The invention relates to a power equipment defect intelligent identification method and system based on in-process check images obtained by an unmanned aerial vehicle. The method includes acquiring power transmission line image data in batches by adopting a data flow mode; extracting image features; performing integrated analysis on the image features to achieve automatic positioning and identification for critical components; performing corresponding defect analysis on the critical components according to set defect identification rules to achieve analysis and identification on common defects; summarizing and analyzing analysis and identification results; performing classification according to component types, defect types and the degree of defects so as to facilitate search by classification according to needs; and locally enlarging and displaying specific components. The method and the system can effectively excavate huge value of unstructured big data of in-process check of power grids, refine in-process check processes, and have significance effects on stable running of power transmission lines.

A power equipment defect intelligent identification method and system based on in-process check images obtained by an unmanned aerial vehicle

The invention discloses an unmanned aerial vehicle comprehensive management platform system and belongs to the unmanned aerial vehicle comprehensive management technical field. The unmanned aerial vehicle comprehensive management platform system comprises at least one unmanned aerial vehicle system and a management center end system, wherein each unmanned aerial vehicle system includes an unmanned aerial vehicle and a ground control station or a remote control unit and carries out wireless transmission with the management center end system through the ground control station or the remote control unit, wherein the unmanned aerial vehicle is connected with the ground control station or the remote control unit through a wireless communication mode; and the unmanned aerial vehicle comprehensive management platform system further comprises an authentication module, an air traffic control module, an interference module and a meteorological module, wherein the authentication module, the air traffic control module, the interference module and the meteorological module are connected with the unmanned aerial vehicles through wireless communication and by means of the management center end system. The unmanned aerial vehicle comprehensive management platform system can comprehensively manage unmanned aerial vehicle flight access authentication, command scheduling, alarm notification and the like, and has a bright application prospect in aspects such as management of unmanned aerial vehicles for mass consumption and management of unmanned aerial vehicles for national industrial departments.

Unmanned aerial vehicle comprehensive management platform system

The invention discloses a system and method for flight obstacle avoidance of an unmanned aerial vehicle based on real-time kinematic (RTK). The method comprises the following steps: a step S1: the unmanned aerial vehicle flies according to a planned path; a step S2: pictures in front of a flight line are shot in real time through a camera; a step S3: the shot pictures are transmitted to an image processor; a step S4: ground station software marks obstacles; a step S5: after processing the pictures, the image processor transmits processing results to an RTK positioning system; a step S6: the RTK positioning system exactly positions the unmanned aerial vehicle, quickly corrects the air line according to the sizes of the obstacles, determining a flight track, and finally going round the obstacles; and a step S7: after going round the obstacles, the unmanned aerial vehicle continues to fly according to the original planned path. The camera shooting is adopted in the system, so that the weight of the unmanned aerial vehicle is alleviated, and the cost of the unmanned aerial vehicle is reduced. The RTK positioning system is adopted to improve the positioning accuracy of the unmanned aerial vehicle to a centimeter level, the unmanned aerial vehicle can learn about its exact spatial position in the flight process, and support is provided for real-time obstacle avoidance and quick correction of the error air line.

System and method for flight obstacle avoidance of unmanned aerial vehicle based on real-time kinematic (RTK)

The embodiment of the invention provides an aircraft autonomous obstacle avoidance system and method and an aircraft. A binocular camera and a millimeter wave radar are combined. A push broom stereo vision algorithm and an advanced image data fusion method are used to mark an obstacle and detect the obstacle. The position and shape and texture information of the obstacle in front of the aircraft can be quickly and accurately acquired. An accurate basis is provided for the aircraft to avoid the obstacle in real time. The autonomous flight and intelligence level of the aircraft is improved. Theenvironmental adaptability of the aircraft is enhanced. The aircraft can safely fly to complete a task in a complex environment.

Aircraft autonomous obstacle avoidance system and method and aircraft

The invention discloses a monitoring system based on an unmanned aerial vehicle, comprising an unmanned aerial vehicle terminal, an intelligent equipment terminal, a cloud terminal server and a monitoring terminal, wherein the intelligent equipment terminal is adhered to the monitored target, a first communication module and a processor module are arranged in the intelligent equipment terminal, the unmanned aerial vehicle terminal is connected with the intelligent equipment terminal, a tracking module is arranged in the unmanned aerial vehicle terminal, the unmanned aerial vehicle terminal can fly along the intelligent equipment terminal by the tracking module. The internal shooting module is used for obtaining the real-time video information of the monitored target and the surroundings, a second inner communication module is used for communicating with the information of the first communication module, the intelligent equipment terminal uploads the real-time information of the monitored target to the cloud terminal server by the first communication module, and the monitoring terminal can obtain the real-time information from the cloud terminal server. The unmanned aerial vehicle in the invention is used as the front-end monitoring equipment so as to solve the problems of limited monitoring range, high monitoring cost and monitoring dead angle existing in the traditional monitoring system.

