies across four dimensions: perception, cognition, decision-making, and evolution. Summary of the Invention

[0021] In view of the aforementioned shortcomings of the prior art, the technical problem to be solved by the present invention is that existing oil-immersed power transformer fault detection suffers from poor safety performance, endangers the lives of personnel, high cost, poor effectiveness, and lack of intelligence. The present invention provides a virtual reality simulation device and method for oil-immersed power transformers. This device uses virtual reality technology to accurately recreate and interactively simulate the internal structure, working principle, operation and maintenance, and fault phenomena of the transformer, constructing a dynamic behavior model of the transformer in the power network, achieving high-fidelity simulation of the fault evolution process, and providing training for power engineers and maintenance personnel in structural understanding and disassembly / reassembly, as well as fault diagnosis and emergency response drills.

[0022] This invention provides a virtual reality simulation device for oil-immersed power transformers. This simulation device aims to make the "black box" of transformers transparent, achieving efficient, in-depth, and risk-free operation and maintenance skills training. Specifically, it uses an external high-power electric heater to simulate partial discharge or arc insulation faults, and controls the heating time to simulate the severity of the fault. In reality, arc insulation faults are costly and highly dangerous, and their occurrence time is uncontrollable. When an arc insulation fault occurs in a transformer, the transformer oil expands due to heat and generates gas within the transformer, causing oil overflow. This triggers a gas relay, quickly cutting off the power supply to the transformer and ensuring its safety. This device uses transparent piping as much as possible and adds windows to present the characteristics of transformer oil overflow and the operating principle of the relay.

[0023] To achieve the above objectives, the present invention provides a virtual reality simulation device for an oil-immersed power transformer, comprising an oil-immersed power transformer heating chamber, a sensor system, and a data interface module; the sensor system is arranged in the oil-immersed power transformer heating chamber; the sensor system communicates with an online monitoring system or equipment management platform through the data interface module.

[0024] Furthermore, the sensor system includes a temperature sensor, a differential pressure sensor, a pressure pulsation sensor, and a vibration sensor. The temperature sensor is located at the top of the transformer to accurately monitor the internal temperature distribution. The differential pressure sensor is located in the riser section to indirectly monitor changes in transformer oil flow rate and determine if a leak exists. The pressure pulsation sensor is installed on the inner wall of the heating chamber to collect ultra-high frequency sound pressure signals excited by partial discharge or arc insulation faults. The vibration sensor is installed on the rigid structure of the transformer base shell to collect vibration signals caused by mechanical loosening and deformation.

[0025] Furthermore, the pressure pulsation sensor is connected to the transformer chamber via the upper pressure measurement lead-out pipe; the temperature sensor is installed on the top of the transformer near the relay; the differential pressure sensor is installed on the stainless steel pipe to collect the overflow flow rate of the transformer oil after partial discharge or arc insulation fault, transformer oil expansion or gas generation; and the vibration sensor is installed on the transformer base.

[0026] Furthermore, heat sinks are arranged on the side of the heating chamber, and an observation mirror and two lead-out pipes are arranged on the top of the chamber, which are used to install pressure pulsation sensors and temperature sensors, respectively. The lower right side of the heating chamber is connected in sequence by threads to the riser section, tee joint, stainless steel pipe and elbow. The end of the stainless steel pipe extends into the liquid receiving tank to receive the overflowing transformer oil. The riser section of the stainless steel pipe has two threaded holes, which are connected to the inlet and outlet of the differential pressure sensor through transparent silicone tubes, respectively, to indirectly measure the average flow rate of the overflowing oil.

[0027] Furthermore, the heater is installed on the front side of the enclosure, and its heating power, current, voltage and working time are precisely controlled by the control cabinet to simulate partial discharge or arc insulation fault inside the transformer.

[0028] In another preferred embodiment of the present invention, a virtual reality simulation method for an oil-immersed power transformer is provided, using the apparatus described above.

