Switch cabinet condensation mechanism analysis method based on multi-physical coupling field and fractal theory

Abstract

The invention discloses a switch cabinet condensation mechanism analysis method based on a multi-physical coupling field and a fractal theory, and the method comprises the steps: building a three-dimensional simulation model of a switch cabinet based on a solidworks environment; based on electromagnetic-flow-heat-wet coupling field simulation, judging parts easy to damp and condense; establishing a prediction model of condensation distribution in the switch cabinet based on a fractal theory; analyzing the condensation development process of the edge extraction condensation image based on an improved morphological method; the condensation development sequence of insulating parts in the switch cabinet is determined by simulating the diffusion process of wet air in the switch cabinet on the basis of multiple physical fields, the method is simple in principle, the parts, prone to generating condensation, in the switch cabinet can be accurately positioned, and the generation and development process of the condensation can be clearly analyzed and predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of switch cabinet internal condensation mechanism analysis, and in particular to a switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory. Background Art

[0002] As a key equipment for power conversion, switchgear will experience condensation problems under high humidity and pollution conditions. On the surface of insulating components (such as contact boxes) in the switchgear, condensation may distort the electric field distribution due to the different dielectric constants between the insulator, water and dust. Therefore, condensation will cause corona discharge, which will lead to insulation aging and even breakdown. In addition, condensation will cause corrosion of metal parts. In recent years, there has been an increasing number of insulation breakdown accidents caused by condensation in the contact box of switchgear.

[0003] Therefore, studying the condensation mechanism inside the switchgear under high humidity conditions is crucial to preventing condensation in the switchgear and improving the operational reliability of the switchgear.

[0004] Condensation inside switchgear refers to the phenomenon in which water vapor in the air condenses into water droplets on cooled surfaces in humid environments. This phenomenon can cause moisture to form on the equipment and electrical components inside the switchgear. When the absolute humidity reaches a certain value, condensation on the conductor surface distorts the electric field under high humidity conditions, significantly reducing the onset corona voltage, thereby affecting the normal operation of the equipment and even causing damage. Research on condensation in switchgear currently focuses on online partial discharge (PD) monitoring and anti-condensation methods.

[0005] Partial discharge measurement methods are based on various physical and chemical effects, including electromagnetic radiation, ultraviolet emission, thermal radiation, ultrasound, and ozone. The most commonly used anti-condensation methods are heaters, dehumidifiers, and super-hydrophobic materials. Currently, effective research and measurement of the condensation formation time of switchgear or ring network cabinet walls under different humidity and temperature conditions have been carried out. However, the lack of analysis of the condensation mechanism inside the switchgear under high humidity conditions and the lack of research on the location of components prone to condensation have resulted in most switchgear anti-condensation solutions failing to achieve the desired results. Summary of the Invention

[0006] The purpose of the present invention is to provide a switch cabinet condensation mechanism analysis method based on multi-physics coupling fields and fractal theory. This method comprehensively considers the interaction of multiple physical fields (such as flow fields, temperature fields, humidity fields, etc.), as well as the role of fractal theory in describing the condensation form and distribution. It can thus more comprehensively reveal the formation mechanism of condensation inside the switch cabinet, realize the rapid judgment and location of areas susceptible to moisture and condensation in the switch cabinet, and provide theoretical support for the formulation of anti-condensation schemes for switch cabinets.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The switchgear condensation mechanism analysis method based on multi-physics coupling field and fractal theory includes the following steps:

[0009] Step 1: Create a 3D simulation model of the switchgear based on SolidWorks software;

[0010] Step 2: Establish a simulation model of the gas-liquid phase change process in the switchgear based on the flow-heat-humidity coupled field;

[0011] Step 3: Based on fractal theory, a condensation distribution prediction model for areas inside the switchgear that are susceptible to moisture and condensation is established;

[0012] Step 4: Extract condensation images based on the improved morphological method to determine the areas in the switch cabinet that are susceptible to moisture and condensation;

[0013] Step 5: Determine the condensation development sequence of the insulating components inside the switchgear based on multi-physics simulation of the diffusion process of moist air inside the switchgear.

[0014] In step 1, a 3D simulation model of the switch cabinet is established based on SolidWorks software, such as Figure 1 As shown in the figure, a 3D model of a 40.5kV switchgear is established using SolidWorks. The dimensions of the switchgear are 3100mm long, 1400mm wide, and 2600mm high.

