52 results about "Sensitivity distribution" patented technology

The invention relates to the technical field of electrical digital data processing, and discloses a train ice melting simulation optimization method of an electromagnetic thermal coupling model fused with a deep learning method, which comprises the following steps of: inputting a geometric representation tensor and a physical working condition parameter vector containing an electromagnetic excitation frequency and a reference environment temperature into a feature mapping neural network; outputting a dual-channel space source item tensor containing basic heat source power density and a heat source to temperature change sensitivity distribution matrix through nonlinear convolution operation; constructing a heat conduction discrete numerical value evolution operator configured with an active item linear correction interface; time stepping operation is executed according to the heat conduction time scale, a basic heat source is corrected in real time through the Hadamard product of a sensitivity distribution matrix and temperature deviation, and an operator is substituted for solution. On the premise that electromagnetic-thermal nonlinear coupling characteristics are reserved, decoupling of the time scale is achieved, and the calculation efficiency in high-frequency physical field simulation is effectively improved.

The invention discloses a pulse electroplating detection method, a pulse electroplating device and equipment, and the method comprises the steps: synchronously collecting transient current density data of a three-pole assembly in a pulse switching time window, and calculating a time derivative of a current density ratio to obtain electrochemical stress gradient data; performing space-time correlation analysis on the stress gradient data of the continuous pulse period, and tracking a spatial propagation trajectory of stress anomaly; a key monitoring area is determined according to the propagation trajectory, and ion migration impedance sensitivity distribution is detected through micro-amplitude current modulation; performing multi-dimensional coupling analysis on the stress gradient, the propagation trajectory and the impedance sensitivity data, and identifying time sequence correlation characteristics of stress evolution and ion anomaly; and performing quantitative evaluation and grade division on the electrochemical state of the avoidance area based on the coupling correlation characteristics. According to the scheme, early recognition and predictive evaluation of the ion migration abnormity of the boundary layer of the avoidance area can be realized in the pulse electroplating process, and the electroplating quality control precision and the process stability are remarkably improved.

The invention provides a light source control method and system based on data analysis, and the method comprises the steps: carrying out the multi-channel spectral characteristic collection of an LED light source through a spectrum analyzer array and an optical fiber probe, obtaining a spectral response curve and an interference image, carrying out the multi-scale analysis processing, and generating a multi-dimensional data tensor; performing interference mode and defect signal decoupling analysis on the multi-dimensional data tensor to obtain an interference mode feature and an interference-defect discrimination result; performing spatial distribution analysis on the interference sensitivity of the wafer surface by adopting preset kernel density estimation and a graph neural network according to the interference mode characteristics and the interference-defect judgment result, and generating an interference sensitivity distribution matrix; according to the interference sensitivity distribution matrix, the current waveform and light beam phase distribution of the LED light source are accurately modulated, intelligent control over the LED light source is achieved, the influence of multi-mode interference on semiconductor detection is effectively eliminated, and the accuracy of nanoscale defect detection is improved.

The invention belongs to the technical field of wireless charging, and particularly discloses a method based on a magnetic resonance type wireless charging system, which comprises the following steps of: arranging a high-temperature-resistant micro temperature sensor and an array around a magnetic resonance coil curved surface to collect real-time temperature difference data, and integrating environmental noise signals as an initial multi-dimensional parameter set to obtain a preliminary temperature difference data set; according to the preliminary temperature difference data set, applying a support vector machine classification method to separate difference signals between curved surface regions, fusing preset coordinate points in a curved surface geometric parameter correlation model, and determining region sensitivity distribution characteristics; and by adopting a Kalman filtering algorithm, carrying out time sequence smoothing processing on the regional sensitivity distribution characteristics to calibrate offset caused by inaccurate matching of temperature difference data and curved surface geometry, and then obtaining calibrated sensitivity distribution. The invention aims to solve the problem that the influence of temperature distribution difference on frequency matching cannot be accurately identified and adapted under the dynamic temperature change of a complex curved surface coil in the prior art.

