178 results about "Shape matching" patented technology

The invention discloses a glass bottle surface defect detection method based on visual detection, relates to the technical field of surface defect detection, and aims to solve the problem of inaccurate glass bottle surface detection. According to the method, information combination is carried out on the types, the number and the severity of the defects, weight distribution is carried out, then comprehensive scoring is carried out, various factors can be comprehensively considered in the mechanism, a more comprehensive and accurate scoring result is obtained, and defect boundaries are extracted through a contour detection method. According to the method, the defect position can be accurately positioned, the defect boundary can be accurately extracted, a reliable data basis is provided for subsequent analysis and processing, defect candidate areas are generated through a threshold segmentation method, screening is carried out through size filtering, shape matching, texture analysis and other methods, candidate areas without defects can be eliminated, and the defect detection accuracy is improved. And an image of the defective glass bottle can is accurately obtained.

The invention discloses a radioactive measurement data processing method for improving uranium exploration efficiency. The method comprises the following steps: standardized data acquisition: integrating a multi-parameter module, carrying out time-space synchronous acquisition of geological geophysical environment parameters, standardizing protocol alignment data, and supporting three-dimensional modeling; a three-dimensional coupling model is used for processing interference in a sub-module mode, LiDAR-DEM is used for correcting gamma attenuation in the terrain, an optical fiber thermopermeability instrument is used for correcting daughter errors in the hydrology, signal attenuation of a borehole is compensated through a drilling fluid chart, and a space-time continuous interference field is formed; performing dynamic equilibrium coefficient inversion: constructing equilibrium coefficient isoparametric mapping, and inputting rock core, logging and geochemical data into a random forest model; the transfer learning is trained by using historical data, and dynamic inversion and updating of a new area are carried out; intelligent data processing three-dimensional visualization: self-adaptive denoising and spectral shape matching reinforcement abnormity are carried out; constructing a three-dimensional model, and carrying out transfer learning to optimize the precision; the WebGL platform integrates multi-parameter display, virtual drilling functions and high-dimensional data intuitive interpretation.

The invention provides an intelligent boxing method and system. The intelligent boxing method comprises the steps of obtaining boxing task information and generating a boxing scheme. The boxing task information comprises the size, the weight, the stacking limitation, the number and the priority of each cargo, and the size, the bearing capacity and the occupation state of each loading unit. And under the condition that the size, bearing and stacking constraint conditions are met, a plurality of candidate boxing combinations are generated, the loading utilization rate, the residual space distribution and the shape matching degree are evaluated based on a preset optimization target, and an optimal scheme is selected. The system comprises an input terminal, a task information receiving module, a data storage module, a task and scheme storage module, an operation processing module and a final boxing scheme generation module. According to the method, multi-dimensional constraint matching and weight balance are considered, and space waste and transportation risks are avoided; the maximum greedy algorithm and the adaptive large neighborhood search optimization are combined to realize the combination of automation and experience. The method can be expanded to batch task scheduling and grouping sequencing, so that the calculation complexity is reduced, and the overall boxing and transportation efficiency is improved.

The invention discloses an industrial image anomaly detection method and device, equipment and a storage medium, and relates to the field of image recognition. Obtaining a defect-free product graph, making a comparison data set based on the defect-free product graph, and performing pre-storage processing; performing feature point shape matching on the comparison data set based on the received to-be-detected image and the extracted feature point data, and determining a comparison image of the to-be-detected image; taking the to-be-detected image as a target object, correcting a product image area in the image, and aligning the product image area with the product image area of the to-be-detected image according to a pixel shift operation; and comparing the aligned product image areas, and identifying abnormal defects in the to-be-detected image. According to the scheme, the comparison data set of the defect-free product image is constructed, the feature point matching and pixel-level alignment technologies are combined, the problem of false detection caused by product position deviation or form change in a traditional method is effectively solved, the adaptability to illumination change is improved through brightness adjustment and difference matrix analysis, and the detection accuracy is improved. The method has the advantages of high detection precision, high environmental adaptability and high processing efficiency.

