A method and system for determining micro-gap vibration-induced cavitation of insulating oil

Abstract

This invention discloses a method and system for determining vibration-induced cavitation in micro-gap insulating oil, relating to the field of power equipment condition monitoring technology. First, a micro-gap fluid pressure analysis model under vibration is established. By considering a nonlinear model with multi-field coupling, the fluid pressure in the micro-gap is obtained. Then, to analyze the cavitation pressure threshold of bubble nuclei, a multi-parameter coupled analytical model incorporating dynamic gas-liquid balance correction is established to obtain the cavitation pressure threshold. Finally, a dynamic cavitation determination and critical state early warning model for insulating oil is established to obtain the cavitation risk factor and cavitation determination results. The method proposed in this invention considers the influence of multiple dynamic factors, has good dynamic adaptability, and the introduction of a multi-field coupled nonlinear model improves the accuracy of cavitation determination, providing a new approach for micro-gap cavitation research.

Description

Technical Field

[0001] This invention relates to the field of power equipment condition monitoring technology, and more specifically to a method and system for determining vibration-induced cavitation in insulating oil micro-gap. Background Technology

[0002] Currently, the insulating oil in high-voltage equipment such as power transformers is affected by electromagnetic forces and mechanical vibrations during long-term operation. Its internal oil-paper insulation structure is complex, and numerous inherent narrow oil gaps exist at locations such as winding turns, pads, and support bars. Accumulated damage and deformation of structural components under long-term vibration, as well as loosening of parts after mechanical tension relaxation, can lead to the formation of secondary narrow oil gaps within the equipment. The insulating oil in these narrow gaps is hindered from flowing due to the "constraint" of the micro-gap structure, making it more prone to pressure fluctuations under vibration, causing cavitation in the insulating oil, generating bubbles, accelerating the aging of insulation materials, and even triggering partial discharge (PD). Therefore, accurately determining the cavitation state is crucial for equipment health management.

[0003] In recent years, scholars both domestically and internationally have proposed various methods for determining cavitation. One such method involves comparing real-time oil pressures. Compared with the theoretical cavitation threshold Cavitation risk assessment (usually determined by Antoine equations or experimental calibration) is simple to implement, computationally inexpensive, and suitable for embedded systems. However, it does not consider dynamic interferences such as oil flow pulsation and temperature transients, and fixed thresholds cannot adapt to changes in parameters such as gas content (G) and humidity (W), resulting in a false alarm rate of over 30%. Acoustic emission detection uses high-frequency sensors (20 kHz to 1 MHz) to capture the acoustic signals generated by the collapse of cavitation bubbles. Cavitation is identified through characteristics such as amplitude and frequency domain energy. This method can detect early cavitation and has high sensitivity, but it is easily affected by mechanical vibrations (such as oil pump noise), and the sensor placement requirements are also stringent. Vibration-pressure coupling analysis combines vibration acceleration signals with local pressure fluctuations. For example, by calculating the frequency domain energy ratio or phase difference through FFT, the vibration source and cavitation phenomenon can be correlated, improving the specificity of the assessment. However, it requires simultaneous sampling by multiple sensors, resulting in high hardware costs, and temperature changes may affect the vibration signal baseline. Machine learning models are trained on historical data to classify models (such as LSTM and random forest), and multi-parameter prediction of cavitation risk can be integrated to adapt to complex nonlinear working conditions. However, this method relies on a large amount of labeled data, while actual cavitation samples are scarce, and the model's generalization ability is insufficient. For example, different oil products need to be retrained.

[0004] Existing cavitation determination methods have the following drawbacks: (1) Insufficient dynamic adaptability. Critical pressure at which cavitation occurs. It is not a fixed value, but is dynamically affected by multiple factors such as temperature (T), gas content (G), flow rate (v), and oil aging degree (A). Most existing methods use static thresholds, leading to problems such as high false alarm rates and poor adaptability to operating conditions. For example, at high temperatures, the saturated vapor pressure of the oil increases, and if the normal temperature threshold is still used, cavitation will be missed; conversely, at low temperatures, false alarms are likely. If the same equipment increases in service life, the threshold needs to be manually adjusted, lacking adaptability.