[0029] Furthermore, it includes the following steps:

[0030] Various status signals are collected through a sensor system. The collected data is then used to train a machine learning model. The trained model is then used for further fault diagnosis and outputs diagnostic results. At the same time, alarm signals of the corresponding level are triggered according to preset thresholds.

[0031] Furthermore, the slowly varying signal is directly input into the microprocessor; the high-frequency signal is converted by an A / D converter and then sent to the signal processing unit to complete bandpass filtering, wavelet denoising, and feature extraction.

[0032] Furthermore, various status signals are collected through a sensor system. Slowly changing signals such as temperature and pressure difference are directly sent to the microprocessor; high-frequency signals such as vibration, noise, and pressure pulsation are sent to the signal processing unit after A / D conversion.

[0033] Furthermore, feature extraction includes temperature rise slope, root mean square of differential pressure, and vibration kurtosis.

[0034] The advantages of the device of the present invention are:

[0035] (1) By constructing a high-fidelity, interactive, and multi-sensory virtual environment, the "black box" of the transformer is made transparent, enabling efficient, in-depth, and risk-free operation and maintenance skills training and condition assessment training, thereby providing a powerful technical tool for improving the inherent safety level of the power grid. Trainees can "enter" the inside of the transformer and intuitively see processes and consequences that are invisible to the naked eye, such as insulation aging, partial discharge, winding deformation, and multi-point grounding of the iron core.

[0036] (2) In an absolutely safe environment, simulate catastrophic scenarios such as short circuit explosion, fire, and oil spill to conduct emergency response drills without having to bear any real risks.

[0037] (3) Multi-sensory fault diagnosis training, which involves training in visual, auditory, and data linkage aspects. For example, visual training involves observing the dynamic changes in the internal structure, arc generation, and oil flow status during a fault. Auditory training involves associating different fault types with specific vibration and noise spectra and sound characteristics (such as discharge sounds and abnormal magnetic noise) to train auscultation judgment ability. Data linkage involves synchronously displaying virtual phenomena with real data such as online temperature, pressure, and vibration monitoring to establish a cognitive closed loop of "phenomenon-data-fault".

[0038] (4) Standard operating procedure training: Immersive drills of standard procedures such as inspection, switching operation, oil sampling, and desiccant replacement, to standardize operation and prevent misoperation.

[0039] The following will further explain the concept, specific structure, and technical effects of the present invention in conjunction with the accompanying drawings, so as to fully understand the purpose, features, and effects of the present invention. Attached Figure Description

[0040] Figure 1 This is a schematic diagram (front view) of a virtual reality simulation device for an oil-immersed power transformer according to a preferred embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram (rear view) of a virtual reality simulation device for an oil-immersed power transformer according to a preferred embodiment of the present invention.

[0042] Figure 3This is a physical image (front view) of a virtual reality simulation device for an oil-immersed power transformer according to a preferred embodiment of the present invention.

[0043] Figure 4 This is a physical image (rear view) of a virtual reality simulation device for an oil-immersed power transformer according to a preferred embodiment of the present invention. Detailed Implementation

[0044] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0045] In the following description, specific details, such as particular internal procedures and techniques, are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will appreciate that the invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of the invention with unnecessary detail.

[0046] This invention provides a virtual reality simulation device for an oil-immersed power transformer, comprising an oil-immersed power transformer heating chamber, a sensor system, and a data interface module; the sensor system is arranged in the oil-immersed power transformer heating chamber; the sensor system communicates with an online monitoring system or equipment management platform through the data interface module.

[0047] Specifically, the sensor system includes a temperature sensor, a differential pressure sensor, a pressure pulsation sensor, and a vibration sensor. The temperature sensor is installed at the top of the transformer to accurately monitor the internal temperature distribution. The differential pressure sensor is installed in the riser section to indirectly monitor changes in transformer oil flow rate and determine whether there are minor or major gas faults. The pressure pulsation sensor is installed on the inner wall of the heating chamber to collect ultra-high frequency sound pressure signals excited by partial discharge or arc insulation faults. The vibration sensor is installed on the rigid structure of the transformer base shell to collect vibration signals caused by mechanical loosening and deformation.

