6747 results about "Electrical performance" 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 relates to the technical field of probe testing, and discloses a probe testing device and method, and the method comprises the steps: carrying out the synchronous collection of the electric signal response characteristics of a plurality of chip testing probes in a chip contact process, analyzing the signal transmission interference relation between the probes, and obtaining a multi-probe signal coupling feature pattern; identifying a target signal transmission channel to obtain a first test probe configuration scheme; performing test signal input and response acquisition on the chip to obtain electrical characteristic time-frequency data of the chip; and performing multi-probe collaborative analysis and feature extraction on the time-frequency data of the electrical characteristics of the chip to obtain abnormal indication information of the electrical performance of the chip, and adjusting test parameters and contact positions of a plurality of chip test probes to obtain a configuration scheme of a second test probe. Therefore, the test system can intelligently adjust the subsequent test strategy according to the preliminary test result, and the intelligence and automation of the test process are realized.

The embodiment of the invention relates to the photovoltaic field, and provides a back contact battery and a photovoltaic module, the back contact battery comprises first and second main grids which are alternately arranged along a first direction, the first main grid comprises a plurality of first parts which are arranged at intervals along a second direction, and the second main grid comprises a plurality of second parts which are arranged at intervals along the second direction; the first penetrating line extends along the first direction and is in contact connection with the plurality of first parts in the same row along the first direction; the second penetrating lines extend in the first direction and are in contact connection with the multiple second parts located in the same row in the first direction; the adjacent first and second through lines form a through line group, the number of the through line groups is reduced along with the increase of the number of the main grids, in the second direction, the width of at least one of the first and second through lines is reduced along with the increase of the number of the main grids, and the number of the main grids is the sum of the number of the first and second main grids, so that the electrical performance of the back contact battery is improved at least; and the preparation cost of the back contact battery is reduced.

The invention relates to the technical field of wire harness intelligent evaluation, in particular to a wire harness connection performance intelligent test method and system. The method comprises the following steps: collecting wire harness test data generated by a wire harness test device and a wire harness sensor in real time through an edge computing node; performing electrical performance detection extraction and mechanical performance detection extraction according to the wire harness test data to respectively obtain wire harness electrical performance detection data and wire harness mechanical performance detection data; performing electrical performance deep evaluation according to the wire harness electrical performance detection data to obtain wire harness electrical performance evaluation data, and performing mechanical performance deep evaluation on the wire harness mechanical performance detection data to obtain wire harness mechanical performance evaluation data; and performing environment pressure cross reference according to the wire harness electrical performance evaluation data and the wire harness mechanical performance evaluation data to obtain wire harness connection performance test evaluation data. According to the method, the accuracy of wire harness performance evaluation is improved, and reliable performance data can be obtained in different application fields.

The invention relates to the technical field of electrical engineering and sensors, and provides a high-precision current sensor electrical performance detection method, which comprises the steps of collecting an original output signal of a current sensor and performing multi-dimensional signal preprocessing; extracting multi-dimensional feature parameters from the preprocessed signals based on a dynamic feature extraction algorithm; establishing a dynamic compensation model according to the multi-dimensional characteristic parameters, and generating a compensation control signal; a compensation control signal is injected into the detected current sensor to form closed-loop feedback, and a compensated output signal is collected; calculating a sensor performance degradation parameter according to the signal difference before and after compensation; an electrical performance assessment report is generated based on the performance degradation parameter. According to the invention, the measurement precision and reliability of the sensor can be improved, the service life is prolonged, the maintenance cost is reduced, and a powerful guarantee is provided for safe and stable operation of a power system and electronic equipment.

