638results about "Checking time patrols" patented technology

The invention relates to an electrical cabinet state monitoring and intelligent inspection system based on multi-source data fusion, and aims at solving the problems that a traditional electrical cabinet monitoring method is low in efficiency, poor in real-time performance, limited in coverage range and the like. A monitoring platform with high reliability and high real-time performance is constructed by deploying a multi-source sensor network, adopting an edge and cloud cooperative computing model and combining a secure communication protocol design. According to the system, through comprehensive application of a dynamic path planning algorithm, a multi-modal data fusion diagnosis technology and an abnormity diagnosis and early warning model, the inspection efficiency and the fault diagnosis precision are effectively improved. The system not only shows significant advantages in the aspects of data fusion precision, dynamic path planning efficiency and robustness of an anomaly diagnosis model, but also can provide accurate and real-time monitoring and response in a complex industrial environment, and provides reliable guarantee for safe operation of an electrical cabinet.

The invention provides an intelligent inspection assistant system based on AI Agent multi-agents, and the system comprises a main AI Agent module which is used for receiving an inspection instruction and carrying out the intention recognition based on the inspection instruction; the guide AI Agent module is used for performing task allocation based on the intention recognition result of the main AI Agent module; the inspection task generation AI Agent module is used for generating an inspection task; the inspection task execution AI Agent module is used for executing an inspection task; the interior of the inspection task generation AI Agent module and the interior of the inspection task execution AI Agent module adopt workflow to define main execution processes and logics; and the RAG knowledge base is used for storing the inspection execution report and the inspection problem investigation report.

The invention relates to the technical field of Beidou positioning, and discloses a Beidou positioning inspection method and system. The method comprises the following steps: acquiring geographic information and equipment state parameters of an inspection area, and generating a structured task queue according to dimensions such as equipment types and fault levels; constructing a Beidou positioning dynamic model containing a position axis, a time axis and an environment factor axis; determining an initial inspection constraint condition according to the equipment type and the fault level, and performing path planning simulation to generate an initial inspection route; detecting a route anomaly, and adjusting an abnormal node by using a hybrid optimization algorithm to generate a stable route; model parameters are updated in combination with real-time environment data, and a final inspection instruction set containing information such as equipment moving time sequence is generated. The system comprises a data processing module, a model construction module, a constraint determination module, a path planning module, an anomaly detection module, an optimization adjustment module and the like. The inspection efficiency and precision are improved, the stability and reliability are enhanced, and the inspection requirements of complex environments can be effectively met.

The invention relates to the technical field of fire-fighting hidden danger identification, in particular to a fire-fighting hidden danger intelligent identification method. Comprising the following steps: setting a plurality of equipment points according to parameters of a to-be-inspected area, and establishing a monitoring sub-model of each equipment point; acquiring monitoring data of each equipment point, and generating a potential risk value of each equipment point; setting an inspection strategy according to all the potential risk values, obtaining feedback data according to the inspection strategy, and generating a fire-fighting hidden danger diagnosis result according to the feedback data; a plurality of monitoring points are set to carry out multi-dimensional monitoring on a to-be-inspected area, monitoring data of each monitoring point are periodically collected, the operation state of each monitoring point is accurately analyzed, a corresponding inspection strategy is set according to potential risk values of each equipment point, and manual inspection and unmanned aerial vehicle inspection technologies are combined, so that the inspection efficiency is improved. The overall inspection efficiency is improved, the inspection time and labor cost are reduced, potential fire hazards are diagnosed and early warned in time, and the diagnosis precision of the fire hazards is improved.

The invention relates to the technical field of channel monitoring, and discloses an unmanned aerial vehicle water depth monitoring method for channel inspection. The method comprises the following steps: deploying an unmanned aerial vehicle to a target channel area, initializing a carried sonar sensor, a camera and a positioning module, and planning a flight path to cover a to-be-detected point according to a preset algorithm; water depth and image data are collected in real time during flight, position information is obtained, multi-modal monitoring data are formed through space-time alignment, a water depth fusion model is input to generate a channel water depth distribution diagram, an abnormal area is recognized through an abnormal detection model, and finally the position and water depth data of the abnormal area are encrypted and transmitted to a ground control terminal. The method improves the efficiency and accuracy of channel water depth monitoring, can timely discover the abnormality, guarantees the safety and smoothness of the channel, and provides an effective technical means for channel management.