[0048] Specifically, such as Figure 1-2As shown, the simulation device is mounted on a mounting platform 19 with a movable support 1. It mainly includes a receiving tank 2, a heating chamber (transformer housing) 3, a heater 20, piping and connectors, a sensor system, and a control cabinet 15. Heat sinks 4 are arranged on the side of the heating chamber 3. An observation mirror 5, an oil inlet 6, and two outlet pipes are arranged on the top of the chamber, used to install a pressure pulsation sensor 7 and a temperature sensor 8, respectively. A riser section 9, a tee connector 10, a stainless steel pipe 11, and an elbow 12 are connected sequentially by threads to the lower right side of the heating chamber. The end of the stainless steel pipe 11 extends into the receiving tank 2 to collect overflowing transformer oil. The riser section 9 has two threaded holes 17 and 18, which are connected to the inlet and outlet of a differential pressure sensor 13 via transparent silicone tubes, respectively, for indirectly measuring the average flow rate of the overflowing oil. Figure 2 In the configuration, vibration sensor 16 is installed on the left side of the heating chamber near the base to measure the vibration signal of the chamber; heater 20 is installed on the front side of the chamber, and its heating power, current, voltage, and operating time are precisely controlled by control cabinet 15 to simulate partial discharge or arc insulation faults inside the transformer. All sensor signal lines, power lines, and heater power lines are connected to control cabinet 15 via integrated aviation connector 14.

[0049] The core of this device lies in its integration of an oil-immersed power transformer heating chamber, a multi-parameter sensor system, and a data interface module. The sensor system is distributed across key areas of the heating chamber and communicates with an external online monitoring system via the data interface module.

[0050] (1) Temperature sensor: installed on the top of the box to accurately monitor the internal oil temperature distribution and change trend.

[0051] (2) Differential pressure sensor: connected to the riser section, it indirectly and continuously monitors the change in transformer oil flow rate by measuring the differential pressure under a fixed pipe diameter, providing a basis for judging whether leakage or serious gas production has occurred.

[0052] (3) Pressure sensor: installed on the inner wall of the heating chamber, used to collect high-frequency (>10kHz) signals excited by partial discharge or arc fault.

[0053] (4) Vibration sensor: installed on rigid structures such as the base of the box, used to collect broadband vibration signals caused by mechanical loosening, deformation or severe internal electromagnetic force.

[0054] In this embodiment of the invention, the heating chamber (with a volume of approximately 8L) simulates a real transformer oil tank, with a built-in adjustable power heater (maximum power 5kW) and heat sinks and observation mirrors arranged on its surface.

[0055] According to the gas relay industry standard (JB / T9647-1999), the oil speed setting range of pipeline transformers is 0.7~1.5m / s, and national standard stainless steel pipes are used, with pipe diameters of DN25, DN32 and DN40 being preferred.

[0056] Considering the applicability of the device in harsh outdoor environments, the piezoresistive CY300 series differential pressure sensor with IP68 protection rating and a wide pressure range (-10kPa~+100 kPa) should be given priority.

[0057] Vibration sensors preferably use high-bandwidth sensors (such as 10kHz bandwidth sensors) to capture mechanical loosening signals.

[0058] In a preferred embodiment of the present invention, a virtual reality simulation method for an oil-immersed power transformer is provided, using the above-described apparatus.

[0059] Furthermore, it includes the following steps:

[0060] Various status signals are collected through a sensor system. The collected data is then used to train a machine learning model. The trained model is then used for further fault diagnosis and outputs diagnostic results. At the same time, alarm signals of the corresponding level are triggered according to preset thresholds.