The invention discloses an inertial microsystem thermal coupling analysis method based on a physical information neural network, and the method comprises the steps: S1, setting material parameters and boundary conditions of an inertial microsystem, and building a thermal coupling analysis model; s2, performing electrothermal coupling analysis to obtain temperature distribution of the inertial microsystem; s3, thermal stress distribution of the microsystem is obtained through thermal-mechanical coupling simulation analysis; s4, predicting a temperature field of the microsystem through the physical information neural network; s5, taking the temperature field as a boundary condition of mechanical simulation of the microsystem to obtain mechanical properties such as stress and strain of the microsystem; and S6, performing mechanical-electric coupling simulation analysis, and analyzing the influence of structural deformation on each parameter in electrical performance. According to the method, the neural network solving precision is improved through the improved adaptive weight strategy, the complete polynomial basis function is combined with the neural network, the state dimension is reduced by introducing the expansion basis function, the calculation cost and time are reduced, accurate prediction of the micro-system multi-moment temperature field is achieved, and the micro-system performance under electric heating power multi-physics field coupling is calculated.

The invention relates to the field of energy storage system management and battery performance evaluation, in particular to an energy storage system electrical performance evaluation method and system.The method comprises the steps that battery cluster data and environment data are collected in real time, the charging and discharging process of a battery is accurately simulated in combination with simulation data and a digital twin model, and the future running state of the battery is predicted. The reinforcement learning algorithm adaptively optimizes the charging and discharging strategy according to simulation data and feedback results, and adjusts the charging power, the discharging rate and the temperature control strategy in real time through model prediction control. The method effectively evaluates the charging and discharging efficiency, the internal resistance change, the temperature fluctuation and the remaining service life of the battery, and provides decision support for operation optimization and maintenance of the system. According to the invention, the energy storage system can significantly improve the charging and discharging efficiency, prolong the service life of the battery, and ensure the stable and efficient operation of the system under different load and environmental conditions.

The invention discloses a carbon-silicon negative electrode material and a preparation method and application thereof, and the preparation method comprises the following steps: S1, carrying out mixed reaction on a lithium source compound, a lanthanum source compound and a titanium source compound to obtain a mixed reactant; mixing the mixed reactant with a carbon source compound, and dispersing and emulsifying to obtain element-doped microspheres; s2, carbonizing the element-doped microspheres in the step S1 to obtain carbides, and activating the carbides to obtain a porous carbon material; and S3, performing silicon deposition on the porous carbon material in the S2 to obtain silicon deposition porous carbon, and performing carbon deposition on the silicon deposition porous carbon to obtain the carbon-silicon negative electrode material. The carbon-silicon negative electrode material disclosed by the invention is high in lithium ion transmission rate, the problem of poor electronic conductivity of silicon is solved, and the electrical property of a battery can be effectively improved.

The invention discloses a carbon-coated lithium iron phosphate active material and a preparation method thereof, a positive pole piece and a lithium battery, and relates to the technical field of lithium batteries. According to the method, the structure of the carbon coating layer of the carbon-coated lithium iron phosphate active material is comprehensively evaluated through the carbon coating factor beta, # imgabs0 can evaluate the amount of graphitized carbon on the unit surface area of the carbon-coated lithium iron phosphate active material, and compared with amorphous carbon, the graphitized carbon has more excellent conductivity and can better improve the conductivity of a lithium iron phosphate matrix. By regulating and controlling a carbon coating layer structure of the carbon-coated lithium iron phosphate active material, a carbon coating factor beta meets a specific value range, so that the uniform conductivity of the carbon-coated lithium iron phosphate active material is improved; the lithium ion battery prepared from the lithium ion battery positive electrode material is small in internal resistance growth rate, charge transfer impedance Rct sample standard deviation and Warburg coefficient sample standard deviation, and the overall electrical performance of the lithium ion battery is improved.

