111 results about "Reference field" patented technology

The invention discloses a dynamic scene three-dimensional reconstruction method and device based on hydrogen energy unmanned aerial vehicle survey, and the method comprises the steps: obtaining dense time sequence multi-view image data of a target region through a hydrogen energy unmanned aerial vehicle platform, and carrying out the preprocessing of radiation correction and geometric correction; carrying out optical flow analysis and deformation rate clustering on the preprocessed image, identifying a pseudo-static anchor point and constructing a dynamic reference field; introducing a dynamic reference field as a soft constraint in a binding adjustment process, and optimizing a camera pose to generate a three-dimensional point cloud with consistent time and space; and finally, mapping the point cloud to a space-time voxel grid, constructing a surface evolution model by using a graph neural network or an anisotropic diffusion algorithm, and calculating a surface deformation vector to realize continuous and high-precision three-dimensional reconstruction of the disaster scene surface deformation process.

The invention discloses a solid waste-based zinc chloride preparation process control method and system, and relates to the technical field of zinc chloride preparation, and the method comprises the following steps: obtaining a unified time base line, establishing a bubble phase reference field, collecting a sound-induced echo sequence, a micro-pressure waveform sequence and a light scattering sequence of a reaction liquid under the bubble phase reference field, and calculating the solid waste-based zinc chloride preparation process. Fusing to generate a bubble density space-time matrix; and performing reversible time-frequency rearrangement based on the bubble density space-time matrix, decomposing to obtain different frequency band distributions, extracting a narrow-band resident bubble group, calculating critical volume distribution and collapse precursor indexes, and constructing a dynamic risk fingerprint database. According to the method, a unified time base line and a bubble phase reference field are constructed, the bubble state is perceived in real time, collapse forebodes are recognized, a dynamic risk fingerprint database is established, directional intervention and reverse energy channel collapse nucleus extinguishing are achieved in combination with an energy aggregation node, finally closed-loop regulation is constructed through calibration write-back, the safety and stability of zinc chloride preparation are improved, and the method is suitable for large-scale popularization and application. And efficient utilization and clean production of solid waste are promoted.

The invention discloses an industrial data analysis and mining system based on multi-source fusion, which relates to the technical field of information processing, and comprises a time-frequency baseline construction module, an energy coupling modeling module, an anomaly identification and verification module, a pseudo peak shielding and filtering module, a trend node extraction module and a closed-loop regulation and control execution module, a unified time base line and a cross-source phase reference field are obtained, a millisecond-level phase comb index is constructed, a zero phase anchor point is locked, and reversible time-frequency coordinates are generated. According to the method, a unified time-frequency coordinate system is constructed, accurate alignment of multi-source data is realized, a false trend is identified in combination with energy coupling modeling and anti-fact verification, false features are screened out through a rejection domain, reverse energy intervention is implemented based on credible trend nodes, an identification-verification-regulation closed loop is formed, and trend analysis robustness and regulation reversibility are improved.

The invention discloses a self-stabilization system of an exterior wall robot, and relates to the technical field of engineering construction robots, and the self-stabilization system comprises a phase reference module, a frequency spectrum coupling module, a playback prediction module, a gap evolution module, a feedforward compensation module and an energy regulation and control module, constructing a millisecond-level phase comb index based on the wind vibration phase reference field, and locking a zero-phase anchor point in the phase comb index to form an initial constraint condition of attitude perception; according to the method, the closed-loop control of the outer wall robot from disturbance sensing to fine control is realized by constructing a six-stage self-stabilization process. The system introduces millisecond-level phase anchor point locking, cross-frequency information fusion, disturbance trend prediction, adhesion gap dynamic mapping, multi-channel compensation control and energy reverse regulation and control mechanisms, and can significantly improve the operation stability, adaptability and safety in a high-rise complex outer wall environment without depending on a mechanical redundant structure.

The invention discloses a classroom real-time learning emotion knowledge and intelligent intervention system, and relates to the technical field of artificial intelligence auxiliary education. Comprising a time sequence perception modeling module, a conflict identification analysis module, an intervention priority control module, a decision fusion output module, a stability prediction and early warning module and a closed-loop vibration suppression regulation and control module, the time sequence perception modeling module establishes a unified time baseline and a phase reference field, and performs joint modeling on multi-source classroom learning condition data under the constraint of the unified time baseline and the phase reference field; time sequence semantic fusion features are extracted, and a contradictory candidate trajectory set is generated. According to the method, multi-modal time sequence semantic features are fused, a learning situation conflict source is identified, conflict intensity is quantified, an intervention priority and a punishment mechanism are constructed to guarantee rhythm stability, an evidence chain and an attention mechanism are adopted to generate a consistent decision, oscillation detection and time reversal regulation are combined, closed-loop control of the intervention process is achieved, strategy oscillation is effectively avoided, and the method is suitable for popularization and application. And the intervention continuity and stability are improved.