[0015] The switchgear enclosure is enclosed in 2mm thick fully armored metal, and each room is separated by metal plates. The protection level of the switchgear is IP4X, and a 1mm gap is left in the busbar room, circuit breaker room, cable room and the pressure relief channel on the side wall of the switchgear.

[0016] In step 2, the gas-liquid phase change process in the switch cabinet is analyzed based on the electromagnetic-fluid-heat-humidity coupled field, including the following steps:

[0017] Step 2.1: Use a single momentum conservation differential equation to solve the fluid field, where each physical parameter of the fluid is determined by the physical properties of each fluid component and its mass fraction, and the sum of the mass fractions of the fluid components is equal to 1:

[0018]

[0019] Among them, Y i Indicates the mass fraction of the fluid component, ɑ i A physical weight parameter representing the fluid composition.

[0020] Establish a complete mathematical description of fluid physical parameters by using the mass conservation equation, momentum conservation equation, and energy conservation equation;

[0021] The mass conservation equation:

[0022]

[0023] Where ρ represents the density parameter of the fluid component, V represents the volume parameter of the fluid component, and div represents the divergence operator;

[0024] Momentum conservation equation:

[0025]

[0026] Where u represents the velocity component of the fluid on the x-axis, v represents the velocity component of the fluid on the y-axis, w represents the velocity component of the fluid on the z-axis, P represents the fluid momentum, S represents the energy source, and grad represents the gradient operator;

[0027] Energy conservation equation:

[0028]

[0029] Where T represents the fluid temperature field, k represents the heat transfer coefficient, S T Indicates a heat source;

[0030] Each fluid component satisfies the mass transfer equation:

[0031]

[0032] Where ρ represents the density parameter of the fluid component, t represents time, and Y i represents the mass fraction of the fluid component, V represents the fluid velocity field, and D i represents the diffusion coefficient of the i-th fluid component, represents the mass fraction gradient, R i represents the production and consumption of the i-th fluid component;

[0033] Step 2.2: Use the shear stress transfer turbulence boundary condensation model to establish the turbulent flow equations and phase change equations. The turbulence equations are used to describe the motion characteristics of turbulence, including the continuity equation, momentum equation, and energy equation.

[0034] Continuity equation:

[0035]

[0036] Where ρ represents the density parameter of the fluid component, t represents time, and u i represents the velocity component of the i-th fluid component on the x-axis;

[0037] Apply the average operation rule:

[0038]

[0039] Momentum equation:

[0040]

[0041] Where ρ represents the density parameter of the fluid component, t represents time, and u j represents the velocity component of the jth fluid component on the x-axis, μ represents the dynamic viscosity, and f i represents the external force component of the i-th fluid component in the x-axis direction;

[0042] Energy equation:

[0043]

[0044] Where k represents the heat transfer coefficient, ρ represents the pressure, and ρ represents the density parameter of the fluid component;

[0045] Establish a phase change model equation to describe the phase change process between liquid and gas phases, including phase change temperature, phase change pressure, phase change rate, etc.

[0046] Phase transition temperature equation:

[0047] T b =T sat (rho v ,p)

[0048] Phase change pressure equation:

[0049] P v =P sat (rho v ,T v )

[0050] Phase change rate equation:

[0051]

[0052] Among them, T b represents the phase transition temperature, T sat represents the saturation temperature, rho v Represents the liquid density, P v represents the liquid phase pressure, represents the material time derivative, rho v0 represents the reference liquid density;

[0053] Step 2.3: Calculate the heat source parameters caused by the heat loss of the switch cabinet current-carrying circuit resistance, including the heat loss caused by the current-carrying conductor resistance and contact resistance of each current-carrying component. The calculation is as follows:

[0054]

[0055] P=I 2 R

[0056]

[0057] Among them, H gen represents the heating rate, P represents power, L represents the length of the conductor, S represents the cross-sectional area of the conductor, I represents the current flowing through the conductor, R represents the resistance of the conductor, and ρ0 represents the resistivity of the conductor;

[0058] Through calculation, the calculation formula of the heating rate is rewritten as:

[0059]

