RFID temperature measuring device of ring main unit screw integrated antenna and groove shape optimization method

Abstract

The invention provides a ring main unit screw integrated antenna RFID temperature measuring device and a groove shape optimization method, and belongs to the ring main unit temperature measurement technical field; the ring main unit screw integrated antenna RFID temperature measuring device comprises a plug screw, the surface of the plug screw is processed to form a spiral groove and an annular cutting groove; the plug screw rod is provided with a groove, the chip is integrated in the groove, and the RFID temperature sensing chip and the screw rod body form a closed radio frequency loop to form a screw rod antenna; and the reader-writer module is arranged at a far end, is internally provided with a directional antenna, and is in communication connection with the RFID temperature sensing chip through the screw antenna. The screw has the advantages that the ultrahigh frequency radio frequency identification temperature sensing chip is directly embedded into the screw groove and forms a closed radio frequency loop with the screw body, an external antenna structure is omitted, the high-temperature-resistant composite packaging material effectively resists the high-temperature environment in the ring main unit while ensuring the insulativity, and the service life of the ring main unit is prolonged. And the environmental adaptability and the long-term stability of the temperature measuring device are obviously improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of temperature measurement for ring main units, and particularly relates to an RFID temperature measurement device with a screw integrated antenna for a ring main unit and a groove shape optimization method. Background Art

[0002] A ring main unit is an enclosed switchgear used for cable branching, connection, and protection in a distribution network. A plug is a key metal component in a ring main unit, and its function is similar to the combination of a "sealing cover" and a "conductive joint", and is specifically used for the fixation, sealing, and current transmission of a cable terminal.

[0003] As the core conductive component for cable connection in a ring main unit, abnormal temperature of the plug is an important precursor to faults in the distribution system. Due to long-term exposure to large current loads and mechanical vibrations, the plug is prone to Joule heat effect caused by an increase in contact resistance (such as oxidation, loosening), resulting in out-of-control local temperature rise, and further leading to insulation aging or even short circuit explosion.

[0004] Traditional temperature measurement schemes rely on battery power supply. The replacement and maintenance of the battery will require additional operations on the ring main unit, which is not conducive to the stable operation of the ring main unit. Summary of the Invention

[0005] In view of this, in order to address the deficiencies of the prior art, the present invention provides an RFID temperature measurement device with a screw integrated antenna for a ring main unit and a groove shape optimization method. To solve the above technical problems, the technical solution adopted by the present invention is as follows: It includes: a plug screw: a spiral groove and an annular cut groove are formed on the surface of the plug screw; an RFID temperature sensing chip: a groove is provided on the plug screw, and the chip is integrated in the groove. The RFID temperature sensing chip forms a closed radio frequency circuit with the screw body to form a screw antenna; a high-temperature resistant insulation encapsulation layer is provided on the surface of the plug screw to cover the RFID temperature sensing chip and the bonding area with the groove; a reader module: is provided at a distance, and is internally configured with a directional antenna, and is communicatively connected to the RFID temperature sensing chip through the screw antenna.

[0006] Further, the spiral groove extends along the axial direction of the screw, and the annular cut groove is distributed perpendicular to the axis of the screw and intersects with the spiral groove.

[0007] Further, a groove structure is etched on the surface of the screw body by laser micromachining technology, and the processing accuracy is ±0.05 mm.

[0008] Further, the high-temperature resistant insulation encapsulation layer is composed of a composite of a ceramic substrate and a resin layer.

[0009] A groove shape optimization method for a screw conformal antenna of a ring main unit screw integrated antenna, the screw conformal antenna is provided with a spiral groove and an annular groove, and is characterized by including the following steps:

[0010] A three-dimensional parametric model of the screw is established, and the pitch P of the helical groove, the groove depth h1, the groove width w1, the spacing d of the annular groove, and the groove depth h2 are defined as adjustable variables;

[0011] The multi-physics field coupling analysis of the screw model is carried out through an electromagnetic-mechanical co-simulation platform: in the electromagnetic simulation module, the echo loss S of the antenna in the target frequency band is obtained 11 and the radiation gain; in the mechanical simulation module, torque load and temperature load are applied to obtain the maximum equivalent stress σ at the root of the groove von Mises ;

[0012] An optimal solution is generated through a multi-objective optimization algorithm with dynamic weight adjustment under the conditions of meeting the constraints of echo loss, radiation gain, and maximum equivalent stress;

[0013] The radio frequency performance and mechanical reliability of the output solution are verified to ensure its engineering feasibility.

[0014] Furthermore, in the method of setting the pitch, groove depth, groove width of the helical groove, and the spacing and groove depth of the annular groove as adjustable variables, the variable ranges of the helical groove and the annular groove satisfy:

[0015] The pitch P of the helical groove is in a proportional relationship with the wavelength λ of the target frequency band: P = c1λ, where c1 is the proportionality coefficient;

[0016] The spacing d of the annular groove is in a proportional relationship with the pitch P: d = c2P, and the depth h2 of the annular groove = h1 + Δh, where Δh is the depth increment.

