Cable accessory insulation failure simulation analysis method based on multi-physics field aging test

Abstract

The invention discloses a cable accessory insulation failure simulation analysis method based on a multi-physics field aging test, and belongs to the technical field of electric power analysis. Establishing a silicone rubber stress relaxation constitutive equation; establishing an interface defect probability density function; establishing an insulation failure criterion equation; combining a silicone rubber stress relaxation constitutive equation, an interface defect probability density function and an insulation failure criterion equation to obtain an electricity-heat-force combined aging simulation model, and outputting an interface pressure attenuation rate, a partial discharge initial probability and an insulation residual life three-dimensional cloud picture according to interface air gap electric field data and a critical aging state threshold value. According to the method, the electric-thermal-mechanical multi-physical field coupling model is constructed, and the influence of interaction of each physical field on insulation aging is comprehensively considered, so that the technical effect of accurately presenting the full view of the insulation aging process under multi-stress coupling is realized, and the problem that the insulation aging process under multi-stress coupling is difficult to accurately describe in the prior art is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power analysis, and in particular relates to a cable accessory insulation failure simulation analysis method based on a multi-physical field aging test. Background Art

[0002] As the scale of power grids continues to expand, the application scope of power cables is becoming increasingly wide, and their laying length is also growing continuously. As a key component of power cable lines, cable accessories undertake important functions such as connecting cables, ensuring electrical insulation and mechanical fixation. During long-term operation, cable accessories will face the coupling of multiple physical fields such as electric field, thermal field and stress field at the same time. These physical fields influence and restrict each other, and jointly affect the insulation performance and service life of cable accessories.

[0003] Most of the existing cable accessories insulation performance analysis systems are evaluated and predicted through theoretical models of a single physical field or by simply superimposing some physical factors. Since there is actually a complex nonlinear coupling relationship between the physical fields, single physical field analysis or simple physical factor superposition cannot fully and accurately describe the changes in the internal microstructure of the insulation material under the action of multiple stress coupling, the evolution of the interface state, and the comprehensive impact of these changes on the overall insulation aging process. There is a problem that the insulation aging process under multiple stress coupling cannot be accurately described. Summary of the invention

[0004] In view of the above-mentioned problems, the purpose of the present invention is to achieve the technical effect of accurately presenting the overall picture of the insulation aging process under multi-stress coupling, and effectively solve the problem that it is difficult to accurately describe the insulation aging process under multi-stress coupling in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solutions: The cable accessory insulation failure simulation analysis method based on multi-physics field aging test includes the following steps: Step 1, obtaining multi-physical data of cable accessories, including microscopic air gap distribution parameters, aging test data, interface air gap electric field data, and critical aging state threshold; Step 2: Based on the material time-temperature equivalence principle, establish the stress relaxation constitutive equation of silicone rubber; Step 3: Establishing the interface defect probability density function according to the microscopic air gap distribution parameters; Step 4: Establish insulation failure criterion equation based on aging test data; Step 5: Combine the silicone rubber stress relaxation constitutive equation, interface defect probability density function, and insulation failure criterion equation to obtain an electric-thermal-mechanical combined aging simulation model, and output a three-dimensional cloud map of the interface pressure decay rate, partial discharge initiation probability, and insulation remaining life based on the interface air gap electric field data and the critical aging state threshold.

[0006] Preferably, the constitutive equation of silicone rubber stress relaxation in step 2 is: ; In the formula, is the elastic modulus at time t under temperature T, is the initial elastic modulus, e is the natural constant, is the time-temperature superposition characteristic index, is the relaxation time constant at temperature T.

[0007] Preferably, the interface defect probability density function in step 3 is: ; wherein, d is the equivalent diameter of the air gap, e is the natural constant, is the mean value of the air gap diameter distribution, is the standard deviation of the air gap diameter distribution, is the air gap density weight factor, is the air gap size attenuation coefficient.

