Abstract
Wind energy is one of the important renewable energy resources because of its reliability due to the development of the technology and relative less cost. “The wind energy are converted into electrical energy using rotating blades which are connected to the generator. Due to environmental conditions and large structure, the blades are subjected to various faults and cause the lack of productivity. The downtime can be reduced when they are diagnosed periodically using structural health monitoring. These are considered as a pattern recognition problem which consist of three phases, namely feature extraction, feature selection and feature classification. In this research, statistical features are extracted from vibration signals, feature selection are carried out using J48 algorithm and the feature classification is done with a rotation forest algorithm
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