The invention relates to the technical field of slope monitoring, and discloses a slope slippage identification method and system for unmanned aerial vehicle inspection. According to the method, an unmanned aerial vehicle carries a laser radar to collect three-dimensional point cloud data of a slope, and an initial spatial distribution field is generated through spatial gridding preprocessing; establishing a slope space reference field model, and performing space consistency correction on the initial space distribution field to obtain a corrected displacement field at multiple time points; the unmanned aerial vehicle is controlled to periodically inspect according to the displacement safety threshold, and actual displacement is obtained by combining a ground displacement sensor; when the deviation between the grid unit displacement amount and the actual displacement amount exceeds a preset tolerance, extracting a historical displacement feature vector and dynamically adjusting a displacement value, and generating an updated displacement field; and inputting the updated displacement field into the space reference field model for repeated routing inspection until all the deviations are smaller than a preset tolerance. The method improves the accuracy and reliability of slope slippage identification, and is suitable for various slope monitoring scenes.

The invention relates to the technical field of digital twinning, in particular to a high-performance digital twinning system rendering method based on dual-grid and neural network mapping, and the method comprises the steps: constructing a high-precision calculation grid and a low-precision rendering grid, and building a space mapping relation between the two grids; executing multi-working-condition numerical simulation to obtain a high-dimensional simulation result snapshot matrix; the dimension reduction projection operator is used for reducing the dimension of a high-dimensional simulation result of any working condition into an r-dimensional feature vector; generating low-dimensional reference field data by using the space mapping relation; training the neural network until a mapping network parameter is obtained through convergence; obtaining current working condition parameters of the equipment in real time, and obtaining a current r-dimensional feature vector by using the dimensionality reduction projection operator; and quickly generating physical field prediction distribution on the low-precision rendering grid and performing pseudo-color rendering. According to the scheme, the problem that a traditional method is low in rendering efficiency is solved, and the method has the advantages of reducing computing resource consumption and keeping visualization precision.

The invention relates to the technical field of wallboard detection, and discloses an online visual detection system and method for a multilayer bamboo wallboard, and the system comprises a multi-dimensional information fusion module, a reference field texture analysis module, a statistical anomaly identification module, a time sequence thermal excitation module, an isotherm form recognition module and a feature matching and grading module. Pixel-level multi-dimensional information fusion is carried out on the visible light band signal and the near-infrared band signal of the multispectral image set to obtain a fused image; taking the typical trend of the bamboo natural fiber as a reference field, and comparing and analyzing the fiber texture trend to generate a texture feature map; identifying a texture abnormal area of which the fiber trend consistency is lower than that of the reference standard; applying thermal excitation in the texture abnormal area to adjust an intensity time sequence to obtain a time sequence gradient temperature field; recognizing a fracture form to obtain defect boundary and depth features, and outputting a quality grade after matching the defect boundary and depth features with a grading standard; according to the invention, the detection efficiency of the multi-layer bamboo wallboard can be improved.

The invention discloses a cultural relic restoration decision-making method and system based on computer three-dimensional modeling, and relates to the technical field of cultural relic restoration, and the method comprises the following steps: building a unified time baseline, generating a phase reference field, introducing a double-frequency comb interference structure to reconstruct a humidity refraction field, locking a zero-phase anchor point, and forming an initial constraint condition of a scanning path; under an initial constraint condition, an airflow phase gradient is obtained by adopting a Schlenn pilot frequency chromatography method, a nonlinear diffraction nucleus is calculated, and a refraction residual spectrum is output for modeling correction. According to the method, humidity disturbance is recognized through interference measurement and chromatography, real-time compensation is achieved in combination with phase sheath and humidity control, the crack and material characteristics are fused through neural field modeling, the solidification process is played back in combination with a mineralization mechanism, and the three-dimensional modeling precision and the restoration decision scientificity are improved.

