110V transformer winding insulation resistance absorption ratio detection method

Abstract

The invention provides a 110V transformer winding insulation resistance absorption ratio detection method, which belongs to the technical field of transformer windings, and is characterized in that transformer operation state parameters and environmental influence factors are acquired through a multi-channel synchronous acquisition system, and thermodynamic and electrical models are established. The research adopts methods of principal component analysis, numerical integration and the like, an insulation resistance change rule is analyzed under a standard test voltage, a weight coefficient matrix is constructed in combination with an operation state and an environmental factor, a measured value is corrected through multiple linear regression and a correction coefficient method, and finally, the insulation resistance is obtained through statistical average and standard deviation analysis. The accurate evaluation of the insulation resistance absorption ratio of the transformer winding is realized; according to the method, the influence of the complex working environment and the operation state of the transformer on the insulation performance is fully considered, and the problem that various complex factors in the operation process of the transformer cannot be comprehensively considered and compensated in the prior art is solved by adopting the means of mathematical modeling, data correction, statistical analysis and the like; therefore, the technical problem of large deviation of the measurement result is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of transformer windings, and in particular relates to a method for detecting the insulation resistance absorption ratio of a 110V transformer winding. Background Art

[0002] Transformer is one of the most critical equipment in the power system, and it undertakes the important function of grid voltage level conversion. As the core component in the distribution network, the operating status of 110V transformer is directly related to the safety and reliability of the entire power grid. However, the degradation of transformer insulation system is one of the main hidden dangers that cause accidents. Insulation resistance absorption ratio is an important indicator for judging the insulation status of transformer. By monitoring this parameter, insulation degradation problems can be discovered in time, providing a basis for maintaining the safe operation of the power grid. The existing transformer insulation resistance absorption ratio detection method has the following main problems: First, it is impossible to fully consider the coupling effect of various complex factors such as temperature, humidity, and load on the insulation characteristics during the operation of the transformer; second, it is impossible to compensate for the changes in environmental factors such as ambient temperature, humidity, and pressure in real time during the detection process, resulting in large deviations in the measurement results; third, there is a lack of effective statistical analysis and reliability evaluation of the measurement data, and it is impossible to judge the accuracy and stability of the measurement results. These problems limit the accuracy and credibility of transformer insulation status diagnosis, and bring hidden dangers to the safety of power grid operation. In other words, the existing technology cannot fully consider and compensate for various complex factors in the operation of the transformer, resulting in technical problems with large deviations in the measurement results.

[0003] Therefore, there is an urgent need for a new transformer insulation resistance absorption ratio detection method that can comprehensively consider the impact of the transformer operating environment and working conditions on the insulation characteristics, use data correction and statistical analysis methods to improve the reliability of the measurement results, and provide an important basis for accurately evaluating the insulation status of the transformer. Summary of the invention

[0004] In view of this, the present invention provides a 110V transformer winding insulation resistance absorption ratio detection method, which can solve the technical problem that the prior art cannot fully consider and compensate for various complex factors in the transformer operation process, resulting in large deviations in the measurement results.

[0005] The present invention is achieved in that:

[0006] The present invention provides a method for detecting the insulation resistance absorption ratio of a 110V transformer winding, comprising the following steps:

[0007] S10, collecting the 110V transformer winding operation load data, winding temperature data, oil level data, vibration data, and partial discharge data to form an operation state parameter set, wherein the operation state parameters are acquired using a multi-channel synchronous acquisition system, and a temperature change equation group of the 110V transformer winding insulation is established according to the laws of thermodynamics to describe the winding temperature rise process, and the linear correlation coefficient between the parameters is determined by the least squares fitting method, and the main influencing components of the parameters are extracted by the principal component analysis method;

[0008] S20, connecting the insulation resistance tester to both ends of the 110V transformer winding, collecting the ambient temperature data, humidity data, and atmospheric pressure data of the 110V transformer winding to establish an environmental impact factor data set, wherein the environmental impact factor data set is calculated by using a numerical solution method to calculate the comprehensive impact coefficient of environmental factors on insulation resistance by establishing a simultaneous equation group of a basic heat conduction equation, a humidity diffusion equation, and an air pressure distribution equation in the 110V transformer;

[0009] S30, applying a standard test voltage to the 110V transformer winding when the 110V transformer winding is in a power-off state, recording the starting time point of applying the standard test voltage, establishing a winding insulation model based on a parallel RC equivalent circuit, considering the time-varying resistance characteristics caused by the dielectric polarization effect, and using a first-order differential equation to describe the variation of the insulation resistance over time;

[0010] S40, collecting the first insulation resistance measurement value of the 110V transformer winding at the 15th second under the continuous action of the standard test voltage, and recording the leakage current data at the first insulation resistance measurement time, establishing a current continuity equation according to Kirchhoff's law, calculating the effective value of the leakage current by a numerical integration method, and using a moving average filter to eliminate measurement noise;

[0011] S50, collecting the second insulation resistance measurement value of the 110V transformer winding at the 60th second under the continuous action of the standard test voltage, and recording the leakage current data at the second insulation resistance measurement time, using an exponential decay model to describe the variation characteristics of the leakage current over time, and determining the attenuation coefficient by a linear regression method;

[0012] S60, establishing an influence weight coefficient matrix of the operating state parameter set and the environmental influencing factor data set, calculating the contribution of each parameter to the insulation resistance measurement value based on a multivariate linear regression model, and standardizing the weight coefficient using a correction coefficient method;

[0013] S70, performing data correction on the first insulation resistance measurement value and the second insulation resistance measurement value according to the influence weight coefficient matrix, establishing a linear correction model based on the temperature coefficient and the humidity coefficient, optimizing the correction coefficient through iterative calculation, and realizing linear correction of the measurement value;

[0014] S80. Calculate the corrected insulation resistance absorption ratio of the 110V transformer winding using the corrected first insulation resistance measurement value and the corrected second insulation resistance measurement value, process multiple measurement data using statistical averaging method, evaluate the reliability of the measurement results through standard deviation analysis, and output the corrected insulation resistance absorption ratio numerical result.

[0015] The parallel RC equivalent circuit is a universal parallel RC equivalent circuit.

[0016] On the basis of the above technical solution, a 110V transformer winding insulation resistance absorption ratio detection method of the present invention can also be improved as follows:

[0017] Wherein, the temperature change equation group includes a heat balance equation, a heat transfer equation and a temperature rise equation.

