566 results about "Calculation algorithm" patented technology

The invention discloses a large model prompt project optimization system and method fusing a domain knowledge graph. The system comprises an analysis module, a template generation engine module, a large model interaction interface module, a feedback analysis module and an optimization strategy module. And the analysis module forms a constraint coding signal containing an entity attribute incidence matrix. The template generation engine module forms an enhanced prompt text stream with a reservoir physical property parameter slot; the large model interaction interface module receives the enhanced prompt text stream and generates a question and answer response data stream containing geological terminologies; the feedback analysis module forms a feedback signal containing semantic deviation measurement through a semantic error vector calculation algorithm; and the optimization strategy module forms a parameter optimization instruction signal and transmits the parameter optimization instruction signal to the analysis module to complete iterative updating of the constraint condition. According to the large model prompt project optimization system fusing the domain knowledge graph, the problem of low answer accuracy of a large model in the oil-gas exploration field due to lack of professional constraints can be solved.

The invention relates to the technical field of information, and discloses a ciphertext execution exception handling method and system for a privacy computing algorithm, which quantifies the data query sensitivity of each tenant by collecting differential privacy query parameters of a plurality of tenants, and performs time sequence analysis on the sensitivity quantification result by using an ARIMA model to predict the future trend of the tenant, so as to improve the accuracy of the ciphertext execution exception handling of the privacy computing algorithm. The residual error between the actual sensitivity and the predicted sensitivity is calculated to identify abnormal tenants; a sliding window method is adopted to extract statistical features of the abnormal tenants to construct a feature set, and clustering analysis is carried out on the feature set to identify abnormal modes and abnormal fingerprint feature clusters corresponding to the abnormal tenants; and training a model based on the positive and abnormal fingerprint feature clusters of the abnormal tenants, and quantifying the influence degree of each abnormal mode on the privacy protection level of the abnormal tenants by using the model, so as to adjust and execute the privacy budget allocation proportion of each abnormal tenant according to the obtained quantitative analysis result. And therefore, the exception in the ciphertext execution of the privacy calculation algorithm can be effectively processed.

The embodiment of the invention discloses a bridge crack width monitoring method. The method comprises the following steps: acquiring a continuous video image of a bridge surface; generating a pixel-level segmentation mask image of the crack by using the target detection model; when the target detection model is pre-trained, optical flow features between adjacent frames in the first data set are extracted through an optical flow calculation algorithm, and deep fusion is performed on the optical flow features and the image features; contour pixel points of the crack are extracted based on the crack segmentation mask pattern, and the width change information and the width change rate of the crack are obtained; according to the width change information and the width change rate, performing trend prediction on the crack width change by using a time sequence prediction model to obtain a prediction result of the crack width change; in the training process of the time sequence prediction model, a basic model and a complexity capture module are designed, and the weight of a main model is optimized by using a weighted fusion strategy. According to the invention, efficient and accurate crack width monitoring is realized through crack identification and prediction.

The present invention relates to the technical field of calculation, estimation or counting. Disclosed is a critical path sorting method based on a graph neural network. The method comprises: first, obtaining a potential critical path set in a netlist by means of a static timing analysis tool; next, converting a netlist file comprising circuit function information into a graph data structure, and obtaining an initial training set on the basis of a relevant process configuration file; then, inputting the initial training set into a graph neural network for training to obtain a critical unit prediction model, wherein the critical unit prediction model consists of three parts, namely, a deep structure auto-encoder, a nonlinear attribute auto-encoder and a joint error reconstruction module; and finally, quantifying the criticality of each path in the potential critical path set on the basis of critical unit information and a path criticality calculation algorithm in the netlist, and obtaining a critical path sequence under process awareness. According to the method, critical paths in circuits influenced by process deviations can be effectively sorted, providing valuable reference for circuit optimization.

The invention relates to the technical field of disaster prediction and early warning, in particular to a rural water supply project drought disaster prediction and early warning method and system. The method comprises the following steps: acquiring a hydrological data set; performing data preprocessing on the hydrological data set to generate a hydrological core processing data set; performing data feature extraction on the hydrological core processing data set to generate a hydrological feature data set; quantifying the hydrological characteristic data set to generate a multi-water-source drought early warning threshold calculation algorithm; constructing a multi-dimensional interaction model by using a multi-water-source drought early warning threshold calculation algorithm in combination with the hydrological characteristic data set, and generating a multi-source hydrological drought early warning and prediction model; therefore, by optimizing hydrological data processing and early warning threshold calculation, the problem of inaccurate prediction caused by inconsistent multi-source data in a traditional early warning system is solved, and the accuracy and reliability of early warning of drought disasters are greatly improved.

