Fault Detection in Wind Turbines Using Mems Sensor

Mohamed Hassan. S, Mohan Kumar. S, Muthuramalingam. R, Ms. Hemalatha. R ABSTRACT Wind energy is fast-growing sustainable energy technology and wind turbines continue to be deployed in several parts of the world driven by the need for more efficient energy harvesting, the size of the wind turbines has increased over the years (several MW of rated power and over 100m in rotor diameter) for both off-shore and land-based installations. Therefore, Structural health monitoring (SHM) and maintenance as such turbine structures have become critical and challenging and at the same time essential as they evolve into larger dimensions or located in places with limited access. Even small structural damages may invoke catastrophic detriment to the integrity of the system. so, cost-effective, predictive, and reliable structural health monitoring (SHM) system has always been desirable for wind turbines. A real-time non-destructive SHM technique based on multi sensor data fusion is proposed in the project. The objective is to critically analyze and evaluate the feasibility of the proposed technique to identify and localize damages in wind turbine blades. Based on the obtained results, it is shown that information from smart sensors, measuring strains, and vibrations data, distributed over the turbine blades can be used to assist in more accurate damage detection and overall understanding of the health condition of blades.