[0005] (2) Multiphysics field decoupling problem. Cavitation is the result of the coupling effect of flow field, sound field, thermal field and structural vibration. However, existing methods often analyze a single signal in isolation, such as only considering pressure or vibration, which will lead to information loss and cross-interference. Because the pressure signal is modulated by mechanical vibration, it will be misjudged as cavitation if it is not decoupled. In addition, oil temperature changes affect both oil viscosity (flow field) and sensor baseline (vibration field), which cannot be distinguished by a single signal.

[0006] (3) Lack of microscale modeling. Micro-gaps (<100) The initial mechanism of internal cavitation differs significantly from that of macroscopic cavitation, but existing models (such as the Rayleigh-Plesset equation) do not consider it. a. Wall effect: The boundary layer accounts for a large proportion within the micro-gap, leading to nonlinear local pressure gradient.

[0007] b. Gas nucleus distribution: The macroscopic model assumes that the gas nuclei are uniformly distributed, but in the actual micro-gap, the gas nuclei are affected by the surface roughness and aggregate.

[0008] c. Transient characteristics: The collapse time of microscale cavitation bubbles is extremely short ( (Level), traditional CFD mesh scales are difficult to capture.

[0009] Analyzing these common technological shortcomings reveals underlying causes including limitations in theoretical models, bottlenecks in sensor technology, and contradictions in data processing. First, the limitations of theoretical models stem from the incomplete understanding of the cavitation initiation mechanism, especially gas nucleus dynamics at the microscale, and the high complexity of solving multiphysics coupling equations, forcing simplification in engineering. Second, the bottleneck in sensor technology arises because existing pressure / vibration sensors struggle to simultaneously meet microscale resolution requirements (e.g., Requirements include high-frequency response (>100kHz) and resistance to oil contamination. Finally, in terms of data processing, high precision requires multimodal data fusion, but edge devices have limited computing power, making real-time processing difficult.

[0010] Therefore, how to provide a method and system for determining vibration-induced cavitation in insulating oil micro-gap is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0011] In view of this, the present invention provides a method and system for determining vibration-induced cavitation in insulating oil micro-gap, in order to solve the problems in the background art.

[0012] To achieve the above objectives, the present invention adopts the following technical solution: On one hand, this invention discloses a method for determining vibration-induced cavitation in insulating oil micro-gap, comprising: Establish a micro-gap fluid pressure analysis model under vibration, and input the vibration angular frequency. ω The amplitude Δ of the vibrating plate h Dynamic coupling, real-time correction of calculation speed, and adaptive parameter adjustment; the coupling coefficient is updated every set fixed interval to output vibration velocity. u According to the vibration velocity u Establish vibration velocity based on micro-gap structural features u Micro-gap structural characteristics and fluid pressure in micro-gap P f Relationship; A multi-parameter coupled analytical model with dynamic gas-liquid equilibrium correction was established to obtain the bubble nucleus cavitation pressure threshold; Based on fluid pressure P f Based on the cavitation pressure threshold of bubble nuclei, a dynamic cavitation judgment and critical state early warning model for insulating oil was established, and cavitation risk factors were obtained. And cavitation determination results.

[0013] Preferably, in the above-mentioned method for determining vibration-induced cavitation in insulating oil micro-gap, the output vibration velocity... u The specific steps are as follows: ); Where k is the dynamic coupling coefficient, which is dynamically optimized based on historical data using the recursive least squares method and the amplitude change rate. Feedback; ω Δ is the angular frequency of vibration. h This represents the amplitude of the vibrating plate.

