173 results about "Data archival" patented technology

The invention relates to a copper-clad plate layering defect diagnosis method based on pattern recognition, and the method comprises the steps: forming a rich input sample set through spatial multi-channel imaging, variable illumination and time sequence synchronous sampling in order to solve the problems that the recognition capability of tiny layering defects is weak, and the recognition is easily influenced by noise and environment interference in the existing detection; according to the method, an attention mechanism and small sample discrimination are combined, high-confidence-coefficient defect identification is realized, region self-adaptive re-detection is further triggered in real time to reduce the missing detection risk, and finally defect distribution mapping is automatically generated and data archiving and traceability analysis are supported.

The invention discloses an automatic fastening system and method for overhead line system cantilever bolts. The system comprises a maintenance car, a visual ranging parking unit, a laser radar sensing unit, a mechanical arm execution unit, a force feedback control unit, a tail end execution unit, a digital twin unit and an operation management platform. The method comprises the following steps: S1, guiding a maintenance car to stop below a cantilever of the overhead line system; s2, scanning an overhead line system cantilever, generating a three-dimensional model and positioning a bolt; s3, planning a collision-free path; s4, smooth alignment of the bolt sleeve is achieved; s5, bolt fastening is completed according to the preset torque; s6, synchronously displaying the operation progress, and storing whole-process operation data; and S7, performing anomaly detection and task continuous transmission on the whole process, and performing data archiving and early warning. Intelligent and automatic bolt fastening operation is achieved for the first time in the field of railway contact network maintenance, and an effective solution is provided for improving the railway operation and maintenance efficiency and safety.

The invention discloses a self-correction structured bid evaluation guide method for public resource transaction, and relates to the field of resource transaction processing, the method is based on a bid evaluation system, and the method comprises a data preprocessing unit, a structured analysis unit, a rule unit, an intelligent evaluation unit, a workflow management unit, a report generation unit and a data filing unit. Historical similar project scoring data is analyzed based on a large language model through an intelligent review unit, a real-time scoring reference interval is generated, expert experience and data driving are combined, professional judgment is reserved, scoring randomness is reduced through data quantification, a workflow management unit adopts an LSTM neural network to construct a review behavior prediction model, and the review behavior prediction model is used for predicting the review behavior. According to the method, the degree of deviation between expert scores and predicted values is compared in real time, meanwhile, multi-party review cases are integrated based on federal learning to form a dynamic knowledge base, review after the event is changed into real-time monitoring and intelligent intervention, the objectivity of bid evaluation is enhanced, and subjective item scores tend to be standardized.

The invention relates to the technical field of bridge engineering construction, in particular to a bridge deck concrete flatness detection and correction method, which comprises the following steps: synchronously acquiring bridge deck point cloud, elevation and crack data through a three-dimensional laser scanner, a laser profiler and an ultrasonic sensor, and fusing to generate a three-dimensional digital model; defects such as local protrusions and wave deformation are recognized based on an intelligent analysis algorithm, causes are analyzed, and correction process parameters such as milling, cladding, grouting or ultrathin layer pouring are generated in a targeted mode; operation is executed through equipment such as a finish milling machine, closed-loop control is realized by combining real-time monitoring of a laser profiler, and finally, a traceable digital file is formed through laser detection, inspection and acceptance of an unmanned aerial vehicle and data archiving. By means of the method, the pass percent of the flatness of the bridge floor can be increased to 94% or above, the maximum height difference is controlled within 3 mm, the maintenance period of the bridge is prolonged, and the maintenance cost is reduced.

The invention relates to the technical field of power grid load prediction, in particular to a power grid load prediction and dynamic scheduling optimization method based on big data. Comprising the following steps: preprocessing power grid multi-source data; constructing an attention enhanced load prediction model, extracting time sequence load features through an LSTM network, and screening key influence factor features through a random forest; generating a layered constraint improved whale optimal scheduling scheme; real-time closed-loop adjustment is carried out; and data archiving and tracing. According to the method, the attention enhanced load prediction model is constructed, the time sequence load features are extracted by using the LSTM network, the key influence factor features are screened by using the random forest, the attention mechanism is introduced to highlight the power consumption peak period feature weight, and the Adam optimizer training and precision verification are combined, so that the load change rules of different periods can be more accurately captured, and the load prediction accuracy is improved. And the adaptability of the load prediction result and the actual power grid operation condition is improved.