[0061] Specifically, various state signals are collected through a sensor system, including: directly inputting slowly changing signals (temperature, pressure difference) into the microprocessor; high-frequency signals (vibration, pressure pulsation) are converted by an A / D converter and sent to the signal processing unit to complete bandpass filtering (50kHz~200kHz), wavelet denoising and feature extraction; extracted features include: temperature rise slope, root mean square of differential pressure, vibration kurtosis, etc.

[0062] By using historical data samples and their corresponding labels generated by this device, covering various operating conditions such as "normal state", "winding overheating" and "partial discharge", the fusion model of support vector machine (SVM) and convolutional neural network (CNN) is trained under supervision to improve the robustness and accuracy of diagnosis.

[0063] The real-time extracted feature vectors and preprocessed waveform segments are input into the trained fusion model. The model first performs primary classification to identify the presence of anomalies; then it performs fine-grained classification to accurately determine the fault mode.

[0064] This invention utilizes a simulation device to conduct an experiment on the internal overheating phenomenon of an oil-immersed transformer (the experiment simulates the physical phenomena and processes following partial insulation failure in the transformer, as well as the operation of the transformer's relay protection device). The specific implementation process is as follows:

[0065] (1) The heating rod inside the oil-immersed transformer on the experimental platform is turned on through the control cabinet to carry out internal heating.

[0066] (2) When the internal temperature is too high, bubbles will be generated inside, i.e. gas. As the gas increases, it will squeeze the internal fluid out through the stainless steel pipe.

[0067] (3) The control cabinet collects temperature signals, differential pressure signals, pressure pulsation signals and vibration signals under this condition.

[0068] (4) Each sensor converts the collected physical quantities (such as pressure, vibration acceleration, etc.) into electrical signals; then the signals are conditioned, including signal amplification and preliminary filtering to suppress noise; then the analog signals are discretized into digital signals by the analog-to-digital converter in the data acquisition module. On this basis, unit conversion and feature value extraction are performed, and the digital signals are further processed, such as bandpass filtering to remove power frequency interference, noise reduction and normalization.

[0069] (5) Finally, alarm feedback is provided based on multiple signals such as pressure and vibration.

[0070] Example: Simulating a partial discharge accident in a transformer winding

[0071] Step 1: Start heater 20 and set the stepped temperature rise program (initial temperature gradually rises from 20℃ to 120℃) to simulate winding overheating caused by sudden load increase or cooling failure.

[0072] Step 2: When the temperature exceeds 90℃, tiny bubbles (gas) begin to precipitate in the oil, the pressure rises, and the transformer oil flows into the receiving tank 2 through the stainless steel pipe 11.

[0073] Step 3: The differential pressure sensor detects that the oil flow rate reaches 1.2 m / s (within the JB / T9647-1999 standard operating threshold range), triggering a primary alarm;

[0074] Step 4: Continue heating to above 130°C, which causes violent vaporization and local electric arcs, and excites high-frequency pressure pulsations (>100kHz) and abnormal vibrations (with a peak acceleration of 0.8g).

[0075] Step 5: The control system acquires multi-source signals and sends them to the fault diagnosis model.

[0076] Slowly varying signals (temperature, pressure difference) are directly input to the microprocessor; high-frequency signals (vibration, pressure pulsation) are converted by an A / D converter and then sent to the signal processing unit to complete bandpass filtering (50kHz~200kHz), wavelet denoising and feature extraction.

[0077] Extracted features include: temperature rise slope, root mean square of differential pressure, vibration kurtosis, sound pressure envelope energy, etc.

[0078] Step 6: Use a pre-trained support vector machine (SVM) and convolutional neural network (CNN) fusion model for classification and identification to accurately determine the fault chain as "inter-turn short circuit overheating → partial discharge → oil cracking and gas generation → abnormal oil flow".

