A condition-based maintenance policy for offshore wind turbines is presented in consideration of the maintenance uncertainty and the weather effect. In this paper, the offshore wind turbine is divided into four main assemblies—namely, the rotor, gearbox, generator, and pitch system. The support vector machine classification technique is implemented to analyze the failure information, which was collected from field data in China. According to the results of fault diagnosis and prediction, the assembly that reaches the corresponding maintenance threshold will be repaired. At the same time, a maintenance opportunity occurs for the rest of the components, and an optimized plan can be determined by arranging the maintenance combination and time. The calculated results indicate that the proposed condition-based maintenance policy is beneficial to reduce the maintenance expenditure of offshore wind turbines.
Misalignment Fault Prediction of Wind Turbines Based on Improved Artificial Fish Swarm Algorithm
