Real-Time Abnormal-Signal Detection Under a Noisy Environment Using a Resonance Filter

Abstract

In this article, we present improved short-time Fourier transform for fault detection of field coils, among the most important parts in rotating machinery. It is generally difficult to detect a fault signal of a field coil due to the low signal-to-noise ratio (SNR) associated with these signals. To solve this problem, we constructed a parallel resonance circuit using the inductance of the field coil and improved the SNR of the fault detection signal by using the bandpass filter characteristics of the resonance circuit. The transfer function curve upon parameter changes of the proposed resonance circuit is presented, and the governing equation is derived so that the resonance frequency can be calculated. We also carried out a fault detection test to verify the feasibility of the proposed method. As a result, we demonstrated that the proposed method can enhance the SNR and enable fault detection using the extracted abnormal signal. Also, it was confirmed that the proposed system responds instantaneously to an abnormal signal for fault detection. Therefore, it is proved that the methodology presented in this article is efficient for fault detection in rotating machinery.