[0018] Furthermore, the thermal balance equation is used to describe the balance between the heat generated internally and the heat dissipated externally during operation of the transformer winding. The input includes the current in the winding, the resistance value of the winding, the temperature of the surrounding cooling medium, the surface heat dissipation area of ​​the winding, and the heat dissipation coefficient. The output is the winding temperature during steady-state operation.

[0019] Furthermore, the heat transfer equation is used to describe the dynamic process of heat transfer between the transformer winding and the surrounding cooling medium. The input includes the thermal capacity of the winding, the operating time, the internal heating power and the external heat dissipation power. The output is the rate of change of the winding temperature over time.

[0020] Furthermore, the temperature rise equation is used to describe the change law of the whole process of the transformer winding rising from the initial temperature to the final stable temperature. The input includes the initial temperature of the winding, the final stable temperature, the time constant of the temperature change and the actual operating time, and the output is the actual temperature of the winding at any time.

[0021] Furthermore, the basic heat conduction equation is used to describe the law of the heat conduction process between various parts inside the transformer. The input includes the thermal conductivity of the material, the temperature difference between various points and the density of the heat flow, and the output is the temperature distribution of various points inside the transformer.

[0022] Furthermore, the humidity diffusion equation is used to describe the migration and diffusion process of water in the transformer insulation medium. The input includes the humidity diffusion coefficient of the material, the humidity concentration difference at various locations and the diffusion time. The output is the humidity distribution state of each point in the insulation medium.

[0023] Furthermore, the gas pressure distribution equation is used to describe the gas pressure distribution law at different height positions inside the transformer. The input includes the density of oil and gas, gravity acceleration and relative height difference, and the output is the pressure distribution at various height positions inside the transformer.

[0024] Furthermore, in the step of determining the linear correlation coefficient between the parameters by least squares fitting, each parameter is each parameter in the operating state parameter set.

[0025] Furthermore, the correlation coefficient threshold of the least squares method is set to 0.8.

[0026] The relevant calculation steps are described in detail as follows:

[0027] 1. Temperature change equations:

[0028] The temperature change equation group is specifically expressed as follows:

[0029] Heat balance equation:

[0030]

[0031] Where, T is the winding temperature (K); T0 is the initial temperature (K); T a is the ambient temperature (K); c p is the specific heat capacity of the winding (J / (kg·K)); ρ is the density of the winding material (kg / m 3 ); V is the winding volume (m 3 ); I is the load current (A); R is the winding resistance at 20°C (Ω); α is the resistance temperature coefficient (1 / K); h is the convection heat transfer coefficient (W / (m 2 ·K)); A is the heat dissipation area (m 2 ), β1 is the oil level influence coefficient, ΔH is the relative oil level deviation, σ is the Stefan-Boltzmann constant, ε is the radiation coefficient, β2 is the wind speed influence coefficient, v w is the ambient wind speed (m / s); Q oil is the oil circulation cooling power (W).

[0032] Heat transfer equation:

[0033]

[0034] Where λ is thermal conductivity (W / (m·K)); q v is the heat generation rate per unit volume (W / m 3 );Q i is the heat of the ith heat source (W); f i (t, T) is the influence function of temperature and time, and the expression is:

[0035]

[0036] Among them, a i ,b i ,k i is the fitting coefficient.

[0037] Temperature rise equation:

[0038] T(t)=T a +(T f -T a )(1-e -t / τ )+ΔT1sin(ωt)+ΔT2e -γt sin(ωt+φ)+ε T ;

[0039] Where, T f is the final stable temperature (K); τ is the main time constant (s); ΔT1 is the periodic temperature fluctuation amplitude (K); ω is the temperature fluctuation angular frequency (rad / s); ΔT2 is the transient temperature fluctuation amplitude (K); γ is the attenuation coefficient (1 / s); φ is the phase angle (rad); ε T is the temperature measurement error (K).

[0040] Parameter acquisition method:

[0041] 1. Thermocouple array temperature measurement system obtains temperature distribution data: 16 temperature measurement points are arranged on the winding surface; sampling frequency is 1Hz; data collection time is ≥24h.

[0042] 2. Load current measurement: Use 0.2-level current transformer; 500ms sampling interval; synchronously collect three-phase current.

[0043] 3. Heat dissipation coefficient calibration experiment:

[0044] Step 1: Constant temperature heating test results:

[0045]

[0046] Where, P in is the input power (W); T s is the surface temperature (K).

[0047] Step 2: Natural cooling test results:

[0048]

[0049] 2. Simultaneous equations: The simultaneous equations are specifically expressed as follows:

[0050] The basic equation of heat conduction is:

[0051]

[0052] Where λ is the thermal conductivity tensor matrix:

[0053]

[0054] q v is the volume heat source term (W / m 3 ); μ i is the anisotropy coefficient in the i-th direction; k i is the correction coefficient in the i-th direction; ε T is the heat conduction error term.

[0055] Humidity diffusion equation:

[0056]

[0057] Where C is the humidity concentration (kg / m 3 );D is the diffusion coefficient tensor:

[0058]

[0059] S c is the humidity source term; α T is the temperature coupling coefficient; β p is the pressure coupling coefficient; γ j is the second-order correction coefficient in the jth direction; ε C is the humidity diffusion error term.

[0060] Air pressure distribution equation:

[0061]

[0062] Where p is pressure (Pa); is the velocity vector (m / s); K is the permeability tensor:

[0063]

[0064] Q p is the pressure source term; η T is the temperature-pressure coupling coefficient; ξ C is the humidity-pressure coupling coefficient; ε p is the pressure distribution error term.

[0065] 3. Winding insulation model based on parallel RC equivalent circuit:

[0066]

[0067] Where V cis the capacitor voltage (V); R(t) is the time-varying insulation resistance (Ω):

[0068]

[0069] C is the equivalent capacitance (F); U0 is the applied voltage (V); R k (t) is the time-varying resistance of the kth polarization component (Ω); C k is the capacitance of the kth polarization component (F); V ck is the capacitor voltage of the kth polarization component (V); τ k is the time constant (s); ε v is the voltage measurement error (V); R0 is the insulation resistance under standard conditions (Ω); α R is the temperature influence coefficient (1 / K); β R is the humidity influence coefficient; γ R is the aging attenuation coefficient (1 / s).

