944results 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 provides a multi-path security inspection robot intelligent scheduling method, system and device and a medium thereof, and the method comprises the following steps: installing a plurality of sensors in a target inspection area, and collecting the basic parameter information of inspection robots and the inspection area in real time; according to the invention, multi-dimensional data, including various information of the inspection robot and the inspection area, are acquired through various sensors, and through preprocessing and fusion algorithms, noise is removed and multi-source data are integrated, so that an accurate and comprehensive data basis is provided for subsequent decision making, and the problem of information fragmentation is solved; a plurality of factors such as landforms and obstacles are considered through a path planning algorithm, an optimal path is calculated, updating can be carried out according to real-time conditions, and rapid correction is carried out by using an incremental algorithm, so that the planning precision and flexibility are improved, and the inspection efficiency is improved; the robot and obstacle information is acquired in real time through the sensor, so that the route and the task are optimized according to the real-time information, and the inspection effect and the guarantee capability are improved.

The invention discloses a photovoltaic field area unmanned aerial vehicle inspection system, which relates to the field of unmanned aerial vehicle inspection, and specifically comprises a data acquisition and preprocessing module, a data fusion module, a data processing module, a data storage module, a data processing module and a data processing module, and is characterized in that the data acquisition and preprocessing module is used for acquiring environmental parameter data and carrying out dynamic data cleaning and preprocessing to obtain preprocessed environmental parameter data; carrying out weight adjustment on the basis of the preprocessed environmental parameter data, and carrying out cross-modal attention mechanism processing and synchronous fusion processing on the basis of the environmental parameter data subjected to weight adjustment to obtain cross-modal fusion features and synchronous fusion features; by introducing adaptive adjustment of environmental parameter data, cross-modal data fusion, anomaly detection and a self-learning optimization module, the high-precision inspection capability in a complex environment is realized, a data acquisition strategy is dynamically adjusted based on different environmental states, weight distribution and time synchronization fusion are performed on video images, thermal imaging and audio data, and the accuracy of inspection is improved. And the fusion precision of the multi-modal data and the accuracy of anomaly detection are effectively improved.

The invention discloses an intelligent power plant joint inspection system and method based on video AI and a robot, and the method comprises the steps: dividing an intelligent power plant into a plurality of subareas, evaluating the danger levels of the plurality of subareas according to historical data, and obtaining the danger levels of the plurality of subareas; setting an inspection cycle according to the danger levels of the plurality of partitions, and setting a plurality of robots to acquire operation data according to the inspection cycle to obtain inspection data of the plurality of partitions; acquiring a plurality of monitored videos, and performing video analysis on the acquired monitored videos by using an AI technology to obtain an abnormal position; according to the abnormal position, distributing an inspection robot of a corresponding partition to carry out fixed-point inspection to obtain fixed-point inspection data; and performing fault detection on the periodic inspection data and the fixed-point inspection data by using the fault recognition model, and performing fault early warning according to a fault detection result. The invention relates to the technical field of power plant inspection, and solves the technical problems of unreasonable inspection resource distribution and untimely fault early warning in an existing combined inspection system.

A bridge apparent disease inspection method, inspection system and inspection apparatus, relating to the technical field of bridge maintenance. The method comprises: obtaining, in real time, an inspection image set photographed by a monocular camera in a bridge inspection process; dynamically identifying a target disease in the inspection image set by using a visual inspection algorithm; selecting a two-dimensional code positioning point, determining spatial position coordinates of the two-dimensional code positioning point, and calculating a first relative position between the monocular camera and the two-dimensional code positioning point on the basis of an eight-orientation two-dimensional code positioning method; determining a relative distance and a relative angle between the monocular camera and the target disease, and obtaining a relative position between the target disease and the monocular camera by means of calculation by using the relative distance and the relative angle; and obtaining spatial position coordinates of the target disease by means of calculation by using spatial position coordinates of the monocular camera and the relative position between the target disease and the monocular camera. The technical problems in the prior art that bridge apparent disease inspection is mainly manual inspection, the danger coefficient is high, and the inspection result is affected by subjective factors are solved.

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 discloses a patrol safety management system for a new energy power station based on Beidou positioning and image analysis, including: a determination module, used to generate a patrol route according to a patrol plan, determine a standard route trajectory map according to the patrol route, and configure the patrol personnel plan according to the attributes of the patrol personnel; a collection and positioning module, used to locate the real-time position of the patrol personnel through Beidou positioning based on the patrol personnel plan and collect patrol video data at the same time; a first early warning module, used to identify the illegal behavior of the patrol personnel according to the patrol video data, determine the violation type according to the identification result and perform corresponding early warning processing; a second early warning module, used to generate a real-time patrol trajectory according to the real-time position of the patrol personnel, compare the deviation degree of the real-time patrol trajectory with the standard route trajectory map, and issue a deviation warning according to the deviation degree. No human intervention is required, which effectively prevents the occurrence of illegal behaviors during the patrol inspection process and improves safety and processing efficiency.

