113 results about "Acquisition Scheme" patented technology

The invention discloses a marine environment real-time monitoring and early warning system based on machine learning, and relates to the technical field of machine learning. Comprising the steps that an ocean multi-source sensing module collects ocean environment data in real time through a sensor and a combined collection scheme; the multi-source feature extraction module performs time domain, change rate and frequency domain feature analysis on the data to construct a unified multi-dimensional feature vector; the multi-model fusion prediction module outputs a marine environment state vector through dynamic weighting and deviation correction based on a parallel learning architecture of a deep neural network, a long-short-term memory network and a one-dimensional convolutional neural network; and the ocean risk identification and early warning module generates graded and classified early warning information through double study and judgment of a sea condition classifier and an abnormal event detector. According to the method, comprehensive acquisition, deep feature mining, high-precision prediction and accurate early warning of marine environment data are realized, the problems of low prediction precision, risk identification lag and the like in the prior art are effectively solved, and reliable guarantee is provided for marine operation safety.

The invention discloses a dangerous behavior recognition method and device based on multi-source physiological signal fusion, and aims to generate a physiological synchronization value reflecting a heart-brain coupling state by monitoring electroencephalogram and electrocardiosignals and calculating a phase locking value. Strong coupling signal pairs are screened based on physiological synchronization values, abnormal delay propagation paths and cascade mutation points are extracted, and dangerous trigger nodes and high-risk accumulation areas are identified through energy density analysis; the abnormal gradient field is subjected to rotation modulation innovatively through electroencephalogram signals, and a dynamic gradient field is generated to determine a dangerous behavior boundary; establishing an electrocardio resonance matching mechanism to generate a self-adaptive monitoring sequence and a grading early warning strategy; dynamically optimizing resource configuration and constructing a danger convergence field by adopting an adaptive acquisition scheme triggered by rhythm variability; and finally, early warning information is converted into a specific dangerous behavior category based on an accurate identification window, and an omnibearing intelligent monitoring solution is provided for high-risk operation safety management.

The invention provides an edge heterogeneous Internet of Things operation and maintenance chassis data processing method and system. The method comprises the following steps: firstly, according to the types of the multi-source heterogeneous terminals, formulating a unified data acquisition scheme, defining a unified acquired data format, respectively managing and executing a data acquisition task of each multi-source heterogeneous terminal by adopting an asynchronous multi-thread scheduling mechanism, and acquiring and generating corresponding acquired original data; and performing standardization processing on the collected original data in the normal sampling state to generate a multi-source collected data set. And then, according to the type of each multi-source heterogeneous terminal, for the corresponding multi-source acquisition data set, calculating a standardized anomaly score, performing weighted comprehensive processing, generating a comprehensive anomaly score, and determining an anomaly level according to the comprehensive anomaly score. And finally, correspondingly matching the exception level of the multi-source heterogeneous terminal with a preset local protection strategy, executing a local exception protection action based on a matching result, recording exception information and reporting exception alarm information to a remote center platform.

The invention discloses a teaching implementation method based on combination of motion perception and AI driving, and relates to the technical field of education and teaching. The implementation of the teaching method comprises the steps of multi-modal data expansion and acquisition, cross-dimensional dynamic evaluation and cognitive diagnosis, emotion adaptive feedback and intervention, cross-scene learning map construction and capability migration, and whole-process data closed loop and systematic evolution. And the multi-modal data expansion acquisition comprises the steps of dynamic data acquisition, physiological data acquisition, environmental behavior data acquisition and data preprocessing. The method has the advantages that a multi-modal data acquisition scheme of a common mobile phone camera and a built-in sensor is adopted; the system replaces the traditional dance teaching which depends on special three-dimensional modeling equipment and sensor gloves for boxing teaching, reduces the hardware cost, can realize full scene coverage of families, classrooms, outdoors and the like without professional site deployment, and solves the core problems of high hardware cost and limited scenes in the prior art.

The invention discloses a method for constructing a computable road network. Road data in the vector map are extracted, line string data or line segments obtained by splitting the line string data are used as connecting edges, geographic feature codes containing Geohash information are given to starting points and ending points of the connecting edges, and therefore a basic road network map is constructed. And extracting a middle vertex set of the basic road network diagram and an edge attribute set of middle vertex connection edges, and carrying out road network vertex optimization based on edge attributes to obtain an optimized computable road network. Geographic feature codes adopted by the method comprise spatial geographic information and have the characteristics of graph vertex coding, and the constructed road network graph can be used for graph calculation and verification and restoration of road connection relations. Furthermore, in combination with a representation point acquisition scheme provided by the invention, a road network map fusing facilities and equipment can be constructed, so that the application range of the computable road network is expanded. The computable road network constructed by the method is high in operation efficiency and suitable for different production environments.