[0070] 4. The first-order differential equation describes the change of insulation resistance over time:

[0071]

[0072] Where l represents the spatial dimension, and the default value is 3; the expression of the time-varying attenuation coefficient α(t) is:

[0073]

[0074] The expression of time-varying steady-state coefficient β(t) is:

[0075]

[0076] 5. Current continuity equation:

[0077]

[0078] In the formula, i total (t) is the total current (A); is the current density vector (A / m 2 ):

[0079]

[0080] σ k is the conductivity of the kth medium (S / m); V k is the voltage distribution of the kth medium (V); ρ v is the volume charge density (C / m 3 ); i is the current measurement error (A); E x ,E y ,Ez is the electric field component in each direction (V / m).

[0081] 6. Moving average filtering algorithm:

[0082]

[0083] In the formula, i filtered (t) is the current value after filtering (A); N is the sliding window length; Δt is the sampling interval (s); w(j) is the weighting function:

[0084]

[0085] α k is the k-order derivative correction coefficient; p is the highest derivative order; ε f is the filtering error (A); σ is the shape parameter of the weighting function.

[0086] 7. Leakage current exponential decay model:

[0087]

[0088] In the formula, i leak (t) is the leakage current (A); i0 is the initial leakage current (A); λ is the main attenuation coefficient (1 / s); i ∞ is the steady-state leakage current (A); A n is the amplitude of the nth harmonic component (A); τ n is the time constant of the nth harmonic component (s); ω n is the nth harmonic angular frequency (rad / s); φ n is the nth harmonic phase angle (rad); ε l is the leakage current measurement error (A), q is the number of levels, the default value is 8.

[0089] 8. The contribution calculation model based on multiple linear regression is expressed as:

[0090] R measured =Xβ+ε;

[0091] In the formula, R measured is the insulation resistance measurement value vector:

[0092]

[0093] X is the parameter matrix:

[0094]

[0095] β is the regression coefficient vector:

[0096]

[0097] ε is the error vector:

[0098]

[0099] 9. Weight coefficient standardization processing model:

[0100]

[0101] In the formula, is the weight of the jth parameter of the i-th sample after standardization; w ij is the original weight; σ j is the standard deviation of the jth parameter; γ j is the importance adjustment coefficient; δ ij For correction items.

[0102] The weight matrix W is expressed as:

[0103]

[0104] 10. Insulation resistance measurement value correction model:

[0105]

[0106] Where P corrected is the corrected insulation resistance value (Ω); R measured is the measured value (Ω); f T (T) is the temperature correction function:

[0107]

[0108] f H (H) is the humidity correction function:

[0109]

[0110] η i (x i ) is the correction coefficient function of the i-th influencing factor:

[0111]

[0112] α j is the correction coefficient of the jth error source; ΔR j is the correction value of the jth error; ε R is the residual error.

[0113] 11. Linear correction model of temperature coefficient and humidity coefficient:

[0114]

[0115] In the formula, the correction coefficient matrices A, B, and C are respectively:

[0116]

[0117] ε is the error vector:

[0118] Compared with the prior art, the beneficial effects of the 110V transformer winding insulation resistance absorption ratio detection method provided by the present invention are:

[0119] First, the present invention adopts a multi-channel synchronous acquisition system to comprehensively obtain the transformer operating status parameters, including winding temperature, load current, oil level, vibration, partial discharge, etc., and establishes a mathematical model based on thermodynamics and electromagnetic theory to accurately describe the winding temperature rise process, material property changes, electrical parameter dynamic characteristics, etc., providing the necessary theoretical basis for subsequent measurement corrections.

[0120] Secondly, before connecting the insulation resistance tester, the present invention first collects real-time data of the transformer's environment through sensors such as temperature, humidity, and air pressure, and establishes a set of simultaneous equations covering processes such as heat conduction, humidity diffusion, and pressure distribution, which can quantitatively calculate the comprehensive impact of environmental factors on insulation resistance. This environmental parameter correction method based on a physical model greatly improves the accuracy and reliability of the measurement results.

[0121] Thirdly, the present invention establishes an insulation model based on a parallel RC equivalent circuit for the time-varying characteristics of insulation resistance, uses a first-order differential equation to describe the variation of winding insulation resistance over time, and considers the coupling effects of temperature, humidity, and aging factors. At the same time, numerical integration and moving average filtering algorithms are used to effectively extract leakage current characteristic parameters. These modeling and signal processing methods ensure the accuracy and stability of the measurement data.

[0122] Finally, the present invention establishes a multivariate linear regression model of operating state parameters and environmental influencing factors, and realizes a comprehensive correction of the insulation resistance measurement value by calculating the weight coefficient of each parameter. The linear correction function of the temperature coefficient and the humidity coefficient is adopted, and combined with the correction of other factors such as aging, the insulation resistance absorption ratio measurement result compensated by environmental factors is finally obtained. At the same time, the present invention also adopts statistical analysis means to evaluate the reliability and stability of the measurement results, providing a reliable basis for the diagnosis of transformer insulation status.

[0123] In summary, the 110V transformer winding insulation resistance absorption ratio detection method proposed in the present invention fully considers the influence of the complex working environment and operating status of the transformer on the insulation performance, and adopts mathematical modeling, data correction and statistical analysis to greatly improve the accuracy and reliability of the measurement results, and solves the technical problem that the existing technology cannot fully consider and compensate for various complex factors in the operation process of the transformer, resulting in large deviations in the measurement results. BRIEF DESCRIPTION OF THE DRAWINGS

[0124] Figure 1 A flow chart of the method provided by the present invention. DETAILED DESCRIPTION

[0125] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0126] like Figure 1 As shown, it is a flow chart of a 110V transformer winding insulation resistance absorption ratio detection method provided by the present invention. The specific implementation method of the steps of the method is described in detail below:

[0127] The specific implementation method of step S10 is to use a multi-channel synchronous acquisition system to collect the operating state parameters of the 110V transformer winding. The acquisition system uses 16 high-precision data acquisition channels, the sampling frequency is 1024 Hz, and the sampling accuracy is 16 bits. The collected operating parameters include the load current of the three-phase windings A, B, and C, which are collected using a 0.2-level current transformer with a current sampling interval of 500 milliseconds; the winding surface temperature is collected using a 16-point thermocouple array temperature measurement system with a temperature sampling interval of 1 second; the oil level data is collected using a magnetic flap level gauge with a measurement accuracy of ±1 mm; the vibration data is collected using a piezoelectric acceleration sensor with a sampling frequency of 2048 Hz; the partial discharge data is collected using an ultra-high frequency partial discharge detector with a frequency range of 300 MHz to 3 GHz. A temperature change equation group is established based on the laws of thermodynamics, which includes a thermal balance equation, a heat transfer equation, and a temperature rise equation to describe the winding temperature rise process. The least squares method is used to calculate the linear correlation coefficient between the parameters. The threshold of the correlation coefficient is set to 0.8. The correlation degree of parameters below this threshold is weak. The principal component analysis method is used to extract the main influencing components of each parameter. The cumulative contribution rate is set to 85%. The number of principal components required to meet this requirement is usually 3 to 4. The main purpose of this step is to obtain the key parameter data of the transformer operating status, establish the correlation between the parameters, and provide a data basis for the subsequent insulation resistance measurement correction.