The invention relates to the technical field of medical wearable equipment monitoring control, in particular to a wearable intelligent physical sign monitoring control method. The method comprises the following steps: continuously monitoring a sitting posture pressure value of the intelligent seat; when the sitting posture pressure value is larger than a first threshold value, it is judged that the sitting posture is in a pressing state, and initial site fitting information is obtained; and obtaining a human body sitting posture form and carrying out adaptive posture adjustment on the intelligent seat according to the human body sitting posture form, so that the intelligent seat is matched with the human body sitting posture form, the initial sitting standby state reaches the optimal sitting posture form of the intelligent seat, and optimal sitting posture memory data is stored. Through a data processing technology, a real-time monitoring technology and an automatic control technology, human body sitting posture shape matching mapping is carried out on vital sign data detected by wearable intelligent sign equipment and site fitting information monitored by the intelligent seat, and self-adaptive posture adjustment is carried out on the intelligent seat; therefore, the automatic adjustment degree of the intelligent seat is improved.

The invention discloses a whole-process vascular interventional operation training method and system based on a virtual reality technology, and the method comprises the steps: firstly, developing a vascular interventional mechanics and collision simulation module, and achieving the deformation simulation of a blood vessel and a guide wire through the combination of position dynamics, a region shape matching technology and a Cosseerat elastic rod model, the collision between the blood vessel and the guide wire is treated by adopting a wide-to-narrow three-layer progressive collision detection method; secondly, constructing an immersive virtual operation scene through model construction and rendering optimization; visual angle roaming, instrument operation and interface interaction are fused, and multi-mode interaction control driving intervention training is achieved; finally, based on a'module-event 'dual-drive framework, operation tasks such as anesthesia, puncture, radiography, intervention, stent release and hemostasis are sequentially connected in series through a unified state machine, and whole-process training is achieved. The accuracy and stability of blood vessel and guide wire simulation are improved, the training immersion sense is enhanced, interventional operation whole-process training is achieved, and high teaching and practical value is achieved.

The invention discloses a laser point cloud-based industrial equipment digital twin model rapid reconstruction method and system, and the method combines a model matching mode and a point cloud reconstruction mode, and effectively solves the problem of twin model reconstruction in different scenes. According to the first mode, on the basis of an existing three-dimensional model, through shape matching, feature extraction and model retrieval methods, registration of point cloud data and the three-dimensional model is combined, and rapid reconstruction of the equipment twinborn model is successfully achieved. The mode is suitable for equipment with an existing standard three-dimensional model, the repeated utilization rate of the model can be improved, and the reconstruction time and cost are reduced. In the second mode, the reverse grid model construction method based on the point cloud data is provided for equipment which cannot be retrieved through an existing model. Through an improved greedy projection triangulation algorithm, point cloud data is converted into a grid model, and the precision and authenticity of the model are improved in combination with a grid optimization algorithm and a surface texture mapping technology. According to the method, the digital twinborn model of the industrial equipment can be efficiently and accurately reconstructed, the modeling difficulty in an industrial scene is relieved, the actual demand of field modeling is met, and the method has high application value and practicability.

The invention provides a migration scene-oriented adversarial sample generation method and device, a storage medium and a program product, and the method comprises the steps: receiving a to-be-attacked agent model, selecting a plurality of network layers in the agent model, and generating a random mask matched with the parameter shape of the selected network layer; shielding the parameters of the selected network layer based on the random mask to generate a multi-version proxy model; an original input sample is input into the multi-version agent model for forward propagation, gradient information of each agent model for a current adversarial sample is calculated, and a gradient direction is generated; and iteratively updating disturbance by using the gradient direction, and superposing the updated disturbance to the original input sample to generate an adversarial sample. According to the method, high-quality adversarial samples can be generated, and the attack efficiency is remarkably improved.

The invention discloses a photovoltaic module bird droppings defect detection method and system, and the method comprises the steps: carrying out the image screening of at least one first target image according to a preset shape matching strategy, and obtaining at least one second target image; inputting the at least one second target image into a preset neural network, and performing iterative training on the neural network to obtain a defect recognition model; at least one real-time initial image containing the photovoltaic module is obtained, the real-time initial image is input into the defect recognition model, and the defect recognition model outputs and obtains a defect detection result corresponding to the at least one real-time initial image. The remote dependency relationship and the position information of the input image can be coded from the two dimension directions of the horizontal space and the vertical space, so that the network can obtain the characteristics in a larger range, and the precision of the model is improved under the condition of not increasing extra calculation overhead.

