Fault Diagnosis for Wind Turbine Systems
Abstract This chapter presents a tutorial treatment on the basis principles of model based and data driven fault detection and isolation strategies with application to dynamic processes. The FDI problem has been formalized in a uniform framework by presenting a mathematical description and definition. Within this framework, the residual generation has been identified as a central issue in both model based and data driven FDI. By choosing the proper design approach, the FDI task can be performed. The residual generator is summarized in different residual generation structures. The ways of designing residuals for fault isolation are also discussed. The most commonly used residual generation strategies are recalled by presenting related problems and discussing the applicability of model based and data driven FDI methods to dynamic processes such as wind turbine systems. The success of fault diagnosis depends on the quality of the residuals. Successful diagnosis requires residual signals, which should be robust with respect to modeling uncertainty. The robust FDI problem is also discussed in this chapter, and the implementation of robust residual generators will be shown in the following chapters of the book.