The invention provides a safety patrol method, a patrol device and patrol equipment, and relates to the technical field of building safety, and the safety patrol method comprises the steps: responding to an operation instruction of an editable interface, configuring a multi-stage process template of building safety patrol, and generating a corresponding safety patrol task; the shooting device collects real-time patrol data of a construction site; identifying violation operation, equipment abnormity and environment risk in the real-time patrol data, and generating a corresponding risk level result; generating a visual alarm signal according to the risk level result, issuing the visual alarm signal to a mobile terminal, and sending the visual alarm signal to a monitoring center when the visual alarm signal is an emergency signal; monitoring response information of the mobile terminal, updating the state of the safety patrol task and recording an operation log of processing a risk level result by patrol personnel; if the mobile terminal does not respond within the preset time, the alarm information is sent to the mobile terminal again, the alarm information is sent to the monitoring center, and the patrol efficiency and the risk handling capacity can be improved.

The invention discloses an intelligent electric power inspection control method, an inspection robot and a medium, and the method comprises the steps: carrying out the initial inspection according to a preset path, so as to obtain the first inspection data of an electric power facility; analyzing the first inspection data to determine an abnormal area of the electric power facility; an abnormal scoring index of each abnormal area is determined based on abnormal data of the abnormal areas, the abnormal areas are divided into a first abnormal area and a second abnormal area according to the abnormal scoring indexes, and the abnormal data are data in a non-preset range; the abnormal scoring indexes comprise a visual index, an operation sound index, an infrared imaging index and a gas concentration index; determining a first inspection task of the first abnormal area and a second inspection task of the second abnormal area based on the abnormal data; and respectively executing the first inspection task and the second inspection task to obtain second inspection data. The inspection efficiency of the power plant transformer substation can be improved.

The invention provides a distribution network unmanned aerial vehicle inspection intelligent management and control system based on multi-source data fusion. The system comprises a data acquisition module, a fusion processing module, an analysis decision module, a scheduling management and control module and a user management module. The data acquisition module is used for acquiring state information of the power distribution network in real time through various sensors carried by the unmanned aerial vehicle; the fusion processing module is used for performing standardization processing and fusion on the information data acquired by the data acquisition module; the analysis decision module analyzes the fault risk of each part of the distribution network line based on the data output by the fusion processing module and optimizes the subsequent inspection route of the unmanned aerial vehicle; the scheduling management and control module is used for managing and controlling the execution process of the inspection task of the unmanned aerial vehicle; the user management module is used for providing a user interface to complete interaction between a user and the system; according to the invention, through multi-source data fusion and intelligent analysis optimization, accurate sensing of distribution network line faults and efficient dynamic management of unmanned aerial vehicle inspection tasks are realized.

The invention discloses an intelligent inspection method and system based on multi-dimensional data fusion analysis, and relates to the technical field of intelligent monitoring and maintaining.The intelligent inspection method comprises the steps that telemetering data, telecommand data and remote vision data of equipment are collected from multiple management platforms; constructing a time sequence model based on the telemetry data to process the telemetry data to obtain processed telemetry data; performing primary fusion on the processed telemetering data and telesignalling data to obtain primary fusion data; performing visual feature vector extraction on the remote vision data; performing advanced fusion on the primary fusion data and the visual feature vector to obtain advanced fusion data; and evaluating the equipment state based on the advanced fusion data, and finally generating an inspection report. According to the method, abnormal points can be accurately identified and removed, and complex association among different data sources is fully mined. The precision and reliability of equipment state evaluation are improved, a detailed inspection report is provided for inspection personnel, potential problems can be found in time, and an effective maintenance plan can be made.

The invention relates to the technical field of digital twinning, and discloses an intelligent park inspection method and system based on digital twinning. The method comprises the following steps: acquiring image data, point cloud data, inertial navigation data and GPS positioning data, and performing format standardization and timestamp synchronization processing to obtain a multi-dimensional environment data set; performing point cloud space alignment according to image data and the point cloud data to obtain a three-dimensional space frame; performing spatial position calibration according to inertial navigation data and the GPS positioning data to obtain positioning reference data; constructing a digital twinborn model of the park according to a three-dimensional space frame and the positioning reference data; performing path calculation and rehearsal correction according to the digital twinborn model to obtain an inspection track; and according to the inspection track and the digital twinborn model, generating an inspection instruction, so that inspection equipment performs a park inspection task. According to the method, intelligent inspection rehearsal and path optimization can be realized, and the park inspection efficiency is improved.

