Diagnosis Methods on the Blade of Marine Current Turbine
Résumé
The global energy crisis has allowed marine currents to enter the field of vision of all countries. Marine current turbine (MCT) is a kind of deep-sea equipment that converts marine current energy into electric power, and its safe and reliable operation is very important. In order to facilitate monitoring of the blade status of MCTs in multiple scenarios, the chapter deals with the diagnosis method of MCT blade followed by different methods. First, a review of the MCT blade fault diagnosis method has been presented. Then two different methods are discussed in this chapter. One is the signal processing method based on the stator current, which includes VMD denoising and proposed novel LDA classifier; the another one is the image semantic segmentation technique based on the MCT image, which includes semantic segmentation and adaptive recognition technical. These two methods can be organically combined under different biofouling cases. When the biofouling is low to affect the output torque of the turbine, the method based on image processing can be useful. On the contrary, the method based on current signal is more convenient and effective. The experimental results show that the two methods proposed in this chapter can effectively detect MCT biofouling in different scenarios. It also proposes several trends for a handle with biofouling problem in conclusion.