[0008] Preferably, the insulation failure criterion equation in step 4 is: ; wherein, , , , are the weight coefficients of electric field distortion, thermal aging and interface pressure attenuation on insulation failure respectively, is the maximum local electric field strength, is the breakdown field strength, is the temperature rise of thermal aging, is the glass transition temperature, is the time-varying interface pressure, is the reference interface pressure, , , are the power-law exponents for controlling the weight coefficients of electric field distortion, thermal aging and interface pressure attenuation on insulation failure respectively.

[0009] Preferably, the weight coefficients , , are determined by the principal component analysis method: ; wherein, , , are the first largest eigenvalue, the second largest eigenvalue and the third largest eigenvalue of the covariance matrix respectively.

[0010] Preferably, the method for generating the three-dimensional cloud map in step 5 includes: Step 5.1, constructing the field quantity distribution of non-uniform sampling points by Kriging interpolation method; Step 5.2, extracting the isosurface by Marching Cubes algorithm; Step 5.3, rendering the multi-physical field coupling effect by Phong shading model.

[0011] Preferably, in the electro-thermal-mechanical combined aging simulation model, it also includes a cold shrinkage expansion rate constraint condition: Cold shrinkage expansion rate : ; Wherein, is the initial diameter of the cable accessory, is the diameter after cold shrinkage expansion, is the first threshold.

[0012] Preferably, in the electro-thermal-mechanical combined aging simulation model, it also includes a permanent deformation rate constraint condition: Permanent deformation rate : ; Wherein, is the diameter after permanent deformation, is the second threshold.

[0013] Preferably, the partial discharge initiation probability in step 5 is calculated by the Monte Carlo method: ; Wherein, N is the total number of interface air gaps, i is the air gap number, is the interface defect probability density function, is the indicator function, is the electric field strength at the i-th air gap, is based on the air gap diameter of the discharge threshold function.

[0014] Preferably, the discharge threshold function based on the air gap diameter is specifically: , Wherein, is the partial discharge threshold proportionality coefficient.

[0015] The beneficial effects of the present invention are: The present invention constructs an electro-thermal-mechanical multi-physical field coupling model, thereby comprehensively considering the influence of the interaction of each physical field on insulation aging, and further achieving the technical effect of accurately presenting the whole picture of the insulation aging process under multi-stress coupling, effectively solving the problem in the prior art that it is difficult to accurately describe the insulation aging process under multi-stress coupling.

[0016] The present invention constructs a constitutive equation for silicone rubber stress relaxation through the time-temperature equivalence principle of materials, thereby obtaining the stress relaxation characteristics of silicone rubber that fit different temperature-time conditions, and further fitting the actual simulation of the influence of materials on insulation performance.

[0017] The present invention establishes a probability density function of interface defects based on the microscopic air gap distribution parameters, then combines the aging test data, etc. to establish an insulation failure criterion equation, and uses the principal component analysis method to determine the weight coefficient, thereby obtaining a visible result that comprehensively considers the influence of various factors on insulation failure and accurately determines the insulation failure situation, and further achieving more accurate and reliable insulation failure judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a schematic flow chart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to make the above objects, features and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention will be given with reference to the accompanying drawings of the specification.

[0020] Example 1: As Figure 1 shown, a method for simulating and analyzing the insulation failure of cable accessories based on a multi-physical field aging test includes the following steps: Step 1: Obtain multi-physical data of cable accessories, including microscopic air gap distribution parameters, aging test data, interface air gap electric field data, and critical aging state threshold; Step 2: Based on the time-temperature equivalence principle of materials, establish a constitutive equation for silicone rubber stress relaxation; Step 3: According to the microscopic air gap distribution parameters, establish a probability density function of interface defects; Step 4: According to the aging test data, establish an insulation failure criterion equation; Step 5: Combine the constitutive equation for silicone rubber stress relaxation, the probability density function of interface defects, and the insulation failure criterion equation to obtain an electro-thermal-mechanical combined aging simulation model, and output three-dimensional cloud maps of the interface pressure decay rate, the probability of partial discharge initiation, and the remaining insulation life according to the interface air gap electric field data and the critical aging state threshold.