[0017] Furthermore, the electromagnetic-mechanical co-simulation includes:

[0018] Calculate the surface volume current density distribution J of the screw and generate a heat source load based on the formula where:

[0019] The calculation of the volume current density J needs to consider the skin effect, and the skin depth δ satisfies The current density distribution

[0020] where: Q is the Joule heat source density, ω is the angular frequency, μ is the conductor permeability; z is the depth from the conductor surface; σ is the conductor conductivity; σ e is the material conductivity; J0 is the amplitude of the surface current density;

[0021] The meshed model after mechanical deformation is fed back to the electromagnetic simulation module, and the groove geometry parameters are updated through the interpolation algorithm.

[0022] Furthermore, the method for generating an optimal solution by the multi-objective optimization algorithm with dynamic weight adjustment under the conditions of satisfying the constraints of return loss, radiation gain, and maximum equivalent stress includes:

[0023] Define the design variable vector X = [P, h1, d, h2] T , where P is the pitch of the helical groove, h1 is the depth of the helical groove, d is the spacing of the annular grooves, h2 is the depth of the annular grooves, and set the initial population {X1, X2,..., XN}, satisfying: P ∈ [0.2λ, 0.3λ], h1 ∈ [0.05λ, 0.1λ], d ∈ [0.1λ, 0.15λ], h2 ∈ [h1 + 0.01λ, h1 + 0.03λ], where λ is the central frequency wavelength of the target frequency band, λ = c / f, where: c is the speed of light, f is the frequency;

[0024] Perform mixed constraints, where: electromagnetic constraint: g1(X) = S 11 (X) + 10 ≤ 0, in dB; mechanical constraint: g2(X) = σ von Mises (X) - 0.7σ y ≤ 0, in MPa; gain objective: f1(X) = -Gain(X), convert maximizing gain to minimizing negative gain; bandwidth objective: f2(X) = -BW -10dB (X); where: S 11 (X) is the return loss; σ von Mises (X) is the maximum equivalent stress; σy represents the yield strength of the material, which is the critical stress value at which the material begins to undergo plastic deformation; -Gain(X) is the negative form of the antenna radiation gain, as the minimized objective function term in the multi-objective optimization; -BW -10dB (X) is the operating bandwidth of the antenna when the return loss S11 ≤ -10 dB;

[0025] Adaptive weight adjustment: According to the constraint violation degree δ = max(g1, g2) of the current solution, dynamically allocate the objective weights: if δ > 0, the weights w1:w2 = 10:1, giving priority to satisfying the constraints; if δ ≤ 0, the weights w1:w2 = 1:2, giving priority to optimizing the gain and bandwidth;

[0026] Adopt the improved MOEA / D algorithm, decompose the multi-objective problem into multiple single-objective sub-problems, allocate the weight vector λi = (λi1, λi2) for each sub-problem, and define the sub-problem objective function:

[0027]

[0028] where: f1 = -Gain, f2 = -Bandwidth; g1, g2 are penalty terms for electromagnetic and mechanical constraints; ρ is a penalty factor, ρ = 10 6 ; λi is a weight vector, λi = (λi1, λi2, …, λim), the weight vector assigned to the i-th sub-problem, where λ ik represents the relative importance of the k-th objective in this sub-problem; f k (X) is the objective function, the mathematical expression of the k-th optimization objective, and X is the decision variable vector; F(X∣λi) is the sub-problem objective function; max(·) is the core of the Chebyshev decomposition, taking the maximum value of the weighted objectives to force the optimization to balance each objective; ρ is the penalty coefficient used to adjust the penalty intensity for constraint violation; g j (X) describes the conditions that the design must satisfy, usually expressed in the form of inequalities. Mechanical stress constraint: g1(X) = σ vonMises (X) - 160 MPa ≤ 0; gain lower limit constraint: g2(X) = 2.5 dBi - Gain(X) ≤ 0; ρΣg j (X) is the total penalty for constraint violation, and the penalty strength is adjusted by ρ;

[0029] By adjusting different weight vectors, the final solution set of the sub-problems covers all regions of the Pareto front;

[0030] Through the mutation and crossover operations of differential evolution DE, a widely distributed set of candidate solutions is generated for each sub-problem;

[0031] Through the perturbation of simulated annealing SA and the Metropolis criterion, the current optimal solution of the sub-problem is refined;

[0032] When the change rate of the hypervolume HV of the Pareto front solution set is less than 1% for 5 consecutive generations, or when the maximum number of iterations 1000 times is reached, the optimization is terminated.