The invention relates to the technical field of cylindrical lithium ion battery production, and discloses a method for detecting insufficient welding of a cylindrical lithium ion battery, and the method comprises the following steps: S1, appearance inspection; s2, initial internal resistance benchmark test; s3, applying a short-time large-current pulse to the battery by using a pulse generator, simulating an actual load condition, and recording an instantaneous voltage drop and current response curve of the voltage of the battery end during the pulse period; s4, performing infrared thermal imaging identification and data processing; s5, learning the picture and establishing a model; s6, comparing the test picture and the data with the model; s7, dynamic internal resistance calculation; s8, cold solder joint query and sorting processing; and S9, retesting the electrical performance. According to the invention, the technologies of dynamic internal resistance measurement, nondestructive X-ray or ultrasonic detection, rate discharge test and the like are adopted, so that efficient, accurate and nondestructive detection of the cold solder joint of the cylindrical lithium ion battery is realized, and the production efficiency and the detection precision are remarkably improved.

The invention provides a method and system for preparing a high-temperature anti-aging test board for chip testing, and relates to the technical field of data energy storage and resource scheduling, and the method comprises the steps: designing a schematic circuit diagram and a PCB wiring scheme; a test plate is made of a high-temperature resistant material; bare board verification, electrical performance verification, program setting verification, high temperature verification and junction temperature measurement verification are carried out; using data is recorded, ultrasonic cleaning and drying are carried out, and a performance evaluation model is established through a hardware management system to judge whether maintenance or replacement is needed. According to the invention, the accuracy of chip testing in a high-temperature environment is improved, and the service life of the test board is prolonged.

The invention relates to the technical field of electrical performance testing, in particular to a water supply equipment electrical performance detection system based on artificial intelligence, which comprises an electrical parameter acquisition module, an energy efficiency analysis module, an insulation performance evaluation module and a comprehensive diagnosis module. According to the invention, a three-phase voltage and current root-mean-square value is dynamically calculated through a broadband current transformer and a sliding window integration method, a 50Hz fundamental component amplitude is extracted to separate power frequency and high frequency harmonic waves, a continuous period energy efficiency ratio standard deviation triggers an insulation detection threshold value, and a parameter fluctuation and insulation degradation response mechanism is established. Harmonic interference correction synchronous processing energy efficiency ratio and leakage current integration, the detection error being lower than 5%, temperature rise rate linear regression and bearing current threshold value cooperative determination, winding aging cross validation, fault misjudgment rate reduction to 26%, closed-loop detection fusion transient capture, dynamic threshold value triggering and multi-parameter diagnosis, early warning success rate reaching 92%, and positioning response being reduced to 3 seconds.

The invention provides a semiconductor device and a manufacturing method thereof, and the method comprises the steps: providing a substrate, forming a gate structure and a side wall on the substrate, and enabling the gate structure to comprise a gate dielectric layer, a dummy gate, a first hard mask layer, a second hard mask layer and an amorphous carbon layer; forming a first patterned photoresist layer covering the NMOS region; forming grooves in the substrate at two sides of the gate structure in the PMOS region, and reserving an amorphous carbon layer with a partial thickness on the second hard mask layer; the first patterned photoresist layer is removed; and removing the amorphous carbon layer by adopting an ashing process. In the process of forming the groove in the PMOS region, the amorphous carbon layer protects the second hard mask layer below the amorphous carbon layer from being thinned, and after the amorphous carbon layer is removed, the thickness of the second hard mask layer in the two regions can be ensured to be consistent, so that the height of the dummy gate is ensured to be consistent, and the electrical performance of the device is improved.

The invention provides a circuit board electrical performance test and diagnosis method, which comprises the following steps of: constructing a structured process-electrical data set by collecting process parameters such as etching time, pressing temperature, drilling precision, copper foil thickness and the like and electrical test indexes such as impedance deviation, leakage current, signal attenuation and the like; screening key process variables by adopting mutual information analysis and a maximum correlation-minimum redundancy criterion; through modeling of a three-layer causal diagram and a structural equation, quantitative influence evaluation of process parameters on electrical performance and fault types is realized; when a fault is detected, the system can automatically perform reverse reasoning, identify a main manufacturing deviation item and generate attribution diagnosis and process optimization suggestions, so that the accuracy of fault diagnosis and the pertinence of process adjustment are improved, and the fault occurrence rate is reduced and the product quality is improved.