[0060] In addition, the skin effect of the conductor causes the actual flow area of the alternating current in the conductor to be smaller than the cross-sectional area of the conductor, thereby increasing the Joule heat generated by the conductor. It is necessary to consider the additional loss of the main busbar due to the skin effect. The skin effect coefficient is K if , the actual calorific value is corrected to:

[0061] H′ gen =K jf H gen

[0062] Step 2.4: Calculate the water vapor content ratio according to the following formula;

[0063]

[0064] Where F represents the relative humidity of the internal environment of the switchgear under normal operating conditions, and F represents the water content of saturated humid air at the normal operating temperature of the switchgear;

[0065] Step 2.5: Determine the thermal boundary conditions at the switchgear housing. In the simulation model, the switchgear housing serves as the truncation boundary. The heat exchange between the housing and the external environment includes convection heat transfer and thermal radiation. The radiation heat transfer equation between the inner enclosure and the cavity is expressed according to the Stefan-Boltzmann law as follows:

[0066]

[0067] Among them, q r represents the heat flux of convective heat transfer, and σ represents the Stefan-Boltzmann constant, which is 5.67×10 - 8 w / (m 2 ·k 4 ), A1 and A2 are the radiation surface areas of the two objects, T1 and T2 are the temperatures of the two objects;

[0068] The cavity and inner enclosure are set as the environment and switch cabinet shell respectively, that is, T1 = T W ,T2=T c, since A1>>A2, the heat generated by thermal radiation at the shell is calculated as:

[0069]

[0070] The thermal boundary conditions at the switchgear housing are:

[0071]

[0072] In step 3, a condensation distribution prediction model for locations susceptible to moisture and condensation inside the switchgear is established based on fractal theory, including the following steps:

[0073] Step 3.1: Approximate the surface of each component inside the switch cabinet as a square with a side length of L, and then divide it into small squares of δ×δ, where δ is equal to L / r max , r max is the maximum diameter of the first generation of dewdrops, randomly selected r s ×δ 2 Small squares to simulate the first generation of dewdrops, r s is the effective area ratio, defined as the ratio of the area covered by each generation of cells to the area not covered by the previous generations of cells, r s <1;

[0074] Step 3.2: Reduce the side length of the next generation square to γδ to create the second generation of cells, where γ is the reduction ratio of the dew drop size between two adjacent generations of cells, resulting in (L / γδ) 2 A small square with a side length of γδ is randomly selected to simulate the generation of the second generation of dewdrops;

[0075] Step 3.3: Repeat step 3.2 to form aggregates composed of smaller and smaller cells. Replacing a small square with an inner circle can obtain a realistic condensation distribution image. Compare a large number of simulated images with the actual dew distribution photos to determine the dew distribution of the nth generation that is closest to the actual situation.

[0076] Among them, the electric field distortion caused by the nth generation and later dewdrops can be ignored, so the nth generation dewdrop distribution is selected as the final simulation result.

[0077] In step 4, the condensation image is extracted based on the improved morphological method to determine the locations in the switch cabinet that are susceptible to moisture and condensation, including the following steps:

[0078] Step 4.1: Perform an opening operation on the simulated dewdrop distribution image of the first n generations obtained in Step 3. This operation removes smaller bright spots while preserving all grayscale and larger bright area features. This eliminates small objects and burrs, separates the dewdrops at the fine connection points of the image, and smoothes the boundaries of larger objects without significantly changing their shape, area, and position. Perform a dilation operation on the resulting image to highlight the target dewdrops, remove isolated points in the image, and simplify the image data. This yields image A1, a superposition of the opening and dilation operations.

[0079] Step 4.2: Perform a closing operation on the simulated image of the first n generations of dewdrop distribution obtained in step 3 to remove smaller dark spots in the image, retain the original larger brightness features, fill the small holes inside the condensed beads, connect adjacent condensed beads, and smooth the boundaries of the condensed beads. Perform an erosion operation on the resulting image to further fill the holes in the image and enhance the bright areas of the image, obtaining image A2 after the superposition of the closing and erosion operations.