[0033] Furthermore, the method of generating a widely distributed set of candidate solutions for each sub-problem through the mutation and crossover operations of differential evolution DE includes:

[0034] Differential evolution DE stage: For each individual Xi, a new solution is generated:

[0035] Mutation operation: By randomly selecting parent individuals and generating a difference vector Vi = X r1 + F·(X r2 - X r3 ), exploring the unexploited regions in the solution space;

[0036] Crossover operation: Mixing the original individual and the mutated individual Increase the diversity of solutions, where: r1, r2, r3 are random individual indices, F is the mutation factor, F ∈ [0.5, 1.0]; CR is the crossover probability, CR ∈ [0.8, 1.0];

[0037] Generate a set of potential high-quality solutions and select the current optimal solution X from them best 。

[0038] Furthermore, the method for finely adjusting the current optimal solution of the sub-problem by simulating the perturbation of Simulated Annealing SA and the Metropolis criterion includes:

[0039] Simulated Annealing SA stage: For the current optimal solution X best ,generate a perturbed solution X′ = X best +ΔX, where ΔX ~ N(0, σ2); where σ = T·σ0: is the perturbation amplitude, T: is the current temperature, σ0 = 0.01λ: is the initial perturbation amplitude;

[0040] SA generates a perturbed solution X′ based on a certain solution in the current non-dominated solution set;

[0041] The perturbation acceptance probability in the Simulated Annealing SA stage satisfies the Metropolis criterion:

[0042] where: F(X) is the fitness function; F: is the combination of the objective function and the constraint penalty term, T is updated as T k+1 = αT k , α is the cooling coefficient, α ∈ [0.9, 0.99];

[0043] The Differential Evolution stage and the Simulated Annealing stage are iterated cyclically. If the perturbed solution is better than the original solution, replace the original solution and update X best ;

[0044] Dynamic ratio adjustment: According to the population diversity index H, adjust the execution ratio β ∈ [0.5, 0.8] of DE and SA, satisfying β = 0.7 - 0.1·sign(H - H0); where: H0 is the preset threshold;

[0045] High diversity H > H0: Increase the DE ratio and strengthen the global search;

[0046] Low diversity H < H0: Increase the SA ratio and strengthen the local development.

[0047] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0048] 1. By directly embedding the UHF RFID temperature sensor chip into the screw groove and forming a closed RF loop with the screw body, the external antenna structure is eliminated, realizing the integrated design of mechanical and RF functions; the high-temperature resistant composite packaging material can effectively withstand the high temperature environment inside the ring network cabinet while ensuring insulation, significantly improving the environmental adaptability and long-term stability of the temperature measuring device.

[0049] 2. The combined structure of the spiral groove and the annular groove expands the antenna resonance frequency band through the coordinated design of the groove parameters and utilizes the electromagnetic coupling effect, significantly reducing the return loss and improving the radiation gain; the gradient transition groove design suppresses near-field electromagnetic interference and greatly extends the wireless communication distance.

[0050] 3. The groove etching process based on high-precision laser micromachining technology effectively reduces the stress concentration coefficient at the root of the groove; through electromagnetic-mechanical joint simulation verification, the optimized groove structure can still maintain a low stress level when subjected to high torque loads, avoiding the risk of mechanical failure.

[0051] 4. The dynamic weight adjustment algorithm integrates multiple optimization strategies to significantly improve the efficiency of coordinated optimization of electromagnetic performance and mechanical reliability; the adaptive termination mechanism accelerates the convergence of the optimal solution set and greatly shortens the calculation time. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0053] Figure 1 : A schematic diagram of the structure of the installation of the plug screw and the ring network cabinet in Example 1 of the present invention;

[0054] Figure 2 : A schematic structural diagram of a cross-section of the plugging screw in Example 1 of the present invention;

[0055] Figure 3 : Schematic diagram of signal distribution at the terminal in embodiment 1 of the present invention;

[0056] Figure 4 : Schematic diagram of the method flow in Example 2 of the present invention;

[0057] Among them, 10 is a plug screw, 11 is a spiral groove, 12 is an annular groove, 20 is an RFID temperature sensor chip, and 30 is a reader / writer module. DETAILED DESCRIPTION

[0058] In order to better understand the present invention, the content of the present invention is further clearly described below in conjunction with the embodiments and the accompanying drawings, but the protection content of the present invention is not limited to the following embodiments. In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without one or more of these details.

