A Blades Biofouling Diagnosis Method Based on Gray-Weighted Dempster-Shafer Evidence Theory for Marine Current Turbine

Marine current turbine (MCT) blades are continuously exposed to seawater, making them susceptible to marine biofouling and causing MCT blade imbalance faults. The diagnosis method based on a single sensor often fails when the data quality is poor. To realize the complementarity of multi-sensor information, a blades biofouling diagnosis method of MCT based on Gray-weighted Dempster-Shafer (GD-S) evidence fusion is proposed, which uses the fusion of the current sensor and image sensor. Firstly, the collected images and stator current are preprocessed to enhance the features of blade biofouling. Secondly, the MCT images and current signal features are used to construct 1DCNN and 2DCNN models respectively, and the probability of the two models are output. Finally, the probabilities of the two models are fused based on the proposed GD-S evidence fusion method. To verify the effectiveness of the proposed method, experiments are carried out on a 230W MCT platform. The results show that the proposed method has satisfactory performance for symmetrical biofouling and poor illumination.