Unmanned aerial vehicle system for fan blade detection and control method

Abstract

The invention discloses an unmanned aerial vehicle system for fan blade detection. The unmanned aerial vehicle system comprises a control unit, a communication unit, a first unmanned aerial vehicle and a second unmanned aerial vehicle, wherein the first unmanned aerial vehicle is used for carrying out thermal imaging image sampling on a detected fan blade; the second unmanned aerial vehicle is used for carrying out high-definition image sampling on the detected fan blade. The invention provides the unmanned aerial vehicle (UAV) system and method for fan blade detection, which can improve the detection efficiency and the recognition accuracy, reduce the risk of collision between the UAV and the fan blade, and prolong the service life of the UAV and the fan blade.

Description

technical field [0001] The invention relates to the technical field of detection of wind power generators, in particular to an unmanned aerial vehicle system and control method for detection of fan blades. Background technique [0002] Wind energy is an important renewable energy source. With the expansion of my country's wind energy market, the fan manufacturing industry has gradually entered a period of rapid development. The life and safety of wind turbines affect the pace of wind power utilization and development. Fan blades are the core components of wind turbines, and their life and safety directly affect the life and safety of the entire wind turbine. Due to the complex operating environment of the wind farm, the wind turbine blades operate at high altitude around the clock, and are affected by various factors such as wind and sand, pollution, lightning strikes and typhoons for a long time. The wind turbine blades are prone to defects and gradually expand. If the defe...

AI Technical Summary

Problems solved by technology

Due to the complex operating environment of the wind farm, the wind turbine blades operate at high altitude around the clock, and are affected by various factors such as wind and sand, pollution, lightning strikes and typhoons for a long time. The wind turbine blades are prone to defects and gradually expand. If the defects of the wind turbine blades are not found in time, it will be Directly affects the load and stiffness matrix, ultimately reducing blade life and operational safety

[0003] Currently, the patrol inspection of fan blades is carried out by flying the drone over the designated fan to take pictures and then return, and then export the images taken by the drone for viewing and analysis. The above method requires more labor costs for processing, reducing Detection efficiency and recognition accuracy; in addition, due to human manipulation during the flight of the drone, it is easy to hit the fan and cause damage to the drone, and increase the damage to the surface of the fan blade

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