[0021] After obtaining the electro-thermal-mechanical combined aging simulation model, simulation software such as COMSOL and ANSYS can be used to output three-dimensional cloud maps of the interface pressure decay rate, partial discharge initiation probability, and insulation remaining life based on the interface air-gap electric field data and the critical aging state threshold.

[0022] For example, using COMSOL, the electric field analysis module of COMSOL is used to process the interface air-gap electric field data, the structural mechanics module is used to analyze the interface pressure decay rate, and user-defined equations are combined to calculate the partial discharge initiation probability (such as using the Monte Carlo method) and the insulation remaining life (such as using existing technologies such as the Arrhenius model, electrical aging model, and machine learning methods). Finally, its visualization tool is used to generate a three-dimensional cloud map.

[0023] Another example is to use ANSYS. The electromagnetic module of ANSYS (such as Maxwell) is used to process the interface air-gap electric field data, the structural mechanics module (such as Mechanical) is used to analyze the interface pressure decay rate, and the calculation of the partial discharge initiation probability and the insulation remaining life is achieved through the custom APDL (ANSYS Parametric Design Language) or Workbench. Finally, the visualization tool of ANSYS (such as the post-processing module of ANSYS Fluent) is used to generate a three-dimensional cloud map.

[0024] The microscopic air-gap distribution parameters refer to parameters such as the size, distribution, and density of microscopic air-gaps existing inside the cable accessory. These parameters are mainly obtained through experimental techniques such as microscope observation, X-ray tomography, or ultrasonic detection, and are used to establish the interface defect probability density function to describe the distribution of air-gaps in the cable accessory. The aging test data are data obtained through accelerated aging tests, including the performance changes of the cable accessory under different temperatures, electric fields, and mechanical stresses. These data are obtained through accelerated aging tests that simulate the long-term use environment conditions in the laboratory, and are used to establish the constitutive equation of silicone rubber stress relaxation and the insulation failure criterion equation to provide the law of material performance change over time. The interface air-gap electric field data are the electric field distribution data at the air-gap inside the cable accessory, which are usually obtained through electric field simulation calculations using numerical simulation software (such as COMSOL, ANSYS, etc.) or measured through experimental equipment such as electric field probes, and are used to evaluate the electric field strength at the air-gap, thereby affecting the partial discharge initiation probability and the insulation failure risk. The critical aging state threshold is the critical condition for insulation failure during the aging process of the cable accessory, including electric field strength, temperature rise, etc. These thresholds are determined through long-term experimental research and data analysis, usually based on the statistical analysis of a large number of experimental samples to determine the critical point of insulation failure, and are used to establish the insulation failure criterion equation to evaluate the insulation failure risk of the cable accessory under different aging conditions.

[0025] The constitutive equation of silicone rubber stress relaxation in Step 2 is as follows: ; In the formula, is the elastic modulus at time t and temperature T, is the initial elastic modulus, e is the natural constant, is the time-temperature superposition characteristic index, is the relaxation time constant at temperature T; It is calculated through the WLF equation: ; Among them, is the shift factor, is the first empirical parameter (15.6), is the second empirical parameter (56.7 K), is the temperature is the relaxation time constant at temperature is the reference temperature.

[0026] The time-temperature superposition characteristic index can be obtained by the following method: S101, Dynamic Thermomechanical Analysis (DMA): Obtain the storage modulus-temperature curve of silicone rubber through a frequency sweep experiment; S102, Master curve construction: Translate the relaxation modulus curves at different temperatures based on the WLF equation (Williams-Landel-Ferry); S103, Nonlinear fitting: Use the least squares method to fit the relaxation time distribution function and extract the value.

[0027] The interface defect probability density function described in Step 3 is: ; Among them, d is the equivalent diameter of the air gap, is the mean value of the air gap diameter distribution, is the standard deviation of the air gap diameter distribution, is the air gap density weight factor, is the air gap size attenuation coefficient.

[0028] Method for obtaining the air gap size attenuation coefficient: Obtain the two-dimensional morphology of the interface air gap by Scanning Electron Microscopy (SEM); Reconstruct the three-dimensional air gap distribution by X-ray Computed Tomography (micro-CT); Extract the equivalent diameter dataset of the air gap; Perform maximum likelihood estimation on the probability density function and solve for .