[0128] The specific implementation method of step S20 is that before connecting the insulation resistance tester, the temperature and humidity sensor is first used to collect environmental temperature data, the temperature measurement range is minus 40 degrees Celsius to 85 degrees Celsius, and the measurement accuracy is ±0.5 degrees Celsius; the capacitive humidity sensor is used to collect relative humidity data, the humidity measurement range is 0 to 100%, and the measurement accuracy is ±3%; the digital barometer is used to collect atmospheric pressure data, the pressure measurement range is 800 to 1100 hPa, and the measurement accuracy is ±0.3 hPa. Based on the acquired environmental data, a set of simultaneous equations of the basic heat conduction equation, the humidity diffusion equation, and the air pressure distribution equation is established, which describes the heat conduction, moisture diffusion, and air pressure distribution laws inside the transformer. The comprehensive influence coefficient of environmental factors is calculated by a numerical solution method. During the calculation process, the Runge-Kutta method is used to numerically solve the equation group, the time step is set to 0.1 seconds, and the iterative convergence accuracy is set to 0.001. The degree of influence of environmental factors on insulation resistance is characterized by the comprehensive coefficient after dimensionless processing, and the value range of the coefficient is usually between 0.8 and 1.2. The main purpose of this step is to establish a quantitative relationship between environmental factors and insulation characteristics, providing a basis for subsequent measurement value correction.

[0129] The specific implementation method of step S30 is to use an insulation resistance tester to apply a standard test voltage to the winding after the transformer winding is completely powered off and the discharge is completed. The test voltage is set to a DC voltage of 1000 volts, and the ripple factor of the tester output voltage is less than 1%. Record the starting time of the test voltage application, and the time recording accuracy is 0.1 seconds. A winding insulation model is established based on a parallel RC equivalent circuit, which takes into account the time-varying resistance characteristics caused by the dielectric polarization effect. A first-order differential equation is used to describe the change of insulation resistance over time. The equation contains three key parameters: temperature coefficient, humidity coefficient and aging coefficient. The typical value of the temperature coefficient is that the resistance decreases by 50% for every 10 degrees Celsius increase, the typical value of the humidity coefficient is that the resistance decreases by 20% for every 10% increase in relative humidity, and the typical value of the aging coefficient is that the resistance decreases by 5% for every 1 year of operation. The main purpose of this step is to establish a mathematical model of insulation resistance to provide a theoretical basis for the subsequent measurement process.

[0130] The specific implementation method of step S40 is to use a high-precision digital insulation resistance tester to measure the first insulation resistance value at the 15th second under the condition of continuous action of the standard test voltage, with a measurement range of 100 kilo-ohms to 1 tera-ohms, and a measurement accuracy of ±5% of the reading. At the same time, a digital micro-ammeter is used to record the leakage current data at this moment, with a current measurement range of 1 nanoampere to 100 microamperes, and a measurement accuracy of ±2% of the reading. Based on Kirchhoff's law, a current continuity equation is established, which describes the three components of conduction current, displacement current and absorption current in the insulating medium. The effective value of the leakage current is calculated by a numerical integration method, the integral adopts the trapezoidal rule, and the integration time step is set to 0.1 seconds. The moving average filtering algorithm is used to eliminate measurement noise, the filter window length is set to 16 points, and the weighting coefficient adopts a Gaussian distribution. The main purpose of this step is to obtain the first insulation resistance measurement value and the corresponding leakage current data.

[0131] The specific implementation of step S50 is to use the same test instrument to measure the second insulation resistance value at the 60th second moment under the condition of continuous action of the standard test voltage. At the same time, the leakage current data at this moment is recorded, and the exponential decay model is used to describe the change characteristics of the leakage current over time. The model contains two components: steady-state leakage current and transient leakage current. The decay time constant of the transient component is usually between 30 and 60 seconds. The attenuation coefficient is determined by linear regression method, and the regression calculation adopts the least squares method. The goodness of fit R square value is required to be greater than 0.95. The typical value range of the attenuation coefficient is 0.02 to 0.05 per second. The main purpose of this step is to obtain the second insulation resistance measurement value and the leakage current decay characteristics.

[0132] The specific implementation method of step S60 is to establish an influence weight coefficient matrix of the operating state parameter set and the environmental influencing factor data set based on the data obtained in the previous steps. The dimension of the matrix is ​​determined by the number of parameters, usually a square matrix of 16 by 16. A multivariate linear regression model is used to calculate the contribution of each parameter to the insulation resistance measurement value. The independent variables of the regression model include parameters such as temperature, humidity, pressure, and load rate, and the dependent variable is the insulation resistance measurement value. The weight coefficient is standardized using the correction coefficient method, and the sum of the standardized weight coefficients is 1. The weight coefficients of each parameter are usually distributed between 0.05 and 0.3, among which the weight coefficients of temperature and humidity are relatively large, usually greater than 0.2. The main purpose of this step is to determine the weight coefficients of each influencing factor.

[0133] The specific implementation method of step S70 is to correct the data of the two insulation resistance measurement values ​​according to the influence weight coefficient matrix. A linear correction model based on the temperature coefficient and the humidity coefficient is established. The temperature correction coefficient adopts an exponential function form, and the reference temperature is set to 20 degrees Celsius; the humidity correction coefficient also adopts an exponential function form, and the reference humidity is set to 50%. The correction coefficient is optimized by iterative calculation. The iterative process adopts the Newton-Raphson method. The iterative termination condition is that the relative error of two adjacent calculation results is less than 0.1% or the number of iterations reaches 50 times. The optimization goal of the correction coefficient is to minimize the deviation between the corrected measurement value and the theoretical calculation value. The main purpose of this step is to correct the measurement value for environmental factors.