The invention relates to the technical field of nondestructive testing, and discloses a multi-modal signal fusion detection method and system for an electromagnetic ultrasonic transducer, and the method comprises the steps: exciting and receiving ultrasonic signals of a plurality of propagation modes in a detected medium based on the electromagnetic ultrasonic transducer, obtaining multi-modal original data containing different physical characteristics, time synchronization and preprocessing are carried out; feature parameters of the internal state of the medium are extracted, normalization is carried out according to physical attributes, and a unified multi-modal feature space is constructed; setting a dynamic weight strategy based on the sensitivity distribution of the characteristic parameters and the structure parameters, and executing information fusion to form a multi-modal characteristic vector; carrying out comprehensive interpretation analysis to generate a detection conclusion containing abnormal region coordinate data and spatial boundary data; and outputting the corresponding visual representation information. According to the method, signals of different propagation modes are cooperatively utilized, and the defect identification capability and the space positioning precision in a complex structure are improved.

The present invention discloses a quantitative evaluation method of in vivo molecular probes based on xenon / phosphorus multi-nuclear magnetic resonance, which obtains the corresponding curve between the pH value of the molecular probe saturated solution and the molecular probe saturation concentration and 129 Sensitivity distribution diagram of the Xe transceiver integrated coil; obtain the hydrogen proton magnetic resonance structure image of the test area of ​​the test object; obtain the 3D 31 P chemical shift imaging data, to obtain molecular probe 129 Xe magnetic resonance signal distribution image; obtain pH value distribution image of the detection object to be tested area; obtain molecular probe concentration distribution image in the detection object to be tested area; calculate the molecular probe position coordinates of the detection object to be tested area and the molecular probe concentration distribution image; calculate the molecular probe position coordinates of the detection object to be tested area and the molecular probe concentration distribution image; calculate the molecular probe position coordinates of the detection object to be tested area and the molecular probe concentration distribution image; calculate the molecular probe concentration distribution image ... 129 The present invention can realize the concentration of molecular probes and the molecular probes that are difficult to detect in vivo without damage. 129 Quantitative measurement of parameters such as Xe apparent binding rate.

The embodiment of the application discloses a method for determining the sensitivity distribution of a magnetic resonance receiving coil. The method comprises the following steps: obtaining a reference image, contrast information between at least two kinds of tissues corresponding to a target part in the reference image is suppressed; determining an initial radio frequency field map corresponding to the target part based on the reference image; obtaining a transmission field map of a transmission field where the target part is located, and determining the sensitivity distribution of the magnetic resonance receiving coil corresponding to the target part based on the initial radio frequency field map and the transmission field map. According to the sensitivity distribution of the magnetic resonance receiving coil and the transmission field map of the transmission field, the uniformity correction of a magnetic resonance image under high field strength can be realized.

The application discloses a kind of facet angle parameter automatic calculation and process parameter mapping method and system, it is related to digital parameter processing technical field;Method includes: the angle difference of each facet junction of lens is acquired in advance;For each facet junction, in the minimum transition bandwidth reference data acquired in advance, according to the corresponding angle difference, form transition bandwidth lower limit list;Based on the optical sensitivity distribution data acquired in advance, form transition bandwidth upper limit list;Based on transition bandwidth lower limit list and transition bandwidth upper limit list, conflict determination and solution are carried out, and form final transition bandwidth list;Based on facet angle matrix and final transition bandwidth list, transition band geometry is generated for each facet junction, and new lens surface model is obtained;The application can consider the dual needs of facet angle keeping and step elimination, so that transition bandwidth adapts to the optical and processing requirements of different regions.

