A study of condition monitoring for induction motors under accelerated aging process

Wavelets and principal component analysis method for vibration monitoring of rotating machinery

“…Effective utilization of vibration signals depends upon the effectiveness of applied signal processing techniques. The analysis of stationary vibration signals has largely been based on well-known spectral techniques such as: Fourier Transform (FT) and Short Time Fourier Transform (STFT) (Seker and Ayaz, 2002;Shibata et al, 2000). Unfortunately, these methods are not suitable for non-stationary signal analysis (Wu and Liu, 2008).…”

A Review Study on Mathematical Methods for Fault Detection Problems in Induction Motors

“…(1)(2)(3)(4)(5)(6)(7) This paper addresses fault detection methods in induction motors together with theory and applications on experimental data acquired during performance test of the motors subjected to accelerated aging (6)(7) . Detection of eccentricity fault (7)(8)(9) , bearing fault (10)(11)(12)(13)(14)(15)(16)(17)(18) , and stator insulation fault (19)(20) is considered. Applications of statistical methods, power spectral density analysis, coherence analysis, continuous and discrete wavelet transform, autoregressive modeling method, adaptive neuro-fuzzy inference system, artificial neural network is presented by means of the experimental data.…”

Application of Wavelet Transform for Fault Diagnosis in Rotating Machinery

“…Effective utilization of the vibration signals, however, depends upon the effectiveness of the applied signal processing techniques for fault diagnostics. With the rapid development of the signal processing techniques, the analysis of stationary signals has largely been based on well-known spectral techniques such as: Fourier Transform (FT), Fast Fourier Transform (FFT) and Short Time Fourier Transform (STFT) [1], [2]. Unfortunately, the methods based on FT are not suitable for non-stationary signal analysis [3].…”