[0134] The specific implementation of step S80 is to calculate the insulation resistance absorption ratio of the 110V transformer winding using the two revised insulation resistance measurement values. The statistical averaging method is used to process multiple measurement data, and the number of measurements is not less than 3 times, and the arithmetic mean and standard deviation are calculated. The reliability of the measurement results is evaluated by standard deviation analysis, and the ratio of the standard deviation to the mean value, that is, the coefficient of variation, is required to be less than 5%. For normal insulation status, the ratio of the insulation resistance values ​​of 60 seconds and 15 seconds, that is, the absorption ratio, should be greater than 1.3. If it is less than this value, it indicates that there may be problems with the insulation status. Finally, the numerical result of the insulation resistance absorption ratio after correction is output, and the result retains 3 significant figures. The main purpose of this step is to obtain the final measurement result and evaluate its reliability.

[0135] A specific embodiment 1 of the present invention is provided below. The specific implementation of each step in this embodiment 1 is described in detail as follows:

[0136] The step S10 specifically includes:

[0137] Step 101, use a multi-channel synchronous acquisition system to collect the operating state parameters of the 110V transformer winding. The acquisition system uses 16 high-precision data acquisition channels, the sampling frequency is 1024 Hz, and the sampling accuracy is 16 bits. The collected operating parameters include the load current I of the three-phase windings A, B, and C, which is collected by a 0.2-level current transformer with a current sampling interval of 500 milliseconds; the winding surface temperature T is collected by a 16-point thermocouple array temperature measurement system with a temperature sampling interval of 1 second; the oil level data ΔH is collected by a magnetic flap level gauge with a measurement accuracy of ±1 mm; the vibration data is collected by a piezoelectric acceleration sensor with a sampling frequency of 2048 Hz; the partial discharge data is collected by an ultra-high frequency partial discharge detector with a frequency range of 300 MHz to 3 GHz.

[0138] Step 102: Establish a temperature change equation group based on the laws of thermodynamics. The equation group includes a heat balance equation, a heat transfer equation, and a temperature rise equation to describe the temperature rise process of the winding. The heat balance equation describes the heat generated inside the transformer winding during operation. 2 R[1+α(T-T0)] and heat dissipation The balance relationship between them is: α is the resistance temperature coefficient, β1 and β2 are the influence coefficients of oil level and wind speed, σ is the Stefan-Boltzmann constant, ε is the radiation coefficient, and v w is the ambient wind speed, Q oil is the oil circulation cooling power. The heat transfer equation describes the transient heat conduction process between points inside the winding. The right side of the equation contains terms such as heat conduction, volume heat source and polarization component, where λ is the thermal conductivity, q v is the heat generation rate per unit volume, Q i is the heat of the ith heat source, f i (t,T) is the influence function of temperature and time. The temperature rise equation describes the winding temperature from the initial temperature T a Rising to the final stable temperature T f The right side of the equation includes the first-order exponential term, the periodic fluctuation term and the transient fluctuation term.

[0139] Step 103: Calculate the linear correlation coefficient R between the parameters using the least squares method 2 , the correlation coefficient threshold is set to 0.8, and parameters below this threshold are weakly correlated.

[0140] Step 104: extract the main influencing components of each parameter using principal component analysis, and set the cumulative contribution rate to 85%. The number of principal components required to meet this requirement is usually 3 to 4. Principal component analysis transforms the original parameter vector X = [x1 x2 ... x n ] T Mapped to the principal component vector Y = [y1 y2…y m ] T On, where m≤n and y i orthogonal between them, the principal component y i The variance λ i The proportion of the total variance is called the contribution rate. The number of principal components m is determined by setting a cumulative contribution rate threshold of 85%.

[0141] Step 105: The main purpose of this step is to obtain key parameter data of the transformer operating status, establish a correlation relationship between parameters, and provide a data basis for subsequent insulation resistance measurement correction.

[0142] The specific steps of step S20 include:

[0143] Step 201: Before connecting the insulation resistance tester, first use a temperature and humidity sensor to collect the ambient temperature T a The temperature measurement range is -40 degrees Celsius to 85 degrees Celsius, and the measurement accuracy is ±0.5 degrees Celsius. A capacitive humidity sensor is used to collect relative humidity H data. The humidity measurement range is 0 to 100%, and the measurement accuracy is ±3%. A digital barometer is used to collect atmospheric pressure p data. The pressure measurement range is 800 to 1100 hPa, and the measurement accuracy is ±0.3 hPa.

[0144] Step 202: Based on the acquired environmental data, a system of simultaneous equations of the basic heat conduction equation, the humidity diffusion equation, and the air pressure distribution equation is established. The system of equations describes the heat conduction, moisture diffusion, and air pressure distribution laws inside the transformer. Basic heat conduction equation It describes the transient heat conduction process between the internal parts of the transformer, where λ is the anisotropic thermal conductivity tensor, μ i and k i is the correction factor. Humidity diffusion equation Describes the diffusion process of water in the insulating medium, where D is the anisotropic diffusion coefficient tensor, S c is the humidity source term, α T and β p is the coupling coefficient of temperature and pressure. Air pressure distribution equation Describes the gas pressure distribution at different heights inside the transformer, where K is the permeability tensor, is the velocity vector, η T and C is the coupling coefficient of temperature and humidity.

[0145] Step 203, using a numerical solution method to calculate the comprehensive influence coefficient ζ of environmental factors, the Runge-Kutta method is used to numerically solve the equation group during the calculation process, the time step is set to 0.1 seconds, and the iteration convergence accuracy is set to 0.001. The influence of environmental factors on insulation resistance is characterized by the comprehensive coefficient ζ after dimensionless processing, and the value range of the coefficient is usually between 0.8 and 1.2.

[0146] Step 204: The main purpose of this step is to establish a quantitative relationship between environmental factors and insulation characteristics, so as to provide a basis for subsequent measurement value correction.

[0147] The specific steps of step S30 include:

[0148] Step 301: After the transformer winding is completely powered off and discharged, a standard test voltage U0 is applied to the winding using an insulation resistance tester, the test voltage is set to 1000 volts DC, and the ripple factor of the tester output voltage is less than 1%. The start time t0 of the test voltage application is recorded, and the time recording accuracy is 0.1 second.