[0080] Step 4.3: Superimpose image A1 and image A2 to obtain image A. The expansion and erosion gradient operator expression is as follows:

[0081] g(A)=(A·C+B)-(A·CB)

[0082] In the formula, B and C are two different structural elements. The relationship between the size x and direction y of the structural element B is as follows:

[0083]

[0084] The expression of the multi-directional gradient operator is as follows:

[0085]

[0086] The expression of the multi-scale gradient operator is as follows:

[0087]

[0088] Where B 2j+1 It is represented as a set of structural elements of size (2j+1)×(2j+1). Finally, the weighted sum of multi-directional gradients and multi-directional scales is used as the final gradient image. The image background is removed using MATLAB image processing functions to eliminate the uneven contrast caused by the environment or noise. Edge extraction is performed using an improved mathematical morphology method.

[0089] The grayscale value of each pixel in the condensation image is caused by water droplets generated by the condensation phenomenon. The total number of grayscale levels in each area is counted, and the area with a large total number of grayscale levels is a condensation-prone area.

[0090] In step 5, the condensation development sequence of the insulating components inside the switch cabinet is determined based on the multi-physics simulation of the diffusion process of the moist air in the switch cabinet, which includes the following steps:

[0091] Step 5.1: Simulate the gas-liquid phase change process in the switch cabinet based on the electromagnetic-fluid-heat-humidity coupled field simulation model established in Step 2. The initial temperature and initial relative humidity inside and outside the switch cabinet are set to the average values under the normal operating state of the switch cabinet;

[0092] The initial state of the mixed gas is static (fluid velocity is 0 m / s), the total simulation time is 30 min, and the simulation adopts iterative adaptive step size with a minimum simulation step size of 10 s.

[0093] Step 5.2: Analyze the thermal field distribution obtained in Step 5.1. When the switchgear is in operation, current changes will cause the temperature rise of different conductors to change, thereby changing the temperature distribution inside the switchgear. Observe the thermal field changes in the cable compartment current transformer and contact box. On the surface of components with uneven temperature distribution, there are slow convection areas, and the surrounding air is difficult to circulate, which is conducive to the formation of condensation.

[0094] Step 5.3: Analyze the fluid field distribution obtained in Step 5.1. Due to the applied current and the temperature difference between the inside and outside of the switchgear, the conductive structure heats up, causing the air inside the switchgear to have a certain degree of fluidity. Using the fluid field distribution, we can measure the air component flow rates in each room within the switchgear, as well as the average flow rate for the entire interior space. The airflow around electrical equipment and in the corners of rooms where humid air tends to accumulate is significantly lower than the average.

[0095] Step 5.4: Analyze the humidity field distribution obtained in step 5.1. Due to the difference in temperature and humidity inside and outside the switch cabinet, humid air will diffuse into the switch cabinet, gradually changing the distribution of humid air inside the switch cabinet. Use the water vapor mass distribution cloud map to locate the accumulation of humid air.

[0096] Beneficial effects of the present invention:

[0097] (1) This application establishes a three-dimensional simulation model of the switch cabinet based on SolidWorks software, which can quickly create various components of the switch cabinet. SolidWorks can also perform stress simulation analysis and fluid simulation analysis, and the three-dimensional model has good intuitiveness;

[0098] (2) This application analyzes the gas-liquid phase change process in the switch cabinet based on the flow-heat-humidity coupled field, and can simultaneously consider the interaction between multiple physical fields, such as fluid dynamics field, temperature field, and humidity field. The multi-physical field simulation capability can more accurately simulate the complex environment of the gas-liquid phase change process in the switch cabinet;

[0099] (3) Based on fractal theory, the present invention establishes a condensation distribution prediction model for areas inside the switchgear that are susceptible to moisture and condensation. This model can better consider the fractal mechanism of condensation growth, thereby more accurately simulating and predicting the distribution and growth patterns of condensation.

[0100] (4) The present invention extracts condensation images based on an improved morphological method to determine the locations in the switch cabinet that are susceptible to moisture and condensation. This method can effectively reduce noise and interference in the image, improve the reliability of extraction, and help to better extract features from the condensation image, thereby more accurately determining the locations in the switch cabinet that are susceptible to moisture and condensation.

[0101] (5) The present invention determines the condensation development sequence of the insulating components inside the switch cabinet by simulating the diffusion process of moist air in the switch cabinet based on multi-physical fields. It can comprehensively consider the influence of multiple physical factors (such as temperature, humidity, airflow, etc.) on the diffusion of moist air, thereby more accurately simulating and predicting the order of condensation development. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] The present invention will be further described below with reference to the accompanying drawings.