The present disclosure proposes a liquid cooling system with leak protection and method for cooling liquid leak protection. The liquid cooling system is adapted to a server system including a rack and a server. The liquid cooling system includes: a cooling distribution unit (CDU), a liquid detector, a local leak management device and a central leak management device. The CDU distributes coolant to a cold plate disposed inside the server through a manifold and a water valve. The liquid detector is disposed inside the sever and configured to generate a server leakage event. The local leak management device is disposed inside the rack and configured to control the sever to shutdown after data archiving, close the water valve and output a server leak notification after receiving the event. The central leak management device controls the CDU to reduce a flow rate distributed to the cold plate based on the notification.

The invention relates to the technical field of unmanned vehicle scheduling and charging management, and discloses an unmanned vehicle remote non-inductive scheduling and multi-vehicle cluster charging cooperative management system, which comprises a cluster state sensing module, a multi-vehicle cluster charging cooperative management module, an unmanned vehicle remote non-inductive scheduling module and a multi-vehicle cluster charging cooperative management module, the scheduling feature analysis module performs modeling analysis on the two types of flows to generate feature sets; the collaborative decision-making module is used for matching scheduling strategy levels based on strategy matrix fusion features; the charging strategy generation module calls a charging strategy according to the grade; and the central processing unit verifies and generates a final instruction set. The system is further provided with a communication relay interface, a charging pile dispatching module and the like, and data transmission, charging optimization, instruction execution and data archiving are achieved. The system improves unmanned vehicle cluster scheduling and charging cooperation efficiency, is suitable for large-scale management, and has the advantages of being high in real-time performance, accurate in decision making and the like.

The invention relates to the technical field of environment-friendly production equipment control, and discloses a multi-equipment cooperative dust removal control system for an environment-friendly production line. The system comprises a dust data acquisition module for acquiring and dividing operation data flow of production line equipment; the dust state reconstruction module is used for generating a dust and airflow distribution situation map; the dedusting efficiency evaluation module is associated with the situation map to determine a dedusting level; the regulation and control strategy generation module is used for matching control strategies; and the cooperative control unit performs bidirectional verification to generate a cooperative dust removal instruction. The system is also provided with an industrial communication gateway for realizing protocol interaction, an equipment linkage module for optimizing a dust removal process, an instruction issuing module for controlling equipment operation, and a data archiving module for storing data and generating a record chain. The system can comprehensively collect dust data, accurately evaluate the dust removal efficiency, efficiently cooperate with multi-equipment dust removal, improve the dust removal effect and management level of an environment-friendly production line and reduce energy consumption, and has a good application prospect.

The invention relates to the technical field of data archiving, and comprises a big-data-oriented cloud multi-modal data dynamic archiving system which comprises a storage topology monitoring module, a storage hierarchy dynamic adjustment module, a data writing task decomposition module, a data consistency verification module and an archiving task dynamic execution module. According to the method, the storage node state is monitored, the storage topology is optimized, the data storage balance and the system throughput capacity are improved, the storage hierarchy is dynamically adjusted, the data write-in task distribution is performed according to the data access frequency, the storage resource utilization rate is improved, the computing resources of the adaptive storage nodes, the storage hot spots are avoided, and the real-time data consistency verification is utilized; storage abnormity is found and corrected in time, data reliability is guaranteed, storage node network time delay and load conditions are considered in an archiving task, data storage distribution is optimized, archiving efficiency and system stability are improved, data processing efficiency is improved jointly, and high availability and expandability are guaranteed.

The invention relates to the technical field of data processing, in particular to a geotechnical engineering-oriented investigation data archiving and backup method and system and a medium. According to the technical scheme, multiple types of investigation data of geotechnical engineering are obtained, and each type of investigation data corresponds to a single investigation category of geotechnical engineering; obtaining a plurality of target time periods of the plurality of types of investigation data according to the fluctuation characteristics of the data value of each type of investigation data along with the change of the acquisition time; as the target time period is the time period with the maximum data anomaly degree represented by each type of investigation data, performing anomaly reason analysis on the investigation category corresponding to each target time period to obtain the anomaly importance degree of each target time period; according to the abnormal importance degree of each target time period, configuring a threshold value for implementing data compression in the corresponding target time period; and according to the threshold value of each target time period, correspondingly compressing the investigation data of the target time period, and performing archiving and backup, thereby realizing accurate compression of the investigation data.

