ABSTRACT
This chapter gives a general outline in the thrust area of artificial intelligence (AI) paradigm for structural health monitoring (SHM) process for damage detection used for wind turbine and allied areas. The machine learning techniques provide an opportunity for condition monitoring by observing the various components of wind turbine to identify changes in its operation and notify about the promising failure. In addition to this, some fundamental and future scopes of the machine learning approach for SHM have been discussed. This chapter briefs about applying machine learning techniques for fault assessment such as detection of damage and its localization and quantification for different parts associated with wind turbine tower. The capability of different machine learning models to estimate damage in wind energy system has motivated us to utilize them. Thus, this chapter focuses on the different AI techniques and acquires significant consideration and are established themselves as a novel group of intelligent methods for use in structural engineering for wind turbine.