The invention discloses a road intelligent diagnosis method based on an AI large model, and relates to the technical field of road engineering detection, and the method comprises the following steps: building a unified time base line, constructing a phase reference field, injecting a calibration pulse, separating dynamic shadow time sequence texture and crack initial features in a road image sequence, and obtaining a road image sequence; generating prior information of dynamic shadows and cracks; under the constraint of prior information, polarization spectrum three-dimensional coding imaging is carried out, polarization angle distribution and spectrum gradient are extracted, a feature dictionary of dynamic shadows and cracks is constructed, and phase drift in the prior information is calibrated. According to the method, a unified time base line and a phase reference field are constructed, and accurate distinguishing of dynamic shadows and cracks is realized by combining polarization spectrum imaging and anti-fact distillation; the point cloud and acceleration data are fused for geometric reconstruction, and through phase conjugate extinguishing and closed-loop feedback, the continuity and accuracy of diagnosis are significantly improved, and maintenance error decisions caused by misjudgment are avoided.

The invention discloses an intelligent robot grabbing control method and system based on AI vision, original vision and kinematics flow are fused through space-time alignment, and a physical-level dynamic shielding mask is accurately extracted through forward kinematics and reverse perspective projection. Then, the limitation of traditional pure semantic matching is broken through, a narrow-band gradient reference field of a shielding boundary is explicitly extracted to serve as a spatial topology bias injection attention mechanism, feature illusion completion guided by physical continuity prior is executed in a hidden space, and high-fidelity perspective features are generated; on the basis, the network synchronously regresdes six-degree-of-freedom grabbing pose and execution uncertainty, the uncertainty serves as an independent variable to dynamically attenuate and adjust the impedance rigidity of the mechanical arm, finally, self-adaptive compliant interaction in a blind area is achieved in a bottom layer physical servo link, and space positioning precision and operation safety are both considered.

The invention relates to the technical field of industrial image recognition, and discloses an industrial weld X-ray image defect AI recognition system, which comprises a feature acquisition unit for acquiring a to-be-processed target digital grayscale image; the reference field construction unit identifies edge morphological characteristics of a target object to establish a global geometric central axis and generate a second-order smooth reference field; a feature decoupling unit calculates a displacement vector of a local gray distribution mass center relative to a global geometric center axis, performs nonlinear stretching compensation on a second-order smooth reference field local partial derivative matrix by using the displacement vector so as to reconstruct a self-repairing reference field, and extracts a residual feature map through a digital gray image and self-repairing reference field convolution subtraction; according to the method, nonlinear gray jump is balanced by using the endogenous geometric features of the image, accurate stripping of weak features under a complex surface fluctuation working condition is realized, and the recognition accuracy and stability of a system are improved.

The invention discloses a computer information processing method and system, and relates to the technical field of computers, and the method comprises the following steps: establishing a unified time baseline and a bit stream phase reference field, constructing a residual bit observation matrix, and locking the boundary of a state machine according to the residual bit observation matrix; rare symbol sequence features are extracted based on the locked state machine boundary, a symbol sequence fingerprint set is constructed, a reversible auto-encoder is utilized to invert symbol sequence triggering conditions, and risk mapping is generated; and constructing a buffer micro-residual spectrum according to the risk mapping, generating a bit-level topological link, calibrating a cross-fragment pollution starting point in the topological link, and outputting a positioning index. According to the method, bit stream anomaly identification and dynamic repair based on the time base line and the phase reference are realized, residual observation, symbol fingerprints, topological positioning, error correction rearrangement and time reversal reset are combined, a closed-loop information processing flow is constructed, the data processing stability and fault-tolerant capability are improved, and the method is suitable for high-density real-time data and complex transmission scenes.

The invention discloses an airfield pavement crack monitoring and maintenance method based on an unmanned aerial vehicle and image recognition, and relates to the technical field of airfield pavement crack monitoring and maintenance, and the method comprises the following steps: an unmanned aerial vehicle carries a thermal imager and a multispectral camera to synchronously scan an airfield pavement through a PTPv2 clock protocol, and obtains multi-modal information of a temperature field and a reflectivity spectrum; establishing a thermal expansion coefficient inversion model, generating a dynamic reflection reference field, and setting an abnormal triggering mechanism to mark a deformation sensitive area; according to the method, a reflection suppression image is generated by establishing a thermal expansion coefficient inversion model and a hot spot physical model, so that multi-modal thermodynamic characteristic data and polarization-spectral characteristic data synchronously acquired by a thermal imager carried by an unmanned aerial vehicle and multiple sensors of a multispectral camera are fused, airfield pavement cracks are comprehensively and deeply detected, and the detection accuracy is improved. Therefore, micro cracks and hidden cracks are accurately identified, and the accuracy and reliability of crack detection are effectively improved.

