150 results about "Multiphysics" patented technology

The invention discloses an automatic control method and system for secondary granulation of a high-voltage zinc oxide resistor disc, relates to the technical field of intelligent manufacturing of power equipment, and solves the problems of out-of-control particle morphology caused by dynamic coupling parameter identification lag and control instability caused by multi-physical field parameter coupling in an existing method. According to the invention, a dynamic physical property parameter matrix is generated in real time based on multi-band dielectric relaxation spectrum analysis and terahertz wave tomography; predicting a fluidized phase change threshold value and an energy gathering area through multi-physics field coupling modeling; a time sequence attention deep reinforcement learning algorithm is adopted to generate a multi-field cooperative adjustment instruction; positioning a parameter conflict source and triggering decoupling compensation by combining a high-frequency vibration and acoustic emission combined monitoring module; performing closed-loop correction on the control network weight based on the laser spectrum data and a partial least squares regression model; the real-time performance of fluidization parameter identification, the stability of multi-field coupling control and the recovery efficiency of abnormal working conditions are remarkably improved, and meanwhile the batch consistency of the electrical performance of the resistor discs is guaranteed.

The invention provides a multi-physics field cooperative regulation and control method in coal mine rock burst prevention and control, and relates to the technical field of coal mine rock burst prevention and control, and the method comprises the steps: synchronously collecting stress field, fracture field and vibration wave field data in real time through a distributed optical fiber sensor network and a micro-seismic monitoring system, and constructing a dynamically updated three-dimensional geomechanical model; based on an adaptive Kalman filtering algorithm, noise reduction multi-source data are fused, a dynamic stress concentration factor and an energy accumulation critical index are extracted, and a rock burst risk probability model is established; a multi-objective optimization algorithm is adopted to generate graded regulation and control instructions of grouting reinforcement, mining speed adjustment and pressure relief drilling, and the graded regulation and control instructions are executed in real time; and iteratively optimizing the model weight by using a transfer learning algorithm in combination with a historical case library to form a closed-loop feedback adaptive prevention and control system. According to the method, the analysis precision of rock mass fracture evolution under complex geological conditions is improved through multi-physics field collaborative perception and dynamic modeling, and risk quantification and real-time regulation and control are realized through multi-algorithm coupling analysis.

The invention discloses an electronic product performance intelligent test system. The electronic product performance intelligent test system comprises an enhanced digital twinning and multi-physics field modeling system, a multi-modal perception fusion and intelligent test planning engine, a deep fault diagnosis and predictive health management feedback optimization module and a comprehensive optimization objective function framework. An intelligent and integrated test and evaluation system capable of comprehensively improving the test efficiency, the test coverage, the fault early warning capability and the product reliability can be realized.

The invention belongs to the technical field of tunnel engineering, and provides a multi-physics field real-time assimilation simulation and regulation method and system in a tunnel grouting process in order to solve the problem that real-time dynamic simulation and automatic regulation are lacked in existing tunnel construction, and the real-time assimilation simulation and regulation method and system in the tunnel grouting process are provided by utilizing ensemble Kalman filtering and combining real-time monitoring data in the tunnel grouting process. Dynamically correcting parameters of the multi-physical model; time correlation in the slurry condensation process is considered, a time-varying condensation model depicting physical property changes of slurry evolving along with time is integrated, the time-varying condensation model serves as an external function in the time step length to be embedded into the multi-physical field model in correction, and the slurry flowing state is adjusted in a self-adaptive mode through numerical simulation; and generating control parameters of tunnel grouting according to a dynamic simulation result, and realizing closed-loop regulation and control of tunnel grouting. Synchronous linkage of numerical simulation and on-site working conditions is realized.

The invention relates to the technical field of geological disaster early warning, and discloses a geological disaster early warning device, which comprises an acoustic electromagnetic fusion sensor array for collecting multi-physical field data related to the internal structure change of a rock-soil body; the data pre-processing and feature extraction module is used for performing pre-processing and feature extraction on the original multi-physics field data so as to identify the change features of the internal structure of the rock-soil body; the multi-physics field collaborative inversion module reconstructs the internal structure distribution of the rock-soil body by adopting a multi-physics field collaborative inversion algorithm; the structure change cause analysis and risk assessment module is used for analyzing causes of internal structure change of the rock-soil body and assessing potential geological disaster risks; the grading early warning information generation module is used for generating targeted grading early warning information; according to the invention, high-precision monitoring of the internal structure change of the rock-soil body is realized through an acoustic electromagnetic fusion sensing technology, the monitoring precision is improved, and possible landslide or collapse events can be predicted in advance.