The invention relates to the technical field of hot-rolled strips, in particular to a three-point difference dynamic adjusting method in the rolling process of hot-rolled strips, which comprises the following steps: S1, preparation before rolling and parameter initialization: roller shape matching and model parameter preloading; s2, dynamic regulation and control at the threading stage: thickness pre-compensation and temperature gradient suppression; s3, steady-state rolling control is conducted, specifically, three-point difference real-time monitoring and compensation are conducted, and thermal convexity dynamic compensation is conducted; and S4, drifting and exception handling: tail stability control and intelligent transition material insertion. According to the method, a full-process control system covering dynamic roll gap regulation and control, temperature-stress coupling compensation and intelligent decision support is constructed, and the problems that head and tail thickness fluctuation is difficult to restrain and edge thinning exceeds the standard by developing an asymmetric roll bending force distribution model and a rolling rhythm self-adaptive roll type matching strategy through traditional single-point thickness control can be effectively solved.

The invention relates to the technical field of pixel tracking, in particular to an AI application-based high-definition video stream pixel tracking training method, which comprises the following steps of: analyzing texture, edge and color distribution of a video frame by adopting a DCNN network on the basis of set video input parameters, adjusting the size and the shape of a convolution kernel, matching the change of video features, and obtaining an AI application-based high-definition video stream pixel tracking training result; and obtaining feature data mapping. According to the method, the high-definition video stream is processed by combining the deep convolution and the recurrent neural network, fine tracking and efficient analysis are achieved, the accuracy and speed of pixel tracking are remarkably improved by refining local and global information in the high-definition video stream and adjusting dynamic parameters, and especially in a rapidly changing video scene, the accuracy and speed of pixel tracking are greatly improved. Through frame-by-frame analysis, the color and texture changes of pixels can be accurately extracted and analyzed, and the pixel tracking performance is optimized, so that when large-scale high-definition video data is processed, real-time adjustment can be performed, and the accuracy and timeliness of a tracking result are ensured.

The invention relates to the technical field of image processing, in particular to a tablet defect detection method and system based on machine vision. The method comprises the following steps: calculating a shape matching coefficient of each pixel point in a tablet image; performing multi-layer decomposition on the tablet image and the template image by using a wavelet packet decomposition method, extracting a high-frequency sub-band after each layer of decomposition, and calculating an energy difference degree of texture energy of each pixel point in the tablet image; and obtaining the initial similarity of each pixel point of the tablet image through an NCC algorithm, optimizing the initial similarity through the shape matching coefficient and the energy difference degree to obtain the multi-modal matching degree of the pixel point, and detecting the tablet based on the multi-modal matching degree. The tablet defect detection method has the effect of improving the tablet defect detection precision and accuracy.

A method of inspecting a mark of a semiconductor package includes: acquiring an original inspection image and an original reference image to determine whether the mark is defective; acquiring a target reference image and a target inspection image by converting each of the original reference image and the original inspection image into a binary image through thresholding; calculating an area matching rate by calculating a number of error pixels that have different brightness values from each other, among pixels of the target reference image that correspond to pixels of the target inspection image, and by using the number of error pixels relative to a number of total pixels of the target reference image; and calculating a shape matching rate by acquiring a first circularity of the target reference image and a second circularity of the target inspection image, and by comparing the first circularity with the second circularity.

The invention relates to a ginkgo leaf abnormal phenotype detection method, and belongs to the field of ginkgo leaf phenotype anomaly recognition. The method comprises the following steps: ginkgo leaf data acquisition: acquiring ginkgo leaf image data through a camera, and preprocessing the ginkgo leaf image data to obtain a ginkgo leaf image data set; extracting the contour of the ginkgo leaf: extracting the contour of the image in the ginkgo leaf data set by using a geodesic distance method to obtain a contour curve of the ginkgo leaf image; constructing a shape matching model: obtaining a matching cost mean value and a matching cost variance of each category of the ginkgo leaf images according to the ginkgo leaf images and the contour curves of the ginkgo leaf images; and ginkgo leaf abnormal phenotype detection: inputting a to-be-detected image in the data set into the shape matching model, and judging whether the to-be-detected image is an abnormal phenotype or not. The method can achieve the precise recognition of the abnormal phenotype of the ginkgo leaf.