The invention relates to the technical field of electrical performance testing, and particularly discloses a method and system for evaluating the electric shock life of an arc extinguish chamber of a low-voltage circuit breaker, and the method comprises the steps: S1, collecting real-time arc extinguish performance index parameters in the arc extinguish chamber of different low-voltage strength grades in a preset time period and the cumulative number of closing operations of the circuit breaker of different low-voltage strength grades; s2, simulating an arcing process change image of each closing operation of the circuit breaker based on real-time arc extinguishing performance index parameters in the arc extinguishing chamber with different low-voltage strength grades, establishing an arc extinguishing three-dimensional model, and performing feature extraction analysis on the arcing process change image to obtain a standard arc state coefficient; s3, inputting the real-time arc extinguishing performance index parameter and the standard arc state coefficient into a preset analysis model for prediction analysis, and obtaining an arc extinguishing prediction value; and S4, inputting the predicted arc extinguishing value, the cumulative number of closing operations and a historical evaluation factor into the predicted analysis model for training to construct an arc extinguish chamber electric shock life evaluation model.

The invention discloses a power line carrier communication fault detection system, and relates to the technical field of power line fault detection, the fault detection system comprises a data acquisition module, an abnormity analysis module, a fault diagnosis positioning module, a fault grading evaluation module, a response measure matching module and an alarm module, and the modules are in electric signal connection. According to the invention, the signal change on the power line is rapidly captured by monitoring the modulation signal after carrier demodulation on the power line, including the sending performance index and the electrical performance index, and the performance trend of the power system can be timely evaluated and the abnormal modulation signal can be timely detected by calculating the sending performance trend index and the electrical performance trend index. Key information is provided for fault positioning and grading, the accuracy and response speed of fault detection are greatly improved, the influence of faults on a power system is reduced, and the reliability of power supply is improved.

The invention relates to a CLCC converter full-transparent carrier construction method, which comprises the steps of mapping parameters of a CLCC converter, and constructing a full-transparent information base; based on a full-transparent information base of the CLCC converter, full-transparent information is mapped into a relational CLCC converter full-transparent information carrier from two aspects of the type and related attributes of the equipment and the relation between a three-dimensional model of the equipment and an equipment body; establishing an information calling mode based on a recognizable language based on a full-transparent information carrier of the relational CLCC; and performing data model maintenance on the full-transparent information carrier in two modes of data maintenance and topology maintenance, and executing the full-transparent information carrier of the CLCC by updating an information calling mode. Compared with the prior art, full-transparent management of the converter in the aspects of form, mechanical structure, electrical performance, control strategy, environmental adaptability, temperature management and the like is realized.

Disclosed in the present invention is a physics-informed neural network-based thermo-mechanical coupling analysis method for an inertial microsystem, the method comprising: S1, configuring material parameters and boundary conditions of an inertial microsystem, and establishing a thermo-mechanical coupling analysis model; S2, performing electro-thermal coupling analysis to obtain a temperature distribution of the inertial microsystem; S3, performing thermo-mechanical coupling simulation analysis to obtain a thermal stress distribution of the microsystem; S4, predicting temperature fields of the microsystem by means of a physics-informed neural network; S5, using the temperature fields as boundary conditions for mechanical simulation of the microsystem, obtaining mechanical properties such as stress and strain of the microsystem; and S6, performing electromechanical coupling simulation analysis to analyze the impact of structural deformation on various parameters of electrical performance. The present invention improves the solution accuracy of the neural network by means of an improved adaptive weighting strategy, combines a complete polynomial basis function with the neural network, and introduces an expanded basis function to reduce the state dimensionality, thus reducing computational costs and time, achieving accurate prediction of temperature fields of microsystems at multiple moments, and allowing for computation of the performance of microsystems under electro-thermal-mechanical multi-physics coupling.

