Multi-rotor unmanned aerial vehicle intelligent inspection system

[0016] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0017] like figure 1 As shown, a multi-rotor UAV intelligent inspection system includes an inspection UAV. The main body of the inspection UAV is equipped with a background analysis unit, an intelligent analysis unit, an alarm unit and an intelligent inspection analysis unit. The background analysis unit is used to make auxiliary judgments for the inspection system, perform fuzzy analysis to judge suspicious targets, and then send out signals. The intelligent analysis unit is used to receive the signal from the background analysis unit, detect suspicious targets, take pictures of suspicious targets and transmit the images. The intelligent inspection analysis unit is used to receive the image transmitted by the intelligent analysis unit, and analyze and confirm suspicious objects. The intelligent inspection analysis unit analyzes the location of the inspection UAV, and then analyzes and sets according to the TSP, loads the relevant intelligent algorithm module, and optimizes the algorithm of CNN-TSP, so that the inspection UAV can find the optimal location in the first time. line. The inspection UAV traces to the suspicious object, collects the information of the suspicious object and transmits it to the intelligent analysis unit. The intelligent analysis unit analyzes the suspicious object as the fault target and transmits the signal to the alarm unit. The alarm unit is used to receive the signal of the intelligent analysis unit and issue an alarm. The intelligent analysis unit includes linkage unit, early warning unit and redundant architecture (including intelligent inspection), which can realize linkage alarm and detect suspicious targets. Intelligent linkage improves the accuracy and efficiency of inspections. Suspicious targets are generally huge objects or equipment/facilities that affect safety. After receiving the image transmitted by the intelligent analysis unit, the intelligent patrol analysis unit converts the image into binary data, stores and analyzes the binary data, and uses decision tree analysis method to judge and confirm suspicious objects.

[0018] like image 3 As shown, the background analysis unit includes smart analysis unit monitoring, alarm unit detection and behavior recommendation, smart analysis unit and psobp decision-making. The background analysis can make auxiliary judgments for the UAV intelligent inspection system, and perform fuzzy analysis to judge suspicious targets. The intelligent analysis unit monitoring is used to analyze and monitor whether the behavior of the intelligent analysis unit is accurate. Alarm unit detection and behavior recommendation is used to detect the good or bad state of the alarm unit and perform behavior recommendation. Behavior recommendations include recommendations on whether to perform intelligent inspections and the protective measures to be taken by intelligent inspections. The intelligent analysis unit and psobp decision-making use big data to train and identify the psobp algorithm, establish a network architecture NET, and then enter the original set network for a certain new data to make judgments and decisions, and intelligently assist humans to make judgments . The intelligent analysis unit and psobp decision-making mainly carry out the intelligent analysis of the inspection UAV, analyze the fault types and the integrity of the function realization of each interface unit, ensure the reliability and safety of the whole system, and collect big data for psobp algorithm-based Analysis and judgment.

[0019] like figure 2 As shown, the intelligent inspection analysis unit includes UAV position analysis, optimal route analysis, and distribution of UAV path schemes. First, the position of each UAV is obtained, and then the optimal route analysis is performed. The most suitable path achieves the effect of asking for help or linkage at the first time, and finally assigns the UAV path and informs the UAV to carry out the distribution image. The location analysis of inspection UAVs includes the fusion of data from GPS devices, cameras, and sensors, and comprehensive processor synthesis from the perspective of multi-information. According to the different heights and states of the drone, the structure of the sensor input information is adjusted to achieve centimeter-level accurate analysis of the drone, which is more robust.

[0020] The working principle of the patrol inspection is as follows: the background analysis unit makes auxiliary judgments on the patrol inspection system, performs fuzzy analysis to judge suspicious targets, and sends out signals, and the intelligent analysis unit receives signals from the background analysis unit to detect suspicious targets and conduct The image is taken and sent out, and the intelligent inspection analysis unit receives the image transmitted by the intelligent analysis unit, analyzes and confirms the suspicious object. That is, after the intelligent analysis unit discovers suspicious targets, it transmits the information to the intelligent patrol analysis unit, and then the intelligent patrol analysis unit analyzes and sets according to the TSP, loads the relevant intelligent algorithm module, and optimizes the algorithm of CNN-TSP, so that all unmanned The drone can find the best path in the first time (according to the safety distance standard of the relevant transmission line), select the best distance, track the target and diagnose suspicious situations, the optimal route is sent to each UAV, and the UAV according to Take images at the places you want to go, and pass the collected images to the intelligent analysis unit through the communication module, and the intelligent analysis unit analyzes suspicious objects, such as fires, hidden defects, etc. If the suspicious object is determined to be the fault target, the signal will be transmitted to the alarm unit, and the alarm unit will send out an alarm to notify relevant personnel.

[0021] The principle of image processing after the inspection, the UAV receives the instructions of CNN-TSP, takes pictures according to the location it is going to, and transmits the collected images to the intelligent analysis unit, which also includes the image processing unit and communication module , Carry out relevant intelligent analysis on the image, such as fire, hidden defects, dangerous failure analysis, etc., and timely push relevant information to the staff's mobile phone or computer to remind and eliminate defects in time.

[0022] The above is only a preferred embodiment of the present invention, it should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, some improvements and modifications can also be made. It should also be regarded as the protection scope of the present invention.