The invention discloses a power transmission line mountain fire smoke detection method and system, and the method comprises the steps: segmenting a mountain fire smoke candidate region in a to-be-detected power transmission channel picture through a pre-trained semantic segmentation model, and calculating a semantic segmentation confidence score; for each mountain fire smoke candidate area, calculating a shape similarity score through a shape matching method, calculating a position confidence score through a position function, and calculating a color confidence score through color distribution comparison; and carrying out weighted summation on the semantic segmentation confidence score, the shape similarity score, the position confidence score and the color confidence score to obtain a final smoke confidence score, and comparing the final smoke confidence score with a preset threshold to judge whether the corresponding mountain fire smoke candidate region is mountain fire smoke. According to the technical scheme provided by the invention, the forest fire smoke condition in the power transmission line channel picture can be effectively identified, the misidentification conditions of pond smoke, chimney smoke, cloud and mist and the like are obviously reduced, and the method has a wide application scene.

The invention discloses a Web-based virtual digital person teaching method and system, a storage medium and equipment, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out micro-course content production based on pre-provided courseware data, obtaining micro-course content data, and storing the micro-course content data in a JSON format; the method comprises the following steps: acquiring micro-class content data, performing classified storage on the micro-class content data to obtain a plurality of JSON sub-files, and outputting the JSON sub-files according to a preset teaching process; according to a teaching process, performing picture content identification and video content identification on the JSON sub-file in sequence, and outputting teaching text content; and controlling the virtual digital person to carry out lip shape matching and action matching according to the teaching text content, and outputting audio content corresponding to the micro-class content data. According to the invention, the information interaction logic of the teaching of the virtual digital person is optimized, the expression of the teaching of the virtual digital person is improved, and the teaching effect is improved.

The invention relates to the technical field of digital people, and provides a method and equipment for generating a digital people video, which can be applied to a digital marketing scene. According to the method, the generation of the digital human video is divided into an audio generation process and a video generation process, when the audio is generated, a target text, an emotion parameter and a reference audio are taken as input, and the target audio of the target text is broadcasted by the sound of a reference person in the reference video and a set emotion, so that sound cloning is realized, the degree of violation of the generated digital human video is reduced, and the user experience is improved. And the text features are extracted from two dimensions of characters and pronunciation, so that the pronunciation accuracy during sound cloning is ensured. When the video is generated, the cloned target audio and the cloned reference video are used as input, and the fidelity of the digital human video is improved through expression and mouth shape matching, so that a reference person can quickly and efficiently generate vivid digital human videos with different broadcast contents only by shooting one reference video without shooting one by one, thereby reducing the manufacturing cost of the digital human video, and improving the user experience. And the video production efficiency is improved.

The invention relates to the technical field of cargo loading optimization, in particular to a cross-border e-commerce logistics big data optimization system, which comprises a data acquisition unit, a data storage unit, a loading algorithm unit and a real-time guidance unit. The storage unit stores goods and transportation tool data, the loading algorithm unit divides three-dimensional grid units according to transportation tool space data, goods are classified according to the weight through a clustering analysis algorithm, and the optimal position of a single goods is determined through shape matching and a heuristic search algorithm. Goods are grouped and arranged through a path planning algorithm in combination with information such as a distribution sequence, the real-time guidance unit receives new data during loading, the algorithm is operated again, guidance information is generated, the problem of the loading space utilization rate is effectively solved, and the space utilization rate is improved.

The invention belongs to the technical field of overhead line butt joint detection, and particularly discloses and provides a method for detecting overhead conductor steel strands after butt joint, and the method comprises the steps: building and correcting a digital twinborn model of a to-be-detected wire clamp based on a CAD drawing and three-dimensional scanning data of the to-be-detected wire clamp; extracting interface geometric parameters and identifying actual shapes of the interface geometric parameters; generating an initial gridding detection path based on a shape matching grid node distribution strategy; collecting a first ultrasonic data set according to the detection path and identifying an abnormal region; dynamically adjusting the grid density according to the abnormal index of the abnormal region, generating an updated detection path, and collecting a second ultrasonic data set; the first and second ultrasound data sets are combined to form a final detection data set. Through model correction and adaptive path planning, the defect of a fixed point distribution mode is overcome, the transformation from wide screening to accurate focusing is realized, and the defect identification accuracy and the evaluation reliability are remarkably improved.

