A Review: Full-cycle Nondestructive Testing Based on Visible Light and Thermography of Wind Turbine Blade

doi:10.3901/JME.2023.06.032

Abstract

Abstract: Non-destructive testing of wind turbine blades is very important during manufacturing, service, and maintenance. The blade works under the high-strength wind load for a long time, thus any tiny defects produced in the manufacturing process will expand in service, which further threatens the normal operation of the fan. Therefore, the non-destructive testing of blades has always been a difficult problem in industry and academia. According to the visual inspection method, combined with the application of unmanned arrial vehicle(UAV) technology, related data including image processing method and the intelligence of defect evaluation method, the previous work of predecessors will be summarized, analyzed and compared. At present, vision-based detection methods such as visible light visual detection and infrared thermal imaging detection have met the requirements on non-contact, high efficiency, low cost, safety, and so on. The combination of visual inspection and UAV inspection technology could ensure the safety of personnel, and overcome the problem of limited field of vision of telescope inspection. However, this detection method still has some shortcomings, such as difficulty quantifying the defects and low recognition rate of internal defects. Through the analysis and comparison of visible light detection and thermal imaging detection technology, a conclusion can be drawn that the UAV equipped with a dual light fusion detection method combined with an intelligent algorithm is expected to solve the shortcomings of wind turbine blade detection in the future.

Key words: wind turbine blades, thermography, nondestructive testing, machine learning, deep learning

CLC Number:

HE Yunze, LI Xiang, WANG Hongjin, HOU Yuejun, ZHANG Fan, MU Xinying, LIU Hao, CHENG Hao, LI Shihua, LI Jie. A Review: Full-cycle Nondestructive Testing Based on Visible Light and Thermography of Wind Turbine Blade[J]. Journal of Mechanical Engineering, 2023, 59(6): 32-45.

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