• ANKIT A. DARJI
• Dr. P. H. Darji
• Dr. D. H. Pandya

This Diagnosis of rolling bearing based on vibration signature analysis in Time-frequency domain. Its signal analysis techniques, centered on spectral approaches such as the FFT are powerful in diagnosing a selection of vibrationrelated problems in rotational machinery. While these techniques provide powerful diagnostic tools in stationary conditions, they fail to do so in numerous practical cases concerning non-stationary data. Recent development in signal processing approaches make available new methods in time-frequency representation, which major information regarding the time happening of the fault. In this research paper delivers a comparative learning between traditional signal processing methods, like periodograms, Welch Periodogram, Spectrogram and the Scalogram. Presentations of these techniques are evaluated through experimentations and compared for single point defects on IR, OR and ball fault, including balanced condition of rotor bearing system.

Bearing Diagnostics, Time-frequency domain, Spectogram, Welch Periodogram

"Fault Diagnosis of Rolling Element Bearing with Advance Signal Processing Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.720-724, December-2018, Available :http://www.jetir.org/papers/JETIR1812791.pdf

"Fault Diagnosis of Rolling Element Bearing with Advance Signal Processing Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp720-724, December-2018, Available at : http://www.jetir.org/papers/JETIR1812791.pdf