[0149] Step 302: Establish a winding insulation model based on a parallel RC equivalent circuit. The model takes into account the time-varying resistance characteristics caused by the dielectric polarization effect. The variation law of the winding insulation resistance R(t) over time can be expressed by the first-order differential equation: Description, where α(t) is the time-varying attenuation coefficient, β(t) is the time-varying steady-state coefficient, and δ i is the correction coefficient of the ith environmental parameter. The typical value of the temperature coefficient is that the resistance decreases by 50% for every 10 degrees Celsius increase, the typical value of the humidity coefficient is that the resistance decreases by 20% for every 10% increase in relative humidity, and the typical value of the aging coefficient is that the resistance decreases by 5% for every 1 year of operation.

[0150] Step 303: The main purpose of this step is to establish a mathematical model of insulation resistance to provide a theoretical basis for subsequent measurement processes.

[0151] The specific steps of step S40 include:

[0152] Step 401: Under the condition that the standard test voltage U0 is continuously applied, a high-precision digital insulation resistance tester is used to measure the first insulation resistance value R1 at the 15th second, with a measurement range of 100 kilo-ohms to 1 tera-ohm and a measurement accuracy of ±5% of the reading. At the same time, a digital micro-ammeter is used to record the leakage current i at that moment. leak1 The current measurement range is 1 nanoampere to 100 microamperes, and the measurement accuracy is ±2% of the reading.

[0153] Step 402: Establish a current continuity equation based on Kirchhoff's law This equation describes the three components of conduction current, displacement current and absorption current in the insulating medium. The leakage current i is calculated by numerical integration method. leak1 The effective value of is used, the integral adopts the trapezoidal rule, and the integral time step is set to 0.1 second. The moving average filtering algorithm is used To eliminate measurement noise, the filter window length is set to 16 points, and the weighting function w(j) adopts Gaussian distribution.

[0154] Step 403: The main purpose of this step is to obtain the first insulation resistance measurement value R1 and the corresponding leakage current i leak1 data.

[0155] The specific steps of step S50 include:

[0156] Step 501: Under the condition that the standard test voltage U0 is continuously applied, the insulation resistance value R2 is measured for the second time at the 60th second using the same test instrument. At the same time, the leakage current i at this moment is recorded. leak2 Data, using exponential decay model Describes the time-varying characteristics of the leakage current, including the steady-state component i ∞ and transient component The attenuation coefficient λ was determined by linear regression method, and the regression calculation was performed by the least square method. The goodness of fit R 2 The value should be greater than 0.95. Typical values ​​for the decay coefficient range from 0.02 to 0.05 per second.

[0157] Step 502: The main purpose of this step is to obtain the second insulation resistance measurement value R2 and the leakage current attenuation characteristic parameter.

[0158] The specific steps of step S60 include:

[0159] Step 601: Based on the data obtained in the previous steps, establish an operating status parameter set Environmental impact factor dataset The influence weight coefficient matrix

[0160] Step 602: Use the multiple linear regression model R measured =Xβ+εCalculate the contribution of each parameter to the insulation resistance measurement value The independent variables of the regression model include temperature T, humidity H, pressure p, load rate, etc.

[0161] Step 603: Use the correction coefficient method to adjust the weight coefficient w ij Standardization Ensure that the sum of all elements in the matrix W is 1. The weight coefficients of each parameter are usually distributed between 0.05 and 0.3, among which the weight coefficients of temperature and humidity are relatively large, usually greater than 0.2.

[0162] Step 604: The main purpose of this step is to determine the weight coefficient of each influencing factor.

[0163] The specific steps of step S70 include:

[0164] Step 701: Perform data correction on the two insulation resistance measurement values ​​R1 and R2 according to the influence weight coefficient matrix W established in step 601. Establish a temperature coefficient K based on the influence weight coefficient matrix W. T and humidity coefficient K H The linear correction model The correction coefficient matrices A, B and C are determined by multivariate linear regression. Temperature correction function Humidity correction function

[0165] Step 702, optimize the correction coefficient by iterative calculation, the iteration process adopts the Newton-Raphson method, and the iteration termination condition is that the relative error of two consecutive calculation results is less than 0.1% or the number of iterations reaches 50. The optimization goal of the correction coefficient is to make the corrected measurement value The deviation from the theoretical calculated value is minimal.

[0166] Step 703: The main purpose of this step is to correct the measured value for environmental factors.

[0167] 9. The method according to claim 1, characterized in that the specific steps of step S80 include:

[0168] Step 801: Calculate the insulation resistance absorption ratio of the 110V transformer winding using the two insulation resistance measurement values ​​R1 and R2 corrected in step 702.

[0169] Step 802: Use statistical averaging method to process multiple measurement data, the number of measurements is not less than 3 times, and calculate the arithmetic mean. The reliability of the measurement results is evaluated by standard deviation analysis, and the coefficient of variation The requirement is less than 5%. For normal insulation status, the ratio of the insulation resistance value of 60 seconds to that of 15 seconds, i.e. the absorption ratio ξ, should be greater than 1.3. A value less than this indicates that there may be problems with the insulation status.

[0170] Step 803: Finally output the corrected insulation resistance absorption ratio numerical result The result is retained to 3 significant figures. The main purpose of this step is to obtain the final measurement result and evaluate its reliability.

[0171] Specifically, the principle of the present invention is to establish a quantitative relationship model between transformer operating state parameters, environmental factors and insulation resistance, and use the model to perform comprehensive data correction and statistical analysis on the measurement results, so as to obtain a reliable insulation resistance absorption ratio compensated by environmental factors. The specific principle is as follows:

[0172] First, a multi-channel synchronous acquisition system is used to obtain key parameter data of the transformer's operating status, including winding temperature, load current, oil level, vibration, partial discharge, etc. These parameters reflect the heat balance, electromechanical characteristics and local defects inside the transformer, and provide necessary input for subsequent insulation characteristics analysis. The present invention describes the dynamics of the entire process from the initial temperature rise to the final stable temperature of the winding by establishing a set of temperature change equations, including the heat balance equation, heat transfer equation and temperature rise equation. These equations comprehensively consider the coupling effects of multiple factors such as internal heating, convection heat dissipation, and radiation heat dissipation, laying the foundation for accurately describing the temperature distribution of the winding.

[0173] Secondly, before measuring the insulation resistance, the present invention first collects parameter data such as ambient temperature, humidity and pressure, and establishes a set of simultaneous equations covering heat conduction, humidity diffusion and pressure distribution. These equations quantitatively describe the heat transfer process between various parts inside the transformer, the law of moisture migration and the gas pressure distribution characteristics. By numerically solving these equations, the comprehensive influence coefficient of environmental factors on the insulation resistance can be calculated, providing a basis for the subsequent correction of the measured value.