[0014] Through the above technical solution, a micro-gap fluid pressure analysis model under vibration is established, in which the wall vibration velocity is solved using a nonlinear coupled model, with the vibration angular frequency as the input. ω The amplitude Δ of the vibrating plate h， The recursive least squares method is used to correct the dynamic coupling coefficient and update the vibration velocity in real time, which has good dynamic adaptability.

[0015] Preferably, in the above-mentioned method for determining vibration-induced cavitation in insulating oil micro-gap, the vibration velocity is established. u Micro-gap structural characteristics and fluid pressure in micro-gap P f Relationship:

[0016] in, For oil density, For dynamic viscosity, This represents the static pressure gradient. ; This refers to the width of the micro-gap. It is the vibration acceleration; The vibration velocity is considered. Since the micro-gap height shifts during vibration due to the displacement of the vibrating plate, dynamic gap compensation is introduced to correct the gap height in real time through vibration displacement integration. h :

[0017] in h 0 represents the initial gap height.

[0018] The above technical solution allows for dynamic adjustment of oil viscosity based on oil temperature, and introduces dynamic clearance compensation to correct the clearance height in real time through vibration displacement integration, which is closer to engineering practice.

[0019] Preferably, in the above-mentioned method for determining vibration-induced cavitation in insulating oil micro-gap, the specific steps for establishing a multi-parameter coupled analytical model with dynamic gas-liquid balance correction to obtain the bubble nucleus cavitation pressure threshold are as follows: Calculate the critical radius of the bubble nucleus With oil saturated vapor pressure To establish a dynamic equilibrium relationship between dissolved gas and free gas bubbles; To quantify the effects of humidity and temperature on the surface tension of the oil-gas interface To investigate the combined effects of these factors, a hybrid attenuation model was established. The critical radius of the bubble nucleus Surface tension at the oil-gas interface Calculate the final cavitation pressure threshold. .

[0020] By introducing the above technical solution, a Henry's constant temperature correction is introduced to quantify the influence of humidity and temperature on the surface tension of the oil-gas interface. A cavitation threshold is generated based on parameters such as gas content (G), oil temperature (T), and humidity (W). This stability assessment indicator.

[0021] Preferably, in the above-mentioned method for determining vibration-induced cavitation in insulating oil micro-gap, the critical radius model is expressed as: ; in, k H ( T () is the temperature-corrected Henry's constant. The external static pressure is taken as the actual oil pressure; Gas content in insulating oil; Temperature of the insulating oil; Avogadro's constant; Since changes in oil temperature typically cause a drift in the Henry's constant, a temperature correction term for the Henry's constant is introduced: ; in, It is the heat of solution of the gas. This is a reference temperature, typically 298 K; Reference temperature Henry's constant under the following conditions; is the ideal gas constant.

[0022] Preferably, in the above-mentioned method for determining vibration-induced cavitation in insulating oil micro-gap, a mixed attenuation model is established, and the surface tension of the oil-gas interface is considered.

[0023] ; in, As a reference surface tension, The humidity attenuation coefficient is... This is the temperature linearity coefficient; It is a natural constant; This refers to the moisture content in the insulating oil. This refers to the temperature of the insulating oil.

[0024] Preferably, in the above-mentioned method for determining vibration-induced cavitation in insulating oil micro-gap, the final cavitation pressure threshold is calculated. : ; in, This refers to the gas content in the insulating oil. Temperature of the insulating oil; This refers to the moisture content in the insulating oil. The temperature-dependent saturated vapor pressure of the oil. To compensate for localized temperature rise; The surface tension at the oil-gas interface; The specific heat capacity at constant pressure of insulating oil; Density of insulating oil; The critical radius of the bubble nucleus.