[0059] The installation position of the existing plug screw is as Figure 1 shown, where A is the ring main unit; B is the plug; C is the screw; D is the cable terminal

[0060] Example 1: Refer to Figures 1-3 , an RFID temperature measurement device with a screw integrated antenna for a ring main unit in this embodiment, which includes:

[0061] Plug screw 10: A helical groove 11 and an annular cut groove 12 are formed on the surface of the plug screw 10. The annular groove divides the helical groove 11 into multiple independent short groove segments arranged alternately, restricting the continuous expansion of cracks along the direction of the helical groove 11 and prolonging the fatigue life;

[0062] RFID temperature sensing chip 20: A groove is provided on the plug screw 10, and the RFID temperature sensing chip 20 is integrated in the groove. The RFID temperature sensing chip 20 forms a closed radio frequency loop with the plug screw body to form a screw antenna; a groove is machined on the metal screw body, the RFID temperature sensing chip 20 is embedded at the bottom of the groove, and the chip electrodes are electrically connected to the groove wall metal through laser welding. The radio frequency loop and the mechanical structure are integrated, eliminating the risk of external antenna fracture; the overall structure adapts to the narrow space and complex electromagnetic environment of the ring main unit;

[0063] High-temperature resistant insulation encapsulation layer, which is arranged on the surface of the plug screw 10 and covers the RFID temperature sensing chip 20 and the bonding area with the groove; the groove is filled with a composite encapsulation layer composed of a ceramic substrate made of high-temperature resistant ceramic powder and epoxy resin, and a dense insulation structure is formed through a stepped curing process. The composite encapsulation layer takes into account high-temperature stability and electrical insulation performance;

[0064] Reader-writer module 30: It is arranged at the remote end, configured with a directional antenna, and is communicatively connected to the RFID temperature sensing chip 20 through the directional antenna.

[0065] Refer to Figures 1-2 , the helical groove 11 extends along the axial direction of the screw, and the annular cut groove 12 is distributed perpendicular to the screw axis and intersects with the helical groove 11; the main helical groove 11 and the auxiliary annular cut groove 12 are machined on the screw surface, and multi-groove cooperative coupling realizes broadband impedance matching and improves the antenna radiation efficiency. The pitch of the main groove is one-fourth of the wavelength corresponding to the center frequency of the UHF band, and the depth of the annular cut groove 12 is distributed in a gradient. The transition area between the grooves is connected by a smooth surface with continuous curvature; the combined structure of the helical groove 11 and the annular cut groove 12 realizes the expansion of the antenna resonance frequency band and the suppression of near-field electromagnetic interference by setting the pitch, groove depth and intersection angle.

[0066] The surface of the screw body is etched with spiral grooves 11 and annular grooves 12 by laser micromachining technology. The machining accuracy is ±0.05 mm. A femtosecond laser is used to etch micro-grooves on the screw surface, and a three-dimensional groove shape is generated by off-axis beam scanning. After etching, micro-shot peening treatment is carried out on the groove root.

[0067] Beneficial effects:

[0068] 1. The design of the combined layout of the spiral groove 11 and the annular groove, with the annular groove distributed perpendicular to the screw axis, forms a periodic transverse strengthening rib structure, which can effectively restrain the deformation in the extending direction of the spiral groove 11, suppress the shear stress concentration of the spiral groove 11 under torque loading while enhancing the radio frequency resonance efficiency. The combination of the spiral groove 11 and the annular groove can generate multiple current resonance modes, such as the spiral groove 11 dominating the low-frequency resonance and the annular groove regulating the high-frequency resonance, etc., expanding the antenna bandwidth and realizing the coordinated improvement of electromagnetic radiation and mechanical load-bearing capacity.

[0069] 2. Through the parametric matching of the annular groove spacing and depth, the risk of crack propagation at the groove root under high-frequency vibration is reduced, and the service life of the device under complex working conditions is extended.

[0070] 3. The parametric model supports optimizing the groove shape distribution density in a limited space, reducing the proportion of redundant materials, and meeting the space constraint requirements of the antenna structure for miniaturized devices.

[0071] 4. The groove shape geometric parameters are optimized based on the laser processing process tolerance to ensure high surface quality and dimensional consistency, and reduce the influence of assembly errors on radio frequency performance.

[0072] Embodiment 2: A method for optimizing the groove shape of a screw integrated antenna in a ring main unit, applied to the RFID temperature measurement device of the screw integrated antenna in a ring main unit as in Embodiment 1, refer to Figure 4 , and it includes the following steps:

[0073] A1. Use SolidWorks or ANSYS SpaceClaim to establish a three-dimensional parametric model of the screw, define the pitch P, groove depth h1, groove width w1 of the spiral groove and the spacing d, groove depth h2 of the annular groove as adjustable variables, and realize automatic parameter adjustment and batch modeling through the script interface. The proportional relationship between parameters is designed based on the electromagnetic wavelength of the target frequency band;

[0074] A2. Perform multi-physical field coupling analysis on the screw model through an electromagnetic-mechanical joint simulation platform: In the electromagnetic simulation module, obtain the return loss S 11 of the antenna in the target frequency band and the radiation gain; in the mechanical simulation module, apply torque load and temperature load to obtain the maximum equivalent stress σ vonMises; Set the operating frequency band of the antenna, and calculate the radio frequency performance parameters such as return loss S11, gain, bandwidth, etc. through electromagnetic simulation tools;

[0075] A3. Through the multi-objective optimization algorithm with dynamic weight adjustment, generate the optimal solution under the conditions of meeting the constraints of return loss, radiation gain, and maximum equivalent stress, and combine the material properties, apply mechanical and temperature loads, and analyze the stress distribution of the groove structure under complex working conditions;

[0076] A4. Verify the radio frequency performance and mechanical reliability of the output solution to ensure its engineering feasibility.