The invention relates to the technical field of safety management, in particular to a safety management early warning method and system based on the digital twinning technology, and the method comprises the following steps: collecting the entity state data of a plurality of physical entities in a campus, and constructing a digital twinning model containing the entity state data; defining a current scene risk factor, and analyzing the interaction influence between the scene risk factors by performing simulation interaction influence analysis between the scene risk factors in the digital twin model; based on a simulation interaction influence analysis result, constructing an incidence matrix between risk factors, establishing a dynamic association graph between physical entities, and evaluating the weight of each node and edge through a graph calculation algorithm; and calculating a comprehensive risk score according to the dynamic association graph, and setting multi-level early warning levels. According to the method, real-time dynamic modeling of risk factors is realized, limitation of traditional single entity monitoring is avoided, a dynamic association graph based on data driving is provided, and risk propagation and influence ranges among physical entities are accurately described.

The invention discloses a three-dimensional model lightweight reconstruction and rendering method based on multi-strategy collaboration, and the method comprises the steps: 1, extracting geometric information, appearance information and semantic attribute information of a three-dimensional model, separating the geometric information from the appearance information and the semantic attribute information, and storing the semantic attribute information to a three-dimensional model database; 2, instantiating components with the same geometric structure in the three-dimensional model, realizing material sharing through a material reference mechanism, and reducing rendering overhead on the premise of not changing the structure of the model; step 3, carrying out lightweight processing on the exported geometric and appearance information to obtain reconstructed lightweight models with different precision grades; and 4, dynamically adjusting the geometric complexity of the lightweight model through the sight distance and the frame rate by using a hierarchical calculation algorithm for rendering, and meanwhile, obtaining component semantic attribute information and synthesizing the semantic attribute information by calling a three-dimensional model database interface to realize visual display of the reconstruction model.

A water and soil loss pattern spot landing system based on land utilization information weak constraint comprises a land utilization information acquisition module, a factor evaluation and analysis module, a time sequence analysis and pattern spot landing module and a data integration and visualization module. The factor evaluation and analysis module is used for calculating a water and soil loss erosion modulus and evaluating and analyzing influence factors, the time sequence analysis and pattern spot landing module is used for analyzing water and soil loss changes and generating landing pattern spots, and the data integration and visualization module is used for data integration and pattern spot visualization display. According to the water and soil loss pattern spot landing system based on the land utilization information weak constraint, an erosion modulus calculation algorithm based on data fusion and pixel unmixing is proposed to calculate an erosion modulus, and a water and soil loss pattern spot change analysis algorithm based on time sequence classification is proposed to analyze pattern spot change.

The invention relates to the technical field of network attack defense, and discloses a network attack countering method and device, computer equipment and a storage medium, and the method comprises the steps: constructing a network security knowledge graph through employing historical attack event data; mining an association relationship among key entities in the historical attack event data by using a graph embedding algorithm; screening the association relationships by using a similarity calculation algorithm to obtain a historical attack event data set with the highest similarity with the current security event data in each dimension; and mining an association path between the current security event data and the historical attack event data set with the highest similarity by using the network security knowledge graph, and integrating to obtain countering information corresponding to the current security event data. According to the method, the key entities of the network attack event and the incidence relation of the key entities are deeply mined, the insight ability for the attack mode is remarkably improved, the counterattack strategy information for the network attack event is efficiently mined, and accurate counterattack of the network attack event is realized.

The present invention provides a method, system, device and medium for automatically cataloging RQD of drilling cores, which belongs to the field of underground engineering drilling engineering informatization. The system of the present invention includes an image acquisition module, an image preprocessing module, an RQD calculation module and a cataloging module. The present invention collects core box images in batches in a standardized manner, uses a semantic segmentation network and a projection transformation to correct the distortion of the core box images, and then uses semantic segmentation to mark core blocks of 10CM and above, sorts the recognition results and calculates the RQD; uploads the on-site collected images to the cloud, and integrates the core box image correction and RQD calculation algorithm in the cloud, and performs image data storage, RQD calculation and RQD database cataloging in the cloud to achieve digitalized and standardized data backup. The technical solution of the invention can efficiently and standardizedly digitize and store core information, reduce the cost of mine data storage, improve data utilization, and provide data basis for mine rock mass quality evaluation.