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 an intelligent inspection method, system and device for a smart power plant, and relates to the technical field of smart energy, and the method comprises the steps: collecting the real-time equipment data of target equipment in a target smart power plant, constructing a three-dimensional virtual power station model, obtaining the historical and real-time operation data of the target equipment, constructing an equipment fault prediction model based on a machine learning algorithm to locate a fault position, collecting a photovoltaic inspection image of a photovoltaic module in the target intelligent power station through unmanned inspection equipment, carrying out hot spot recognition to generate potential photovoltaic hot spot information, and recognizing an equipment surface abnormal state based on a visual technology and a deep learning algorithm. A fireproof detection network is constructed to monitor the current area temperature of a target intelligent power station, the current area temperature is compared with a preset temperature threshold value to generate abnormal temperature information, and finally an intelligent inspection result is generated and sent to a management end, so that efficient, accurate and real-time intelligent inspection of electric power facilities can be realized, the operation and maintenance efficiency is improved, and the operation and maintenance cost is reduced. And safe and stable operation of power facilities is ensured.

The invention relates to the field of security inspection management, and particularly discloses a public place security inspection management system based on Internet of Things, which is characterized in that a plurality of fixed inspection nodes are arranged in a key inspection area according to public place types and layout identification, and the rationality of the arrangement of the fixed inspection nodes is ensured; each to-be-selected inspection route of the inspection equipment is formulated according to a fixed inspection node, a historical emergency location and current pedestrian flow distribution, and an optimal inspection route is screened according to an inspection coverage degree and an inspection equipment energy consumption evaluation index, so that the dynamic planning and adjustment of the inspection route of the inspection equipment are realized, and the inspection efficiency is improved; according to the method, video data and measurement data collected by fixed inspection nodes and inspection equipment are extracted, hidden danger points in a public place are identified and safety risk levels are evaluated and corresponding early warning is performed in combination with a safety event sample map library and an environment parameter range, multi-source data fusion is realized, and the judgment precision of safety risks in a complex scene is improved.

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 provides a robot automatic inspection management method and system and electronic equipment, and relates to the technical field of automation control, and the method comprises the steps: obtaining a to-be-inspected area, dividing the to-be-inspected area into a plurality of inspection subareas, then distributing the inspection subareas for a plurality of robots, and determining the inspection routes of the robots. And controlling the robot to execute an inspection task according to the inspection route, and recording inspection state information including the current inspection partition and the completion degree of the robot in real time. When an emergency inspection task is received, acquiring emergency inspection task information, determining a target robot based on the emergency inspection task information and the inspection route and the inspection state information of each robot, merging the emergency inspection task into the inspection route of the target robot, and setting priority processing to obtain a target inspection route; and controlling the target robot to execute the inspection task. The inspection efficiency of the robot and the flexibility in the inspection process can be improved.

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 relates to the technical field of inspection robots, and particularly discloses an underground pipe gallery environment detection system and method based on an inspection robot, and the system comprises a robot inspection system, a data transmission system, a monitoring system, an alarm system, and an artificial auxiliary inspection system. The robot inspection system comprises a pipeline, a charging storage bin, a controller, a carrying mechanism, a ground moving mechanism and an external detection mechanism. The carrying mechanism is arranged outside the charging storage bin; the ground moving mechanism is arranged outside the carrying mechanism; and the external detection mechanism is detachably placed outside the pipeline. Mobile inspection can be quickly and automatically carried out in the pipe gallery, inspection personnel are prevented from directly entering a dangerous environment, data are remotely analyzed in real time, early warning is carried out in time when fault hidden dangers are found, detection operation can be carried out along an external area of a pipeline and a ground area, and comprehensive state information of the pipe gallery is obtained at a time; and the time cost of multiple times of detection is reduced.

The invention relates to the technical field of data acquisition and analysis of inspection equipment, in particular to an intelligent inspection method and system based on data acquisition and multi-modal AI and terminal equipment. Performing data consistency judgment analysis on each voxel block in the voxel space to obtain each multi-modal data set of the inspection target in a preset time; obtaining modal features of each multi-modal data set, and processing the modal features of each multi-modal data set according to a preset mapping and weight mechanism to obtain a multi-modal fusion feature vector fusion model of the inspection target; the inspection target is analyzed according to the multi-modal fusion feature vector fusion model and the multi-modal fusion feature vector reference model, the working state of the inspection target is obtained, and the working state of the inspection target can be accurately judged, so that the accuracy, reliability and comprehensiveness of inspection are improved, and normal operation of equipment is guaranteed.