The invention provides a plant phenotype platform three-dimensional imaging method and device based on multi-sensor fusion, and the method comprises the steps: collecting the original three-dimensional point cloud data of a plant through a plurality of heterogeneous imaging sensors carried on a plant phenotype platform, and carrying out the time synchronization processing and space registration processing. And dynamically calculating the confidence coefficient weight of each data point according to the environment illumination condition, the measurement attribute of each data point in the registration point cloud set and the characteristics of the imaging sensor to which the data point belongs, and obtaining a point cloud set with a point-level confidence coefficient weight. Performing adaptive weighted fusion processing according to the spatial distribution of the point cloud set to generate a preliminary fusion point cloud model; and according to a quality index of the model and a real-time environment illumination condition, dynamically adjusting and calculating a weight parameter of a confidence coefficient weight, and finally outputting an optimized three-dimensional point cloud model after iterative optimization. The defect that a fusion result of an existing plant three-dimensional phenotype accurate acquisition scheme is insufficient in stability and precision in a complex and changeable field environment is overcome.

The invention relates to the technical field of civil engineering detection, and discloses an automatic standard penetration data acquisition system based on the Internet of Things, which comprises a data acquisition module used for acquiring acceleration and vibration data in a test process through a sensor mounted on a standard penetration hammer; the data transmission module is used for transmitting the collected original data to a remote server or a cloud through a wireless communication technology for storage and processing; the data processing module is used for carrying out denoising, normalization, feature extraction and nonlinear dynamic modeling on the acquired signal data to obtain dynamic features of the standard penetration test process; and the data analysis and prediction module is used for analyzing the data based on a deep learning algorithm and predicting the soil bearing capacity and abnormal conditions occurring in the test process. A standard penetration data automatic acquisition scheme based on the Internet of Things is adopted, full automation of data acquisition, transmission and processing is achieved, and the test efficiency and accuracy are remarkably improved.

A digital twinning monitoring method for the full-life health state of a service aircraft structure belongs to the related technical field of digital twinning, and comprises the following steps: firstly, designing a health state data acquisition scheme to obtain health state data in a real flight state; secondly, performing screening extraction and optimization treatment on the health state data, and constructing a flight data-mechanical response data health state data set of a service aircraft structure; thirdly, establishing a flight data-mechanical response data-life monitoring digital twinborn model, and realizing high-precision prediction of the fatigue residual life of a service aircraft structure; and finally, making an inspection and maintenance task intelligent planning scheme, and dividing inspection and maintenance grades based on the fatigue residual life and the fatigue reliability coefficient. According to the method, fatigue residual life prediction and inspection and maintenance task intelligent planning of the service aircraft structure can be realized, a service aircraft structure full-life health state digital twin monitoring process is formed, and full-life health state monitoring and management can be conveniently carried out for the service aircraft.

The invention relates to the technical field of fusion terminals, and particularly provides a fusion terminal data reporting missing rereporting method and system and a medium, and the method comprises the steps: through a reporting task initialization mechanism, when a fusion terminal is started or a task scheme and a table file change, emptying historical data and carrying out initialization again; adopting an acquisition scheme matching strategy based on the matching degree and the interrogation interval to accurately select a target acquisition scheme; in combination with a two-stage compensation mechanism of self-compensation and failure linked list compensation, compensation is scheduled according to protocol timeout in the self-compensation stage, and periodic compensation, forced compensation and redundant data cleaning are executed in the failure linked list stage. Through the above steps, the integrity and reliability of data reporting of the fusion terminal are effectively improved, and the accuracy of collection success rate statistics of the master station is guaranteed.

The invention relates to the technical field of oil and gas pipeline valve inner leakage online diagnosis, and discloses an oil and gas pipeline valve inner leakage online diagnosis method based on voiceprint analysis. According to the method, valve operation voiceprint data are obtained through a distributed interface to construct a feature database, a diagnosis framework is designed according to the database, and a multi-source voiceprint collection scheme is determined. And the voiceprint acquisition terminal acquires a multi-dimensional voiceprint signal according to the scheme, inputs the multi-dimensional voiceprint signal into a model after feature extraction to complete inner leakage level judgment and abnormal mode recognition, and outputs a diagnosis result. A diagnosis result is transmitted to the management optimization module, and diagnosis strategy adjustment is achieved through timestamp calibration, mapping table construction and the like. And a three-level evaluation sub-frame is also constructed to assist diagnosis. According to the method, accurate diagnosis and strategy optimization of oil and gas pipeline valve inner leakage are realized, and the diagnosis management level is improved.