Monitoring system and device based on unmanned aerial vehicle

The invention discloses a multi-sensor fusion-based autonomous obstacle avoidance unmanned aerial vehicle system and a control method. The system includes an environment information real-time detection module which carries out real-time detection on surrounding environment through adopting a multi-sensor fusion technology and transmits detected information to an obstacle data analysis processing module, the obstacle data analysis processing module which carries out environment structure sensing construction on the received information of the surrounding environment so as to determine an obstacle, and an obstacle avoidance decision-making module which determines an obstacle avoidance decision according to the output result of the obstacle data analysis processing module, so as to achieve obstacle avoidance of an unmanned aerial vehicle through the driving of power modules which is performed by a flight control system. According to the multi-sensor fusion-based autonomous obstacle avoidance unmanned aerial vehicle system and the control method of the invention, binocular machine vision systems are arranged around the body of the unmanned aerial vehicle, so that 3D space reconstruction can be realized; and an ultrasonic device and a millimeter wave radar in an advancing direction are used in cooperation, so that an obstacle avoidance method is more comprehensive. The system has the advantages of high real-time performance of obstacle detection, long visual detection distance and high resolution.

Multi-sensor fusion-based autonomous obstacle avoidance unmanned aerial vehicle system and control method

The invention discloses a system and a method for real-time unmanned plane flight state evaluation early warning. The system comprises an evaluation early warning platform, an unmanned plane and a ground monitoring station, wherein the ground monitoring station is used for monitoring the flight state data of the unmanned plane and transmitting the data to the evaluation early warning platform, the evaluation early warning platform is used for reading the flight state information and flight control data of the unmanned plane, through the flight control data of the unmanned plane accumulated at each inspection, an unmanned plane flight state evaluation model is constructed, the flight state of the unmanned plane is determined, a flight instruction transmitted by a host computer is further received, and flight of the unmanned plane is adjusted. According to the method, the flight control data of the unmanned plane can be inspected through a power transmission line, through the combined time sequence analysis, clustering analysis and supporting vector machine analysis method, the flight state evaluation early warning model is constructed, and real-time flight state evaluation early warning of the unmanned plane in the power transmission line inspection process can be realized.

System and method for real-time unmanned plane flight state evaluation early warning

The invention discloses an automatic detection method for partial discharge of a switch cabinet based on a multi-vision system. The automatic detection method comprises the steps that a robot autonomously moves along a navigation route according to navigation marks laid in a switching station, and the robot stop in front of a switch cabinet to be detected when a stop mark is detected; target location is completed according to shape features, which are acquired by a binocular vision system, of a target, then three-dimensional coordinate calculation for related points in an image is completed based on feature point matching and a parallax principle; movement of a mechanical arm is controlled so as to enable the tail end of the mechanical arm to carry partial discharge detection equipment to reach the position of a target point, pixel deviation of a target area is calculated by using an image taken by a monocular camera arranged at the tail end of the mechanical arm, and position correction is carried out on the mechanical arm according to coordinate position deviation of the target; and different modes of partial discharge detection are carried out on the switch cabinet. According to the invention, a binocular vision system and monocular vision system combining target positioning method is adopted, accurate positioning for a partial discharge detection target is realized, and the error caused by single vision system positioning is reduced.

Automatic detection method for partial discharge of switch cabinet based on multi-vision system

The invention relates to a patrol wheel-pedrail type obstacle-crossing robot for transformer substations. The patrol wheel-pedrail type obstacle-crossing robot mainly comprises a chassis, a power mechanism and swing arms. The power mechanism is installed on the chassis and is provided with a walking power source and a swing arm power source, and the walking power source outputs power to walking wheels installed on two sides of the chassis through a transmission shaft. The swing arms are driven by the swing arm power source and are provided with a main walking belt wheel, a swing arm belt wheel and meshed walking pedrails, and the main walking belt wheel is coaxially assembled with the walking wheels. The swing arm power source drives the swing arms to swing for realizing the pedrail walking mode and/or the walking wheel walking mode of the robot. The patrol wheel-pedrail type obstacle-crossing robot can walk in different modes according to different road conditions and obtain the high obstacle-crossing ability through swinging of the swing arms.

Patrol wheel-pedrail type obstacle-crossing robot for transformer substations

The invention discloses a method and system for rapidly transferring multi-source heterogeneous power grid big data to HBase. The method includes the following steps that a power grid database is connected with an HBase data platform; each datum in the power grid database has a unique mark ID and is composed of the mark ID and data content; according to unique mark IDs, an ID mapping table is established; after a data source is selected, the ID mapping table is read and written into a memory for residence; codes in the ID mapping table are each compressed, so that data class ID row keys and data class internal ID row keys are formed; the data class ID row keys and the data class internal ID row keys are converted into a byte array; the data class ID row keys, the data class internal ID row keys and the row name qualifier of HBase are written into an HBase table in a byte form. Rapid transferring is achieved for a complex electric power data format through the method and system.

Li Yong

Papers

Multi-sensor fusion-based autonomous obstacle avoidance unmanned aerial vehicle system and control method

System and method for real-time unmanned plane flight state evaluation early warning

Automatic detection method for partial discharge of switch cabinet based on multi-vision system

Patrol wheel-pedrail type obstacle-crossing robot for transformer substations

Method and system for rapidly transferring multi-source heterogeneous power grid big data to HBase