The invention relates to the technical field of bridge engineering intelligent construction, discloses a digital twinborn and multi-physics field simulation-based lattice pier assembly error intelligent prediction method, and aims to construct a lattice pier assembly error prediction model. The lattice pier assembly error prediction model is composed of a channel independent feature extraction module of multi-physics field data, a self-adaptive space-time coupling and multi-factor dynamic fusion module and a training lattice pier assembly error prediction model, the multi-physical field data channel independent feature extraction module maps data of each physical field to a high-dimensional feature space through calculation, and according to a state space model, the adaptive space-time coupling and multi-factor dynamic fusion module introduces a plurality of factors to dynamically adjust weights of the physical fields in different time steps. Carrying out adaptive fusion on the processed physical field data through a space-time coupling function to obtain coupled physical field data; and finally, taking the output of the two as the input, and combining a regression model to predict the lattice pier assembly error.

A method for predicting in-situ leaching effects of sandstone-type uranium mining deposits after blasting is provided, which comprises: based on a finite element analysis platform, establishing an HJC rock-blasting constitutive model, and carrying out a blasting numerical simulation; calibrating a cloud map of blasting crack damage by using a Kriging interpolation algorithm; establishing a COMSOL multiphysics model; establishing a coupling interface between the COMSOL multiphysics model and PHREEQC based on MATLAB, and optimizing a cycle duration and a time step; performing a geochemical reaction calculation and saving results, running COMSOL files, and inputting the results of geochemical reaction calculation into PHREEQC to obtain a dynamic cyclic iterative simulation; dynamically correcting migration coefficients of uranyl complexes by integrating an LSTM neural network, and stopping the cycle to output multi-scale dynamic simulation results of migration of uranium.

The invention provides a fault diagnosis system based on multi-physics field data fusion, and the system comprises a multi-physics field data fusion module which is used for constructing a four-dimensional tensor input matrix, and carrying out the fusion of multi-physics field features; the fault knowledge graph construction module is used for constructing a fault knowledge graph; and the fault diagnosis module is used for performing similarity matching on the fused feature vector and a fault knowledge graph, judging a fault type, positioning a fault position and evaluating the severity of the fault. According to the technical scheme, accurate and real-time diagnosis of faults of the energy storage equipment is realized, and the reliability and the safety of operation of the energy storage equipment are improved.

The invention belongs to the technical field of direct shear-seepage tests of rock joints, and discloses a numerical test method for direct shear-seepage of rock joints under different boundary conditions, which comprises the following steps of: establishing a joint surface numerical model by using finite element software, and performing tests for simulating joint shear mechanical behaviors by applying different boundary conditions. And the contact state and the opening distribution of the joint surface under different shear displacements are obtained, so that the shear stress evolution mechanism of the joint surface is better revealed, and the mechanical behavior of the rough joint surface in the shear process is accurately expressed. According to the method, the evolution law of mechanical properties in the joint shearing process can be reflected, the influence of shearing deformation on the joint seepage characteristics can be reflected, joint opening data distribution is imported into programming software to be processed, a joint seepage numerical model is constructed, then multi-physics field simulation analysis software is imported, and the joint seepage performance is improved. The flow velocity, the osmotic pressure and the streamline distribution characteristics in the flowing process are calculated, so that the joint permeability characteristics are analyzed.

The invention provides a coupling space-spectrum conversion operator transformer multi-physics field distribution prediction method and system, and the method comprises the steps: mapping the initial condition distribution of multi-physics field distribution to a potential space of a unified dimension through independent linear transformation, generating an initial potential feature vector, and carrying out the prediction of the initial potential feature vector; performing spatial expansion on the cross-field coupling state of the multi-physical field distribution in combination with the GRU, splicing the obtained current global cross-field coupling state and the current potential feature input, and obtaining the potential feature input of the next layer of the GRU through a space-spectrum conversion operator layer; and inputting the potential features of all the current physical field distribution and the global cross-field coupling state into a GRU unit, updating the cross-field coupling state including cross-physical field interaction, minimizing weighted error optimization parameters of a physical field distribution prediction result, inversely mapping the reconstructed final potential features to a target space, and generating the prediction result of the physical field distribution. The method has higher generalization ability, the modeling precision is improved, and the calculation complexity is reduced.