The invention relates to the field of fault early warning, in particular to a fault early warning method for a tailing paste filling system. Comprising the steps of monitoring and storing parameters in real time to form a parameter matrix; a sliding time window technology is introduced, standardization processing is carried out on the parameters at each moment, and standardized parameter values are obtained; on the basis of the standardized parameter values, a dynamic feature extraction algorithm is adopted for processing to obtain feature values; based on the characteristic value, a fault probability value is calculated through a dynamic gain adjustment fault probability calculation algorithm, the fault probability value is compared with a fault threshold value, and a fault judgment result is obtained; according to the characteristic value and the fault judgment result, a saliency score is calculated through a fault positioning algorithm, and a fault source is determined according to the saliency score; and performing fault early warning based on the fault source. The technical problems that in a tailing paste filling system, multiple monitoring points exist, so that real-time data processing becomes complex, and unified comparison and analysis are difficult to conduct are solved.

The invention relates to an intelligent multi-source autonomous navigation system, and belongs to the field of navigation and guidance. The system comprises a multi-source sensing measurement module which is integrated with a plurality of navigation sensors and outputs observed quantity for navigation and positioning; the information processing module is used for receiving observed quantities of multiple navigation sensors and obtaining navigation positioning information of a carrier by adopting corresponding navigation calculation algorithms, and a combination of a single navigation sensor and the corresponding navigation calculation algorithm is recorded as a single navigation information source; according to navigation task requirements, evaluating navigation positioning information output by each single navigation information source to obtain an optimal navigation information source configuration scheme in a current task and a current scene, screening out an optimal information fusion algorithm suitable for optimal navigation information source configuration from a stored navigation algorithm library, and carrying out information fusion according to the optimal information fusion algorithm. And carrying out multi-source fusion on the output of the optimal navigation information source by adopting an optimal information fusion algorithm to obtain an optimized navigation positioning result.

The invention relates to an integer decomposition method based on a quantum approximate optimization algorithm, and belongs to the technical field of password decoding. The method comprises the following steps: constructing clauses to describe an optimization algorithm for decomposing an RSA key M, wherein M is an integer; constructing a parameterized quantum circuit based on the clauses; solving parameters of the parameterized quantum circuit based on a quantum approximate optimization algorithm, and measuring a final quantum state; the quantum state measurement result is mapped into two factors P and Q of an RSA key M, and P and Q are used for calculating private keys of an RSA algorithm. According to the method, the key integer decomposition optimization problem is described by adopting the parameterized quantum gate circuit, and the method is easy to implement and expand on a general quantum computer.

The invention relates to the technical field of intelligent prevention and control of agricultural pests, in particular to a monitoring, trapping and killing method for field fruit fly pests, and adopts the technical scheme that the top is fixed through an adjustable hook, the pests are attracted by a food attractant to be in contact with an annular pulse power grid, the shot-down pests enter a pest receiving device through a funnel, and the quantity is counted in real time by an infrared counter; the adjustable hook is provided with an anti-rotation buckle structure, the tail end of the anti-rotation buckle structure is integrated with a spiral anti-bird thorn, the hanging stability is improved, a solar panel is adopted for automatically tracking illumination, the electricity utilization cost is saved, and potential safety hazards are reduced; a food attractant constant-temperature slow-release system is constructed through a PTC constant-temperature heating piece, the optimal volatilization temperature is maintained, the trapping and killing efficiency is improved, real-time analysis and remote transmission of insect situation data are supported through an environment sensor and an edge calculation algorithm, and the problems that a traditional trap is low in efficiency, high in mistaken trapping rate, lagged in data feedback and the like are solved. The method is suitable for precise monitoring and green prevention and control of field fruit flies.