The invention discloses an intelligent reservoir inspection system based on a knowledge graph and digital twinning. The system comprises a sensing acquisition layer, a modeling simulation layer, a data processing and decision support layer, a communication layer and an interactive visualization layer, the sensing acquisition layer obtains image video data, water level data, rainfall data and temperature and humidity data of the reservoir and the surrounding environment through a camera and a sensor; the modeling simulation layer maps an actual reservoir and a surrounding environment into a virtual model, imports data acquired by the sensing acquisition layer into the virtual model, and realizes dynamic monitoring and analysis through a digital twinborn technology; the data processing and decision support layer is used for processing, analyzing and mining data and providing decision support; the communication layer is responsible for interconnection, remote control and automatic task execution of the system; and the interactive visualization layer provides an operation interface and data display.

The invention provides an AR inspection method and device applied to a waste incineration station and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring in-station temperature data for a waste incineration station sent by a temperature acquisition sensor; constructing a thermodynamic diagram according to the in-station temperature data; scanning data, sent by the laser radar, of the waste incineration station are obtained; according to the scanning data, constructing an obstacle distribution map; acquiring environment data of the waste incineration station, wherein the environment data comprises gas concentration data and vibration data; generating a dynamic environment model of the waste incineration station based on the thermodynamic diagram, the obstacle distribution diagram, the gas concentration data and the vibration data; according to the dynamic environment model, an inspection strategy of inspection personnel corresponding to the waste incineration station is planned, and the inspection personnel wear AR glasses; and displaying the dynamic environment model and the inspection strategy to inspection personnel through AR glasses. By implementing the technical scheme provided by the invention, the inspection efficiency of the waste incineration station can be improved.

The invention discloses a dynamic inspection method and system for a subway tunnel, and relates to the technical field of tunnel inspection methods, and the method comprises the steps: determining a dynamic inspection route of the subway tunnel according to a plurality of inspection routes of each sub-tunnel region, the model of a corresponding inspection robot, and the internal environment of each sub-tunnel region; the accuracy of the dynamic inspection route of the subway tunnel is ensured; determining a plurality of abnormal nodes based on the internal image of the subway tunnel and the abnormal signal; triggering the inspection robot to control the abnormal nodes according to the positions of the plurality of abnormal nodes, the current position of the inspection robot and the dynamic inspection route, and outputting a corresponding abnormal event; therefore, the passing path of the subway tunnel is regulated and controlled according to the abnormal event and the passing state of the corresponding sub-tunnel area, reasonable regulation and control of the passing path of the subway tunnel are guaranteed, and reasonable processing of the abnormal event in the subway tunnel and normal passing of the subway tunnel are guaranteed.

The utility model provides an inspection collection system, which is applied to the field of financial science and technology or other related fields, and in the inspection collection system, inspection equipment enters inspection areas corresponding to equipment to be detected according to a preset inspection sequence; at least one inspection information acquisition device correspondingly arranged in an inspection area corresponding to the at least one to-be-detected device is powered on when the inspection device enters the inspection area, is in communication connection with the inspection device and outputs inspection information, and the inspection information comprises inspection time; the server in communication connection with the inspection equipment accurately obtains the inspection condition of the inspection equipment on each to-be-detected equipment and the condition of each to-be-detected equipment based on the inspection information uploaded by each inspection information acquisition device, and accurately monitors the overall inspection condition of the inspection equipment according to the sequence of the obtained inspection information acquisition devices. And the accuracy of the inspection information generated in the inspection process is ensured.

The invention belongs to the field of medical care, and particularly relates to an intelligent nursing inspection auto-induction recording device and method, and the device comprises a directional RFID card reader at the entrance of a ward, an NFC activation module at the side of a sickbed, an integrated pressure-sensitive foot pad, and an adjustable installation structure. Timing is started through ward entrance identification, nurse information is recorded through close-range induction of a sickbed, and nursing operation and passing behaviors are distinguished by detecting a two-foot standing mode through a pressure-sensitive foot pad. The mounting structure comprises an L-shaped mounting plate and a sliding inner plate and is matched with the width of a sickbed; the angle adjusting component fixes the position; the intelligent pressure-sensitive foot pads are integrated at the four corners of the sickbed base, the pressure distribution sensors detect the standing mode of the two feet, nurses and temporary passing persons are distinguished, false inspection in the mode of waving for walking is avoided, substantive nursing operation of the nurses is accurately verified, and it is ensured that patients are truly and effectively nursed.