The invention relates to the field of pile structure damage evolution, in particular to a soft soil foundation pile structure damage evolution prediction method and system, and the method comprises the steps: obtaining soft soil foundation investigation information; determining a spiral groove design scheme according to the soft soil foundation investigation information, wherein a spiral groove is used for installing an optical fiber composite cable; acquiring multi-physical field information according to the optical fiber composite cable, wherein the multi-physical field information comprises data corresponding to a mechanical field, a seepage field, a temperature field and a chemical field; obtaining construction record information; constructing an initial damage field according to the construction record information; according to the method, the spiral groove design is determined through investigation, the optical fiber composite cable is used for obtaining the multi-physics field data, the initial damage field is constructed in combination with construction records, and damage evolution analysis on the soft soil foundation pile structure is achieved. The data comprehensiveness and accuracy can be improved, the construction disturbance influence is quantified, and a scientific basis is provided for safety assessment and maintenance of the soft soil foundation pile structure.

The invention discloses a grounding grid electric heating power multi-field coupling modeling method and system considering soil nonlinear breakdown, and belongs to the technical field of power system grounding grids. The method comprises the following steps: establishing a three-dimensional geometric model containing a soil domain and a grounding grid conductor; defining non-linear conductivity characteristics of the soil; setting multi-physical field parameters and corresponding boundary conditions of the three-dimensional geometric model; and establishing a multi-physical field coupling control equation set including an electric field equation, a heat conduction equation and a thermal stress equation, and solving by adopting a finite element method to obtain three-dimensional space distribution data of the grounding grid under lightning current impact. According to the invention, on the basis of fully considering the nonlinear breakdown characteristic of the soil, the accurate simulation of the electric heating power multi-physical field behavior of the grounding grid under the impact current effect is realized, and the accuracy of impact impedance, potential distribution and temperature rise prediction is obviously improved.

The invention provides a digital twin modeling method and device for a wind turbine generator control system, and relates to the technical field of new energy, and the method comprises the steps: constructing a multi-physical field mechanism model of the wind turbine generator control system according to obtained aerodynamic characteristic parameters, mechanical characteristic parameters and electrical characteristic parameters; performing comparative analysis based on the multi-physics field mechanism model and the preprocessed operation data to generate deviation data; if the deviation data is greater than a preset first threshold value, performing deviation prediction through a pre-trained deviation prediction model based on the preprocessed operation data, and generating a deviation correction value; and correcting a simulation result of the multi-physics field mechanism model by using the deviation correction value to form a data-mechanism dual-driven digital twinborn model. According to the digital twinning modeling method and device for the wind turbine generator control system, the output precision and environmental adaptability of the wind turbine generator digital twinning system under various working conditions are effectively improved, and the fitting ability and continuous stability of the model to the actual operation state are enhanced.

The invention relates to the technical field of power system equipment state monitoring and fault diagnosis, in particular to a GIS basin-type insulator operation state evaluation method and system, and the system comprises an asset information and baseline modeling module which is used for building a high-fidelity multi-physics field finite element reference model and generating a defect state-external representation mapping data set; the physical information driven agent model generation module is used for constructing a neural network agent model fusing physical law constraints; the real-time data acquisition and feature extraction module is used for acquiring and processing online monitoring data such as UHF, gas, temperature and vibration; the state inversion and digital twinning calibration module is used for inverting internal defect parameters by adopting a Bayesian inference and MCMC method so as to realize real-time calibration of the model; and the evaluation diagnosis and life prediction module carries out fault mode identification and residual life prediction based on the calibration model.

The invention provides a computer cross-scale integrated analysis method based on a multi-physics field coupling mechanism, and the method comprises the steps: constructing a multi-level finite element model from a system level to a micro-area level, and integrating thermal-mechanical-electric coupling modeling; therefore, the technical problems that in a traditional method, multi-physics field coupling lacks, local area modeling is not fine, and electrical performance evolution is not introduced are solved, high-precision simulation of a typical device failure mechanism is achieved, and the method is suitable for device packaging reliability evaluation in special electronic systems such as military and high-reliability civil use and the like. The method can be widely popularized in microelectronic structures such as a power supply module, a processor and a memory, and can improve the evaluation precision of the high-frequency signal transmission performance of complex electronic equipment, thereby improving the precision of predicting the service life.