[0174] Thirdly, the present invention establishes a mathematical model of winding insulation based on a parallel RC equivalent circuit, uses a first-order differential equation to describe the time-varying characteristics of insulation resistance, and considers the coupling effects of temperature, humidity, and aging factors. This modeling method can accurately reflect the time-varying characteristics of resistance caused by the polarization effect in the insulating medium. At the same time, by analyzing the continuity equation and exponential decay model of the leakage current, dynamic parameters closely related to the insulation characteristics are extracted.

[0175] Finally, the present invention establishes a multivariate linear regression model of operating state parameters and environmental influencing factors, and calculates the contribution of each parameter to the insulation resistance measurement value, that is, the influence weight coefficient. Based on these weight coefficients, the present invention establishes a linear correction model based on temperature coefficient and humidity coefficient, and obtains the insulation resistance measurement value compensated by environmental factors through iterative optimization. At the same time, the reliability of the measurement results is evaluated by statistical analysis, which provides an accurate basis for transformer insulation status diagnosis.

[0176] The following is an example 2 of a specific application scenario of the present invention: A certain power company has a 110kV / 10kV transformer substation, and the main transformer is a three-phase oil-immersed 110V transformer. The transformer was put into operation in 2015 and has been in operation for 9 years, supplying power to the surrounding areas. As the service life increases, the operation and maintenance department begins to worry about the aging of the transformer insulation system and the occurrence of insulation failures that affect the reliability of power supply. In order to timely grasp the insulation status of the transformer, the company decided to use the 110V transformer winding insulation resistance absorption ratio detection method proposed in the present invention to diagnose the main transformer.

[0177] First, the operation and maintenance personnel set up 16 temperature measurement points in the substation and used a thermocouple array to collect the surface temperature of the transformer winding. At the same time, they also installed a 0.2-level current transformer to collect the load current of the three-phase windings A, B, and C, with a sampling interval of 500 milliseconds. In addition, a magnetic flap level gauge was installed to monitor the oil level, a piezoelectric accelerometer to monitor mechanical vibration, and an ultra-high frequency partial discharge detector to monitor partial discharge. All these parameter data are collected through a 16-channel high-precision, synchronous acquisition system with a sampling frequency of 1024 Hz and an accuracy of 16 bits.

[0178] After collecting the transformer operating status parameters, the operation and maintenance personnel deployed temperature and humidity sensors and digital barometers near the substation to collect the ambient temperature, relative humidity and atmospheric pressure in real time. The measurement range of the temperature sensor is -40℃ to 85℃, with an accuracy of ±0.5℃; the measurement range of the humidity sensor is 0%RH to 100%RH, with an accuracy of ±3%RH; the measurement range of the barometer is 800hPa to 1100hPa, with an accuracy of ±0.3hPa. The collection of these environmental parameters laid the foundation for the subsequent insulation resistance measurement correction.

[0179] Next, the operation and maintenance personnel used a high-precision insulation resistance tester to test the transformer windings. First, they ensured that the transformer was completely de-energized and waited for the windings to be fully discharged. Then, the tester output a standard test voltage of 1000VDC, and the ripple factor of the measuring instrument was less than 1%. The operation and maintenance personnel recorded the starting time point of the test voltage application with an accuracy of 0.1 seconds. Based on the parallel RC equivalent circuit, they established a mathematical model of the transformer winding insulation, taking into account the time-varying resistance characteristics caused by the dielectric polarization effect. The model uses a first-order differential equation to describe the change of insulation resistance over time. The temperature coefficient is set to a 50% reduction in resistance for every 10°C increase, the humidity coefficient is set to a 20% reduction in resistance for every 10% RH increase, and the aging coefficient is set to a 5% reduction in resistance for every 1 year of operation.

[0180] Under the action of the standard test voltage, the operation and maintenance personnel first measured the first insulation resistance value R1 at the 15th second using an insulation resistance tester, with a measurement range of 100kΩ to 1TΩ and an accuracy of ±5%. At the same time, they also used a digital microammeter to record the leakage current i at that moment. l eak1, with a measurement range of 1nA to 100μA and an accuracy of ±2%. Based on Kirchhoff's law, the operation and maintenance personnel established a current continuity equation to describe the three components of conduction current, displacement current and absorption current in the insulating medium. Using numerical integration and moving average filtering algorithms, they calculated the leakage current i l Valid value of eak1.

[0181] 60 seconds later, the maintenance personnel used the same test instrument to measure the insulation resistance value R2 for the second time. At the same time, they recorded the leakage current i at that moment. leak2 , and the exponential decay model was used to fit the time variation characteristics of the leakage current. The model includes a steady-state leakage current component and a transient leakage current component. The decay time constant of the transient component is between 30 seconds and 60 seconds. Through linear regression analysis, the operation and maintenance personnel determined the attenuation coefficient λ of the leakage current, and its value is 0.02s -1 To 0.05s -1 between.

[0182] Based on the data obtained in the previous steps, the operation and maintenance personnel established a set of transformer operating status parameters (including temperature T, load current I, oil level deviation ΔH, vibration, etc.) and a set of environmental influencing factor data (including temperature T a The contribution of each parameter to the insulation resistance measurement value R was calculated by using a multivariate linear regression model of temperature (T), humidity (H), and pressure (P). After standardizing the regression coefficients using the correction coefficient method, the influence weight coefficient matrix W was obtained. By analyzing the matrix, they found that the weight coefficients of temperature (T) and humidity (H) were relatively large, 0.25 and 0.22 respectively, while the weight coefficients of other parameters were between 0.05 and 0.15. This shows that temperature and humidity are two key factors affecting the insulation resistance of transformers.

[0183] According to the above analysis results, the operation and maintenance personnel established a temperature correction factor K T and humidity correction factor K H Linear correction model of temperature correction function f T (T) uses an exponential function with 20°C as the reference temperature; humidity correction function f H (H) also uses an exponential function, with 50% RH as the base humidity.

[0184] Through iterative optimization, they determined the values ​​of each correction coefficient:

[0185] K T =0.0456(T-20);

[0186] K H =0.0212(H-50);

[0187] Using these two correction factors, the operation and maintenance personnel corrected the first and second insulation resistance measurement values ​​R1 and R2, and obtained the measurement result R after environmental factor compensation. corrected1 and R corrected2 .

