An On-Line Condition Monitoring System for Incipient Fault Detection in Double-Cage Induction Motor

Abstract

This paper presents a complete on-line condition monitoring system (CMS) designed to detect incipient broken rotor bar (BRB) fault in double-cage induction motor (DCIM) using the stator current signature. The novelty of this paper lies in the successful combination of one of the latest variants of wavelet techniques, the recursive stationary wavelet packet transform and the widely used tool in quality control, the statistical process control (SPC) in order to deal with several challenges in the continuous monitoring of incipient BRB fault. In fact, breakage in outer bars (OBs) of a DCIM is known to be less prone to exhibit fault signature in the stator current than that of a single-cage IM, especially during the steady motor operation mode. Furthermore, on-line CMSs should at the same time act at normal motor operating mode, including steady and transient modes and be reconfigurable with no motor size dependence. The complete on-line CMS was designed and implemented in a low-cost hardware environment and was validated with 3-kW DCIM featuring incipient OB faults. A 100% fault detection accuracy starting from 3-mm OB breakage during normal motor operating mode, with the autolearning fault threshold, demonstrates the reliability and flexibility of the proposed system.