The invention relates to the technical field of power equipment state monitoring, and particularly discloses a power cable electrical performance detection method and system, and the method comprises the steps: synchronously collecting a broadband electromagnetic signal, a mechanical vibration signal and a temperature signal at a cable monitoring point; calculating a wavelet coherence coefficient between the signals through continuous wavelet transform, and constructing a multi-modal coupling tensor fusing amplitude and cross-modal time-frequency correlation characteristics; performing time slicing and high-order singular value decomposition on the tensor to obtain a time-varying core tensor sequence, mapping the time-varying core tensor sequence into a high-dimensional manifold curve, and generating a system state fingerprint by calculating local curvature distribution and topology invariants of the curve; inputting the fingerprints into a pre-trained defect prediction model, and directly outputting defect inoculation probability and evolution stage judgment; according to the method, the limitation that early weak defect detection is not sensitive in a traditional method is broken through, and early warning and accurate diagnosis of cable insulation latent defects are achieved.

The invention relates to the technical field of electrical fault detection, in particular to a mobile power supply fault detection method and system based on intelligent diagnosis, and the method comprises the following steps: collecting voltage and current data of a mobile power supply in a normal operation state, and generating an electrical performance baseline data set through recording the timestamp of the data and a corresponding electrical performance index; and based on the electrical performance baseline data set, extracting time sequence features of voltage and current to obtain electrical performance feature data. According to the invention, based on voltage and current data acquisition in a normal state of the mobile power supply, a baseline data set covering timestamps and electrical performance indexes is established, and detail information of electrical performance changes is captured by extracting time sequence features such as peak values, mean values and standard deviations; meanwhile, frequency spectrum features are accurately extracted by means of fast Fourier transform, the intensity and phase information of frequency components is mastered, then signals are decomposed through wavelet transform, and richer electrical performance anomaly information under multiple scales is obtained.

The invention belongs to the field of electrical performance test equipment, and particularly discloses insulation performance test equipment for a power distribution cabinet. Comprising a cabinet body; the double-head hydraulic cylinder is arranged in the cabinet body, and the double-head hydraulic cylinder is provided with an electric sliding rail; the electric sliding block is connected to an electric sliding rail of the double-end hydraulic cylinder in a sliding mode, an elastic telescopic rod is rotationally connected to the electric sliding block, and the telescopic end of the elastic telescopic rod is rotationally connected with a connecting frame; the circular plate is rotationally connected to the connecting frame, the connecting frame is rotationally connected with a rotating shell, sliding cylinders which are uniformly distributed in the circumferential direction are arranged on the rotating shell, and probes are slidably connected into the sliding cylinders. Through rotation of the double-head hydraulic cylinder and swinging of the elastic telescopic rod, in cooperation with stretching operation of the probe, the welding seam detection range is expanded, the integrity of welding seam detection of the power distribution cabinet is improved, meanwhile, the device can accurately and continuously detect a plurality of welding seams through the elastic telescopic rod, and the working continuity of the device is improved.

The invention discloses an intelligent control system and method for production and processing of a photovoltaic panel, and relates to the technical field of intelligent control. During operation of the system, key data involved in the production process of the photovoltaic panel is collected, a light-transmitting effect data set, a durability data set and an electrical performance data set are generated and preprocessed, and a multivariate data analysis algorithm is applied to obtain a data set; and after calculation, obtaining a quality index Zlzs of the agricultural photovoltaic panel, receiving an analysis result of the data processing module, and performing real-time quality monitoring on the photovoltaic panel subjected to production process optimization by adjusting a material ratio, production environment parameters and a process flow. A quality index Zlzs of an agricultural photovoltaic panel is compared with a preset first quality qualification threshold value M and a preset second quality qualification threshold value N, potential quality problems in production are identified, a quality evaluation strategy scheme is obtained, an evaluation result is fed back to a production process optimization module and a data processing module, and a closed-loop control system is formed. And continuous optimization and quality improvement are realized.