[0103] Figure 1 It is a 3D model of KYN61-40.5 switchgear;

[0104] Figure 2 Prediction diagram of condensation bead distribution on the surface of internal components of switchgear;

[0105] Figure 3 Schematic diagram of condensation image area division;

[0106] Figure 4 Gray value distribution map of condensation image area;

[0107] Figure 5 Temperature distribution cloud diagram inside the switchgear;

[0108] Figure 6 Vector distribution cloud diagram of fluid field inside switchgear;

[0109] Figure 7 Cloud diagram of water vapor mass fraction distribution inside the switchgear;

[0110] Figure 8 Flowchart of the switchgear condensation mechanism analysis method based on multi-physics coupling field and fractal theory. DETAILED DESCRIPTION

[0111] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0112] like Figure 8 As shown, the present invention is a switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory, comprising the following steps:

[0113] Step 1: Create a 3D simulation model of the switchgear based on SolidWorks software;

[0114] Step 2: Establish a simulation model of the gas-liquid phase change process in the switchgear based on the flow-heat-humidity coupled field;

[0115] Step 3: Based on fractal theory, a condensation distribution prediction model for areas inside the switchgear that are susceptible to moisture and condensation is established;

[0116] Step 4: Extract condensation images based on the improved morphological method to determine the areas in the switch cabinet that are susceptible to moisture and condensation;

[0117] Step 5: Determine the condensation development sequence of the insulating components inside the switchgear based on multi-physics simulation of the diffusion process of moist air inside the switchgear.

[0118] In step 1, a 3D simulation model of the switch cabinet is established based on SolidWorks software, such as Figure 1 As shown in the figure, a 3D model of a 40.5kV switchgear is established using SolidWorks. The dimensions of the switchgear are 3100mm long, 1400mm wide, and 2600mm high.

[0119] The switchgear enclosure is enclosed in 2mm thick fully armored metal, and each room is separated by metal plates. The protection level of the switchgear is IP4X, and a 1mm gap is left in the busbar room, circuit breaker room, cable room and the pressure relief channel on the side wall of the switchgear.

[0120] In step 2, the gas-liquid phase change process in the switch cabinet is analyzed based on the electromagnetic-fluid-heat-humidity coupled field, including the following steps:

[0121] Step 2.1: Use a single momentum conservation differential equation to solve the fluid field, where each physical parameter of the fluid is determined by the physical properties of each fluid component and its mass fraction, and the sum of the mass fractions of the fluid components is equal to 1:

[0122]

[0123] Among them, Y iIndicates the mass fraction of the fluid component, ɑ i Physical weight parameters representing fluid components;

[0124] Establish a complete mathematical description of fluid physical parameters by using the mass conservation equation, momentum conservation equation, and energy conservation equation;

[0125] The mass conservation equation:

[0126]

[0127] Where ρ represents the density parameter of the fluid component, V represents the volume parameter of the fluid component, and div represents the divergence operator;

[0128] Momentum conservation equation:

[0129]

[0130] Where u represents the velocity component of the fluid on the x-axis, v represents the velocity component of the fluid on the y-axis, w represents the velocity component of the fluid on the z-axis, P represents the fluid momentum, S represents the energy source, and grad represents the gradient operator;

[0131] Energy conservation equation:

[0132]

[0133] Where T represents the fluid temperature field, k represents the heat transfer coefficient, S T Indicates a heat source;

[0134] Each fluid component satisfies the mass transfer equation:

[0135]

[0136] Where ρ represents the density parameter of the fluid component, t represents time, and Y i represents the mass fraction of the fluid component, V represents the fluid velocity field, and D i represents the diffusion coefficient of the i-th fluid component, represents the mass fraction gradient, R i represents the production and consumption of the i-th fluid component;

[0137] Step 2.2: Use the shear stress transfer turbulence boundary condensation model to establish the turbulent flow equations and phase change equations. The turbulence equations are used to describe the motion characteristics of turbulence, including the continuity equation, momentum equation, and energy equation.