The invention discloses a privacy protection effect evaluation method and system, and the method comprises the steps: carrying out the hierarchical analysis of a privacy protection effect evaluation index system, defining the definition and calculation boundaries of four first-level dimensions, i.e., data features, compliance, availability and safety, and subordinate second-level indexes, carrying out the adaptation of a calculation algorithm for different types of indexes, and carrying out the weighted integration of the second-level indexes through employing an analytic hierarchy process, thereby achieving the evaluation of the privacy protection effect. Multi-dimensional quantitative evaluation is realized; an index association rule base and a matrix are constructed through static analysis and dynamic mining, and linkage analysis is achieved; determining an index fluctuation reference according to scene characteristics and historical data, converting user demands into a variation amplitude of a fluctuation reference unit, and realizing index dynamic linkage updating based on an incidence matrix; and finally, the optimization rule is verified through simulation testing and historical data backtracking, and a dynamically adaptive and self-iterative optimization relation rule system is formed, so that the limitation of traditional evaluation is broken through, a scientific basis is provided for privacy protection strategy optimization, and the privacy governance efficiency is improved.

The invention discloses a geotechnical engineering catastrophe dynamic real-time intelligent early warning method and system based on displacement monitoring, and the method comprises the steps: collecting the real-time displacement data and related parameters of a geotechnical engineering region through displacement monitoring equipment, and transmitting the real-time displacement data and related parameters to a bank slope stability evolution analysis platform to establish a multi-dimensional database; calling a fractured rock mass effective stress analysis model to calculate rock mass effective stress distribution characteristics, and inputting a multi-grid sliding surface stress calculation algorithm to obtain a potential sliding surface stress state and a critical threshold value; inputting the sliding surface stress parameters and the displacement data into a multi-field coupling analysis learning prediction model to obtain a displacement evolution trend and a catastrophe risk coefficient; and finally, real-time early warning information is generated and fed back through the catastrophe dynamic real-time intelligent early warning module. The method improves the real-time performance and accuracy of early warning, can effectively guarantee the safety of geotechnical engineering, and is suitable for catastrophe early warning scenes of geotechnical engineering such as bank slopes and foundation pits.

The invention discloses a multi-device collaborative passenger flow statistical method and system, and the method comprises the following steps: presetting a unique identity label and a physical position index for devices, reading the unique identity label and the physical position index, and initializing the attribute information of the devices; a user datagram protocol broadcasting mechanism is started, and heartbeat information including the unique identity label, the physical position index and the online state is sent according to a preset period; monitoring the user datagram protocol broadcast message in the local area network, constructing and maintaining an online equipment list, and updating the online state of the equipment according to the heartbeat information receiving analysis condition; judging adjacent equipment based on a physical location index, and deciding whether to start a first boundary or a second boundary according to the online state of the adjacent equipment; and the decision result is transmitted to a passenger flow statistical algorithm to generate a shop-crossing detection line. According to the invention, multi-device collaborative passenger flow statistics dynamic boundary configuration is realized, the shop-crossing detection line is accurately generated, and the passenger flow statistics problems of fixed boundary configuration, easy missed counting and poor multi-device collaboration are solved.

The invention belongs to the technical field of informatization management, and particularly relates to a data import method based on similarity calculation, automatic matching of file fields and database fields is realized by calculating the similarity of the file fields and the fields in a database, and the workload of manual configuration can be effectively reduced; a common editing distance calculation similarity algorithm is improved, the influence of the longest common subsequence on similarity calculation is considered, a similarity calculation formula is improved, and the matching success rate is increased; when the similarity is calculated, literal matching and semantic matching can be carried out by adopting a method of combining an improved editing distance similarity calculation algorithm and word semantic similarity calculation based on the Zhinetting, so that the matching success rate is effectively improved; besides automatic matching, a user configuration interface is provided, a user can manually adjust the mapping relation, and the flexibility and usability of the method are improved; user configuration content can be automatically recorded, and repeated configuration work of a user is avoided.

The invention discloses an industrial printer ink-jet control system based on negative feedback control, and relates to the technical field of industrial printers. The ink-jet control system for the industrial printer based on negative feedback control comprises a data input processing module which is responsible for receiving printing data input by a user, converting the printing data into a format which can be identified by the printer, and carrying out preliminary optimization and arrangement on the data at the same time; the data input processing module is connected with a high-speed data transmission module, and the high-speed data transmission module is connected with a sensor monitoring module, a feedback signal processing module, an optimization algorithm control module and a distributed local control module. The calculated amount can be reduced and the time required by deviation calculation can be shortened by simplifying the deviation calculation algorithm, and the deviation can be predicted and adjusted in advance by the predictive control algorithm, so that the system can quickly cope with the change of the ink jet state, and the printing efficiency and quality are improved.