The application discloses a large-aperture array antenna subarray structure adjustment method facing electrical performance, and comprises the following steps: S1, determining maximum gain loss; S2, establishing sensitivity distribution matrix; S3, calculating position tolerance distribution weight; S4, giving initial installation tolerance standard; S5, calculating position tolerance distribution matrix; S6, generating position error random sample; S7, calculating antenna electrical performance; S8, judging whether the position error random sample meets the requirement; S9, calculating new position tolerance standard; and S10, calculating maximum allowed structure adjustment amount. The application can realize the target of taking antenna electrical performance as the target, quantitatively giving the subarray structure adjustment amount of different regions of a large-aperture array antenna, strictly requiring the structure precision of the subarray in the region with high electrical performance sensitivity, appropriately reducing the structure precision requirement in the region with low electrical performance sensitivity, reducing the processing and manufacturing difficulty of the large-aperture array surface, improving the adjustment efficiency of the large-aperture array antenna, and guaranteeing the high performance of the array antenna.

The application relates to the technical field of path planning, in particular to a path planning method and system for a patrol robot, and the application proposes the following scheme: an initial electronic map is used to perform a patrol task, first image data and pose information are collected, a patrol target is identified and image registration is completed, and second image data is generated; based on the structure sensitivity distribution of local visual features and the illumination change trend, an optimal observation direction is inverted and calibrated, a shooting position and an angle are determined to form a path node; a multi-objective optimization model is used to comprehensively consider path length, visual angle continuity and illumination interference, and an optimal patrol path is generated; and the application is suitable for outdoor patrol scenes with complex structures and uneven target distribution.

The application relates to a coplanar capacitive sensor and an optimization method thereof, and belongs to the technical field of capacitive sensing, and solves the technical problem of poor imaging effect of a single-pair-electrode coplanar capacitive sensor in the prior art. The optimization method of the coplanar capacitive sensor comprises the following steps: changing the shape of adjacent edges of two electrodes, increasing the spacing of a part of positions of the adjacent edges of the two electrodes, and keeping the spacing of another part of positions of the adjacent edges of the two electrodes unchanged, so that an optimized coplanar capacitive sensor is obtained. In the application, by changing the shape of the adjacent edges of the two electrodes, the sensitivity distribution and the detection performance indexes such as the detection depth of the coplanar capacitive sensor are optimized, so that the imaging effect of the coplanar capacitive sensor is improved.

The image processing apparatus includes: an acquisition unit that acquires K-space data obtained by undersampling using a plurality of coils, the K-space data corresponding to each of a plurality of frames; a classification unit that classifies the auto-calibration signal data in the K-space data corresponding to each of the plurality of frames into a plurality of groups; and a sensitivity profile calculation unit that generates a sensitivity profile corresponding to each of the plurality of coils on the basis of data based on the auto-calibration signal data classified into the first group among the plurality of groups and data based on the auto-calibration signal data classified into the second group among the plurality of groups.

fog detection device (1), comprising a first optical transmitter (S1) that emits first light with a first spatial intensity distribution (I1) and a first direction of emission in the direction and around a first optical axis (1) generating a first beam of light (11); a second optical transmitter (S2) which, at a time offset from the first optical transmitter (S1), emits second light with a second spatial intensity distribution (I2) and a first emission direction in the direction of and around a second optical axis (2) which is not parallel to the first optical axis (1), generating a second beam of light (12); an optical receiver (E) which is oriented with its receiving direction in the direction of and around a third optical axis (3) which is not parallel to the first optical axis (1) and / or not parallel to the second optical axis (2), to receive reflected first light with a first spatial sensitivity distribution (E1) and reflected second light with a second spatial sensitivity distribution (E2) and to output a first output signal corresponding to the intensity of the received, reflected first light and a second output signal corresponding to the intensity of the received, reflected second light; an evaluation unit (8) configured to form a quotient of the first and second output signals and to assign a fog state to the quotient only if the quotient does not differ by more than a predetermined amount from a predetermined fog threshold value, which was determined or specified as the quotient of a first fog intensity and a second fog intensity prior to the calculation, wherein the first fog intensity corresponds to the first output signal obtained when the first light penetrates a substantially spatially uniform fog distribution and the second fog intensity corresponds to the second output signal obtained when the second light penetrates a substantially spatially uniform fog distribution.