[0077] Refer to Figure 4 , in the method of setting the pitch, groove depth, groove width of the spiral groove and the spacing and groove depth of the annular groove as adjustable variables, the variable ranges of the spiral groove and the annular groove satisfy:

[0078] The pitch P of the spiral groove is in a proportional relationship with the wavelength λ of the target frequency band: P = c1λ, where c1 is the proportionality coefficient;

[0079] The spacing d of the annular groove is in a proportional relationship with the pitch P: d = c2P, and the depth h2 of the annular groove = h1 + Δh, where Δh is the depth increment;

[0080] Based on the wavelength range of the target frequency band, calibrate the proportional relationship of the geometric parameters of the spiral groove and the annular groove through experiments to ensure the balance of radio frequency resonance and mechanical strength.

[0081] Refer to Figure 4 , the electromagnetic-mechanical co-simulation includes:

[0082] Calculate the volume current density distribution J on the surface of the screw rod, and generate the heat source load based on the formula where;

[0083] Combined with the distribution characteristics of the high-frequency electromagnetic field, calculate the skin effect depth on the surface of the conductor, and convert the current density distribution into a heat source and input it into the thermodynamic simulation. The calculation of the volume current density J needs to consider the skin effect, and the skin depth δ satisfies Current density distribution

[0084] J0 is the amplitude of the surface current density;

[0085] where: Q is the Joule heat source density, ω is the angular frequency, μ is the magnetic permeability of the conductor; z is the depth from the surface of the conductor; σ is the conductivity of the conductor; σ e is the conductivity of the material;

[0086] Feed back the mesh model after mechanical deformation to the electromagnetic simulation module, and update the groove geometry parameters through the interpolation algorithm.

[0087] Refer toFigure 4 , a method for generating an optimal solution by a multi-objective optimization algorithm with dynamic weight adjustment under the conditions of meeting the constraints of return loss, radiation gain, and maximum equivalent stress includes:

[0088] S1. Define the design variable vector X = [P, h1, d, h2] T , where P is the pitch of the spiral groove, h1 is the depth of the spiral groove, d is the spacing of the annular grooves, h2 is the depth of the annular grooves, and set the initial population {X1, X2,..., XN}, satisfying: P ∈ [0.2λ, 0.3λ], h1 ∈ [0.05λ, 0.1λ], d ∈ [0.1λ, 0.15λ], h2 ∈ [h1 + 0.01λ, h1 + 0.03λ], where λ is the central frequency wavelength of the target frequency band, λ = c / f, where: c is the speed of light, f is the frequency;

[0089] S2. Perform mixed constraints, where: Electromagnetic constraint: g1(X) = S 11 (X) + 10 ≤ 0, in units of dB; Mechanical constraint: g2(X) = σ von Mises (X) - 0.7σ y ≤ 0, in units of: MPa; Gain objective: f1(X) = -Gain(X), convert maximizing the gain into minimizing the negative gain; Bandwidth objective: f2(X) = -BW -10dB (X); where: S 11 (X) is the return loss; σ von Mises (X) is the maximum equivalent stress; σy represents the yield strength of the material, which is the critical stress value at which the material begins to undergo plastic deformation; -Gain(X) is the negative form of the antenna radiation gain, as the minimized objective function term in the multi-objective optimization; -BW -10dB (X) is the operating bandwidth of the antenna when the return loss S11 ≤ -10 dB;

[0090] S3. Adaptive weight adjustment: According to the constraint violation degree δ = max(g1, g2) of the current solution, dynamically allocate the objective weights: If δ > 0 (constraint violation), the weights w1:w2 = 10:1, giving priority to meeting the constraints; If δ ≤ 0 (constraint satisfied), the weights w1:w2 = 1:2, giving priority to optimizing the gain and bandwidth;

[0091] S4. Adopt an improved MOEA / D algorithm, decompose the multi-objective problem into multiple single-objective sub-problems, allocate the weight vector λi = (λi1, λi2) for each sub-problem, and define the sub-problem objective function:

[0092]