[0025] Preferably, in the above-mentioned method for determining vibration-induced cavitation in insulating oil micro-gap, a dynamic cavitation determination and critical state early warning model for insulating oil is established, and the specific steps are as follows: Calculate fluid pressure P f With cavitation pressure thresholdP B The difference is normalized, and an exponential decay term is introduced to suppress misjudgments caused by transient pressure fluctuations. The normalized pressure difference is then normalized. ; Normalized pressure difference The transformation mapping is converted into a cavitation risk factor, and a Sigmoid function and a risk perception correction factor are introduced to enhance risk perception during sudden temperature changes. Early warning of cavitation state in insulating oil micro-gap under vibration is achieved by using the dynamic change rate of risk factors. Absolute pressure threshold A multi-judgment mechanism is used, where a cavitation critical state is determined when multiple criteria are met simultaneously.

[0026] The above technical solutions introduce an exponential decay term to suppress misjudgments caused by transient pressure fluctuations, a sigmoid function and a risk perception correction factor to enhance risk perception during sudden temperature changes, and a dynamic rate of change of risk factors. Absolute pressure threshold Multiple judgment mechanisms are used to avoid the limitations of a single criterion.

[0027] Preferably, in the above-mentioned method for determining vibration-induced cavitation in insulating oil micro-gap, the cavitation risk factor is: in, This is the sensitivity coefficient. As a weight for temperature stability; Normalized pressure difference; This is the absolute pressure threshold; This represents the rate of change of the cavitation threshold with respect to temperature.

[0028] On the other hand, the present invention discloses a system for determining vibration-induced cavitation in insulating oil micro-gap, which applies the above method and includes: The micro-gap fluid pressure analysis module under vibration includes a wall vibration velocity solution submodule and a fluid pressure calculation submodule based on multi-field coupling. The wall vibration velocity solution submodule dynamically couples, corrects the calculation speed in real time, and adaptively adjusts the parameters. It updates the coupling coefficient once every set fixed time interval and outputs the vibration velocity. The fluid pressure calculation submodule based on multi-field coupling calculates the fluid pressure in the micro-gap based on the vibration velocity and the micro-gap structural characteristics. The bubble nucleus cavitation pressure threshold analysis module includes a gas-liquid balance submodule, a surface tension correction submodule, and a cavitation threshold synthesis submodule. The gas-liquid balance submodule calculates the critical radius of the bubble nucleus through Henry's constant temperature correction. The surface tension correction submodule calculates the surface tension under the combined influence of temperature and humidity. The critical radius of the bubble nucleus and the surface tension are integrated to calculate the final cavitation pressure threshold. The insulating oil dynamic cavitation determination and critical state early warning module includes a dynamic pressure difference normalization submodule, a cavitation risk factor synthesis submodule, and a critical state early warning submodule. The dynamic pressure difference normalization submodule calculates the normalized pressure difference and introduces an exponential decay term to suppress transient fluctuations. The cavitation risk factor is calculated using the Sigmoid function and a temperature correction factor. The critical state early warning submodule determines whether the system is in a critical cavitation state based on multiple criteria.

[0029] As can be seen from the above technical solution, compared with the prior art, this invention discloses a method and system for determining vibration-induced cavitation in insulating oil micro-gap. First, a micro-gap fluid pressure analysis model under vibration is established. This model includes a wall vibration velocity solution module and an insulating oil micro-gap fluid pressure calculation module based on multi-field coupling. By considering a nonlinear model with multi-field coupling, the micro-gap fluid pressure is obtained. Then, to analyze the bubble nucleus cavitation pressure threshold, a multi-parameter coupled analytical model incorporating dynamic gas-liquid balance correction is established, including a gas-liquid balance module, a surface tension correction module, and a cavitation threshold synthesis module, to obtain the bubble nucleus cavitation pressure threshold. Finally, a dynamic cavitation determination and critical state early warning model for insulating oil is established, including a dynamic pressure difference normalization module, a cavitation risk factor synthesis module, and a critical state early warning module, to obtain the cavitation risk factor. The method proposed in this patent considers the influence of multiple dynamic factors, has good dynamic adaptability, and introduces a multi-field coupled nonlinear model, which improves the accuracy of cavitation determination and provides a new approach for the study of micro-gap cavitation.