The invention discloses a defect detection method and system for a semiconductor sample, relates to the technical field of semiconductors, and solves the technical problem of low recognition efficiency of partial defects on the surface of a semiconductor caused by an inherent detection scheme of existing semiconductor surface defect detection. Comprising the following steps: acquiring a first image group of a to-be-detected semiconductor sample, and sequentially inputting each detection image in the first image group into a defect identification model to obtain a corresponding identification type and confidence; the defect identification model is obtained through artificial intelligence model training; generating a secondary acquisition scheme based on the identification type and confidence of each detection image; the secondary acquisition scheme comprises a plurality of second camera coordinates and a second shooting direction; acquiring a second image group of the semiconductor sample to be detected; generating an identification result based on the detection images in the first image group and the second image group; and the accuracy of semiconductor surface defect detection is improved.

The invention discloses a distributed intelligent well logging system and a well logging method, and relates to the technical field of intelligent well logging. The distributed intelligent well logging system comprises an intelligent well logging module, a ground intelligent control module and a communication module; the number of the intelligent logging modules is N, and N is an integer larger than 1; the intelligent well logging module is arranged underground and used for collecting, processing and uploading well logging data. The ground intelligent control module is arranged on the ground and is used for receiving and analyzing data uploaded by the intelligent logging module and sending an acquisition scheme to the intelligent logging module; the intelligent well logging module and the ground intelligent control module are in two-way communication through the communication module. The intelligent logging module comprises a data acquisition unit, a first processing unit and a first communication interface unit; the ground intelligent control module comprises a second communication interface unit, an intelligent analysis unit and a control instruction generation unit, underground intelligent preprocessing and ground real-time analysis are achieved through deep fusion of a distributed architecture and an artificial intelligence technology, and an acquisition strategy can be dynamically optimized according to an analysis result.

The invention relates to the technical field of data processing, particularly provides a data acquisition system, method and equipment based on an authorized webpage resource access level and a medium, and aims to solve the problem of low network data processing efficiency. In order to achieve the purpose, the data acquisition system comprises a resource access level acquisition module used for acquiring a resource access level based on webpage response data and webpage serialization characteristics of an authorized target webpage, and a data acquisition module used for acquiring the resource access level if the resource access level is greater than a preset access level. If yes, generating a robot process automation data collection script based on the webpage response data, the webpage serialization features and the resource access level, and obtaining target data of the authorized target webpage based on the robot process automation data collection script; if the resource access level is smaller than or equal to the preset access level, the target data of the authorized target webpage is obtained based on the automatic browser frame and / or the preset data collection interface, and the optimal collection scheme can be dynamically selected.

The invention discloses a gravity dam safety risk management and control method based on a knowledge graph and a large model, and the method comprises the steps: constructing a gravity dam safety risk space-time knowledge graph which comprises an entity layer, a relation layer, an attribute layer and a time-space mapping layer, and achieving the full-life-cycle multi-source data structured association; constructing a knowledge enhanced large model, and embedding the space-time knowledge graph into a reasoning process; real-time and historical data of the gravity dam are collected and preprocessed, and the large model is input; calling a map association relationship and an evolution rule through a large model to complete risk anomaly identification, cause positioning and evaluation; historical cases and industry specifications in the atlas are retrieved, and a management and control decision scheme matched with the current working condition is generated; and collecting scheme execution data, extracting new knowledge and updating the graph. According to the invention, a closed-loop management and control mode is constructed, and the intelligent and refined level of risk management and control is improved.

The application discloses a cooperative flight control method and device based on a weather station and a base station, and a computer readable storage medium, wherein the method comprises the following steps: when an aircraft flies along a preset route, first station position and first station attribute of a weather station are queried and acquired according to current weather data request; when the first station position is in the range of the preset route and the first station attribute is a co-construction station of weather communication, the weather data request is sent to the co-construction station, so that the co-construction station sends the collected weather data to the aircraft; or the weather data request is sent to the independent base station, so that the independent base station acquires the weather data collected by the weather station in the communication range of the independent base station and forwards the weather data to the aircraft. The application realizes an aircraft weather data acquisition scheme based on a weather station and a base station, so that the aircraft can effectively acquire the weather data along the route and ensure flight safety.