[0093] where: f1 = -Gain, f2 = -Bandwidth; g1, g2 are penalty terms for electromagnetic and mechanical constraints; ρ is a penalty factor, ρ = 10 6 ; λi is a weight vector, λi = (λi1, λi2, …, λim), the weight vector assigned to the i-th sub-problem, where λ ik represents the relative importance of the k-th objective in this sub-problem. By different weight combinations, the diversity of covering the Pareto front is ensured; f k (X) is the objective function, the mathematical expression of the k-th optimization objective, X is the decision variable vector, used to quantify the performance of each objective and guide the optimization direction; F(X|λi) is the sub-problem objective function; max(·) is the core of the Chebyshev decomposition, taking the maximum value of the weighted objective, forcing the optimization to balance each objective; ρ is the penalty coefficient, used to adjust the penalty intensity of constraint violation; g j (X) describes the conditions that the design must satisfy, usually expressed in the form of inequalities. Mechanical stress constraint: g1(X) = σ vonMises (X) - 160 MPa ≤ 0; gain lower limit constraint: g2(X) = 2.5 dBi - Gain(X) ≤ 0; ρ∑g j (X) is the total penalty for constraint violation, and the penalty intensity is adjusted by ρ

[0094] By adjusting different weight vectors, the final solution set of the sub-problem covers all regions of the Pareto front;

[0095] S5. Through the mutation and crossover operations of differential evolution (DE), a widely distributed set of candidate solutions is generated for each sub-problem, including:

[0096] Differential evolution (DE) stage: For each individual Xi, a new solution is generated:

[0097] Mutation operation: By randomly selecting parent individuals and generating a difference vector Vi = X r1 + F·(X r2 - X r3 ), explore the unexploited regions in the solution space;

[0098] Crossover operation: Mix the original individual and the mutated individual to increase the diversity of the solution, where: r1, r2, r3 are random individual indices, F is the mutation factor, F ∈ [0.5, 1.0]; CR is the crossover probability, CR ∈ [0.8, 1.0]; X i,j is the original individual;

[0099] Generate a set of potential high-quality solutions, and select the current optimal solution X best ;

[0100] S6. Refine and adjust the current optimal solution of the sub-problem through the perturbation of simulated annealing SA and the Metropolis criterion, including:

[0101] Simulated annealing SA stage: For the current optimal solution X best , generate a perturbed solution X' = X best + N(0, σ 2 ), where σ = T·σ0 is the perturbation amplitude, T is the current temperature, and σ0 = 0.01λ is the initial perturbation amplitude;

[0102] SA generates a perturbed solution X' based on a certain solution in the current non-dominated solution set;

[0103] The perturbation acceptance probability in the simulated annealing SA stage satisfies the Metropolis criterion:

[0104] where: F(X) is the fitness function; F is the combination of the objective function and the constraint penalty term, and T is updated as T k+1 = αT k , α is the cooling coefficient, and α ∈ [0.9, 0.99];

[0105] The differential evolution stage and the simulated annealing stage are iterated cyclically. If the perturbed solution is better than the original solution, replace the original solution and update X best ;

[0106] S7. Dynamic ratio adjustment: According to the population diversity index H, adjust the execution ratio β ∈ [0.5, 0.8] of DE and SA, satisfying β = 0.7 - 0.1·sign(H - H0); where: H0 is the preset threshold

[0107] High diversity H > H0: Increase the DE ratio to strengthen the global search;

[0108] S8. Low diversity H < H0: Increase the SA ratio to strengthen the local development. Terminate the optimization when the change rate of the hypervolume HV of the Pareto front solution set is less than 1% for 5 consecutive generations or reaches the maximum number of iterations 1000 times.

[0109] Beneficial effects

[0110] 1. Through the electromagnetic-thermal-mechanical multi-physics field coupling simulation and parameter linkage optimization, synchronously improve the radio frequency performance (such as bandwidth, gain) and mechanical reliability (such as fatigue resistance, deformation resistance) of the screw antenna, and avoid the performance loss caused by traditional step-by-step design.

[0111] 2. Introduce a dynamic weight strategy in the multi-objective optimization algorithm, give priority to meeting the constraint conditions (such as mechanical strength threshold), and then gradually balance the performance objectives, significantly improving the global convergence efficiency and design success rate.

[0112] 3. Based on the grid update and parameter feedback mechanism, realize the data closed-loop interaction between electromagnetic simulation and mechanical simulation, and effectively solve the problem of electromagnetic performance deviation caused by structural deformation.

[0113] 4. Parametric modeling and scripted processes support rapid adjustment of target frequency bands, material properties, and operating conditions, and are suitable for the customized design requirements of different specifications of screw antennas.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Other modifications or equivalent replacements made by those of ordinary skill in the art to the technical solutions of the present invention shall be covered within the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solutions of the present invention.