[0030] The technical advantages of this invention are as follows: 1) The proposed method for determining vibration-induced cavitation in insulating oil micro-gap takes into account multiple influencing factors such as temperature (T), gas content (G), and humidity (W), which improves the static threshold of traditional methods that consider a single factor and has good dynamic adaptability.

[0031] 2) The proposed method for determining vibration-induced cavitation in insulating oil micro-gap introduces multi-field coupling effects and considers both oil temperature and gap geometry, thereby improving the accuracy of cavitation determination.

[0032] 3) The proposed method for determining vibration-induced cavitation in insulating oil micro-gap is based on micro-scale modeling and introduces dynamic gap compensation. The gap height is corrected in real time through vibration displacement integration, which is closer to engineering practice and provides ideas for studying the initial mechanism of micro-gap cavitation and macroscopic size differences. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0034] Figure 1 This is a schematic diagram of the vibration structure of the insulating oil micro-gap wall provided by the present invention; Figure 2 The present invention provides a micro-gap fluid pressure analysis model under vibration. Figure 3 This invention provides a bubble nucleation cavitation pressure threshold analysis model. Figure 4 The present invention provides a dynamic cavitation determination and critical state early warning model for insulating oil. Figure 5 The method flowchart provided by the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] This invention discloses a method for determining vibration-induced cavitation in insulating oil micro-gap, such as... Figure 1 and 5 As shown, it includes: Establish a micro-gap fluid pressure analysis model under vibration, and input the vibration angular frequency. ω The amplitude Δ of the vibrating plate h Dynamic coupling, real-time correction of calculation speed, and adaptive parameter adjustment; the coupling coefficient is updated every set fixed interval to output vibration velocity. u According to the vibration velocity u Establish vibration velocity based on micro-gap structural features u Micro-gap structural characteristics and fluid pressure in micro-gap P f Relationship; A multi-parameter coupled analytical model with dynamic gas-liquid equilibrium correction was established to obtain the bubble nucleus cavitation pressure threshold; Based on fluid pressure P f Based on the cavitation pressure threshold of bubble nuclei, a dynamic cavitation judgment and critical state early warning model for insulating oil was established, and cavitation risk factors were obtained. And cavitation determination results.

[0037] It should be noted that, for analysis purposes, Figure 1 The fluid pressure in the structure is analyzed by establishing a micro-gap fluid pressure analysis model under vibration, and solving for the wall vibration velocity and the insulating oil micro-gap fluid pressure based on multi-field coupling. To further optimize the above technical solutions, such as Figure 2 As shown, the output vibration velocity u The specific steps are as follows: ); Where k is the dynamic coupling coefficient, which is dynamically optimized based on historical data using the recursive least squares method and the amplitude change rate. Feedback; ω Δ is the angular frequency of vibration. h This represents the amplitude of the vibrating plate.

[0038] Furthermore, establish vibration velocity u Micro-gap structural characteristics and fluid pressure in micro-gap P f Relationship:

[0039] in, For oil density, This refers to dynamic viscosity (including temperature correction). This represents the static pressure gradient. ; This refers to the width of the micro-gap. It is the vibration acceleration; The vibration velocity is considered. Since the micro-gap height shifts during vibration due to the displacement of the vibrating plate, dynamic gap compensation is introduced to correct the gap height in real time through vibration displacement integration. h :

[0040] in h 0 represents the initial gap height.

[0041] To further optimize the above technical solutions, such as Figure 3 As shown, the specific steps for establishing a multi-parameter coupled analytical model with dynamic gas-liquid equilibrium correction to obtain the bubble nucleus cavitation pressure threshold are as follows: Calculate the critical radius of the bubble nucleus With oil saturated vapor pressure To establish a dynamic equilibrium relationship between dissolved gas and free gas bubbles; To quantify the effects of humidity and temperature on the surface tension of the oil-gas interface To investigate the combined effects of these factors, a hybrid attenuation model was established. The critical radius of the bubble nucleus Surface tension at the oil-gas interface Calculate the final cavitation pressure threshold. .