[0138] Continuity equation:

[0139]

[0140] Where ρ represents the density parameter of the fluid component, t represents time, and u i represents the velocity component of the i-th fluid component on the x-axis;

[0141] Apply the average operation rule:

[0142]

[0143] Momentum equation:

[0144]

[0145] Where ρ represents the density parameter of the fluid component, t represents time, and u j represents the velocity component of the jth fluid component on the x-axis, μ represents the dynamic viscosity, and f i represents the external force component of the i-th fluid component in the x-axis direction;

[0146] Energy equation:

[0147]

[0148] Where k represents the heat transfer coefficient, ρ represents the pressure, and ρ represents the density parameter of the fluid component;

[0149] Establish a phase change model equation to describe the phase change process between liquid and gas phases, including phase change temperature, phase change pressure, phase change rate, etc.

[0150] Phase transition temperature equation:

[0151] T b =T sat (rho v ,p)

[0152] Phase change pressure equation:

[0153] P v =P sat (rho v ,T v )

[0154] Phase change rate equation:

[0155]

[0156] Among them, T b represents the phase transition temperature, T sat represents the saturation temperature, rho v Represents the liquid density, P v represents the liquid phase pressure, represents the material time derivative, rho v0 represents the reference liquid density;

[0157] Step 2.3: Calculate the heat source parameters caused by the heat loss of the switch cabinet current-carrying circuit resistance, including the heat loss caused by the current-carrying conductor resistance and contact resistance of each current-carrying component. The calculation is as follows:

[0158]

[0159] P=I 2 R

[0160]

[0161] Among them, H gen represents the heating rate, P represents power, L represents the length of the conductor, S represents the cross-sectional area of the conductor, I represents the current flowing through the conductor, R represents the resistance of the conductor, and ρ0 represents the resistivity of the conductor;

[0162] Through calculation, the calculation formula of the heating rate is rewritten as:

[0163]

[0164] In addition, the skin effect of the conductor causes the actual flow area of the alternating current in the conductor to be smaller than the cross-sectional area of the conductor, thereby increasing the Joule heat generated by the conductor. It is necessary to consider the additional loss of the main busbar due to the skin effect. The skin effect coefficient is K if , the actual calorific value is corrected to:

[0165] H′ gen =K jf H gen

[0166] Step 2.4: Calculate the water vapor content ratio according to the following formula;

[0167]

[0168] Where F represents the relative humidity of the internal environment of the switchgear under normal operating conditions, and F represents the water content of saturated humid air at the normal operating temperature of the switchgear;

[0169] Step 2.5: Determine the thermal boundary conditions at the switchgear housing. In the simulation model, the switchgear housing serves as the truncation boundary. The heat exchange between the housing and the external environment includes convection heat transfer and thermal radiation. The radiation heat transfer equation between the inner enclosure and the cavity is expressed according to the Stefan-Boltzmann law as follows:

[0170]

[0171] Among them, q r represents the heat flux of convective heat transfer, and σ represents the Stefan-Boltzmann constant, which is 5.67×10 -8 w / (m 2 ·k 4 ), A1 and A2 are the radiation surface areas of the two objects, T1 and T2 are the temperatures of the two objects;

[0172] The cavity and inner enclosure are set as the environment and switch cabinet shell respectively, that is, T1 = T W ,T2=T c , since A1>>A2, the heat generated by thermal radiation at the shell is calculated as:

[0173]

[0174] The thermal boundary conditions at the switchgear housing are:

[0175]

[0176] In step 3: Based on fractal theory, a condensation distribution prediction model for the parts inside the switch cabinet that are susceptible to moisture and condensation is established, such as Figure 2 As shown, the following steps are included:

[0177] Step 3.1: Approximate the surface of each component inside the switch cabinet as a square with a side length of L, and then divide it into small squares of δ×δ, where δ is equal to L / r max , r max is the maximum diameter of the first generation of dewdrops, randomly selected r s ×δ 2 Small squares to simulate the first generation of dewdrops, r s is the effective area ratio, defined as the ratio of the area covered by each generation of cells to the area not covered by the previous generations of cells, r s <1;

[0178] Step 3.2: Reduce the side length of the next generation square to γδ to create the second generation of cells, where γ is the reduction ratio of the dew drop size between two adjacent generations of cells, resulting in (L / γδ) 2 A small square with a side length of γδ is randomly selected to simulate the generation of the second generation of dewdrops;

[0179] Step 3.3: Repeat step 3.2 to form aggregates composed of smaller and smaller cells. Replacing a small square with an inner circle can obtain a realistic condensation distribution image. Compare a large number of simulated images with the actual dew distribution photos to determine the dew distribution of the nth generation that is closest to the actual situation.