Claims

1. An RFID temperature measurement device for a ring main unit screw integrated antenna, characterized in that, Including: Plug screw (10): A spiral groove (11) and an annular cut groove (12) are formed on the surface of the plug screw (10); RFID temperature sensing chip (20): A groove is provided on the plug screw (10), and the chip is integrated in the groove. The RFID temperature sensing chip (20) forms a closed radio frequency circuit with the screw body to form a screw antenna; A high-temperature resistant insulating encapsulation layer is provided on the surface of the plug screw (10) to cover the RFID temperature sensing chip (20) and the bonding area with the groove; Reader-writer module (30): It is arranged at the far end, internally configured with a directional antenna, and is communicatively connected to the RFID temperature sensing chip (20) through the screw antenna.

2. The RFID temperature measurement device of the ring main unit screw integrated antenna according to claim 1, characterized in that The spiral groove (11) extends along the axial direction of the screw, and the annular cut groove (12) is distributed perpendicular to the screw axis and intersects with the spiral groove (11).

3. The RFID temperature measurement device for the ring main unit screw integrated antenna according to claim 1, characterized in that, The surface of the screw body is etched with a groove structure by laser micro-machining technology, and the machining accuracy is ±0.05 mm.

4. The RFID temperature measurement device of the ring main unit screw integrated antenna according to claim 1, characterized in that, The high-temperature resistant insulating encapsulation layer is composed of a composite of a ceramic substrate and a resin layer.

5. A slot-shaped optimization method for a screw integrated antenna in a ring main unit. The screw conformal antenna is provided with a helical slot and an annular slot, characterized in that, Including the following steps: Establish a three-dimensional parametric model of the screw, and define the pitch P, groove depth h1, groove width w1 of the spiral groove, and the spacing d and groove depth h2 of the annular groove as adjustable variables; Perform multi-physics field coupling analysis on the screw model through an electromagnetic-mechanical joint simulation platform: In the electromagnetic simulation module, obtain the echo loss S of the antenna in the target frequency band 11 and radiation gain; In the mechanical simulation module, apply torque load and temperature load to obtain the maximum equivalent stress σ at the root of the groove vonMises ; Through a multi-objective optimization algorithm with dynamic weight adjustment, generate an optimal solution under the conditions of meeting the echo loss, radiation gain, and maximum equivalent stress constraints; Verify the radio frequency performance and mechanical reliability of the output solution to ensure its engineering feasibility.

6. The slot shape optimization method of the ring main unit screw integrated antenna according to claim 5, characterized in that, In the method of defining the pitch, groove depth, groove width of the spiral groove, and the spacing and groove depth of the annular groove as adjustable variables, the variable ranges of the spiral groove and the annular groove satisfy: The pitch P of the spiral groove is in a proportional relationship with the wavelength λ of the target frequency band: P = c1λ, where c1 is a proportionality coefficient; The spacing d of the annular groove is in a proportional relationship with the pitch P: d = c2P, and the depth h2 of the annular groove = h1 + Δh, where Δh is the depth increment.

7. The slot shape optimization method of the screw integrated antenna of the ring main unit according to claim 5, characterized in that The electromagnetic-mechanical co-simulation includes: Obtain the surface volume current density distribution J of the screw and generate a heat source load based on the formula where: The calculation of the volume current density J needs to consider the skin effect, and the skin depth δ satisfies Current density distribution Where: Q is the Joule heat heat source density, ω is the angular frequency, μ is the conductor magnetic permeability; z is the depth from the conductor surface; σ is the conductor conductivity; σ e is the material conductivity; J0 is the amplitude of the surface current density; Feed back the mesh model after mechanical deformation to the electromagnetic simulation module, and update the groove geometry parameters through an interpolation algorithm.