[0042] To further optimize the above technical solution, the critical radius model is expressed as follows: ; in, k H ( T () is the temperature-corrected Henry's constant. The external static pressure is taken as the actual oil pressure; Gas content in insulating oil; Temperature of the insulating oil; Avogadro's constant; Since changes in oil temperature typically cause a drift in the Henry's constant, a temperature correction term for the Henry's constant is introduced:

[0043] in, It is the heat of solution of the gas. This is a reference temperature, typically 298 K; Reference temperature Henry's constant under the following conditions; is the ideal gas constant.

[0044] To further optimize the above technical solution, a hybrid attenuation model was established, and the surface tension of the oil-gas interface was considered.

[0045] ; in, The reference surface tension is 0.03 N / m for mineral oil. This is the humidity attenuation coefficient (experimental calibration value). The temperature linearity coefficient is 0.0005~0.001 K. -1 ); It is a natural constant; This refers to the moisture content in the insulating oil. This refers to the temperature of the insulating oil.

[0046] To further optimize the above technical solution, the final cavitation pressure threshold is calculated. : ; in, This refers to the gas content in the insulating oil. Temperature of the insulating oil; This refers to the moisture content in the insulating oil. The temperature-dependent saturated vapor pressure of the oil. To compensate for localized temperature rise; The surface tension at the oil-gas interface; The specific heat capacity at constant pressure of insulating oil; Density of insulating oil; The critical radius of the bubble nucleus.

[0047] To further optimize the above technical solutions, such as Figure 4 As shown, a dynamic cavitation determination and critical state early warning model for insulating oil is established. The specific steps are as follows: Calculate fluid pressure P f With cavitation pressure threshold P B The difference is normalized, and an exponential decay term is introduced to suppress misjudgments caused by transient pressure fluctuations. The normalized pressure difference is then normalized. ; Normalized pressure difference The transformation mapping is converted into a cavitation risk factor, and a Sigmoid function and a risk perception correction factor are introduced to enhance risk perception during sudden temperature changes. Early warning of cavitation state in insulating oil micro-gap under vibration is achieved by using the dynamic change rate of risk factors. Absolute pressure threshold A multi-judgment mechanism is used, where a cavitation critical state is determined when multiple criteria are met simultaneously.

[0048] To further optimize the above technical solution, the pressure difference is normalized: ; in, This is the oil flow pulsation time constant (default 10 ms, calibrated through CFD simulation).

[0049] To further optimize the above technical solution, cavitation risk factors: in, This is the sensitivity coefficient. As a weight for temperature stability; Normalized pressure difference; This is the absolute pressure threshold; This represents the rate of change of the cavitation threshold with respect to temperature.

[0050] when When defined as "safe"; when When is defined as "early warning"; when The time is defined as "critical" and a critical state warning is input.

[0051] To further optimize the above technical solution, an early warning system is developed for the cavitation state in the micro-gap of insulating oil under vibration. A dynamic change rate of risk factors is introduced. Absolute pressure threshold Multiple judgment mechanisms are employed to avoid the limitations of a single criterion. When multiple criteria are simultaneously met, the state is determined to be cavitation critical. The multiple criteria are as follows: .