[0180] Among them, the electric field distortion caused by the nth generation and later dewdrops can be ignored, so the nth generation dewdrop distribution is selected as the final simulation result.

[0181] In step 4, the condensation image is extracted based on the improved morphological method to determine the locations in the switch cabinet that are susceptible to moisture and condensation, including the following steps:

[0182] Step 4.1: Perform an opening operation on the first five generations of dewdrop distribution simulation images obtained in step 3 to remove smaller bright spots while preserving all grayscale and larger bright area features. This eliminates small objects and burrs, separates dewdrops at the thin connection points of the image, and smoothes the boundaries of larger objects without significantly changing their shape, area, and position. Perform a dilation operation on the resulting image to highlight the target dewdrops, remove isolated points in the image, and simplify the image data, resulting in image A1, which is a superposition of the opening and dilation operations.

[0183] Step 4.2: Perform a closing operation on the simulated image of the first n generations of dewdrop distribution obtained in step 3 to remove smaller dark spots in the image, retain the original larger brightness features, fill the small holes inside the condensed beads, connect adjacent condensed beads, and smooth the boundaries of the condensed beads. Perform an erosion operation on the resulting image to further fill the holes in the image and enhance the bright areas of the image, obtaining image A2 after the superposition of the closing and erosion operations.

[0184] Step 4.3: Superimpose image A1 and image A2 to obtain image A. The expansion and erosion gradient operator expression is as follows:

[0185] g(A)=(A·C+B)-(A·CB)

[0186] In the formula, B and C are two different structural elements. The relationship between the size x and direction y of the structural element B is as follows:

[0187]

[0188] The expression of the multi-directional gradient operator is as follows:

[0189]

[0190] The expression of the multi-scale gradient operator is as follows:

[0191]

[0192] Where B 2j+1 It is represented as a set of structural elements of size (2j+1)×(2j+1). Finally, the weighted sum of multi-directional gradients and multi-directional scales is used as the final gradient image. The image background is removed using the MATLAB image processing function to eliminate the uneven contrast caused by the environment or noise. Finally, the edge is extracted using the improved mathematical morphology method, and the extracted image is divided into equal areas, which are recorded as regions 1, 2, 3 and 4 from the outside to the inside, as shown in Figure 3 , count the pixel grayscale values of each area, such as Figure 4It can be seen that the grayscale level gradually increases from the center area to the edge area, and the condensation phenomenon in the edge area is more serious, that is, the condensation phenomenon develops from the edge to the middle area.

[0193] In step 5, the condensation development sequence of the insulating components inside the switch cabinet is determined based on the multi-physics simulation of the diffusion process of the moist air in the switch cabinet, which includes the following steps:

[0194] Step 5.1: Simulate the gas-liquid phase change process in the switch cabinet based on the electromagnetic-fluid-heat-humidity coupled field simulation model established in Step 2. The initial temperature and initial relative humidity inside the switch cabinet are set to 25°C and 40%, respectively. In addition, the initial temperature of the external environment of the switch cabinet is set to 30°C, and the initial relative humidity is set to 90%. In addition, the initial state of the mixed gas is static (fluid velocity is 0 m / s). The total simulation time is 30 minutes. The simulation adopts an iterative adaptive step size, and the minimum simulation step size is 10 seconds.

[0195] Step 5.2: Analyze the thermal field distribution obtained in step 5.1. The thermal field distribution cloud diagram is as follows: Figure 5 It can be observed that the temperature of most areas on the surface of the current transformer only rises by about 1°C compared to the initial temperature inside the switchgear. Due to weak airflow, the area between the three phases of the current transformer is the main area where condensation is prone to form. The temperature distribution on the surface of the contact box is uneven, and there is a slow convection area. In particular, the surface temperature of the concave part of the contact box is low, and the surrounding air is not easy to circulate, which is conducive to the formation of condensation.

[0196] Step 5.3: Analyze the fluid field distribution obtained in step 5.1. The fluid field distribution cloud map is as follows: Figure 6 , it can be observed that the air inside the switch cabinet has a certain fluidity, with an average flow rate of 0.055m / s;

[0197] This is due to heating of the conductive structure caused by the applied current and the temperature difference between the inside and outside of the switchgear. However, airflow around electrical equipment and in corners of rooms where humid air tends to accumulate is significantly below average. The switchgear exchanges air with the outside environment through the pressure relief duct and the gaps in the switchgear side walls, but the air exchange rate is low: the average flow rate in the pressure relief duct is only 0.047m / s.