The invention discloses a method for constructing an air pressure fingerprint model, and the method comprises the steps: carrying out the sampling based on known sampling equipment of horizontal positioning and vertical positioning, and obtaining the sample information; constructing a sample information base; defining an influence range of the sampling equipment, and performing grid division based on the influence range; fitting an air pressure base line of each grid according to the sample information base, wherein the air pressure base line is an air pressure reference value at a specified temperature and a specified height in the grid; sampling sample information in any grid based on a terminal device with known horizontal positioning, comparing the sample information with a preset environment semantic label template to obtain an environment semantic label of at least one grid, and constructing an air pressure fingerprint model, wherein the air pressure fingerprint model comprises an air pressure base line of each grid and an environment semantic label of at least one grid. According to the method, the standardized air pressure reference field is constructed and environment semantic intelligent labeling is realized, so that the environment perception precision in a complex scene can be improved.

The invention relates to the technical field of radiotherapy and medical data processing, in particular to a radiotherapy safety early warning system and method based on multi-modal data fusion. Comprising the following steps: a multi-modal acquisition step: synchronously acquiring a static plan, a dynamic log and a real-time monitoring stream; an ideal field reconstruction step: reconstructing an ideal reference field by using the log-driven plan; a fault simulation step: injecting an interference operator to generate a theoretical fault state space; a double-track difference step: respectively extracting a real residual feature library and a theoretical residual feature library; a risk positioning step: calculating topological similarity to generate an auxiliary decision report; according to the method, a double-track differential mechanism is used for eliminating time asynchronization errors, and high-sensitivity recognition of tiny mechanical faults is achieved under the physiological noise background.

A system and method for generating canonical views for volumetric imaging data are disclosed. The system includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to receive volumetric imaging data, segment the at least one organ structure of the volumetric imaging data into a plurality of organ components, compute, for each organ component, one or more eigenvectors and corresponding eigenvalues, divide each organ component into a plurality of three-dimensional octants, receive a user input, wherein the user input includes a selection of a reference field of view, determine which of the plurality of three-dimensional octants are intersected by the reference field of view and output the volumetric imaging data with the canonical view.

The invention relates to the field of cell antenna factor calibration, in particular to a power domain estimation method and device based on GTEM cell antenna factor calibration. The scheme comprises the following steps: determining a working frequency band according to application requirements, and selecting a plurality of calibration frequency points in the working frequency band; performing reference field intensity calibration on each selected calibration frequency point; measuring an initial azimuth angle based on the GTEM cell; measuring noise power, and establishing a noise power matrix; measuring the receiving power under the full angle; subtracting the corresponding noise power from the measured receiving power to obtain net signal power; calculating an antenna factor of the antenna under the current set angle and the calibration frequency point according to the antenna factor definition; and finally, calibrating and verifying the antenna factors. The method is suitable for power domain estimation based on GTEM cell antenna factor calibration.

The embodiment of the invention provides a cross-platform data query method. The cross-platform data query method comprises the steps of obtaining an encryption behavior identifier of a current user behavior; the encrypted behavior identifier is decrypted, a target list is obtained, the target list comprises actual field values of multiple fields, and the multiple fields comprise behavior type fields. A plurality of pre-stored encryption behavior mode identifiers are decrypted, a plurality of reference lists are obtained, a single reference list comprises reference field values of at least part of fields in a plurality of fields, and the at least part of fields comprise behavior type fields. And for the target list and any first reference list, determining a corresponding matching mode according to actual field values and reference field values of behavior type fields contained in the target list and any first reference list, and performing field matching on other fields in the target list and the first reference list in the matching mode. And under the condition that the rest fields in the target list and the first reference list are matched, obtaining target data stored in association with the first encryption behavior mode identifier.

When determining that a change amount (resistance value change amount)of a resistance value (field winding resistance value) of a field winding of a winding field type rotary electric machine with respect to a predetermined reference field winding resistance value is larger than a reference change amount, a control device according to the present embodiment adjusts an armature winding current value, which is a value of a current flowing through an armature winding of the winding field type rotary electric machine, by using the resistance value change amount.