The invention relates to the technical field of community emergency management, and discloses a community multi-mode emergency event grading response system. The multi-modal data acquisition module acquires and divides community multi-modal sensing data, the event feature extraction module respectively analyzes and generates event feature sets, the grading evaluation module fuses features to match emergency event grades, the response decision module calls a target response scheme according to the grades, and the central processing unit verifies related parameters to generate a final response instruction. The system is further provided with a resource scheduling module for optimizing emergency resource allocation, an instruction feedback module for triggering equipment response action, and a data archiving module for storing data to form an event record chain. According to the system, multi-modal data deep processing, accurate grading evaluation and intelligent response decision making are realized, the community emergency management efficiency and the intelligent level are improved, and the community safety is guaranteed.

The invention relates to the technical field of medical image intelligent diagnosis, and provides an interpretable lung CT image intelligent diagnosis method and device, and the device comprises an image calling module, an image processing module, an image analysis module and a result display module. According to the method, identity information of a patient is read to automatically verify and authorize, and an electronic CT image is called and stored in a data storage card through an encryption transmission channel. And the image processing module performs denoising, enhancement and interpretability analysis on the original image to generate a thermodynamic diagram to assist in decision making. The image analysis module completes lesion detection and classification, verifies the consistency between a model decision and doctor experience through a thermodynamic diagram, and optimizes network parameters in combination with feedback data. And the result display module displays a diagnosis result and a thermodynamic diagram in real time, and supports multi-terminal cooperation and data archiving. The device supports data sharing and remote consultation, the efficiency and convenience of diagnosis are improved, and the wide application prospect of artificial intelligence in the field of medical diagnosis is shown.

The invention discloses a multi-modal sensing edge intelligent monitoring system, which relates to the field of edge intelligent monitoring and comprises a multi-modal data acquisition module for acquiring multi-modal data; the edge intelligent processing module performs space-time registration, feature extraction and feature level fusion on the multi-modal data to generate a multi-modal feature vector; performing joint reasoning on the multi-modal feature vector by adopting an intelligent analysis model, outputting a structured analysis result, and generating a local early warning instruction when the danger level indicated by the structured analysis result exceeds a threshold value; and the central control module carries out early warning information issuing, data archiving and model iteration training according to the structured analysis result. Localized feature level fusion and intelligent analysis are carried out on multi-modal data through an edge intelligent processing module, and low-delay risk identification and early warning are realized. Meanwhile, continuous optimization and global situation awareness of the model are realized through a cloud edge coordination mechanism, and the defects of the traditional architecture in real-time performance, reliability and intelligent level are effectively overcome.

The invention relates to the technical field of education informatization, in particular to a multidisciplinary-oriented intelligent homework reviewing management platform and method, and the platform comprises the following steps: an image structure subdivision module, a behavior path recognition module, a rule execution monitoring module, an error cause structure labeling module, and a data label filing module. According to the method, stroke path analysis is combined with corner frequency and closed region detection, the handwritten character recognition precision is improved, the misjudgment rate of interdisciplinary symbol hybrid scenes is reduced, the structural expression ability of the problem solving process is enhanced by means of sequential construction of writing paths and logic nodes, and the problem solving efficiency is improved by combining parameter linkage of scoring frequency and scoring fluctuation. According to the method, the dynamic adaptive capacity of the scoring rule is optimized, the sequence comparison of a causal chain and knowledge nodes is adopted, the logic integrity of error cause positioning is improved, label clustering and distribution statistics are used, homework data archiving has the multi-dimensional screening and teaching backtracking capacity, and the collaborative efficiency of a homework reviewing system is promoted.

The invention discloses a hydroelectric generating set data acquisition and analysis method, system, equipment and medium, and belongs to the technical field of data acquisition and analysis, and the method comprises the steps: obtaining various original data of the operation of a hydroelectric generating set, and achieving the information collection of the set and the operation environment; performing multi-level structured modeling and node feature extraction on the acquired data by adopting a mode of combining a knowledge graph and a graph convolutional neural network, and analyzing an operation state and a future trend of a unit; according to a data analysis result, comparing a historical working condition with a scheduling task, judging whether the operation of the unit is in a reasonable interval, and triggering a corresponding regulation and control measure when the operation is abnormal; by monitoring the state and operation data of key equipment in real time, actual and reference parameters are compared, potential fault risks are identified, early warning information is generated, and data archiving and statistical analysis are carried out; and carrying out visual display on data acquisition, analysis, scheduling and early warning results. Collected data are effectively utilized, and scheduling decision and early warning maintenance are powerfully supported.