The invention relates to the technical field of inspection, in particular to an AI intelligent agent-based inspection method, equipment and system, and the method comprises the steps: obtaining a target region image of a to-be-inspected region, determining an abnormal region according to the target region image, generating a bidding request under the condition that the environment illumination condition of the abnormal region does not meet a preset condition, the bidding request comprises illumination demand information of an abnormal area and an area position of the abnormal area, sending the bidding request to a plurality of second devices, when bidding information generated by the second devices according to the bidding request is received, determining a target device from the plurality of second devices according to the bidding information, and sending a task execution instruction to the target device, and the target device provides illumination for the abnormal area according to the area position and the illumination demand information. By transferring the illumination energy consumption of the first equipment, the endurance time of the first equipment can be prolonged, the first equipment is prevented from being exposed, and the illumination requirement can be met to the maximum extent.

The invention relates to the technical field of pipe network maintenance, and discloses an RFID-based intelligent inspection method and system for a drainage pipe network, and the method comprises the steps: carrying out the regional division of a target drainage pipe network through a background server, and obtaining drainage pipe network inspection regions; the mobile terminal performs path planning on the drainage pipe network inspection area to obtain a global optimal inspection path; the RFID reader-writer positions the RFID tag based on the global optimal inspection path to obtain the spatial position information of the RFID tag; and the mobile terminal patrols the target drainage pipe network by using the spatial position information of the RFID tag to obtain a drainage pipe network patrolling result. According to the invention, efficient planning of drainage pipe network inspection is realized, and the coverage and real-time performance of inspection work are ensured.

An equipment system comprises an intelligent inspection equipment terminal, the intelligent inspection equipment terminal is electrically connected with an Internet of Things module, and the Internet of Things module is in communication connection with an intelligent inspection robot, warehouse inspection and tray integrated equipment, an equipment monitoring sensor and a monitoring camera; the intelligent inspection equipment terminal comprises an operation and maintenance simulation platform, a digital twin platform, a health assessment platform, a safety warning platform, a fault database and a display module. The method comprises the following steps: S1, arranging inspection points and inspection routes; s2, inspection and monitoring; s3, monitoring a key area; s4, preprocessing and analyzing the data information; s5, building a virtual metering production line and a storage warehouse; s6, health assessment analysis and display; s7, core area management and control; the intelligent inspection system has the advantages of intelligent inspection, health and fault analysis and improvement of facility control force.

The invention relates to the technical field of cable tunnel inspection, in particular to a cable tunnel inspection method and system based on deep learning, a cable image is collected through an inspection robot, automatic defect identification is realized based on a convolutional neural network, and further, temperature, humidity and gas concentration parameters of a defect position are combined, so that the defect position is identified. And splicing with image features to form a fusion feature vector, so that more accurate defect cause judgment is realized. And inputting the fusion feature vector into an inference model embedded with a prior rule, and outputting a cause category and a confidence score in combination with domain knowledge. And reversely positioning the cause source according to the cause label, and controlling the visual angle of the robot to obtain a corresponding image and identify the image to form closed-loop correlation of the defect and the cause source. And finally, in combination with the three-dimensional map and the pose data, the cause source is mapped into a three-dimensional coordinate point, a spatial causal relationship is established, and automatic and closed-loop intelligent inspection work of the cable tunnel is completed.

The invention relates to a power equipment inspection method, device and equipment, a readable storage medium and a product, and relates to the technical field of power. Comprising the following steps: acquiring equipment image data, equipment temperature data and equipment type of to-be-inspected power equipment; performing external health analysis on the to-be-inspected power equipment based on the equipment image data to obtain external health state information of the to-be-inspected power equipment; performing internal health analysis on the to-be-inspected power equipment based on the equipment temperature data to obtain internal health state information of the to-be-inspected power equipment; performing priority analysis on the to-be-inspected power equipment based on the equipment type to obtain an inspection priority of the to-be-inspected power equipment; according to the external health state information, the internal health state information and the inspection priority, determining an inspection strategy of the to-be-inspected power equipment; and controlling the inspection robot to inspect the to-be-inspected power equipment according to the inspection strategy. The method can improve the inspection reliability of the power equipment.