The invention discloses a customer portrait analysis method and system based on a knowledge graph, and the method comprises the steps: S1, collecting a user behavior event flow and an external environment event flow, and generating a dynamic event signal carrying a timestamp based on a heterogeneous data source; s2, responding to a dynamic event signal, and analyzing an event type to trigger incremental updating operation; s3, in response to the real-time graph updating signal, updating the feature vector of the user node through an incremental graph calculation algorithm to generate a portrait updating signal; s4, generating a graph updating instruction and a portrait recalculation instruction to form a cooperative control signal; and S5, feeding back a graph updating instruction in the cooperative control signal to an incremental updating operation step, and feeding back a portrait recalculation instruction to a feature vector updating step to drive a real-time cooperative closed loop. According to the air quality intelligent monitoring method and system based on sensing data feedback, the problems of client portrait hysteresis quality and low map-portrait cooperation efficiency can be solved.

The invention discloses an indoor research and development test platform for a multi-rotor unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicle testing, the indoor research and development test platform comprises a test bench, a main control unit is arranged on the test bench, the main control unit is provided with a flight path resolving algorithm, and the test bench comprises a rectangular cubic frame. An annular outer ring is arranged in the rectangular cubic frame in a connected mode through a three-degree-of-freedom rotating shaft connecting piece and a frame body connecting plate, and an annular middle ring is arranged in the annular outer ring in a connected mode through a three-degree-of-freedom rotating shaft connecting piece and a ring connecting piece. The interior of the annular middle ring is connected with an annular inner ring and an annular outer ring which serve as unmanned aerial vehicle connecting plates through three-degree-of-freedom rotating shaft connecting pieces and fixing grooves, magnetic encoders are arranged on the middle ring and the inner ring, and meanwhile the cubic frame and the outer ring, the outer ring and the middle ring and the middle ring and the inner ring are connected through conductive sliding rings; according to the invention, an indoor unmanned aerial vehicle testing environment which is safe, reliable, accurate in data, simple to operate, friendly in interface, visual and efficient can be provided for users.

The invention provides a method and a device for generating a customized report of an SAAS (Software as a Service) system based on dynamic template configuration. The method comprises the following steps: acquiring a customized visual report template for realizing business data decoupling; editing the report template based on a preset editor, and generating a template configuration file; analyzing a structured marker in the template configuration file to generate a metadata description file; querying a business database through a unified data interface according to a data requirement defined by the metadata description file, and obtaining and assembling customized business data corresponding to the tenant ID; and at least based on the customized business data, controlling a rendering process through a dynamic position calculation algorithm, and dynamically filling the data to a corresponding position of the report template to generate a customized report. According to the method, the problems of code redundancy and difficulty in maintenance of the SAAS multi-tenant report are solved, zero code configuration is realized, and report generation efficiency and tenant personalized adaptation capability are improved.

The invention relates to a two-dimensional image and geometric constraint-based cargo stack three-dimensional pose detection method and device, which are applied to the technical field of computer vision and logistics automation, and comprises the following steps of: through an edge straight line screening strategy, combining robust fitting of a random sampling consistency algorithm, calculating a three-dimensional pose of a cargo stack; a real physical boundary can be effectively and accurately recognized from complex visual interference such as adhesive tape, labels and printed patterns on the surface of a container, the accuracy and robustness of edge detection are remarkably improved, and therefore the high precision of final three-dimensional pose calculation is guaranteed; and secondly, only a common industrial camera is needed, and an expensive three-dimensional sensor such as a laser radar or a depth camera is not needed, so that the hardware cost and the maintenance complexity of the system are greatly reduced, and the cost benefit is extremely high. And thirdly, an efficient image processing and geometric calculation algorithm is mainly adopted, the calculation complexity is low, and the requirement for real-time detection of the goods stack on an industrial automatic assembly line can be met.