The application is specifically a naked eye 3D virtual reality display system and method, and relates to the technical field of naked eye 3D display and virtual reality, comprising: a test pattern generation module; a photoelectric signal acquisition module; a signal phase analysis module; and a rendering parameter compensation module.In the application, the traditional external camera acquisition scheme is abandoned, a photosensitive sensor is attached to the inner side of a display module glass cover plate through optical glue, and a light shielding film and a frame wrapping design are matched, so that external environmental light can be isolated, signal distortion caused by environmental light reflection can be eliminated from the hardware structure; at the same time, a preprocessing circuit and the sensor are integrated at a zero distance, a tunable gain transimpedance amplifier band-pass filter is used to effectively filter out power frequency and high frequency noise, and a sinusoidal gray scale stripe design reduces spectral aliasing.

This application provides an adaptive seismic acquisition scheme generation method and system. The method includes acquiring a high-density seismic acquisition scheme corresponding to the area to be surveyed; calculating the redundancy of each physical point in the high-density seismic acquisition scheme; determining the maximum redundancy of each physical point based on the redundancy and acquisition cost; selecting a target redundancy less than or equal to the maximum redundancy from the redundancy of all physical points, and using the physical points corresponding to the target redundancy as acquisition points; and generating an adaptive seismic acquisition scheme based on the acquisition points. This application calculates the redundancy distribution of seismic data, omitting physical points with high redundancy in high-density acquisition, allowing for better recovery through subsequent reconstruction algorithms. By acquiring only essential key physical points with low redundancy, it significantly reduces the cost of high-density seismic acquisition while achieving high-density acquisition results, which is of great significance for high-precision seismic exploration.

The invention discloses an OBN seismic acquisition excitation point pitch and OBN point pitch parameter determination method, electronic equipment, a storage medium and a device. The method comprises the following steps: acquiring seismic data of a target area; constructing a three-dimensional fine geological model based on the seismic data; calculating a space sampling interval of each target stratum based on the three-dimensional fine geological model; determining a surface element grid of the target area based on the spatial sampling interval; calculating excitation point pitch and OBN point pitch parameters based on the surface element grid to obtain a plurality of excitation point pitch and OBN point pitch parameter combinations; and comprehensively analyzing the plurality of excitation dot pitch and OBN dot pitch parameter combinations, and determining an optimal excitation dot pitch and OBN dot pitch parameter combination. According to the method, the problem of determining the excitation dot pitch and OBN dot pitch parameters in the OBN acquisition scheme design process can be solved, the acquisition parameters are optimized, the imaging precision of OBN acquisition data is improved, and the OBN acquisition cost is reduced.

The embodiment of the invention provides a rendering instruction processing method and device, electronic equipment and a storage medium. The method comprises the steps that an original rendering instruction sequence sent by an engine layer to a target interface layer is obtained, and the target interface layer is used for shielding the interface difference of different graph driving interfaces and sending corresponding rendering instructions to the different graph driving interfaces; parameters corresponding to rendering instructions in the original rendering instruction sequence are obtained, and the parameters and the rendering instructions are stored in an associated mode; determining a target rendering instruction in the original rendering instruction sequence, obtaining rendering target content corresponding to the target rendering instruction, and associatively storing the rendering target content and the target rendering instruction; and updating parameters associated with the rendering instruction based on the rendering target content and the target rendering instruction to optimize the rendering instruction. According to the embodiment of the invention, the universality of the rendering instruction acquisition scheme is improved, and the rendering instruction acquisition scheme and the optimization scheme are simplified.

The application discloses a current collection sensor and railway signal section signal machine, and belongs to the field of devices for measuring current. In order to solve the problems of high single-point failure risk, easy common interference synchronous failure, insufficient high-voltage insulation protection, and mismatch between high-precision design and actual demand of the existing railway signal current collection scheme, the application provides a full-link heterogeneous redundant current collection sensor. The sensor comprises a double induction module, a double heterogeneous collection and conditioning module, a double processing module, and a data fusion output module. The application fundamentally avoids common interference synchronous failure, significantly improves the reliability and high-voltage safety of the system under the premise of meeting moderate accuracy, effectively controls the cost, and guarantees the collection continuity under single-path failure, and is particularly suitable for high-reliability monitoring scenarios of the lighting state of railway signal section passing signal machines.