The invention relates to the technical field of ship data management, and particularly provides a ship inspection data intelligent management system and method based on structured storage, and the method comprises the following steps: obtaining a ship number, an inspection item and an inspection number, and constructing a data positioning layer; obtaining an inspection document, performing content analysis on the inspection document, and constructing a data structure layer; obtaining multi-source inspection data, associating the multimedia inspection data in the multi-source inspection data with the data content of the data structure layer, and constructing an association mapping layer; constructing a three-dimensional data storage structure based on the data positioning layer, the data structure layer and the association mapping layer; based on table cell index description, binding the multi-source inspection data to table cells with corresponding semantics, and performing cell data fusion to obtain a plurality of assembly cells; and dynamically reconstructing the inspection document based on all the assembly cells to obtain an interactive inspection document, so that the structural data storage of the inspection data is realized, and the inspection efficiency and the traceability positioning efficiency after data archiving are improved.

The invention relates to the technical field of defect detection, in particular to a crankshaft quality inspection method and system based on image data, and the method comprises the following steps: extracting crankshaft coordinates to generate a serial number list, binding an image center to generate a list, constructing a path table by an attribution image, extracting a gray difference to generate an array, recognizing the position of an abnormal mapping structure, and outputting crack positioning information. According to the method, the accurate positioning basis is obtained by establishing the corresponding relation between the structure number and the space coordinate and image acquisition, the mapping between the image content and the structure area is realized by combining the imaging center point extraction and the image attribution binding, the traceability of data archiving is enhanced, the gray value point pairs are extracted by using the symmetric center line, and the gray difference matrix is constructed. According to the overall scheme, image attribution and defect identification under structure dominance are achieved, the detection accuracy and the positioning precision are improved, the false detection rate is reduced, and the stability and the engineering adaptation capacity are enhanced.

The invention relates to the technical field of numerical control machine tool monitoring, in particular to a monitoring method and a monitoring system for an intelligent machining machine tool, and the method comprises the steps: collecting static data information of the numerical control machine tool and dynamic data information in an operation process according to a plurality of collection devices arranged on the machine tool, and summarizing the static data information and the dynamic data information into multi-source data, obtaining state data of the numerical control machine tool; constructing a digital twin model corresponding to the numerical control machine tool based on a digital twin system, and transmitting the state data to the digital twin model, so that the digital twin model is matched with the actual state of the machine tool; according to the method, real-time collection of multivariate data signals is carried out, accurate and comprehensive machine tool operation state information is further obtained in real time, and the recognition and prediction precision of the machine tool health state is improved by constructing a data twin model, carrying out data archiving and optimized storage, constructing machine tool health state classification and establishing an incidence relation between degradation characteristics and the health state; the production accident rate is reduced.

The application discloses a block data archiving method and device for a blockchain and a medium. The method comprises the following steps: determining a block start number and a block end number corresponding to to-be-archived block data, constructing a to-be-executed archiving application through a private key of a to-be-archived blockchain node corresponding to the to-be-archived block data; publishing the to-be-executed archiving application on a chain, auditing the to-be-executed archiving application by an archiving smart contract in the blockchain, and publishing an archiving audit result; in the case that the audit is passed, packaging the to-be-archived block data by the to-be-archived blockchain node to generate a to-be-archived block data file and uploading the to-be-archived block data file to a preset storage area; after receiving a message notification of successful uploading, constructing a successful archiving notification based on an archiving application transaction Hash corresponding to the to-be-executed archiving application and a storage address of the to-be-archived block data file contained in the message notification, and publishing the successful archiving notification. The application avoids the risk of data loss or leakage and ensures that the archiving behavior is traceable.