The present invention relates to the field of welding detection, and in particular to a system and method for detecting welding of the bottom pins of components. The system comprises: acquiring and preprocessing welding point images, further performing edge detection, and obtaining edge response maps; extracting feature points based on the edge response maps, performing shape matching on the extracted feature points, and obtaining shape matching degrees; detecting the electrical performance of welding points, and obtaining resistance values ​​of welding points; calculating welding point electrical performance evaluation indicators based on the resistance values ​​of welding points; calculating the welding quality score of the bottom pins of components based on the shape matching degrees and welding point electrical performance evaluation indicators; and setting evaluation thresholds to judge welding quality. The system solves the technical problems that welding point images are easily affected by noise and changes in illumination when faced with complex welding point images; the traditional feature point extraction and matching methods are not effective in dealing with a variety of shape and scale changes; and the internal electrical performance of welding points cannot be fully evaluated only through appearance detection and shape matching.

To provide a technology to search for a product according to customer needs.SOLUTION: The product search device comprises receiving means for receiving a shape of a product to be searched from input information entered on a terminal device, extracting means for extracting product information about products corresponding to the shape of the product to be searched from a product information database containing information representing the three-dimensional shape of the product and output means for outputting the product information.SELECTED DRAWING: Figure 1

The invention discloses a small-scale workpiece three-dimensional reconstruction method based on laser line scanning and application. The three-dimensional reconstruction method comprises the following steps: analyzing a key surface, and planning a scanning path and a scanning angle; performing multi-view scanning to obtain multi-view point cloud data; preprocessing to obtain preprocessed point cloud data; carrying out point cloud registration and splicing to obtain registration and splicing data; and generating a reconstructed high-precision triangular mesh surface as a three-dimensional reconstruction model. According to the technical scheme of multi-view scanning path planning, collection of point cloud data is more accurate and reliable, and parameters do not need to be frequently adjusted due to working condition changes; meanwhile, a multi-view point cloud registration and splicing mechanism and a point cloud feature extraction architecture of a U-net architecture are adopted, more details are reserved for surface geometric features of workpiece point cloud, meanwhile, a curved surface is implicitly expressed through a symbol distance function, and the method has remarkable advantages for digital-analog comparison of a workpiece with a complex profile. Three-dimensional shape matching and error evaluation can be efficiently and accurately carried out.

Techniques for adjusting the shape of an ion beam are described. Characteristics of a desired beam shape may be defined. The ion beam generator may include beam shaping elements associated with tunable parameters that can be set in combination with each other. A search space for the possible combinations is defined. A set of exploratory points in the search space are measured and used to interpolate a large number of interpolated points based on a regression model. Interpolated points that are associated with low confidence values may be measured. Based on the measured and interpolated points, clusters of tunable parameter combinations may be identified for evaluation. The clusters are evaluated for stability and sensitivity, and one of the clusters is selected based on the evaluation. The ion beam generator may be configured based on the selected cluster.

The invention discloses a robot path recognition method and system, and belongs to the technical field of robots, and the system comprises an acquisition module, a recognition module, a coffee cup shape recognition result acquisition module, a coffee cup position recognition result acquisition module, a determination module, a position posture acquisition module and a path recognition module. The method comprises the following steps: acquiring an environment image including a coffee making area, and performing multi-stage identification and processing on the image, including determining candidate block images of suspected coffee cups, obtaining coffee cup structure standard parameters for shape matching, and identifying a coffee making area range for position judgment. And finally, fusing the shape and position identification results to determine a target coffee cup so as to confirm the moving path of the coffee cup. The method can effectively solve the problem that in the prior art, due to the fact that coffee powder is attached to a camera lens, an image is blurred, coffee cup recognition is inaccurate, and path planning deviation is caused.

The invention provides a three-dimensional effect rendering method and device and electronic equipment, and the method comprises the steps: carrying out the zooming processing of a target surface patch according to the model size of a target three-dimensional model and the camera orientation of a virtual camera, obtaining a zoomed target surface patch of which the size is matched with the model size, and keeping the zoomed target surface patch facing the virtual camera; stretching the scaled target surface patch according to the model shape of the target three-dimensional model to obtain a stretched target surface patch of which the shape is matched with the model shape; and moving the stretched target patch to the position of the target three-dimensional model in the virtual scene, deleting the target three-dimensional model in the virtual scene and rendering the stretched target patch to obtain a rendered target patch so as to simulate the three-dimensional effect of the target three-dimensional model through the rendered target patch. According to the method, the target surface patch is stretched in the camera space according to the visual angle, so that the surface patch fitting three-dimensional effect is realized, and a better three-dimensional effect is realized with extremely low rendering performance consumption.

