Abstract

In this paper, two simple digital signal processor (DSP)-based motor fault signature detection techniques are presented. First, the reference frame theory and its applications to fault diagnosis of electric machinery are introduced. Second, phase sensitive detection (PSD) of motor fault signatures is presented. Both techniques provide very simple and robust way to find the magnitude and phase of the specified fault signatures in the line current. Particularly, PSD has a powerful line current noise suppression capability while detecting the fault signatures. Various faults are experimentally tested both offline using the data acquisition system, and online employing the TMS320F2812 DSP to prove the efficacy of the proposed tools. The advantages of these methods include the following: (1) no need to employ external hardware or a PC running a high level program; (2) provides instantaneous fault monitoring using a DSP controller in real time; (3) embedded into the motor drive; thus, readily available drive sensors and the core processor are used without employing additional hardware; (4) no need to store machine currents data, and thus no need for large memory size; (5) very short convergence time capability; (6) immune to non- idealities like sensor dc offsets, imbalance, etc. ; (7) no need for a notch filter to filter out the fundamental harmonic; (8) steady state or stationary current signal assumptions are not necessary; (9) a familiar concept for motor control engineers; and (10) applicable to all multi-phase and single phase motors.

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