The invention belongs to the field of foundation engineering construction, and provides a building foundation engineering construction method which comprises the following steps: S1, geological improvement, cushion construction and expansive soil treatment; s2, prefabricated foundation components are assembled; s3, intelligent reinforcement cage construction; s4, concrete pouring and curing; and S5, performing quality verification and data archiving. The lime and coal ash mixed curing layer is adopted to inhibit ion exchange expansion, the expansion coefficient of expansive soil is reduced, liquid water permeation is blocked through the breathable film, gaseous water diffusion is allowed, damage to a film body caused by air pressure is reduced, temperature rise and deformation data are fed back in real time through the sensor network embedded in the reinforcement cage, pouring parameters are dynamically adjusted, and the construction quality is improved. A point cloud model is generated through three-dimensional laser scanning, an acceptance report is generated by comparing with BIM design deviation, manual measurement is replaced, the acceptance efficiency is higher, and whole-process intelligent monitoring can be achieved.

The invention relates to the technical field of supply chain management, in particular to a supply chain multi-source heterogeneous data integrated filing and management method, which comprises the following steps of: 1, acquiring multi-source heterogeneous data; 2, data preprocessing; step 3, carrying out data normalization; step 4, semantic annotation: semantic tags are added to the normalized data set, the semantic annotation comprises ontology construction, tag generation and context association, the ontology construction is based on a supply chain domain ontology, the tag generation adopts a rule matching or machine learning method, and the context association associates data with a supply chain context; step 5, data archiving; step 6, index construction; and 7, data management: performing continuous management on the archived data. Through the combination of semantic annotation and dynamic indexing, the data access efficiency can be ensured, and meanwhile, the querizability and interpretability of the data can be improved.

One example method includes receiving, at a node of a data lifecycle management system, a data stream, performing an assessment of the data stream, based on the assessment, assigning a data confidence score to the data stream, providing the data confidence score to an immutable ledger, and performing a data lifecycle operation on the data stream based on a policy to which the data confidence score corresponds. The data lifecycle operation may be performed by the node and may include data processing, data storage, data usage, data archiving, and data destruction.

The invention relates to the technical field of data archiving, in particular to an intelligent rescue carriage emergency record archiving system. The system comprises a rescue carriage pre-first-aid self-checking module, an emergency field checking and filing module, an on-transit emergency risk updating module and a department emergency task ending and filing module. Communication electric quantity corresponding to various types of intelligent medical equipment in the intelligent rescue carriage and data storage residual capacity corresponding to a data processing terminal can be obtained, and pre-first-aid self-inspection processing is carried out, so that the intelligent equipment complete rescue carriage is generated; intelligent medical equipment is started at a first-aid site to monitor emergency physiological information of a first-aid patient in real time, basic information of the patient and symptom information of the first-aid site are input for emergency checking and preliminary filing, and meanwhile emergency physiological update information corresponding to the patient is continuously monitored on the way for emergency risk update processing and emergency record automatic filing; and generating a patient archived electronic medical record of the emergency task. According to the invention, the information record in the medical first-aid process can be optimized.

A dynamic cadastral data updating and management method based on a space-time sequence specifically comprises the following steps: S1, collecting dynamic cadastral data, preprocessing the dynamic cadastral data, and outputting a standardized space-time sequence database; s2, performing dynamic modeling on the standardized space-time sequence database, adjusting granularity, and outputting an optimized space-time model; s3, performing space-time sequence comparison by utilizing the optimized space-time model, automatically identifying data change, and outputting a cadastre change incremental data set; s4, constructing a relation chain according to the change incremental data set, writing change data into a current potential library, and archiving historical data into a difference file library; s5, performing space-time consistency verification and efficiency optimization on the current potential library and the difference file library, and outputting a quality inspection passing library; and S6, performing service packaging on the quality inspection passing library, and deploying the quality inspection passing library to a cloud service platform. The method dynamically adapts to change features of different regions, reduces storage cost and update time consumption, improves verification efficiency, and provides dynamically updated spatial basic data support for smart city construction.

The invention relates to the technical field of evaluation, and particularly discloses an RLHF-based AI evaluation auxiliary system, and the system comprises a field evaluation module which is used for recording key data of each evaluation item, and carrying out the data archiving and processing, and obtaining field evaluation data; the unit evaluation module is used for processing and feeding back based on the evaluation text; the level evaluation analysis module is used for acquiring a plurality of unit evaluation records, performing classification analysis according to the safety control level to which the unit evaluation records belong, and performing evaluation feedback on each level; the overall evaluation module is used for carrying out feedback, modification and adoption or regeneration based on overall evaluation result analysis; the report compiling module is used for combining the overall evaluation results to generate an evaluation report first draft and auditing the evaluation report first draft; and the report auditing module is used for carrying out learning adjustment based on an RLHF mechanism to generate an evaluation report, strengthening the precision and controllability of a model generation behavior under the RLHF mechanism, reversely optimizing an AI behavior through the RLHF mechanism, and improving the accuracy of the AI model in a subsequent evaluation process.