The invention discloses an application method, system, equipment and medium of plant inspection navigation in a two-ticket intelligent management and control system based on AOA positioning, and belongs to the technical field of positioning navigation, and the application method comprises the following steps: setting a Bluetooth AOA transmitting base station and a Bluetooth AOA module positioning tag in an inspection area, carrying out signal interaction, and constructing an inspection space model; obtaining an interaction signal between the mobile Bluetooth transmitter and the Bluetooth AOA transmitting base station when an inspector carrying the mobile Bluetooth transmitter enters the inspection area, calculating the distance between the inspector and the Bluetooth AOA transmitting base station according to the signal intensity, and determining the real-time position of the inspector in the inspection space model; an inspection navigation route is generated according to the real-time position of the inspector, a preset inspection route and the work ticket information and the operation ticket information provided by the two-ticket intelligent management and control module; and when the inspector arrives at the inspection point and a preset card punching condition is satisfied, recording inspection card punching information and generating an inspection record. According to the invention, the inspection efficiency and safety are improved.

The invention discloses an inspection method, device and equipment, a medium and a computer program product, and relates to the technical field of information and the technical field of operation and maintenance management. In response to the inspection task of the target machine room, determining at least one inspection object from the inspection object list; the inspection object list comprises identification information of inspection objects; the inspection object comprises at least one of hardware equipment, a virtualization platform, an operating system instance and a software application service instance object; determining a target inspection mode of the inspection object from an inspection mode library based on the identification information of the inspection object; and operating the target inspection mode to generate a target inspection result. According to the technical scheme, the inspection object is determined based on the inspection task, the target inspection mode of the inspection object is further determined, and the purpose of automatic inspection is achieved.

The invention provides an intelligent inspection management system in a hybrid expert mode under a cloud edge collaborative architecture, and relates to the technical field of data processing, the system is used for cutting basic inspection data into a plurality of section units according to a business time window, and combining record elements and node sequences in each section unit to obtain a combined data segment; constructing a track series sequence by taking the occurrence sequence of each record element as a reference, and converting the track series sequence into track matrix data; constructing node load data and calculating a process aggregation factor; screening out candidate sections in section combination data and constructing a section traffic matrix; calculating a process shunting factor; and determining process node data, and constructing an inspection service link according to the process node data. According to the invention, the problem of multiple circulation of error events in the process can be solved, and the uniqueness of the inspection task is ensured.

The invention provides an intelligent inspection system, an inspection method, a medium and computer equipment. The intelligent inspection system comprises a data monitoring module, an inspection setting module, an exception handling module, an intelligent inspection module, an inspection item management module, a record prediction module, a model training module, a record report module and a user management module. By adopting the intelligent inspection system, the data is pushed to the terminal equipment, the information transmission delay can be reduced, the conventional point location adopts a rechecking mode, and the key point location adopts a blind inspection mode, so that different inspection requirements are flexibly met; the system breaks information islands of all departments and realizes data sharing; abnormal data are analyzed through machine learning, automatic control strategy adjustment is supported, the processing precision and timeliness are improved, and human intervention is reduced; the system covers inspection of multiple aspects such as process parameters, equipment states and environment-friendly energy consumption, production quality can be guaranteed in an all-around mode, and the overall production management level is improved.

The invention provides a park inspection system based on the Internet of Things, and relates to the technical field of park inspection. The system comprises a data acquisition module, a resident risk assessment module, an inspection system generation module, an inspection execution module, a data feedback module and a resident management module. The method comprises the steps of collecting real-time data, constructing a risk assessment model to judge a risk level, generating a patrol plan and dynamically adjusting the patrol plan, executing patrol and recording exceptions, analyzing the exceptions and informing residents. By collecting environment monitoring data and resident activity data in real time, potential safety hazards can be recognized in time, and it is ensured that preventive measures are taken before problems occur. By analyzing real-time data, an accurate risk level is generated, it is ensured that a high-risk area is preferentially concerned, and the probability of occurrence of security events is effectively reduced. By optimizing a patrol plan and combining a risk level and a scheduling algorithm, the patrol work is ensured to have pertinence and high efficiency.