The present application is applicable to the field of image processing technology, and provides a method, device, electronic device, and readable storage medium for displaying skin sensitivity. The method includes: obtaining an original image containing a photographed object, and extracting a skin area image of the photographed object from the original image; determining the skin sensitivity corresponding to each pixel point in the skin area image; adjusting the pixel value of each pixel point in the skin area image in the original image according to the skin sensitivity, using the original image after adjusting the pixel value as a sensitivity distribution diagram, and displaying the sensitivity distribution diagram. The technical solution provided by the present application is generated based on the original image by adjusting the pixel value of the pixel point. Therefore, the outline of the skin area is consistent with the original image. By viewing the sensitivity distribution diagram, the sensitivity corresponding to each local area can be determined, thereby improving the display effect.

This invention discloses a method for identifying coal and coal gangue based on capacitance tomography. It utilizes a differential capacitance tomography electrode sensor to collect capacitance measurement data of coal, coal gangue, or mixtures thereof within the measured area. Direct coupling capacitance between electrodes is canceled by applying an inverse excitation signal. The raw data is preprocessed, and stable and valid capacitance measurements are selected to form a data vector. A regularized iterative algorithm is used to solve for the dielectric constant distribution, combining a preset sensitivity distribution function. An initial solution is obtained through regularization, and then iteratively updated until convergence. Image reconstruction is performed based on the dielectric constant distribution. After normalization and edge detection, a capacitance tomography image representing the location, size, and dielectric differences of the materials is generated. The image grayscale values ​​are analyzed, and coal and coal gangue regions are automatically identified and marked according to a preset dielectric constant threshold range. Simultaneously, their centroid coordinates and equivalent areas are calculated, achieving non-destructive and accurate identification of the mixture components.

The invention provides a magnetic material surface temperature gradient generation method based on laser regulation and control, and relates to the field of data processing. According to the method, optical absorption, electron energy relaxation, phonon thermal conductivity and magnetic anisotropy parameters of a magnetic material are obtained, modeling is carried out in a three-dimensional space according to a silicon-based substrate, a cobalt layer and a platinum layer, and a cross-scale photo-thermal-magnetic full-coupling model is constructed. The method comprises the following steps: generating a laser coding tensor through light intensity, wavelength and phase parameters of a laser space modulation array, driving a model to solve in a simulation environment, generating temperature gradient evolution data and an implicit field quantity, and constructing a temperature gradient control database. After target temperature gradient distribution is set, a depth prediction model is used for outputting a temperature gradient evolution sequence, sensitivity distribution is calculated through the model, the optimal laser coding tensor is determined, finally verification and application to a laser array are carried out, and temperature distribution consistent with the target temperature gradient is achieved. By implementing the technical scheme, the temperature gradient on the surface of the magnetic material is convenient to generate.

The invention relates to a space sensitivity function estimation method for realizing rapid dimension expansion based on a Gaussian-inverse power function, which comprises the following steps of: 1, constructing a key primary function: carrying out weighted fusion on one or more inverse power functions and a Gaussian function to serve as the key primary function; 2, estimating a two-dimensional plane sensitivity function: performing estimation by using a key primary function to obtain the two-dimensional sensitivity function of the area; 3, estimating a three-dimensional space sensitivity function: constructing a sensitivity function of an air target according to the two-dimensional sensitivity function of the area, and obtaining target sensitivity distribution of the air target; and superposing the two-dimensional sensitivity distribution of the area and the target sensitivity distribution to construct a total sensitivity function of any point in the task scene. The method is suitable for a two-dimensional plane and a three-dimensional space, and sensitivity estimation can be rapidly, effectively and reasonably carried out.