[0079] Step 7: The system automatically outputs a three-level alarm (yellow warning → orange alarm → red trip command), and at the same time plays the corresponding frequency of "crackling" discharge sound and low humming magnetic noise.

[0080] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A virtual reality simulation device for an oil-immersed power transformer, characterized in that, It includes an oil-immersed power transformer heating chamber, a sensor system, and a data interface module; the sensor system is arranged in the oil-immersed power transformer heating chamber; the sensor system communicates with an online monitoring system or equipment management platform through the data interface module.

2. The virtual reality simulation device for an oil-immersed power transformer as described in claim 1, characterized in that, The sensor system includes a temperature sensor, a differential pressure sensor, a pressure pulsation sensor, and a vibration sensor. The temperature sensor is located at the top of the transformer to accurately monitor the internal temperature distribution. The differential pressure sensor is located in the rising section of the stainless steel pipe to indirectly monitor changes in transformer oil flow rate, thereby determining whether a minor or major gas fault exists. The pressure pulsation sensor is installed on the inner wall of the heating chamber to collect ultra-high frequency sound pressure signals excited by partial discharge or arc insulation faults. The vibration sensor is installed on the rigid structure of the transformer base shell to collect vibration signals caused by mechanical loosening and deformation.

3. The virtual reality simulation device for an oil-immersed power transformer as described in claim 2, characterized in that, The pressure pulsation sensor is connected to the transformer chamber via an upper pressure measurement lead-out pipe; the temperature sensor is installed on the top of the transformer near the relay; the differential pressure sensor is installed on the rising section of the stainless steel pipe to collect the overflow flow rate of the transformer oil after the transformer oil expands or generates gas due to partial discharge or arc insulation fault; the vibration sensor is installed at the transformer base.

4. The virtual reality simulation device for an oil-immersed power transformer as described in claim 2, characterized in that, The heating chamber has heat sinks on its side, and an observation mirror and two outlet pipes are arranged on the top of the chamber for installing a pressure pulsation sensor and a temperature sensor, respectively. The lower right side of the heating chamber is connected by threads to a riser section, a tee joint, a stainless steel pipe and an elbow. The end of the stainless steel pipe extends into a receiving tank to collect overflowing transformer oil. The riser section of the stainless steel pipe has two threaded holes, which are connected to the inlet and outlet of the differential pressure sensor through transparent silicone tubes, respectively, for indirectly measuring the average flow rate of the overflowing oil.

5. The virtual reality simulation device for an oil-immersed power transformer as described in claim 4, characterized in that, The heater is installed on the front side of the enclosure. Its heating power, current, voltage and working time are precisely controlled by the control cabinet to simulate partial discharge or arc insulation fault inside the transformer.

6. A virtual reality simulation method for an oil-immersed power transformer, characterized in that, Use the apparatus as described in any one of claims 1-5.

7. The virtual reality simulation method for an oil-immersed power transformer as described in claim 6, characterized in that, Includes the following steps: The sensor system collects various status signals, then trains a machine learning model on the collected data, uses the trained model for further fault diagnosis, outputs diagnostic results, and triggers alarm signals of the corresponding level based on preset thresholds.

8. The virtual reality simulation method for an oil-immersed power transformer as described in claim 6, characterized in that, Slowly varying signals are directly input into the microprocessor; high-frequency signals are converted from digital signals to digital signals and then sent to the signal processing unit to perform bandpass filtering, wavelet denoising, and feature extraction.

9. The virtual reality simulation method for an oil-immersed power transformer as described in claim 8, characterized in that, The sensor system collects various status signals, including slowly changing signals such as temperature and pressure difference, which are directly sent to the microprocessor; and high-frequency signals such as vibration, noise, and pressure pulsation, which are sent to the signal processing unit after A / D conversion.

10. The virtual reality simulation method for an oil-immersed power transformer as described in claim 8, characterized in that, Feature extraction includes temperature rise slope, root mean square of differential pressure, and vibration kurtosis.

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