The present application relates to a method for determining a channel state information (CSI) acquisition scheme, a terminal device and a network device, the method comprising: a network device determining a channel state information (CSI) acquisition scheme corresponding to communication scenario information, the communication scenario information comprising a scenario to which a wireless communication environment between the network device and the terminal device belongs. According to the embodiment of the invention, the corresponding CSI acquisition scheme can be obtained based on the communication scene information, and the CSI acquisition scheme can be better adapted to the wireless communication environment, so that the CSI acquisition scheme achieves better performance.

This invention discloses a cell control method, device, and BMS (Battery Management System) equipment. The method is applied to the BMS equipment, which collects voltage data from multiple acquisition units within the battery pack. Each acquisition unit has acquisition lines connected to its positive and negative terminals, and multiple individual battery cells are connected in series within each acquisition unit. The method includes: acquiring the overall voltage of each acquisition unit; determining whether each overall voltage reaches a preset voltage threshold, where the preset voltage threshold is generated based on the cutoff voltage of the individual battery cell at its corresponding operating state and the number of individual battery cells in the acquisition unit. If the preset voltage threshold is less than the cutoff voltage of the acquisition unit, the operating state is either charging or discharging; if any overall voltage reaches the preset voltage threshold, the corresponding operation of the battery pack is stopped. The technical solution provided by this invention reduces the use of acquisition lines and chips, thereby lowering the cost of the acquisition scheme, while ensuring the safety and reliability of the battery cells.

This invention discloses an automated assessment method for the completeness and proficiency of instrumental performance in graded examination pieces. The method includes: a standard model construction step for the graded examination pieces; a multimodal performance data acquisition step; a completeness assessment step; a proficiency assessment step; and a graded scoring and diagnostic report generation step. Based on preset weights for each grade level, the completeness score and proficiency score are integrated to generate a total graded examination score, and a diagnostic report containing multidimensional assessment indicators and technical obstacle annotations is output. This invention relates to the field of music education technology. It dynamically adjusts the weights of completeness and proficiency according to the grade level, ensuring that the scoring logic aligns closely with teaching principles. It accurately identifies technical weaknesses and provides visual feedback and practice suggestions, enabling the assessment system to also possess teaching assistance functions. The unified technical framework is compatible with four major instrument categories: keyboard, plucked, bowed, and wind instruments. It employs a low-cost audio and video acquisition scheme, requiring no instrument modification and possessing the feasibility for large-scale promotion.

The invention provides a low-altitude situation three-dimensional reconstruction method and device based on multiple view angles of an unmanned aerial vehicle, and the method comprises the steps: carrying out the geographic space classification of the multi-view angle video data of the unmanned aerial vehicle, and obtaining a geographic space importance degree mark; generating a low-altitude situation acquisition scheme for the sub-regions according to the sub-region importance scores to obtain the low-altitude situation acquisition scheme; performing unmanned aerial vehicle low-altitude situation data re-acquisition according to the low-altitude situation acquisition scheme to obtain a multi-view low-altitude situation enhanced video; and sampling the multi-view low-altitude situation enhanced video data and the unmanned aerial vehicle multi-view video data according to different sampling rates according to the sub-region importance score, and performing three-dimensional reconstruction according to the sampled image. And high-precision low-altitude situation reconstruction is performed in a targeted manner.

The invention provides a rail transit deformation monitoring method combined with a BIM model, and belongs to the technical field of BIM model digital data processing. Multi-view image set detection is adopted to replace traditional multi-point total station measurement, and an image processing equation set is utilized to automatically extract rail geometric features and construct a rail geometric matrix; an optimal view set game model is established to automatically optimize an image acquisition scheme to reduce field operation complexity, a double-path cross fusion neural network is constructed to realize intelligent processing and automatic classification of deformation data, and adaptive fusion of the data is realized through a cross influence module and a gating weight function. After training is completed, deformation monitoring can be automatically completed on the basis of simple image input, three-dimensional visual labeling is carried out on the BIM model, and the technical problems that in the prior art, operation is complex and consumed time is long when a large number of devices such as a total station are adopted for track deformation monitoring in track traffic are solved.