[0052] Another embodiment of the present invention discloses a system for determining vibration-induced cavitation in insulating oil micro-gap, such as... Figure 2-4 As shown, applying the above method includes: The micro-gap fluid pressure analysis module under vibration includes a wall vibration velocity solution submodule and a fluid pressure calculation submodule based on multi-field coupling. The wall vibration velocity solution submodule dynamically couples, corrects the calculation speed in real time, and adaptively adjusts the parameters. It updates the coupling coefficient once every set fixed time interval and outputs the vibration velocity. The fluid pressure calculation submodule based on multi-field coupling calculates the fluid pressure in the micro-gap based on the vibration velocity and the micro-gap structural characteristics. The bubble nucleus cavitation pressure threshold analysis module includes a gas-liquid balance submodule, a surface tension correction submodule, and a cavitation threshold synthesis submodule. The gas-liquid balance submodule calculates the critical radius of the bubble nucleus through Henry's constant temperature correction. The surface tension correction submodule calculates the surface tension under the combined influence of temperature and humidity. The critical radius of the bubble nucleus and the surface tension are integrated to calculate the final cavitation pressure threshold. The insulating oil dynamic cavitation determination and critical state early warning module includes a dynamic pressure difference normalization submodule, a cavitation risk factor synthesis submodule, and a critical state early warning submodule. The dynamic pressure difference normalization submodule calculates the normalized pressure difference and introduces an exponential decay term to suppress transient fluctuations. The cavitation risk factor is calculated using the Sigmoid function and a temperature correction factor. The critical state early warning submodule determines whether the system is in a critical cavitation state based on multiple criteria.

[0053] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0054] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining vibration-induced cavitation in insulating oil micro-gap, characterized in that, include: Establish a micro-gap fluid pressure analysis model under vibration, and input the vibration angular frequency. ω The amplitude Δ of the vibrating plate h Dynamic coupling, real-time correction of calculation speed, and adaptive parameter adjustment; the coupling coefficient is updated every set fixed interval to output vibration velocity. u According to the vibration velocity u Establish vibration velocity based on micro-gap structural features u Micro-gap structural characteristics and fluid pressure in micro-gap P f Relationship; A multi-parameter coupled analytical model with dynamic gas-liquid equilibrium correction was established to obtain the bubble nucleus cavitation pressure threshold; Based on fluid pressure P f Based on the cavitation pressure threshold of bubble nuclei, a dynamic cavitation judgment and critical state early warning model for insulating oil was established, and cavitation risk factors were obtained. And cavitation determination results.

2. The method for determining vibration-induced cavitation in insulating oil micro-gap according to claim 1, characterized in that, Output vibration velocity u The specific steps are as follows: ）； Where k is the dynamic coupling coefficient, which is dynamically optimized based on historical data using the recursive least squares method and the amplitude change rate. Feedback; ω Δ is the angular frequency of vibration. h This represents the amplitude of the vibrating plate.

3. The method for determining vibration-induced cavitation in insulating oil micro-gap according to claim 1, characterized in that, Establish vibration velocity u Micro-gap structural characteristics and fluid pressure in micro-gap P f Relationship: in, For oil density, For dynamic viscosity, This represents the static pressure gradient. ; This refers to the width of the micro-gap. It is the vibration acceleration; The vibration velocity is considered. Since the micro-gap height shifts during vibration due to the displacement of the vibrating plate, dynamic gap compensation is introduced to correct the gap height in real time through vibration displacement integration. h : in h 0 represents the initial gap height.

4. The method for determining vibration-induced cavitation in insulating oil micro-gap according to claim 1, characterized in that, The specific steps for establishing a multi-parameter coupled analytical model with dynamic gas-liquid equilibrium correction to obtain the bubble nucleus cavitation pressure threshold are as follows: Calculate the critical radius of the bubble nucleus With oil saturated vapor pressure To establish a dynamic equilibrium relationship between dissolved gas and free gas bubbles; To quantify the effects of humidity and temperature on the surface tension of the oil-gas interface To investigate the combined effects of these factors, a hybrid attenuation model was established. The critical radius of the bubble nucleus Surface tension at the oil-gas interface Calculate the final cavitation pressure threshold. .

5. The method for determining vibration-induced cavitation in insulating oil micro-gap according to claim 4, characterized in that, The critical radius model is expressed as: ； in, k H ( T () is the temperature-corrected Henry's constant. The external static pressure is taken as the actual oil pressure; Gas content in insulating oil; Temperature of the insulating oil; Avogadro's constant; Since changes in oil temperature typically cause a drift in the Henry's constant, a temperature correction term for the Henry's constant is introduced: ； in, It is the heat of solution of the gas. This is a reference temperature, typically 298 K; Reference temperature Henry's constant under the following conditions; is the ideal gas constant.