The invention discloses a real-time data integration and analysis system based on cloud computing, particularly relates to the technical field of data analysis, and aims to solve the problems caused by insufficient real-time processing of multi-source and heterogeneous data and dynamic resource allocation in the prior art. Real-time data from different data sources are acquired and preprocessed through a real-time data acquisition module, and a real-time data analysis module performs windowing calculation and joint aggregation operation by using a distributed calculation algorithm to generate an intermediate analysis result; the tenant resource scheduling module evaluates the resource allocation equilibrium state of the computing node based on the intermediate analysis result, and dynamically adjusts the task scheduling strategy under the support of the task scheduling adjustment module; and finally, the analysis result extraction module further processes the intermediate analysis result to realize integration and efficient analysis of real-time data. The system has strong heterogeneous data processing capability, can optimize computing resource allocation in a multi-tenant environment, and ensures high-precision real-time data analysis and decision support.

The invention relates to the field of data query, and discloses a data aggregation query method and system based on time dimensionalities, the method comprises the following steps: obtaining a data aggregation query request, the data aggregation query request at least comprising a time index table of the time dimensionalities, the time dimensionalities being represented by at least one of year, month, day, hour and minute; analyzing the data aggregation query request, and determining an aggregation granularity, a date index value and an aggregation step length in a time index table; performing aggregation calculation according to the aggregation granularity, the date index value and the aggregation step length, and determining an aggregation date index; and performing field matching in a database through the aggregation date index, and performing grouping aggregation on matching results to determine a data query result. Indexes are added for different aggregation dimensions by creating a date index table, and an index calculation algorithm is combined, so that multiple time dimension query requirements are met, the data query speed can be remarkably increased, consumption of calculation resources is reduced, and the query flexibility is improved.

The invention discloses a visual detection precision improving method and system based on a high-resolution image. The system comprises a plurality of modules such as image acquisition equipment, a lighting system, an image processing unit and a mechanical positioning system. The image acquisition equipment adopts a high-precision industrial camera to acquire high-resolution images, and the illumination system provides uniform and adjustable illumination. Through the steps of image preprocessing, gradient calculation, Canny algorithm application and the like, the edge and geometric features of a detected object are accurately extracted, and size measurement, precision evaluation and defect detection are achieved. The visual detection precision can be effectively improved, the method is widely suitable for detection of various products such as automobile parts and electronic products, dimensional deviation and defects can be found in time, the production efficiency and the product quality are improved, and the method has important practical value and wide application prospects.

The invention discloses a rock shear seepage coupling true triaxial test system, which relates to the technical field of rock mechanical tests, and comprises a host, a sigma 1 / sigma 2 direction loading module, a sigma 3 direction confining pressure module, a pressure chamber auxiliary system, a sample clamp, a pore water seepage system, a temperature system, a control module and a data acquisition and processing module, through servo closed-loop linkage double-pump loading in the sigma 1 / sigma 2 direction, synchronous output of the double pumps and coordination of pressure supply of the two oil cylinders by the controller, a strain correction algorithm is combined, stability of a stress loading center is guaranteed, strain measurement accuracy is improved, confining pressure is accurately controlled in the sigma 3 direction through a double-balance pressure chamber and a pressure regulation algorithm, and the stress measurement accuracy is improved. The pressure chamber is in full-automatic operation, manual steps are omitted, errors are reduced, efficiency is improved, a stress-free blank angle clamp eliminates friction interference, a seepage system supports a double-loading mode, a control module achieves multi-control-mode impact-free switching, a data processing module is combined with an elastic modulus calculation algorithm, rock mechanical parameters are accurately obtained, and the multi-field coupling test requirement is met.

The invention discloses a mineral powder volume measuring and calculating method based on three-dimensional shape data analysis, and relates to the technical field of mineral powder volume measurement. The method comprises the following steps: carrying out mineral powder pile scanning based on a mineral powder pile scanning module, and collecting three-dimensional point cloud data; preprocessing the collected point cloud data based on a point cloud preprocessing module; reconstructing the preprocessed point cloud data by using a three-dimensional reconstruction algorithm based on a mineral powder three-dimensional structure model construction module; based on the volume calculation module, performing mineral powder volume calculation by using a volume calculation algorithm based on voxel representation; and analyzing a calculation result. The method has the beneficial effects that the method has high automation and accuracy, the automatic processing and analysis process reduces manual intervention, the measurement accuracy and reliability are improved, the deep learning algorithm is applied, the capability of data processing and complex structure analysis is optimized, the method is suitable for mineral powder of different shapes and sizes, and the method is suitable for large-scale popularization and application. The method can be popularized to other industries requiring accurate volume measurement and shape analysis.