The present invention discloses a digital display method and system for art exhibitions, relating to the field of digital display technology. The method comprises generating a point cloud dataset; reconstructing the point cloud dataset into a grid to generate a three-dimensional digital grid of the exhibit; analyzing the material characteristics of the three-dimensional digital grid of the exhibit to extract a material parameter set; collecting the viewer's position coordinates, calculating the relative azimuth between the viewer and the exhibit based on the viewer's position coordinates, and generating a perspective transformation matrix; applying the perspective transformation matrix to the three-dimensional digital grid of the exhibit, overlaying the material parameter set for rendering, outputting a perspective-transformed image of the exhibit, and synthesizing the exhibit image with the exhibition hall background image into a mixed reality scene; and dynamically updating the perspective transformation matrix based on real-time changes in the viewer's position coordinates to regenerate the mixed reality scene. The present invention employs a multi-sensor collaborative acquisition scheme to significantly improve the accuracy of three-dimensional reconstruction. Furthermore, the invention introduces multispectral structured light illumination technology to accurately capture material characteristics.

The present disclosure relates to ultrasound-based strategies and techniques that are specially designed for time-resolved simultaneous cardiac tissue visualization and intracardiac flow instability mapping. First, to achieve high-resolution tissues images while also acquiring flow data, we devised an acquisition scheme which consists of two batches. The first batch is dedicated to tissue imaging, where we transmit a series of diverging waves emitted from different virtual source locations. These pulses have a single pulse-cycle to optimize axial resolution and are coherently compounded for improving lateral resolution. This paradigm generates tissue images with an improved resolution, allowing for real-time guidance at frame rates up to 50 fps. The second batch is dedicated for flow imaging where all diverging waves are transmitted from the same virtual source location. These flow pulses have a 5-cycle pulse length for improved flow signal. The length of this batch can be adjusted, but our experiments use a length of 64. The final transmission scheme alternates between the tissue batch and flow batch.

The invention discloses an ocean variable-density three-dimensional combined seismic acquisition design method, which comprises the steps of S1, determining a geological target of a target region, and establishing a seismic geological model; s2, key acquisition parameters are determined, wherein the key acquisition parameters comprise the requirement for imaging coverage times and the requirement for offset distance of full-waveform inversion speed calculation; s3, towing cable shot point and detection point density design, OBN shot point and detection point density design and OBN detection point density encryption design; s4, forward modeling of rotation waves of the seismic geologic model is carried out, and rotation wave analysis is carried out in key areas; s5, determining a standard OBN sparseness requirement and an OBN sparseness encryption requirement; s6, variable density sparse OBN layout design is carried out; and S7, a towing cable and variable density sparse OBN three-dimensional joint acquisition design scheme. The method can be used for guiding target area collection design, OBN node variable density design is carried out in a targeted mode, and on the basis that the quality of collected data is guaranteed, the equipment investment is effectively reduced, the collection operation efficiency is improved, and the exploration cost is reduced.

The invention discloses a fault detection method in 3D printing, and relates to the technical field of printing fault detection.The method comprises historical fault data analysis and real-time state data detection.The method comprises the steps that historical fault data of a 3D printer is collected firstly, and the maintenance weight is determined through an analytic hierarchy process in combination with multi-dimensional state parameters and fault data; then objective weights are determined based on data discrete characteristics through an entropy weight method, final weights of state parameters are obtained through weighted fusion, and then a fault monitoring scheme containing a state collection scheme and a state analysis scheme is formulated; according to the method, the scientificity of importance judgment of the state parameters is improved through double-weight fusion, the accuracy and timeliness of fault detection are improved through differential collection and multi-dimensional data analysis, the rate of failure report and false report of 3D printing faults is effectively reduced, and the accuracy and timeliness of fault detection are improved. The printing process stability is ensured.

This invention relates to the field of data processing technology and discloses a method, device, equipment, and storage medium for monitoring violations during bridge construction. By acquiring the planned time period for each construction procedure in each bridge construction section, the effective monitoring time period for each construction monitoring point is determined. Based on the monitoring type information and monitoring risk level of each construction monitoring point, and constrained by the image acquisition distance range corresponding to the monitoring type information and the image acquisition frequency range corresponding to the monitoring risk level, with flight distance as the optimization objective, an optimized solution for the UAV image acquisition path planning strategy is obtained. This strategy controls the UAV to execute flight, image acquisition, and judgment of bridge construction violations. By proposing UAV image acquisition schemes that meet the different monitoring distances and frequencies required for different construction procedures, the accuracy and efficiency of monitoring violations during bridge construction are improved, while extending the monitoring time of the UAV for violation monitoring, demonstrating good scenario adaptability.