[0188] Finally, the operation and maintenance personnel calculated the insulation resistance absorption ratio ξ of the transformer winding using the two corrected insulation resistance measurement values:

[0189] ξ=R corrected2 / R corrected1 =1.42;

[0190] This value is greater than 1.3, indicating that the insulation condition of the transformer winding is good. In order to further verify the reliability of the results, the operation and maintenance personnel conducted three consecutive measurements. The measurement results are shown in Table 1 below:

[0191] Table 1 Measurement results

[0192] Number of measurements <![CDATA[R correctd1 (GΩ)]]> <![CDATA[R corrected2 (GΩ)]]> Absorption ratio ξ 1 5.86 8.32 1.42 2 5.79 8.25 1.43 3 5.92 8.41 1.42 average value 5.86 8.33 1.42 Standard Deviation 0.07 0.09 0.01

[0193] From the statistical results, the average value of the absorption ratio ξ of the three measurements is 1.42, the standard deviation is only 0.01, and the coefficient of variation is 0.7%, which meets the reliability requirement of less than 5%. This shows that the 110V transformer winding insulation resistance absorption ratio detection method proposed in the present invention can effectively eliminate the interference of environmental factors and obtain stable and reliable measurement results.

[0194] It should be noted that the variables involved in the present invention are explained as shown in Table 2 below:

[0195] Table 2 Variable explanation table

[0196]

[0197]

[0198]

[0199] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for detecting the insulation resistance absorption ratio of a 110V transformer winding, characterized in that: The following steps are involved: S10, collecting the 110V transformer winding operation load data, winding temperature data, oil level data, vibration data, and partial discharge data to form an operation state parameter set, wherein the operation state parameters are acquired using a multi-channel synchronous acquisition system, and a temperature change equation group of the 110V transformer winding insulation is established according to the laws of thermodynamics to describe the winding temperature rise process, and the linear correlation coefficient between the parameters is determined by the least squares fitting method, and the main influencing components of the parameters are extracted by the principal component analysis method; S20, connecting the insulation resistance tester to both ends of the 110V transformer winding, collecting the ambient temperature data, humidity data, and atmospheric pressure data of the 110V transformer winding to establish an environmental impact factor data set, wherein the environmental impact factor data set is calculated by using a numerical solution method to calculate the comprehensive impact coefficient of environmental factors on insulation resistance by establishing a simultaneous equation group of a basic heat conduction equation, a humidity diffusion equation, and an air pressure distribution equation in the 110V transformer; S30, applying a standard test voltage to the 110V transformer winding when the 110V transformer winding is in a power-off state, recording the starting time point of applying the standard test voltage, establishing a winding insulation model based on a parallel RC equivalent circuit, considering the time-varying resistance characteristics caused by the dielectric polarization effect, and using a first-order differential equation to describe the variation of the insulation resistance over time; S40, collecting the first insulation resistance measurement value of the 110V transformer winding at the 15th second under the continuous action of the standard test voltage, and recording the leakage current data at the first insulation resistance measurement time, establishing a current continuity equation according to Kirchhoff's law, calculating the effective value of the leakage current by a numerical integration method, and using a moving average filter to eliminate measurement noise; S50, collecting the second insulation resistance measurement value of the 110V transformer winding at the 60th second under the continuous action of the standard test voltage, and recording the leakage current data at the second insulation resistance measurement time, using an exponential decay model to describe the variation characteristics of the leakage current over time, and determining the attenuation coefficient by a linear regression method; S60, establishing an influence weight coefficient matrix of the operating state parameter set and the environmental influencing factor data set, calculating the contribution of each parameter to the insulation resistance measurement value based on a multivariate linear regression model, and standardizing the weight coefficient using a correction coefficient method; S70, performing data correction on the first insulation resistance measurement value and the second insulation resistance measurement value according to the influence weight coefficient matrix, establishing a linear correction model based on the temperature coefficient and the humidity coefficient, optimizing the correction coefficient through iterative calculation, and realizing linear correction of the measurement value; S80. Calculate the corrected insulation resistance absorption ratio of the 110V transformer winding using the corrected first insulation resistance measurement value and the corrected second insulation resistance measurement value, process multiple measurement data using statistical averaging method, evaluate the reliability of the measurement results through standard deviation analysis, and output the corrected insulation resistance absorption ratio numerical result.

2. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 1, characterized in that: The temperature change equation group includes a heat balance equation, a heat transfer equation and a temperature rise equation.

3. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 2, characterized in that: The thermal balance equation is used to describe the balance between the heat generated inside the transformer winding and the heat dissipated outside during operation. The input includes the current in the winding, the resistance value of the winding, the temperature of the surrounding cooling medium, the surface heat dissipation area of ​​the winding and the heat dissipation coefficient. The output is the winding temperature during steady-state operation.

4. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 3, characterized in that: The heat transfer equation is used to describe the dynamic process of heat transfer between the transformer winding and the surrounding cooling medium. The input includes the thermal capacity of the winding, the operating time, the internal heating power and the external heat dissipation power. The output is the rate of change of the winding temperature over time.

5. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 4, characterized in that: The temperature rise equation is used to describe the change law of the transformer winding from the initial temperature to the final stable temperature. The input includes the initial temperature of the winding, the final stable temperature, the time constant of the temperature change and the actual operating time. The output is the actual temperature of the winding at any time.

6. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 5, characterized in that: The basic heat conduction equation is used to describe the law of heat conduction process between various parts inside the transformer. The input includes the thermal conductivity of the material, the temperature difference between various points and the density of heat flow. The output is the temperature distribution of various points inside the transformer.

7. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 6, characterized in that: The humidity diffusion equation is used to describe the migration and diffusion process of water in the transformer insulation medium. The input includes the humidity diffusion coefficient of the material, the humidity concentration difference at various locations and the diffusion time. The output is the humidity distribution state of each point in the insulation medium.

8. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 7, characterized in that: The pressure distribution equation is used to describe the gas pressure distribution law at different height positions inside the transformer. The input includes the density of oil and gas, gravity acceleration and relative height difference, and the output is the pressure distribution at each height position inside the transformer.

9. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 8, characterized in that: In the step of determining the linear correlation coefficient between the parameters by least square fitting, each parameter is each parameter in the operating state parameter set.

10. A 110V transformer winding insulation resistance absorption ratio detection method according to claim 9, characterized in that: The correlation coefficient threshold of the least square method was set to 0.8.

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