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 generative MR industrial inspection method based on a large model and natural man-machine interaction, and belongs to the technical field of intelligent inspection. In order to solve the technical problems of long development period and high cost of MR inspection, the method comprises the following steps: acquiring a scene image sequence to be inspected by using MR head display equipment, constructing an inspection scene image data set, and training a multi-modal large model by using the inspection scene image data set to obtain category sequence information data to be inspected; acquiring corresponding spatial positioning information and interaction information, constructing an inspection module data set based on the acquired spatial positioning information and interaction information, and then training an inspection module by using the inspection module data set to obtain to-be-detected information of an inspection sequence of the inspection module; fitting the category sequence information to be inspected and to-be-detected information of the inspection sequence of each inspection module to obtain an inspection execution model; and executing a generative MR industrial inspection process based on the large model and natural man-machine interaction by using the inspection execution model.

The invention provides an unmanned aerial vehicle inspection method, system and device and a storage medium, and relates to the technical field of unmanned aerial vehicle inspection, and the method comprises the steps: dividing a to-be-inspected fire region into a plurality of sub-regions, and determining the number of unmanned aerial vehicles required by each sub-region and a first inspection route according to the region area and the region feature of each sub-region; according to the fire behavior data of each sub-region, predicting a fire behavior spreading range of each sub-region in a preset duration, and determining a newly added to-be-inspected sub-region of each sub-region; determining a second inspection route of each unmanned aerial vehicle by combining the target region area and the target region feature of the newly added sub-region to be inspected and the residual electric quantity and the target position of each unmanned aerial vehicle; and sending the first inspection route and the second inspection route to each unmanned aerial vehicle, so that each unmanned aerial vehicle performs inspection according to the first inspection route and the second inspection route. The technical effect of the invention is that the monitoring requirement of dynamic spreading of forest fire can be effectively met.

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 invention discloses an intelligent inspection method for a green building, and the method comprises the following steps: obtaining the latitude and longitude information of an inspection point and the number of the inspection point, and inputting the latitude and longitude information of the inspection point and the number of the inspection point into a label; acquiring positioning source data of the position of the inspection maneuvering equipment; performing data fusion on the positioning source data and the label data, splicing the fused positioning data and the label data to generate combined positioning data, and encrypting the combined positioning data to generate inspection positioning data; and obtaining routing inspection result positioning information, comparing the routing inspection result positioning information with the routing inspection positioning data, and finally obtaining a positioning correction result. Compared with the prior art, the method has the advantages that the accuracy and stability of data are improved, the inspection efficiency is improved by the comprehensive label technology, the workload of personnel is reduced, and the method can adapt to different scenes.

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 unmanned aerial vehicle inspection, in particular to a distribution line unmanned aerial vehicle intelligent autonomous inspection system which comprises a node positioning module, an unmanned aerial vehicle inspection module, a path planning module, a plan customization module, a data receiving module, a cloud server and a central control module. The specific condition of unmanned aerial vehicle inspection is determined according to the actual inspection time of the unmanned aerial vehicle, and when it is determined that the operation of the unmanned aerial vehicle inspection module is abnormal, the operation of the unmanned aerial vehicle is regulated and controlled according to the abnormal proportion. And adjusting the moving speed of each unmanned aerial vehicle to a corresponding value, correcting each planned inspection time or sending a charging instruction for the corresponding unmanned aerial vehicle, thereby improving the inspection efficiency of the unmanned aerial vehicle.

The invention provides an unmanned aerial vehicle cooperative wind power plant intelligent inspection method and system, and relates to the technical field of unmanned aerial vehicle inspection. The method comprises the following steps: receiving a foundation cloud picture and meteorological characteristic data of a wind power plant in a target area; preprocessing the foundation cloud picture to obtain a foundation cloud picture image, and performing segmentation, feature extraction and recognition processing on the foundation cloud picture image to obtain foundation cloud picture features; extracting features of the meteorological feature data to obtain meteorological features; and inputting the ground-based cloud picture features and the meteorological features into a preset fan equipment operation risk prediction model, calculating to obtain a risk index of the fan equipment, and controlling the unmanned aerial vehicle to perform inspection according to the risk index. The problems that the existing inspection system does not consider the influence of meteorological characteristics on the inspection work, so that the inspection system of a wind power system cannot accurately predict the operation risk of fan equipment, the working difficulty is increased, and the operation requirement of a smart wind power plant is difficult to meet are solved.