ABSTRACT
This chapter presents a comprehensive fault detection procedure that performs both the fault detection and decision-making stages taking non ideality into account and maintaining the complexity low enough for digital signal processors (DSP)-based, real-time implementation. Rotor speed is one of the most critical variables that needs to be monitored continuously both for motor control and fault detection. The speed feedback is measured either by an encoder or estimated without speed sensors in the DSP code. The diagnostic decision making based on the threshold trained to the motor line current noise variation can evaluate the reliability of detected signature in DSP applications. Signature-based fault diagnosis performed with reliably detected signatures through the threshold will lead to more accurate condition monitoring while discriminating its results from random noise interference signatures. The power spectral density is one of the algorithms utilizing optimal property of matched filtering, which has been adopted as a high-performance, low-cost fault diagnosis scheme.
