Automatic Detection Technology of Fan Blade Cracks Based on Multi-Scale Feature Fusion under Intelligent Technology

Wind power generation is based on the use of natural wind energy, driven by a lower wind speed, and converting the kinetic energy passed by the wind wheel into mechanical power to drive the generator to rotate. Therefore, it occupies a very important position in the power system. This paper intends to study the automatic detection technology of wind turbine blade cracks from the multi-scale feature fusion of intelligent technology, with the purpose of real-time monitoring of wind turbine failures and prevention of the stop of wind power generation. In this paper, experimental methods and case analysis methods are mainly used to study the automatic detection technology of fan blade cracks and multi-scale feature fusion. The experimental results show that the accuracy of the multi-feature extraction method in the transverse cracks of the fan blade reaches 95%, which basically meets the requirements.