The invention relates to the technical field of coal bed gas development, and particularly discloses a numerical simulation method for multi-field coupling and microwave enhanced drainage and mining of a deep coal bed, which realizes accurate simulation of the whole process of drainage and mining of deep coal bed gas through six key steps: firstly, obtaining a coal bed parameter system; establishing a temperature coupling adsorption and desorption model, and quantifying the influence of the high ground temperature environment on the gas occurrence by correcting a Langmuir equation; constructing a dual-medium heat-gas-liquid-solid full-coupling control equation set which covers coal deformation, gas-water two-phase seepage, heat transfer and electromagnetic field equations; a microwave heat effect model is defined, and electromagnetic energy-heat energy conversion is calculated through a dielectric constant mixing model; deducing a porosity / permeability dynamic evolution equation, and coupling effective stress, matrix shrinkage and a thermal expansion effect; and finally, a COMSOL Multiphysics platform is adopted to realize multi-field coupling solution, and a productivity index is calculated through well circumference integration. According to the method, the inherent limitation of a static parameter model is overcome, and the precision and efficiency of numerical simulation are remarkably improved.

The invention provides a numerical-digital accurate prediction method and system for artificial stratum freezing multi-physics field evolution. The method comprises the following steps: S1, constructing a numerical model of artificial stratum freezing engineering multi-physics fields; s2, a sensor collects multi-physical field data of an engineering field in real time and transmits the multi-physical field data to a data transmission server in real time; s3, carrying out simulation calculation on the numerical model, extracting a multi-physics field calculation result of the numerical model at the measurement position of the sensor at preset time, and comparing the multi-physics field calculation result with the multi-physics field data of the engineering site at the corresponding time; s4, judging whether the difference value between the multi-physics field calculation result and the multi-physics field data is smaller than an allowable value or not, if so, entering S5, and if not, adjusting parameters by an optimization algorithm, and returning to S3; s5, obtaining an optimized numerical model; s6, repeatedly executing the steps S3-S5 in a project proceeding process, and continuously updating and optimizing the numerical model; and S7, a result is extracted from the updated optimization numerical model, and the artificial stratum freezing multi-physics field evolution process is accurately predicted.

The invention discloses a deep underground multi-physical field detection method and system, and particularly relates to the technical field of underground detection, and the method comprises the following steps: S1, obtaining seismic wave field data; s2, based on a multi-physics field original data set; s3, according to the basic characteristic parameter set; s4, calling a comprehensive feature fusion matrix; in the deep underground multi-physics field detection process, waveform, wave velocity and amplitude parameters contained in seismic wave field data and electromagnetic field intensity, resistivity and polarizability parameters contained in electromagnetic field data are collected by adopting a monitoring instrument sensor to generate a multi-physics field original data set, so that comprehensive basic data are provided for subsequent processing; based on the data set, the wave velocity and amplitude characteristics of each waveform segment of seismic wave field data and the resistivity and polarizability characteristics of electromagnetic field data are determined, a basic characteristic parameter set is obtained through integration, and key characteristics of different physical fields are accurately grasped.

The invention discloses a high-precision multi-physics field reconstruction method based on a nested neural network architecture. The method comprises the following steps: S1, acquiring open-source multi-physics field data; s2, a multi-scale Fourier operator-driven U-Net physical field reconstruction model is constructed, the physical field reconstruction model comprises an embedding module, a coding module and a decoding module, the coding module comprises at least one coding layer, each coding layer is formed by sequentially connecting a multi-scale Fourier neural operator layer and a down-sampling layer, and the multi-scale Fourier neural operator layer and the down-sampling layer are embedded into the embedding module; the decoding module comprises at least one decoding layer, and each decoding layer is formed by sequentially connecting a multi-scale Fourier neural operator layer and an up-sampling layer; s3, training the physical field reconstruction model based on a training set; and S4, performing quantitative analysis and qualitative analysis on the reconstructed physical field by using the test set.

The invention relates to the technical field of power fault diagnosis, and particularly discloses a wall bushing fault intelligent diagnosis method based on a physics-causal fusion diagnosis method, and the method comprises the steps: multi-physics field signal collection: deploying a multi-physics field sensor around a wall bushing to collect corresponding data; characteristic quantity extraction of multi-source signals is realized through a physical model; fault reason reasoning is carried out, and fault tracing is realized through a multi-level causal network and a physical constraint back propagation algorithm; and outputting a self-adaptive result, and outputting the possible fault type and the corresponding probability of the wall bushing. According to the wall bushing fault intelligent diagnosis method based on the physics-causal fusion diagnosis method provided by the invention, the technical problem that the multi-physics field coupling fault of the wall bushing is difficult to accurately trace can be effectively solved.