The invention relates to the field of microelectronic manufacturing, and discloses a high-performance monocrystalline silicon nano wafer manufacturing process which comprises the following steps: preparing a monocrystalline silicon wafer, and obtaining a high-quality monocrystalline silicon wafer through fine cutting, chemical mechanical polishing and surface residual stress elimination treatment; multi-stage cleaning and surface treatment are carried out, and surface pollutants are removed through combination of molecular chromatography, electric field assisted ultrasonic cleaning and low-temperature plasma cleaning; and manufacturing a nano structure, and forming a complex nano structure by adopting multi-stage electron beam lithography, segmented reactive ion etching and self-adaptive deep etching regulation and control. The surface quality, the mechanical strength and the electrical property of the wafer are remarkably improved through the technologies of refined monocrystalline silicon wafer preparation, multi-stage cleaning, advanced nanostructure manufacturing, self-adaptive heat treatment and the like; and through surface functionalization and multi-layer high-precision packaging, the environmental tolerance and long-term reliability of the nanostructure are enhanced.

The invention relates to the technical field of chip detection, and discloses a chip detection system and a chip detection method. The multi-modal data acquisition module is used for acquiring optical visual data, thermal performance data and electrical performance data of the chip; the fusion feature modeling module is used for carrying out preprocessing, feature extraction and feature fusion modeling on the multi-modal data; the intelligent detection module is used for carrying out defect detection and positioning on the fusion features; the anomaly classification and marking module is used for carrying out anomaly classification and marking based on a defect detection result; and a feedback optimization dynamic adjustment module. A fusion feature modeling module is adopted, a deep learning network is utilized to perform feature extraction on optical, thermal and electrical performance data, feature weight optimization is realized through a cross-modal attention mechanism, a multi-modal feature fusion technology remarkably enhances the expression ability of a system to a complex defect mode, the detection precision and reliability are improved, and the detection precision and reliability are improved. And particularly, the problems of micro cracks, poor heat dissipation, unstable signals and the like can be identified.

The invention discloses a manufacturing method of a two-dimensional semiconductor field effect transistor based on a high-k gate dielectric integration technology capable of eliminating a buffer layer. The manufacturing method comprises the following steps: depositing a back gate electrode and a back gate dielectric on a substrate in sequence; transferring the channel layer to the back gate medium; sequentially forming a buffer layer, a source electrode, a drain electrode, a top gate dielectric layer formed by a high-k dielectric material and a top gate electrode on the channel layer; and annealing treatment is carried out in a vacuum environment, and the buffer layer sublimates, so that Van der Waals interfaces are formed between the channel layer and the top gate dielectric layer and between the channel layer and the source electrode as well as between the channel layer and the drain electrode. According to the high-k gate dielectric integration technology based on the erasable buffer layer, the erasable buffer layer after vacuum annealing is utilized, damage to a two-dimensional material is avoided, a high-quality high-k gate dielectric is deposited, interface regulation and control between a channel layer and a top gate dielectric are achieved, and the equivalent oxide thickness is reduced; and good contact between the channel layer and source and drain metal is realized, the contact resistance of the transistor is reduced, and the electrical performance of the transistor is improved.

The invention discloses an electronic communication cable detection device in the technical field of cable detection, and the device comprises a workbench, an insulation tester and a dielectric loss tester, the workbench is provided with a darkroom, the axial side wall of the darkroom is symmetrically provided with ports, the ports are internally and fixedly connected with window shades, and the interior of the darkroom is fixedly connected with a defect detection assembly. A roller assembly is fixedly connected to the outer side wall of the darkroom, multi-stage clamping assemblies located on the two sides of the darkroom are symmetrically and fixedly connected to the top of the workbench, a controller is fixedly connected to the workbench, and the flaw detection assembly, the roller assembly, the multi-stage clamping assemblies, the insulation tester and the dielectric loss tester are all in signal connection with the controller. According to the invention, through multi-stage screw-in self-adaption to cables with different diameter specifications, the clamping stability is ensured, and the pressure sensor cooperates with the electrical performance detection instrument and the camera to integrate various detections, so that the detection cost is reduced, the detection accuracy is improved, and the cable to be detected is prevented from being damaged in the detection process.

