FPGA Based Embedded System Development for Rolling Bearings Fault Detection of Induction Motor - Shashidhara SM; Sangameswara P Raju (Institute of Advanced Engineering and Science, 2013)
Bearing fault diagnosis is crucial in condition monitoring of any rotating machine. Early fault detection in machines can save millions of dollars in maintenance cost. Different methods are used for fault analysis such as short time Fourier transforms (STFT), Wavelet analysis (WA), Model based analysis, cepstrum analysis etc. Recently, there have been outstanding technological developments related to digital systems, in both hardware and software. These innovations enable the development of new designing methodologies that aim to the ease the future modifications, upgrades and expansions of the system. This paper presents a study of rolling bearing fault diagnosis of induction motor based on reconfigurable logic. A case study using FPGA, its design, as well as its implementation and testing, are presented.