The application belongs to the field of intelligent human-computer interaction, and relates to a kind of intelligent writing and correcting method and system, comprising: utilizing flexible pressure sensor matrix and coordinate positioning system, the multidimensional data of sensing input pen writing, and constructing four-dimensional writing characteristic space;Adopt three-level correcting system, the logical reasoning verification of answer is carried out through depth semantic understanding model;The three-level correcting system successively includes OCR character shape matching, semantic rectification based on large language model and intelligent correction based on process reward model;Cognitive diagnosis model is introduced, and the degree of hesitation of answering is judged by analyzing answering index;Fusion question solving information, the knowledge point of question is identified using large model, and according to the question answering condition, the weak point of knowledge mastery is inferred;With the intelligent writing capture technology based on multi-modal sensor fusion, the writing information is accurately collected, and the intelligent correcting integrated method is constructed combined with cognitive diagnosis model, the efficient identification and accurate correction of writing content are realized.

The application discloses a power transmission line mountain fire smoke detection method and system, comprising the following steps: for the power transmission channel picture to be detected, a pre-trained semantic segmentation model is used to segment out the mountain fire smoke candidate area in the picture and calculate the semantic segmentation confidence score; for each mountain fire smoke candidate area, the shape similarity score is calculated through a shape matching method, the position confidence score is calculated through a position function, and the color confidence score is calculated through color distribution comparison; the semantic segmentation confidence score, the shape similarity score, the position confidence score and the color confidence score are weighted and summed to obtain the final smoke confidence score, which is compared with a preset threshold to determine whether the corresponding mountain fire smoke candidate area is mountain fire smoke. The technical scheme provided by the application can effectively identify the mountain fire smoke condition in the power transmission line channel picture, and significantly reduce the misidentification conditions such as pond smoke, chimney smoke and cloud and mist, and has a wide application scenario.

The invention relates to a precise infinitesimal displacement photoelectric measurement system and a precise infinitesimal displacement photoelectric measurement method, and belongs to the technical field of photoelectric measurement, and the precise infinitesimal displacement photoelectric measurement system comprises a curvature flow contour extraction module, a geodesic constraint positioning module, a Riemann optimization module and a displacement calculation module. Then parameterized representation and optimization are carried out on the light spot contour by using a curvature flow theory to generate high-quality contour description data; constructing a geodesic distance field based on a differential geometry principle, identifying a local maximum point as a candidate circle center, and evaluating the shape matching degree of each candidate circle center to determine an optimal candidate circle center; converting a sub-pixel positioning problem into an optimization problem on a Riemannian manifold, and determining a target coordinate of sub-pixel precision through gradient descent of a parameter space; finally, target displacement change between adjacent image frames is calculated, a micro displacement measurement result is output, and the displacement measurement precision is improved to 0.01 pixel and is improved by 5-10 times compared with a traditional method.

The application discloses a polygon decomposition method, an electronic device and a computer readable storage medium. The polygon decomposition method comprises the following steps: obtaining a to-be-decomposed polygon of an integrated circuit layout; obtaining a plurality of candidate polygon templates from a template library; performing shape matching processing and polygon update iteration processing on the to-be-decomposed polygon and the candidate polygon templates to obtain a shape matching result; and performing polygon decomposition processing on the to-be-decomposed polygon according to the shape matching result to obtain a trapezoidal set for manufacturing a mask after decomposition. According to the scheme of the embodiment of the application, the polygon in the integrated circuit layout can be efficiently decomposed, thereby reducing the decomposition time consumption and improving the universal applicability.

The present application relates to a kind of far sea wind farm and power grid light weight interaction method, including the pretreatment of power regulation target curve, obtain the trend component, periodic component, random component, shape complexity index, shape descriptor vector and inflection point parameter set corresponding to power regulation target curve;The Fourier coding vector corresponding to the periodic component of power regulation target curve is obtained;Based on the trend component of power regulation target curve, shape descriptor vector and Fourier coding vector and the actual power output curve of real-time acquisition far sea wind farm, obtain comprehensive shape matching degree;Based on the regulation ability dimension reduction coding vector of far sea wind farm and comprehensive shape matching degree, obtain the optimal state estimation of far sea wind farm regulation ability state;Based on the inflection point parameter set of the actual power output curve of far sea wind farm, Fourier coding vector, and optimal state estimation and comprehensive shape matching degree, hierarchical light weight data processing is carried out, and dynamic optimization data package is generated.