The invention discloses a dual-mode tracking sensitivity test method for a global satellite navigation system of a whole vehicle. The method comprises the following steps: constructing a test environment; performing three-dimensional radiation pattern scanning, and improving data reliability through median filtering and continuous stability criterion; intelligently screening key test angles based on a directional diagram; a radiation tracking sensitivity test is carried out at a key angle; and finally synthesizing full-angle sensitivity distribution. Synchronous testing and mutual interference quantification of L1 and L5 dual-band signals are achieved, the testing efficiency and the data accuracy are remarkably improved, and the method is suitable for whole vehicle GNSS performance verification, OTA testing and antenna design optimization.

The application provides a high-pressure-resistant and low-temperature-resistant three-dimensional capacitive array sensor, comprising: an external structure, a polytetrafluoroethylene tube, an auxiliary dielectric, a capacitive array sensor and a signal lead; the external structure is fixedly connected with the capacitive array sensor, and the auxiliary dielectric and the signal lead are connected between the external structure and the capacitive array sensor; the polytetrafluoroethylene tube is located in the external structure and is fixedly connected with the external structure and the capacitive array sensor through the auxiliary dielectric. The pressure resistance of the sensor provided by the application can reach 4 MPa, and the temperature resistance can reach-190 DEG C. By extending the axial length of the two end electrodes and shortening the axial length of the middle layer electrode, the three-dimensional multilayer electrode array sensor is optimized, the conformal transformation principle is used to guide and select the axial length proportion of different layer electrodes, the sensitivity distribution of the center region of the to-be-measured sensitive field is more uniform, and then the axial image reconstruction accuracy and resolution of the center region are improved.

The application discloses a kind of composite material resin matrix interface ultrasonic cross-scale detection method and device, comprising: in response to micro modeling instruction, the microstructure of fiber reinforced resin matrix composite is determined representative volume element model, the equivalent stiffness of fiber and resin interface region in model is determined and introduced interface damage variable, based on the micro simulation result of ultrasonic incident signal of multiple frequency bands applied to model, frequency and interface damage sensitivity distribution are determined, based on sensitivity distribution, determine sensitive frequency band and generate multiple frequency combination;In response to multi-frequency detection instruction, based on multiple frequency combination, macro multi-frequency ultrasonic detection is carried out on the surface of the composite material structure to be detected, to determine the echo signal of each frequency band;In response to echo signal collection completion instruction, based on echo signal, determine multi-frequency ultrasonic characteristics, input interface equivalent stiffness and multi-frequency response mapping model into multi-frequency ultrasonic characteristics, determine the interface damage variable distribution of each detection area based on inversion algorithm, generate the spatial distribution and damage grade of resin matrix interface damage.

Optoelectronic device (1), comprising - an optoelectronic component (21) intended to receive or generate radiation, - a frame (4) having a cavity (51) in which the optoelectronic component is arranged, - a connection carrier (3) to which the optoelectronic component is attached, and - a cover (45) which covers the cavity and which forms a radiation passage surface (10) for the radiation, wherein - a beam path from the optoelectronic component to the radiation passage surface is free of a encapsulation material for the optoelectronic component, - the connection carrier is designed as a printed circuit board, and a through-hole through the connection carrier is designed as an opening (33) for air exchange between the cavity and the environment, - the device is designed as an ambient light sensor and the cover (45) determines a short-wave flank of a sensitivity distribution of the ambient light sensor, and - the device has a further filter (27) which determines the long-wave flank of the spectral sensitivity distribution of the ambient light sensor, so that the spectral sensitivity distribution of the ambient light sensor simulates the sensitivity distribution of the human eye.