The invention relates to an astronomical observation data archiving method and system, the method is applied to the astronomical observation data archiving system, the astronomical observation data archiving system comprises a first server, a second server and a third server, the first server is deployed in a field station, the third server is deployed in a data center, and the second server is deployed in the data center. The first server and the third server are both connected with the second server, and the method comprises the steps that astronomical observation data to be filed are divided into a plurality of data blocks, the first server packages each data block into an AMQP message and then sends the AMQP message to the second server, the second server forwards the AMQP message to a queue in the second server, and the AMQP message is sent to the third server; and pushing the AMQP message in the queue to a third server subscribing the queue so as to realize transmission of the astronomical observation data to be tested from the first server to the third server.

The invention discloses a power grid operation and maintenance service management method based on an informatization means, and belongs to the field of network operation and maintenance, and the method comprises the steps: S1, building power grid operation and maintenance service integrated data information, and generating a multi-source data flow with a timestamp; s2, constructing an operation inspection operation relation model of the hierarchical knowledge graph, and carrying out semantic modeling on equipment, personnel and operation scenes to realize task and risk matching identification; s3, executing task dynamic assignment and resource reconstruction, and performing priority optimization and cross-region scheduling; s4, carrying out digital twin operation inspection site virtual replication, synchronously mapping sensing data and operation images, and realizing track, working condition and risk node visualization; s5, performing abnormal working condition closed-loop management, pushing abnormal data through event triggering, and forming iterative optimization in combination with historical feedback; and S6, forming comprehensive performance evaluation and data archiving, and uniformly incorporating task execution, risk response and equipment maintenance into an intelligent archiving system. The method has the beneficial effects that the power grid operation inspection efficiency, accuracy and traceability are improved.

The invention relates to the technical field of face recognition and safety management, and discloses a multi-dimensional compliance detection system and method based on face recognition safety management. The system comprises an image acquisition module, a feature reconstruction module, a compliance analysis module, a security decision module, a central control unit and the like. The image acquisition module acquires and classifies biological characteristic data streams, the characteristic reconstruction module generates a first characteristic topological graph and a second characteristic behavior chain, the compliance analysis module fuses the data to map the security level, the security decision module calls a security scheme, and the central control unit verifies and generates a final security instruction. The system realizes multi-dimensional biological characteristic acquisition and analysis, accurate evaluation of security level, and efficient making and execution of security decision, also has equipment linkage and data archiving functions, effectively improves the security management level, is suitable for various security management scenes, and ensures the place security.

This invention belongs to the field of Chinese medicinal material acceptance technology, specifically a standardized acceptance method and electronic system for the handover process of Chinese medicinal material storage and transportation. The specific steps of this standardized acceptance method are as follows: unified data standards and cross-process equipment adaptation, real-time data management during transportation, on-site handover acceptance, post-handover data archiving and cross-process linkage. This application achieves data connectivity, technical adaptation and accountability in the handover acceptance, transportation and storage processes by constructing a standardized system covering the entire process of data collection, real-time management, on-site verification, joint maintenance and traceability archiving. This completely solves the problems of data fragmentation, cross-process disconnection and difficulty in accountability in the existing technology.

The present application belongs to the technical field of robot control, and specifically discloses a railway inspection robot laser radar anti-collision and remote video linkage control method, aiming to solve the problems of low inspection efficiency, low sensor fusion degree and missing linkage mechanism in industrial scenarios. The method comprises: performing benchmark calibration and entering inspection line data through system initialization and parameter configuration; acquiring point cloud data by high-frequency dynamic scanning using a laser radar, and real-time matching of multi-level early warning thresholds to trigger linkage response; the power control unit executes brake or speed reduction operation according to the instruction, and resets the mode to resume work after confirming safety; the system also archives the full data of linkage events to support continuous optimization of the inspection plan. Through the deep coupling linkage of the laser radar and the video imaging module, the present application can realize all-weather, high-precision and high-safety autonomous operation of the inspection robot in complex high-dynamic environments, significantly improving the inspection efficiency and risk control level.