The invention discloses a message processing method and device, a storage medium and an electronic device, and the message processing method comprises the steps: detecting the message type of a target message currently received by a target port; obtaining a plurality of reference message types allowed to be processed by the target port in the target network equipment, and corresponding reference field types and reference message operations thereof, and establishing a corresponding relationship among the reference message types, the reference field types and the reference message operations; according to the technical scheme, the message processing method and the message processing device have the advantages that the message processing efficiency of the network equipment in the mixed service scene is low, and the problem that the message processing efficiency of the network equipment in the mixed service scene is low in the prior art is solved.

The application relates to the technical field of semiconductor manufacturing, and discloses a wafer defect detection method, a wafer defect detection device and a medium. The method comprises the following steps: performing image processing on a target wafer image of a wafer object to be detected to obtain a plurality of local spectrum regions; performing complex filtering processing on the local spectrum regions in a plurality of scales and a plurality of directions to obtain response information of each local spectrum region under different scales and different directions; determining a phase consistency residual graph, a frequency band leakage residual graph and a direction offset residual graph based on phase responses and energy responses in the response information, a pre-constructed spectrum phase reference field, a main frequency band and a main direction; performing multi-scale residual back projection processing on the target wafer image to obtain a multi-scale residual back projection graph; generating a defect saliency graph based on any one or several of the phase consistency residual graph, the frequency band leakage residual graph, the direction offset residual graph and the multi-scale residual back projection graph; and performing defect detection based on the defect saliency graph to obtain a target detection result.

The invention discloses an artificial intelligence-assisted animation intermediate frame transition optimization method, belongs to the technical field of animation production, and is used for solving the problems that an existing AI frame insertion technology cannot distinguish artistic deviation and technical errors in key frames and amplification distortion is caused. The method comprises the following steps: constructing a deformation energy reference field representing role deformation space distribution and intensity based on adjacent key frames; performing reverse tracing on the contour and color block boundary motion trail in a high-energy area of the deformation energy reference field, and fitting a dominant motion trend line; generating a physical calibration anchor point defining an ideal motion path based on the trend line; and combining a deformation energy reference field with a physical calibration anchor point, constructing an initial deformation field through anchor point influence domain superposition, and driving a key frame stroke vector field to synchronously deform after rotation field direction correction. According to the method, jitter and distortion caused by key frame deviation can be inhibited, the animation art expressive force is reserved, the visual coherence of the intermediate frame sequence is improved, and the method is suitable for complex deformation character animation production.

The invention relates to a high-order shimming control method and device integrated with B0 field coupling compensation. The method comprises the following steps: acquiring a shimming reference field and a coupling reference field after each channel in a high-order shimming coil is purified and separated; acquiring a three-dimensional field graph of a region of interest of a patient, and acquiring the current center frequency of a magnetic resonance imaging system; determining an initial current value of each channel based on the shimming reference field and the three-dimensional field pattern, the initial current values being not interfered by the coupling reference field; determining a B0 offset according to the initial current value and the coupling reference field, and eliminating uniformity interference of the B0 offset on a B0 field according to the B0 offset and the current center frequency; and after the uniformity interference is eliminated, the initial current value of each channel is set in the corresponding channel, and high-order shimming setting is completed. According to the invention, the high-order shimming quality is improved.

This invention discloses an extreme wind field discrimination method based on non-equilibrium Wasserstein distance, belonging to the field of meteorological wind energy prediction technology. The method includes the following steps: obtaining a set of wind field samples in the study area during the target period to construct a reference field; calculating the non-equilibrium Wasserstein distance between each wind field sample and the reference field as an extremity index; fitting the statistical distribution of the extremity index; calculating an extreme discrimination threshold based on the fitted GEV distribution model; and comparing the extreme index with the extreme discrimination threshold to determine whether the wind field sample is an extreme event or a non-extreme event. This invention, employing the aforementioned extreme wind field discrimination method based on non-equilibrium Wasserstein distance, can provide a high-precision foundation for identifying typical extreme wind fields and constructing scenarios for research such as climate change scenario analysis, extreme scenario risk assessment, renewable energy uncertainty quantification, and energy system resilience optimization.

