Maintenance 4.0 of Wind Turbine

Abstract

Energy production through Wind turbine installations is increasing fast. In fact, wind turbines become bigger in size and power, what incurs that a simple unit defect causes huge energy losses. They are running in severe conditions of speed and load due to the variation of the wind speed. In addition, Wind turbines are subject to the environmental conditions such as wind shear, turbulence, gusts, rain, snow, sand and sea for offshore wind turbines. For this, their diagnoses and their follow-up is a priority to avoid the stops of production. In, developing techniques for prognostic and remaining useful life estimation is a very urgent necessity in wind turbine maintenance. Maintenance 4.0 is smart maintenance which refers to the last industrial revolution “Industry 4.0”: It proposes strategies to meet these expectations by implementing advanced monitoring techniques through highly developed instruments and real-time signal processing techniques and by building models based on algorithm that will ensure a self- improvement and optimize the failure prediction. In this paper, a process of the predictive maintenance 4.0 is proposed and applied to a wind turbine in order to optimize operating costs and improve the energy efficiency of this system. In fact, dynamic, thermal and material information which are extracted from sensors are combined and characterized in the real time for a global process monitoring.