6. The method for determining vibration-induced cavitation in insulating oil micro-gap according to claim 4, characterized in that, Establish a hybrid attenuation model and the surface tension of the oil-gas interface. ； in, As a reference surface tension, The humidity attenuation coefficient is... This is the temperature linearity coefficient; It is a natural constant; This refers to the moisture content in the insulating oil. This refers to the temperature of the insulating oil.

7. The method for determining vibration-induced cavitation in insulating oil micro-gap according to claim 4, characterized in that, Calculate the final cavitation pressure threshold : ； in, This refers to the gas content in the insulating oil. Temperature of the insulating oil; This refers to the moisture content in the insulating oil. The temperature-dependent saturated vapor pressure of the oil. To compensate for localized temperature rise; The surface tension at the oil-gas interface; The specific heat capacity at constant pressure of insulating oil; Density of insulating oil; The critical radius of the bubble nucleus.

8. The method for determining vibration-induced cavitation in insulating oil micro-gap according to claim 1, characterized in that, The specific steps for establishing a dynamic cavitation determination and critical state early warning model for insulating oil are as follows: Calculate fluid pressure P f With cavitation pressure threshold P B The difference is normalized, and an exponential decay term is introduced to suppress misjudgments caused by transient pressure fluctuations. The normalized pressure difference is then normalized. ; Normalized pressure difference The transformation mapping is converted into a cavitation risk factor, and a Sigmoid function and a risk perception correction factor are introduced to enhance risk perception during sudden temperature changes. Early warning of cavitation state in insulating oil micro-gap under vibration is achieved by using the dynamic change rate of risk factors. Absolute pressure threshold A multi-judgment mechanism is used, where a cavitation critical state is determined when multiple criteria are met simultaneously.

9. The method for determining vibration-induced cavitation in insulating oil micro-gap according to claim 1, characterized in that, Cavitation risk factors: ; in, This is the sensitivity coefficient. As a weight for temperature stability; Normalized pressure difference; This is the absolute pressure threshold; This represents the rate of change of the cavitation threshold with respect to temperature.

10. A system for determining vibration-induced cavitation in micro-gap insulating oil, using the method for determining vibration-induced cavitation in micro-gap insulating oil as described in any one of claims 1-9, characterized in that, include: The micro-gap fluid pressure analysis module under vibration includes a wall vibration velocity solution submodule and a fluid pressure calculation submodule based on multi-field coupling; The wall vibration velocity solution submodule is dynamically coupled, corrects the calculation speed in real time, and adaptively adjusts the parameters. The coupling coefficient is updated once every set fixed time interval, and the vibration velocity is output. The fluid pressure calculation submodule based on multi-field coupling calculates the fluid pressure in the micro-gap based on the vibration velocity and the micro-gap structural characteristics. The bubble nucleus cavitation pressure threshold analysis module includes a gas-liquid balance submodule, a surface tension correction submodule, and a cavitation threshold synthesis submodule. The gas-liquid balance submodule calculates the critical radius of the bubble nucleus through Henry's constant temperature correction. The surface tension correction submodule calculates the surface tension under the combined influence of temperature and humidity. The critical radius of the bubble nucleus and the surface tension are integrated to calculate the final cavitation pressure threshold. The insulating oil dynamic cavitation determination and critical state early warning module includes a dynamic pressure difference normalization submodule, a cavitation risk factor synthesis submodule, and a critical state early warning submodule. The dynamic pressure difference normalization submodule calculates the normalized pressure difference and introduces an exponential decay term to suppress transient fluctuations. The cavitation risk factor is calculated using the Sigmoid function and a temperature correction factor. The critical state early warning submodule determines whether the system is in a critical cavitation state based on multiple criteria.

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