The present application relates to the technical field of power system stability control, and discloses a method for adaptive suppression of subsynchronous oscillation of grid-constructed energy storage system. The method comprises the following steps: identifying an energy storage cluster based on power grid topology data; monitoring the frequency in the cluster and extracting electrical parameters such as impedance spectrum and power waveform to generate a cluster oscillation characteristic vector; constructing a global oscillation sensitivity distribution map based on the characteristic vector, and then guiding a movable oscillation suppression robot to a key position to perform damping operation. In the suppression process, the distribution map is updated in real time according to system feedback, and the robot action strategy is dynamically adjusted. The method changes the fixed damping into a movable suppression resource in space, and improves the decision basis from local static information to global dynamic situation map, realizes adaptive tracking and accurate damping of subsynchronous oscillation hotspots, and improves the flexibility and reliability of oscillation suppression in complex power grid environment.

An apparatus and method for testing sensitivity consistency of an acoustic emission sensor are provided. The apparatus uses a cylindrical polymethyl methacrylate (PMMA) rod as a test bench. A clamping seat, a clamping block, and a mounting cylinder are mounted on one end of the test bench in cooperation. Under an action of a pressure spring, an end face of a tested sensor keeps pressure-stable coupling contact with an end face of the test bench. A bracket is mounted on another end face of the test bench, and keeps, together with a fixing seat and the clamping seat, the test bench horizontally placed on a desktop. By adjusting a width and an amplitude of a pulse excitation signal of a signal generator, and according to sensitivity distribution and aggregation between tested sensors, a consistency calculation method is used to screen out tested sensors with first, second, and third sensitivity consistency.

The embodiment of the invention provides a vibration sensor residual life prediction sample processing method and device, and the method comprises the steps: carrying out the sensitivity testing of a vibration sensor under different vibration conditions at different time points, and obtaining a degradation data sequence composed of a plurality of groups of test results; wherein each group of test results comprises sensitivity distribution data sets under different vibration conditions; sampling the degradation data sequence by using a sliding window with a predetermined length to obtain a plurality of groups of short sequences; and for each group of short sequences, randomly extracting multiple groups of sensitivity distribution data from each group of test results of the short sequences, and forming a sensitivity data sample by each group of sensitivity distribution data and the corresponding time point to obtain multiple groups of sensitivity data samples. According to the method, a large number of sensitivity data samples can be amplified based on limited data samples, the model training requirement is met, the structure of the amplified sensitivity data samples is simplified, sensitivity characteristics can be effectively represented, and the model training efficiency and the accuracy of a prediction result are improved.

The present application relates to a genetic algorithm-based optical imaging system sensor optimization configuration method.The present application includes taking the uniformity coefficient of the sensor sensitivity distribution as the optimization target, taking the angle position of the sensor structure light-emitting and light-sensing elements as the optimization object, and obtaining the optimal structure of the optical tomography sensor applicable to the fan-shaped laser through the genetic algorithm.Then, the angles of the light-emitting elements and the light-sensing elements are set according to the optimal sensor structure parameters, so that the optimized sensor is obtained.Finally, the imaging optimization is realized through the imaging system.The present application is not dependent on any specific actual distribution, is applicable to the case without prior information, and has stronger universality.The genetic algorithm is used to realize the optimization of the sensor structure, and the calculation amount of designing an optimal configuration structure with the minimum uniformity coefficient is reduced.

This invention discloses a method for detecting defects on both sides of a wafer, relating to the field of image processing technology. The method includes the following steps: controlling an imaging unit to acquire front and back images of the wafer to be inspected; performing feature deconstruction analysis on the back image to extract a back perturbation feature set; the back perturbation feature set includes texture coherence indices and contamination source coordinate information; based on the back perturbation feature set, outputting adaptive filter morphology parameters and a front detection sensitivity distribution map; processing the back and front images using a dual-stream differential back defect detection strategy and an adaptive filtering front defect detection strategy to extract back and front defects; integrating the extracted back and front defects using spatial coordinates to output a wafer defect detection report. This invention solves the problem that conventional edge detection algorithms easily misjudge highly reflective, high-density laser-etched dots as foreign objects or edge chips.