[0029] The insulation failure criterion equation in Step 4 is: ; Among them, , , , are the weight coefficients of electric field distortion, thermal aging, and interfacial pressure decay on insulation failure respectively, is the maximum local electric field strength, is the breakdown field strength, is the temperature rise of thermal aging, is the glass transition temperature, is the time-varying interfacial pressure, is the reference interfacial pressure, , , are the power-law exponents for controlling the weight coefficients of electric field distortion, thermal aging, and interfacial pressure decay on insulation failure respectively.

[0030] Using the insulation failure criterion equation can effectively judge whether the insulation reaches the failure state, provide a key judgment criterion for judging the use performance and safety of cable accessories, and facilitate the timely and accurate evaluation of the insulation condition of cable accessories during actual operation.

[0031] The weight coefficients , , are determined by the principal component analysis method: ; Among them, , , are the first largest eigenvalue of the covariance matrix (the corresponding eigenvector indicates the direction of the largest variance in the data, i.e., the first principal component), the second largest eigenvalue (the corresponding eigenvector indicates the direction of the second largest variance in the data, i.e., the second principal component), and the third largest eigenvalue (the corresponding eigenvector indicates the direction of the third largest variance in the data, i.e., the third principal component) respectively, and are calculated from at least 200 groups of aging test data.

[0032] The generation method of the three-dimensional cloud map in step 5 includes: Step 5.1, constructing the field quantity distribution of non-uniform sampling points through the Kriging interpolation method; Step 5.2, extracting the isosurface through the Marching Cubes algorithm; Step 5.3, rendering the multi-physical field coupling effect through the Phong shading model.

[0033] The Kriging interpolation method is an interpolation method based on the principles of spatial statistics. It can reasonably infer the distribution of field quantities within the entire spatial range based on the known finite sampling point data, especially suitable for dealing with non-uniformly sampled data. Through this method, the actual spatial distribution patterns of various physical quantities inside the cable accessory can be restored more accurately, providing basic data support for the subsequent generation of intuitive three-dimensional cloud maps. The Marching Cubes algorithm is a classic algorithm for extracting isosurfaces from three-dimensional data fields. It can identify the surfaces composed of points with the same physical quantity value based on the field quantity distribution data, presenting the complex three-dimensional field quantity data in the form of intuitive isosurfaces, facilitating the observation and analysis of the distribution characteristics and variation trends of physical quantities in space. The Phong shading model is a commonly used lighting model in computer graphics. It simulates the interaction between light and the object surface, endowing the isosurface with a realistic light and shadow effect, enabling the finally generated three-dimensional cloud map to more vividly and intuitively display the distribution and mutual relationships of various physical quantities inside the cable accessory under the coupling action of multiple physical fields.

[0034] In the electro-thermal-mechanical combined aging simulation model, it also includes the cold shrinkage expansion rate constraint condition and the permanent deformation rate constraint condition. The cold shrinkage expansion rate constraint condition is: Cold shrinkage expansion rate : ; Among them, is the initial diameter of the cable accessory, is the diameter after cold shrinkage expansion, is the first threshold, set according to requirements, such as 150%.

[0035] The permanent deformation rate constraint condition is: Permanent deformation rate : ; Among them, is the diameter after permanent deformation, is the second threshold, set according to requirements, such as 10%.

[0036] The cold shrinkage expansion rate constraint condition is defined by the relationship between the above diameter parameters, restricting the expansion situation and permanent deformation degree of the cable accessory during the cold shrinkage process to ensure that it meets certain performance requirements and guarantee the reliability and stability of the cable accessory in practical applications.

[0037] The partial discharge initiation probability described in step 5 is calculated using the Monte Carlo method: ; Wherein, N is the total number of interface air gaps, and i is the air gap number. is the probability density function of interface defects. is the indicator function. is the electric field strength at the i-th air gap. Based on the air gap diameter The discharge threshold function is expressed as: , Wherein, is the proportionality coefficient of the partial discharge threshold.