The invention provides a multi-physics field transformer noise reduction method and a related device, relates to the technical field of transformers, and aims to solve the problems of complex multi-physics field modeling, low simulation efficiency and low response surface model precision in the prior art. The method comprises the following steps: constructing a transformer multi-physical field coupling simulation model covering a circuit field, a magnetic field, a solid mechanical field and an acoustic field; obtaining noise response data under different structure parameters through simulation; verifying the reliability of a simulation result based on an experimental test; key structure parameters are selected, and a response surface model between the iron core structure parameters and modal response is constructed; and with noise reduction as a target, an optimal structure combination is obtained through optimization by using an optimization algorithm, so that the electromagnetic noise in the operation process of the transformer is suppressed. The method has the advantages of being high in modeling precision, high in analysis efficiency and capable of effectively optimizing the structure, and theoretical basis and support can be provided for design of the low-noise transformer.

The invention relates to a multi-physical-field deformation analysis method and system based on a COMSOL platform and a particle finite element. The method comprises the steps that a physical deformation analysis model is built, and an initial finite element grid is generated; solving the control equation by using a solver of the COMSOL platform to obtain a multi-physical-field state variable; carrying out particle space position updating on finite element grid nodes according to the multi-physical field state variables, and carrying out Delou inner triangulation and boundary identification based on an updated particle point set to obtain a free boundary; reconstructing the grid based on the free boundary, and mapping the state variable of the previous grid to the new finite element grid; according to the new finite element mesh, updating boundary conditions of the physical deformation analysis model, and iteratively updating the physical deformation analysis model in a COMSOL platform; and outputting a deformation analysis result based on the final physical deformation analysis model. According to the invention, stable and high-precision numerical analysis of large-deformation and multi-field coupling processes in energy geotechnical engineering is realized.

The invention relates to the technical field of geological exploration, and discloses an exploration method and device for intelligent fusion of multi-geophysical field data. The method comprises the steps of signal source excitation, data acquisition and synchronization, data recording and transmission, preprocessing, feature value extraction, AI model fusion processing, joint inversion, imaging and interpretation and the like. According to the invention, multi-physics field data is synchronously acquired, and a multi-source heterogeneous data intelligent preprocessing and feature extraction method and a multi-physics field data fusion and joint inversion method based on artificial intelligence are provided for data such as earthquake, electromagnetism and gravity in a unified signal analysis framework. Through the steps, the problems of data isomerism, space-time inconsistency, inversion multiplicity and the like in geophysical exploration are solved.

The invention relates to the technical field of nanometer motion tables, in particular to a nanometer motion table design method, device and equipment and a storage medium. In the method, a structure sample library is composed of structure samples of a nanometer motion table, and a simulation result covers characteristics such as microscale stress and displacement; the trained parameter prediction model can accurately support the micro-scale performance prediction and optimization of the nano motion platform; a simulation result set of the structure sample library comprises multi-physics field data, a training data set is constructed based on a global simulation result, a proxy model can learn global distribution and coupling relations of physics fields, and optimization hidden dangers caused by single-point simplification are avoided; a proxy model is constructed and trained into a parameter prediction model, traditional finite element analysis is replaced for rapid prediction, and the calculation cost and time consumption in the optimization process are remarkably reduced; the multi-objective optimization algorithm and the parameter prediction model are combined, the optimization scheme is automatically generated, multi-objective optimization can be carried out at the same time, multiple performance indexes can be considered, and the comprehensiveness of the design scheme is improved.

The invention relates to the technical field of vibration suppression, and discloses a multi-physics field cooperative control intelligent vibration suppression method and system, and the method comprises the following steps: S1, building a multi-physics field digital twinborn model based on a finite element analysis method, the multi-physical field at least comprises a coupling relationship among a pneumatic field, an electromagnetic field and a structural field, and the modeling of the fluid-structure interaction effect is included; and S2, based on the digital twin model, an improved particle swarm optimization algorithm is adopted to generate a control weight distribution scheme, and the control weight distribution scheme is used for dynamically adjusting the output proportion of a pneumatic actuator and an electromagnetic actuator. According to the method, the multi-physical field digital twinborn model containing the coupling relation of the pneumatic field, the electromagnetic field and the structural field and taking into account the fluid-solid coupling effect is established, so that the problem that the control precision is limited due to the fact that a single physical field control strategy is mostly adopted in a traditional vibration suppression method is solved.