This invention provides an electronic percussion instrument and a method for detecting the impact, which improves the accuracy of impact position detection. Multiple drumhead sensors (4) are arranged on a frame (3) facing the lower surface of the drumhead (6). In a region where the distance from the center of the striking surface (60a) of the drumhead (6) is more than 50% and less than 75% of the radius (R) of the striking surface (60a), the buffers (41) of the multiple drumhead sensors (4) contact the lower surface of the drumhead (6) (diaphragm 60). This makes the sensitivity distribution of the impact on the striking surface (60a) of the drumhead (6) more uniform and suppresses vibrations caused by the drumhead sensors (4) mistakenly detecting that the drum edge (7) has been struck. Therefore, the accuracy of impact position detection is improved.

The invention discloses a quantitative evaluation method based on a xenon / phosphorus multi-nuclear magnetic resonance in-vivo molecular probe. The quantitative evaluation method comprises the following steps: acquiring a corresponding curve between the pH value of a molecular probe saturated solution and the saturation concentration of the molecular probe and a sensitivity distribution diagram of a 129Xe transceiving integrated coil; acquiring a hydrogen proton magnetic resonance structure image of a to-be-detected area of the detection object; obtaining 3D 31P chemical shift imaging data of a to-be-detected area of the detection object, and obtaining a 129Xe magnetic resonance signal distribution image of the molecular probe; obtaining a pH value distribution image of the to-be-detected area of the detection object; obtaining a molecular probe concentration distribution image in the to-be-detected area of the detection object; calculating the apparent binding rate of the molecular probe at the position coordinates of the molecular probe in the to-be-detected area of the detection object and 129Xe; according to the invention, quantitative measurement of parameters such as the concentration of the molecular probe and the apparent binding rate of the molecular probe and 129Xe which are difficult to carry out nondestructive detection in a living body can be realized.

The application relates to the technical field of electric digital data processing, and discloses a train ice melting simulation optimization method of an electromagnetic heat coupling model fused with a deep learning method, which comprises the following steps: inputting a geometric characterization tensor and a physical working condition parameter vector containing an electromagnetic excitation frequency and a reference environment temperature into a feature mapping neural network, outputting a double-channel space source term tensor containing a basic heat source power density and a heat source temperature change sensitivity distribution matrix through nonlinear convolution operation; constructing a heat conduction discrete numerical evolution operator configured with a source term linear correction interface; performing time step operation in a heat conduction time scale, and correcting the basic heat source in real time by using Hadamard product of the sensitivity distribution matrix and a temperature deviation, and substituting the basic heat source into the operator for solving; and the mixed architecture of neural network static mapping and numerical operator dynamic correction is adopted, time scale decoupling is realized under the premise of retaining electromagnetic-heat nonlinear coupling characteristics, and the calculation efficiency in high-frequency physical field simulation is effectively solved.

The invention discloses a pressure testing method for a mobile phone screen, and relates to the field of mobile phone testing, and the method comprises the steps: collecting pressure data and coordinate data of different regions of the mobile phone screen; constructing a screen pressure signal sensitivity distribution diagram according to the pressure data and the coordinate data; dividing the mobile phone screen into a first area and a second area according to the sensitivity distribution diagram; constructing a convex optimization model according to the signal continuity problem when the pressure is moved from the first region to the second region; the convex optimization model is solved through an optimization algorithm, the optimal parameter configuration of second area pressure signal enhancement is obtained, and the optimal parameter configuration comprises the optimal sampling frequency # imgabs0 #, the optimal signal smoothing factor # imgabs1 # and the optimal historical memory weight # imgabs2 #. In order to solve the problem of poor continuity of cross-regional pressure signals of a mobile phone screen, a convex optimization model with clear constraint conditions is constructed according to the problem of continuity of the cross-regional signals, an optimization algorithm is used for solving, and smooth transition of the pressure signals from a high-SNR region to a low-SNR region is achieved.