[0038] Through the Monte Carlo method, based on a large number of air gap sample data and the corresponding relationship between the electric field strength and the threshold field strength, the partial discharge initiation probability is statistically calculated, so as to evaluate the possibility of partial discharge occurring in the cable accessory from a probability perspective.

[0039] When calculating each formula in this embodiment, the dimension reduction process can be carried out according to needs to simplify the calculation.

[0040] Embodiment 2: An apparatus for implementing the method in Embodiment 1, including a memory, a processor, and a computer program stored on the memory and capable of running on the processor. The method in Embodiment 1 is implemented by the processor executing the computer program.

Claims

1. A cable accessory insulation failure simulation analysis method based on multi-physics field aging test, characterized in that: The following steps are involved: Step 1, obtaining multi-physical data of cable accessories, including microscopic air gap distribution parameters, aging test data, interface air gap electric field data, and critical aging state threshold; Step 2: Based on the material time-temperature equivalence principle, establish the stress relaxation constitutive equation of silicone rubber; Step 3: Establishing the interface defect probability density function according to the microscopic air gap distribution parameters; Step 4: Establish insulation failure criterion equation based on aging test data; Step 5: Combine the silicone rubber stress relaxation constitutive equation, interface defect probability density function, and insulation failure criterion equation to obtain an electric-thermal-mechanical combined aging simulation model, and output a three-dimensional cloud map of the interface pressure decay rate, partial discharge initiation probability, and insulation remaining life based on the interface air gap electric field data and the critical aging state threshold.

2. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 1 is characterized in that: The stress relaxation constitutive equation of the silicone rubber in step 2 is: ； In the formula, is the elastic modulus at temperature T and time t, is the initial elastic modulus, e is a natural constant, is the time-temperature superposition characteristic index, is the relaxation time constant at temperature T.

3. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 1 is characterized in that: The interface defect probability density function described in step 3 for: ； Where d is the equivalent diameter of the air gap, e is a natural constant, is the mean value of the air gap diameter distribution, is the standard deviation of the air gap diameter distribution, is the air gap density weight factor, is the air gap size attenuation coefficient.

4. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 1 is characterized in that: Insulation failure criterion equation in step 4 for: ； in, , , , are the weight coefficients of electric field distortion, thermal aging and interface pressure decay on insulation failure, is the maximum local electric field intensity, is the breakdown field strength, is the thermal aging temperature rise, is the glass transition temperature, is the time-varying interface pressure, is the reference interface pressure, , , are the power law exponents that control the weight coefficients of electric field distortion, thermal aging and interface pressure decay on insulation failure.

5. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 4 is characterized in that: Weight coefficient , , Determined by principal component analysis: ； in, , , are the first, second, and third largest eigenvalues ​​of the covariance matrix, respectively.

6. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 1, characterized in that: The method for generating the three-dimensional cloud image in step 5 includes: Step 5.1, construct the field quantity distribution of non-uniform sampling points by Kriging interpolation method; Step 5.2, extract isosurfaces by Marching Cubes algorithm; Step 5.3: Render the multi-physics coupling effect through the Phong shading model.

7. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 1 is characterized in that: The electrical-thermal-mechanical combined aging simulation model also includes the shrinkage and expansion rate constraints: Cold shrinkage expansion rate : ； in, is the initial diameter of the cable accessories, is the diameter after cold shrinkage expansion, is the first threshold.

8. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 7, characterized in that: The electrical-thermal-mechanical combined aging simulation model also includes permanent deformation rate constraints: Permanent deformation rate : ； in, is the diameter after permanent deformation, is the second threshold.

9. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 1, characterized in that: The probability of partial discharge initiation described in step 5 Monte Carlo method is used to calculate: ； Where N is the total number of interface air gaps, i is the air gap number, is the interface defect probability density function, is the indicator function, is the electric field strength at the ith air gap, Based on the air gap diameter The discharge threshold function.

10. The cable accessory insulation failure simulation analysis method based on multi-physical field aging test as claimed in claim 9, characterized in that: Based on air gap diameter The discharge threshold function is specifically: ， in, is the partial discharge threshold proportionality coefficient.

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