The invention discloses a multi-physics field coupling numerical method for simulating wave-ocean current-earthquake-seabed interaction, and relates to the technical field of ocean engineering numerical simulation, and the method comprises the following steps: model construction, load application, coupling solution, and result analysis and application. According to the method, revolutionary simulation of collaborative response of a seabed and a structure in a complex marine environment and multi-physics field high-precision bidirectional coupling of random waves, steady-state ocean currents and seismic excitation are realized by constructing a total-factor coupled high-precision numerical model, the problems of incomplete coupling dimensions and excessive model simplification of a traditional method are solved, and the method has the advantages of being high in practicability and high in reliability. According to the wave-induced seabed liquefaction simulation method, the simulation result and the actual working condition coincidence degree are remarkably improved, the frequency domain transfer function method is introduced to analyze the seabed pore pressure response, the cognitive depth and the prediction precision of the wave-induced seabed liquefaction mechanism are remarkably improved, and in addition, through efficient algorithms such as GPU parallel calculation, self-adaptive grids and frequency domain-time domain mixed solution, the wave-induced seabed liquefaction simulation method has the advantages that the wave-induced seabed liquefaction simulation precision is improved. And the calculation efficiency is greatly improved while the precision is ensured.

The invention relates to the technical field of fluid mechanical fault diagnosis, and discloses an emulsion pump fault intelligent diagnosis method and system based on multi-dimensional entropy feature fusion, and the method comprises the steps: constructing a multi-dimensional physical field state monitoring space, and synchronously collecting vibration acceleration, outlet pressure and flow time sequence signals; the method comprises the following steps: performing adaptive variational mode decomposition and effective sensitive component screening reconstruction on a vibration signal, calculating a normalized vibration quantile permutation entropy through phase-space reconstruction and quantile mapping, extracting a pressure fluctuation entropy and a flow pulsation variance, fusing the pressure fluctuation entropy and the flow pulsation variance into a multidimensional fault feature vector, inputting the multidimensional fault feature vector into a multi-classification support vector machine, and outputting an operation state label; executing hierarchical closed-loop control; according to the method, through quantile mapping and multi-physics field fusion, the problems of entropy value feature distortion and liquid-machine coupling weak fault feature masking caused by non-Gaussian impact noise are effectively solved, and the fault diagnosis robustness and accuracy of the emulsion pump under complex working conditions are improved.

The invention discloses a polycrystalline material microstructure crack evolution simulation and mechanical property prediction method and system. The method comprises the following steps: establishing a voronoi geometric model of a polycrystalline material containing grain characteristics and microstructure defect characteristics; carrying out spatial distribution modeling on the mechanical property parameters of the polycrystalline material based on a probability statistics theory; importing the voronoi geometric model of the polycrystalline material into a multi-physics field simulation software platform, establishing a complete simulation geometric model for crack prediction based on a phase field fracture theory, and performing phase field solution; setting corresponding material parameters according to the material attributes; and setting corresponding boundary conditions in simulation software to simulate a four-point bending experiment, solving a phase field fracture control equation by utilizing a finite element algorithm, capturing a change rule of a crack propagation path, and recording key mechanical data. According to the method, the polycrystalline Voronoi model is constructed, spatial distribution modeling is carried out on the mechanical parameters of the material in combination with the probability statistics theory, and the non-uniform characteristic of the actual material can be reflected more truly.

The invention provides a dam multi-physical field dynamic simulation method and device based on data and mechanism fusion. According to the dam multi-physics field dynamic simulation method based on data and mechanism fusion, the dynamic simulation precision of the dam multi-physics field coupling effect and the long-term service performance can be improved, and the hidden disease recognition capability and the early warning reliability under the extreme working condition are enhanced.

The invention discloses a high-voltage submarine cable multi-parameter multi-physics field simulation calculation method, system, device, medium and program, and belongs to the technical field of cable detection. The method comprises the following steps: according to a submarine cable structure, establishing initial finite element models of soil direct burial, a seabed, a cable trench and a transition section; according to the initial finite element model, mesh generation is carried out on the submarine cable cross section, and a finite element simulation model after mesh generation is established; performing multi-physical field coupling calculation through the finite element simulation model after mesh generation to obtain the temperature of the submarine cable, and performing simulation calculation of the submarine cable core according to the temperature of the submarine cable; and comparing the cable core temperature of the submarine cable in the simulation calculation result with the temperature measured in an optical fiber temperature measuring device arranged in the submarine cable to obtain a simulation error and an actual error. According to the method, the distribution conditions of the temperature field, the magnetic field and the fluid velocity field around the cable and the temperature change condition of the laying transition section can be observed simultaneously, and the temperature of the submarine cable during change is obtained.