[0198] Step 5.4: Analyze the humidity field distribution obtained in step 5.1. Figure 7 The figure shows the humidity field distribution inside the switchgear. Moist air accumulates at the bottom of the cable compartment and circuit breaker compartment, especially around the current transformer. The cable compartment is most affected by moist air because the electrical equipment is located at a lower position.

[0199] Step 5.5: Based on the analysis of the three physical fields, it can be found that condensation on the electrical equipment inside the switchgear develops from bottom to top, and the condensation diameter gradually increases;

[0200] By sorting the test images, the formation time of mist dew and visible dew at the target location under normal temperature and high humidity environment was obtained. Condensation formed in the following order: 1) cable room current transformer, 2) cable room contact box, 3) busbar room contact box.

[0201] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. The switchgear condensation mechanism analysis method based on multi-physics coupling field and fractal theory is characterized by: The following steps are involved: Step 1: Create a 3D simulation model of the switch cabinet based on SolidWorks software; Step 2: Analyze the gas-liquid phase change process in the switchgear based on the flow-heat-humidity coupled field; Step 3: Based on fractal theory, a condensation distribution prediction model for areas inside the switchgear that are susceptible to moisture and condensation is established; Step 4: Extract condensation images based on the improved morphological method to determine the areas in the switch cabinet that are susceptible to moisture and condensation; Step 5: Determine the condensation development sequence of the insulating components inside the switchgear based on multi-physics simulation of the diffusion process of moist air inside the switchgear.

2. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 1 is characterized in that: In step 1, the three-dimensional simulation model of the switch cabinet established based on SolidWorks includes a cable room, a busbar room, a circuit breaker room and a low-voltage room; Furthermore, different electrical equipment are arranged in the cable room, busbar room, circuit breaker room and low-voltage room.

3. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 2 is characterized in that: The low-pressure chamber is installed at a higher position and is relatively independent from the other three chambers.

4. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 1 is characterized in that: In step 2, the control equation of the thermal fluid field is established, and the thermal fluid field calculation is a multi-physics field coupling analysis process; Based on the influence of air and water vapor convection heat transfer process; When using CFD to simulate condensation on the wall inside the switchgear, the wall condensation model is adopted, and the shear stress transfer turbulent boundary condensation model is used to calculate the thermal flow field. The shear stress is combined with the characteristics of the turbulent boundary layer to simulate and predict the dynamic changes of the condensation phenomenon.

5. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 4 is characterized in that: The ratio of the heat source to the water vapor content inside the switchgear is calculated, and the switchgear shell is used as the truncation boundary. The heat exchange between the shell and the external environment includes convection heat transfer and thermal radiation.

6. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 1 is characterized in that: In said step 3, based on the similarity between the local distribution and the overall distribution of the dewdrops; The growth of dew drops on the surface of internal components of the switchgear follows the fractal growth law. The top n-generation prediction model of dew drop distribution on the contact box surface is established based on fractal theory.

7. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 6 is characterized in that: In step 4, image extraction is performed on the first n generations of condensation distribution prediction model obtained in step 3, and the condensation shape, size and structural features in the image are analyzed and processed; Among them, in the edge extraction of condensation images, the morphological method realizes image filtering and edge detection through dilation, erosion, opening and closing operations.

8. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 7 is characterized in that: The condensation image is traversed through the structural element in the morphological method, the areas matching the structural element are marked and connected, and the edges of the condensation are extracted.

9. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 1 is characterized in that: In step 5, the initial temperature and initial relative humidity inside and outside the switch cabinet are set to the average values under the normal operating state of the switch cabinet; The initial state of the mixed gas is a static state, the total simulation calculation time is 30 minutes, the simulation adopts an iterative adaptive step size, and the minimum simulation step size is 10 seconds.

10. The switch cabinet condensation mechanism analysis method based on multi-physics coupling field and fractal theory according to claim 9 is characterized in that: Based on the distribution of thermal, fluid, and humidity fields inside the switchgear under set conditions, the diffusion process of moist air inside the switchgear is identified, and the condensation development sequence of internal insulating components is determined.

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