The invention relates to the technical field of runoff reduction methods, in particular to a river runoff reduction method in a changing environment based on a GIS (Geographic Information System) technology. Firstly, a static reference field is obtained; further obtaining effective net rain of the runoff producing layer; further combining the earth surface flow velocity gain potential coefficient of each grid unit and the effective net rain of the runoff producing layer, correcting the inherent terrain confluence time grid, and obtaining a rain intensity corrected confluence time grid; further based on the rain intensity correction confluence time grid and the static flow direction matrix, obtaining the accumulated confluence time, and combining with the effective net rain of the runoff-producing layer to count the isochrone partition flow; and finally, superposing the isochrone partition flows in the time sequence to generate natural reconstructed runoff at the drainage basin outlet. According to the scheme, by constructing a static terrain reference field and a dynamic rainfall intensity response mechanism and coupling runoff production and nonlinear confluence processes, systematic deviation caused by neglecting rainfall-terrain nonlinear action of a traditional model is solved, and high-precision natural runoff restoration is realized.

The invention provides a prediction method and device for a carbon dioxide storage capacity diffusion area, and the method comprises the steps: collecting background temperature data in a preset time period before a carbon dioxide injection operation is carried out on a target storage site; constructing a three-dimensional temperature reference field of the target storage site; in the carbon dioxide injection process, collecting real-time temperature data of each spatial position of the monitoring well under different storage capacities; based on the temperature variation between the real-time temperature data and the corresponding reference temperature data, constructing an abnormal temperature field comprising the temperature variation of different spatial positions; performing feature extraction on the abnormal temperature field to obtain a temperature feature vector; and based on the temperature feature vector, the trained sequestration capacity prediction model and the trained diffusion region generation model, obtaining a predicted carbon dioxide sequestration capacity and a corresponding predicted diffusion region. According to the method, storage parameters are directly inverted through temperature, errors caused by dependence on complex instruments are reduced, and the prediction precision of carbon dioxide distribution is improved.

An oral care system for sensing blood in an oral cavity and in gum tissue. The sensing is performed magnetically using a magnetic field source (16) and magnetic sensing arrangement (18) incorporated into a cleaning or treatment portion of an oral care device (e.g. a brush head of a toothbrush or mouthpiece part of a brushing mouthpiece device). The field source generates (16) a reference field and the sensing arrangement (18) is arranged to sense the field strength of the reference field at one or more spatial points. Since blood is magnetic, when brought into the reference field, it magnetically interacts with the field, which may alter field strength, field shape, or flux distribution. This enables presence of blood to be detected. It also allows for detecting specific oral features or disease states associated with presence of blood or abnormal amounts or concentrations of blood. For example, this can be based on application of detection criteria which relate to one or more properties of the sensed field.

The invention discloses a distributed photovoltaic grid-connected adaptability evaluation system, which relates to the technical field of power systems and comprises a benchmark construction module, a time frequency analysis module, a coupling identification module, a capacity evaluation module, a risk suppression module and a closed-loop control module. The meteorological data, the user power generation curve data and the power grid operation data are fused, local inherent frequency distribution is extracted, and a zero-phase anchor point is determined in a phase reference field. According to the method, a unified time base line and phase reference are constructed, multi-source data fusion and dynamic evaluation, oscillation risk identification, coupling node and frequency accurate locking, second-order cone programming and anti-resonance control fusion and coupling energy active weakening are realized, and finally, a high-precision closed-loop grid-connected adaptive regulation and control mechanism is formed through phase conjugate injection and feedback calibration.

The application relates to a vehicle front field of view aestheticity checking method, device, equipment and storage medium, the method comprises the following steps: a plurality of reference field of view curves with a preset length are obtained by extending a plurality of position points on a driver's eye ellipse, a front windshield glass black edge curve of the vehicle is taken as a guide curve, the reference field of view curves are combined, a plurality of front field of view visible surfaces on the eye ellipse are generated and superposed, a superposition surface of the front field of view visible surface is obtained, and the superposition surface is processed in a preset processing mode to obtain a front field of view envelope surface, so that the aestheticity of the front field of view is checked to obtain an aestheticity evaluation result. Therefore, the problems that the aestheticity of the front field of view of the vehicle cannot be checked in real time through a systematic checking method, the project development cycle is long, the cost is high and the like are solved, the design scheme is adjusted in time through CAD auxiliary checking, the problems of front field of view deviation or unattractive vehicle parts are avoided, and therefore the product development cycle is shortened and the design change cost is saved.