The invention relates to a radioactive source library management system, which comprises an intrusion detection unit comprising an infrared detector, an infrared camera and an emergency alarm device; a video monitoring unit; the radiation value detection unit comprises a fixed point radiation detector and a tracing robot moving radiation detector; an access control unit; the management and control platform unit is respectively connected with the intrusion detection unit, the video monitoring unit, the radiation value detection unit and the access control unit and is used for carrying out data acquisition on each unit, and the management and control platform unit is connected with the dynamic display unit and is used for providing display and alarm information for the dynamic display unit. Moving a radiation detector through a tracing robot to regularly collect the radiation dose in the radioactive source library, and judging whether the real-time number of the radioactive sources in the source library and the radiation dose are safe or not; manual collection is not needed, a radiation monitor does not need to be arranged for each radioactive source, the number of devices is reduced, meanwhile, the radiation detector does not need to be fixed to a radioactive source tank, touch is avoided, and damage is not prone to occurring.

The invention discloses a power equipment inspection method and system based on fault prediction, and relates to the technical field of power system monitoring and maintaining.The method comprises the steps that an intelligent sensor marked with current power equipment is arranged on the power equipment, and a corresponding sensor recognition device is set up on an inspection unmanned aerial vehicle; a primary inspection route is formulated by considering expert opinions, and key parameters are recognized; constructing a multi-dimensional-graph neural model to perform fault deviation prediction on the polled data, identifying a propagation path, and performing self-optimization; and formulating a secondary inspection route according to an optimized result, and performing secondary inspection again. According to the method, intelligent equipment monitoring, data analysis and dynamic adjustment strategies are combined, the fault prediction capacity of the power equipment is remarkably improved by implementing the efficient inspection method, the fault occurrence probability can be reduced, the resource configuration and use efficiency can be optimized, and finally safe and stable power supply and management are achieved.

The invention relates to the technical field of substation inspection robots, and discloses an autonomous inspection method and system for a substation inspection robot. The method comprises the following steps: acquiring current environment parameters of a transformer substation and real-time state information of an inspection robot, and constructing an inspection environment model; analyzing historical inspection records, classifying historical inspection strategies into a plurality of experience levels, and establishing a multi-layer experience pool; according to a preset target inspection state in the inspection environment model, calculating an intelligent inspection strategy required for achieving the target inspection state; the intelligent inspection strategy and the experience inspection strategy are corrected in real time by adopting a dual-channel coordination mechanism to respond to the dynamic change of the transformer substation environment, and a final inspection strategy is generated; executing a control instruction based on the final inspection strategy, completing an inspection task and recording an actual inspection state; and comparing the deviation reason between the actual inspection state and the target inspection state, adjusting the experience content in the multilayer experience pool according to the deviation reason, and optimizing the experience data.

The invention discloses a fire-fighting equipment intelligent inspection method based on Internet of Things big data, and the method comprises the following steps: S1, collecting multi-source data, and outputting an original data set; s2, the original data set is preprocessed and fused, and a standardized operation state data sequence is generated; s3, through an FEDform model, extracting equipment state features and generating a health reference baseline; s4, executing offset detection, performance degradation and sensor drift judgment through a DeepSVDD model, and outputting an anomaly level and an anomaly type; s5, generating an inspection task, issuing a task instruction, and recording an inspection execution condition and feedback in real time; and S6, the inspection feedback data and the alarm result are transmitted back to the cloud, and an inspection report and an equipment health file are generated. Through the multi-source data fusion and deep learning technology, the intelligent level of fire-fighting equipment inspection is improved, and the accuracy and response efficiency of anomaly detection are enhanced.

The invention discloses terminal equipment for planning an inspection path of a lithium ion electrochemical energy storage power station and an inspection path generation control method, and the terminal is internally provided with an inspection path control module, a multi-modal data acquisition module, a data management module, a communication module and the like. A directed acyclic routing inspection sequence of a power grid near end, an alternating current side, a PCS and a direct current side is generated based on the electrical topology of a power station, and preposed dependence and jump inspection limitation are implemented. Human-point-time consistency in-place verification is achieved through NFC, and multi-modal data such as infrared temperature and visible light images are collected. And the end side adopts additional structured storage and chained hash evidence solidification, the classification abnormity is judged in combination with threshold-trend-consistency fusion, and the abnormity triggers dynamic rearrangement of downstream sensitive nodes and executes forced recheck. The system supports hierarchical queue and idempotent transmission, the platform side carries out chain type consistency verification and receipt closed loop, and the operation and maintenance guarantee of inspection standardization of the lithium ion electrochemical energy storage power station, rapid abnormal positioning, non-tampering of data and traceability of a whole link can be realized.