Fault Detection in Induction Motors

Abstract

This chapter introduces recent developments in fault diagnostics of induction motors (IMs), by providing theoretical, simulative, and experimental results along with a number of implementation-related practical considerations and guidelines. Remarkably, methods for IM fault detection in both steady-state and transient operating conditions will be outlined. The chapter is structured as follows: Section 14.2 is a short introduction in which the more common faults of IM are concisely described as well as their causes, consequences, and symptoms. Section 14.3 introduces an example of model-based approach for fault detection and isolation (FDI) in IMs based on dynamical observers. Sections 14.4, 14.5, 14.6, 14.7, 14.8, and 14.9 deal with diagnostic techniques based on signal analysis approaches; in all of these approaches the stator current is used as diagnostic signal; stator current is the most used diagnostic signal in the industrial applications, since it enables for noninvasive diagnostic and does not require the use of additional probes. Sections 14.4 and 14.5 are dedicated to signal analysis techniques valid for steady-state operation; these methods, commonly designated as motor current signature analysis (MCSA) include the conventional Fourier transform (FT) approaches, and the more recently developed Hilbert-transform (HT)-based approaches. Today, the steady-state-based techniques are the most spread in the industrial environment; nevertheless, they cannot be used in some important applications—for example, wind generators or electrical vehicles—in which the functioning conditions continuously vary. Thus, in Sections 14.6, 14.7, 14.8, and 14.9,