The invention relates to the technical field of electronic information, and discloses a high-reliability storage chip packaging test method and system.The method comprises the steps that firstly, a to-be-tested storage chip and original parameter information of the to-be-tested storage chip are obtained, packaging structure data are collected to construct a three-dimensional model, chip feature data are extracted, then the chip feature data are compared with standard reference data, and potential defect information is mined; suspicious packaging parts are screened, the sensitivity of the suspicious packaging parts to environmental parameters is monitored, then fault risk types are evaluated, weak links are positioned, performance is detected, specific problem points are found out, then a test planning target is formulated, test means and standards are clarified, a test operation instruction is generated, finally, packaging testing is executed, electrical performance data are collected, and stability is verified. And generating a packaging test report. The stability of the memory chip can be improved.

The invention relates to the technical field of electrical performance detection, in particular to a household appliance wire harness electrical performance detection method and system. The method comprises the following steps: acquiring initial current and voltage data of a wire harness by using a sensor to obtain original electrical parameter matrix data; performing resistance modeling according to the original electrical parameter matrix data to obtain a resistance dynamic model; performing resistance characteristic analysis according to the resistance dynamic model to obtain resistance characteristic analysis data; and according to the resistance characteristic analysis data, carrying out resistance compliance determination to obtain compliance matrix data so as to carry out household appliance wire harness electrical performance detection auxiliary operation. The electrical performance of the household appliance wire harness is comprehensively detected and accurately evaluated, high technical innovation and practical application value are shown, and the crossing from simple static detection to intelligent dynamic analysis is achieved.

The invention relates to the technical field of model prediction, in particular to a power battery thermal management simulation method and system based on a neural network. The method comprises the following steps: acquiring electrical performance parameters, thermal performance parameters and mechanical performance parameters corresponding to the power battery through coupling experiment measurement, and performing three-dimensional coupling simulation construction to generate a three-dimensional physical field coupling model of the power battery; battery thermal characteristic evaluation is carried out from four dimensions of a micro material corresponding to the power battery, a battery monomer, a battery module and a thermal management system through the power battery three-dimensional physical field coupling model, and a power battery thermal characteristic data set is obtained; and constructing a multi-scale deep neural network architecture based on a neural network in combination with the thermal characteristic data set of the power battery to perform thermal management prediction training and thermal management constraint optimization control, and generating an optimal thermal management control strategy of the power battery to execute corresponding thermal management control work. According to the invention, efficient simulation and intelligent prediction optimization of thermal management of the power battery can be realized.

The invention discloses an electric reactor load adjusting method and system based on electrical performance optimization, and relates to the technical field of power equipment control and optimization, and the method comprises the steps: carrying out the real-time monitoring of an electric reactor, and obtaining the monitoring data and load data; and obtaining an evaluation result through the three electrical performance evaluation channels, and judging whether an electrical performance evaluation constraint is met or not. If not, generating a first optimization strategy according to the load data and the evaluation constraint; and if yes, trend prediction is carried out based on the load data, and a second optimization strategy is generated in combination with the evaluation constraint. And finally, carrying out adaptive load adjustment on the reactor according to the first optimization strategy and the second optimization strategy. The technical problems that in the prior art, due to the fact that adjustment of an electric reactor cannot adapt to complex load changes, the adjustment precision of the electric reactor is low, and the electrical performance is poor are solved, and the technical effects of improving the adjustment precision of the electric reactor and optimizing the electrical performance are achieved.