8. The slot shape optimization method of the screw integrated antenna of the ring main unit according to claim 5, characterized in that, The method of generating an optimal solution through a multi-objective optimization algorithm with dynamic weight adjustment under the conditions of meeting the echo loss, radiation gain, and maximum equivalent stress constraints includes: Define the design variable vector X = [P, h1, d, h2] T , where P is the pitch of the helical groove, h1 is the depth of the helical groove, d is the spacing of the annular groove, h2 is the depth of the annular groove. Set the initial population {X1, X2,..., XN} to satisfy: P ∈ [0.2λ, 0.3λ], h1 ∈ [0.05λ, 0.1λ], d ∈ [0.1λ, 0.15λ], h2 ∈ [h1 + 0.01λ, h1 + 0.03λ], where λ is the central frequency wavelength of the target frequency band, λ = c / f, where c is the speed of light and f is the frequency; Perform mixed constraints, where: Electromagnetic constraint: g1(X) = S 11 (X) + 10 ≤ 0, in dB; Mechanical constraint: g2(X) = σ von Mises (X) - 0.7σ y ≤ 0, in MPa; Gain objective: f1(X) = -Gain(X), transforming the maximization of gain into the minimization of negative gain; Bandwidth objective: f2(X) = -BW -10dB (X); where: S 11 (X) is the return loss; σ von Mises (X) is the maximum equivalent stress; σy represents the yield strength of the material, which is the critical stress value at which the material begins to undergo plastic deformation; -Gain(X) is the negative form of the antenna radiation gain and is used as the minimization objective function term in multi-objective optimization; -BW -10dB (X) is the operating bandwidth of the antenna when the return loss S11 ≤ -10 dB; Adaptive weight adjustment: According to the constraint violation degree δ = max(g1, g2) of the current solution, dynamically allocate the target weights: if δ > 0, the weights w1:w2 = 10:1, and give priority to meeting the constraints; if δ ≤ 0, the weights w1:w2 = 1:2, and give priority to optimizing the gain and bandwidth; Adopt an improved MOEA / D algorithm, decompose the multi-objective problem into multiple single-objective sub-problems, allocate a weight vector λi = (λi1, λi2) to each sub-problem, and define the sub-problem objective function: where: f1 = -Gain, f2 = -Bandwidth; g1, g2 are penalty terms for electromagnetic and mechanical constraints; ρ is the penalty factor, ρ = 10 6 ; λi is the weight vector, λi = (λi1, λi2, …, λim), the weight vector assigned to the i-th sub-problem, where λ ik represents the relative importance of the k-th objective in this sub-problem; f k (X) is the objective function, the mathematical expression of the k-th optimization objective, X is the decision variable vector; F(X∣λi) is the sub-problem objective function; max(·) is the core of the Chebyshev decomposition, taking the maximum value of the weighted objectives to force the optimization to balance each objective; ρ is the penalty coefficient, used to adjust the penalty intensity for constraint violation; g j (X) describes the conditions that the design must satisfy, usually expressed in the form of inequalities. Mechanical stress constraint: g1(X) = σ vonMises (X) - 160 MPa ≤ 0; Lower gain constraint: g2(X) = 2.5 dBi - Gain(X) ≤ 0; ρΣg j (X) is the total penalty for constraint violation, and the penalty strength is adjusted by ρ; By adjusting different weight vectors, make the final solution set of the sub-problems cover all regions of the Pareto front; Through the mutation and crossover operations of differential evolution DE, generate a widely distributed set of candidate solutions for each sub-problem; Through the perturbation of simulated annealing SA and the Metropolis criterion, refine and adjust the current optimal solution of the sub-problem; When the change rate of the hypervolume HV of the Pareto front solution set is less than 1% for five consecutive generations, or when the maximum number of iterations 1000 is reached, the optimization is terminated.

9. The groove shape optimization method of the screw integrated antenna of the ring main unit according to claim 8, characterized in that The method of generating a widely distributed candidate solution for each sub-problem by the mutation and crossover operations of differential evolution DE through differential evolution DE includes: Differential evolution DE stage: For each individual Xi, a new solution is generated: Mutation operation: By randomly selecting parent individuals and generating a difference vector Vi = X r1 + F·(X r2 - X r3 ), explore the unexploited regions in the solution space; Crossover operation: Mix the original individuals with the mutated individuals Increase the diversity of solutions where: r1, r2, r3 are random individual indices, F is the mutation factor, F ∈ [0.5, 1.0]; CR is the crossover probability, CR ∈ [0.8, 1.0]; X i,j is the original individual; Generate a set of potential high-quality solutions and select the current optimal solution X from them best .

10. The groove shape optimization method of the screw integrated antenna of the ring main unit according to claim 9, characterized in that, The method of finely adjusting the current optimal solution of the sub-problem by the perturbation of simulated annealing SA and the Metropolis criterion includes: Simulated annealing SA stage: For the current optimal solution X best , generate a perturbed solution X' = X best + N(0, σ 2 ), where σ = T·σ0 is the perturbation amplitude, T is the current temperature, and σ0 = 0.01λ is the initial perturbation amplitude; SA generates a perturbed solution X′ based on a certain solution in the current non-dominated solution set; The perturbation acceptance probability in the simulated annealing SA stage satisfies the Metropolis criterion: Where: F(X) is the fitness function; F: is the combination of the objective function and the constraint penalty term, and T is updated according to T k+1 = αT k where α is the cooling coefficient, α ∈ [0.9, 0.99]; The differential evolution stage and the simulated annealing stage are iterated cyclically. If the perturbed solution is better than the original solution, the original solution is replaced and X is updated best ; Dynamic ratio adjustment: According to the population diversity index H, adjust the execution ratio β ∈ [0.5, 0.8] of DE and SA, satisfying β = 0.7 - 0.1·sign(H - H0); where: H0 is a preset threshold; high diversity H > H0: increase the DE ratio and strengthen the global search; Low diversity H < H0: increase the SA ratio and strengthen the local exploitation.

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