Abstract
In this era of automation, rolling elements such as gear and bearing are widely used to transmit power and motion. The rolling elements’ bearings and gears play a pivotal role in determining the life span of a machine employed in the industry. The bearings and gears produce vibrations in the working machine. These vibrations can be used to estimate the faults in bearings and gears equipped in the machine. In this paper, the vibrational analysis techniques such as time-domain analysis and frequency-domain analysis (using FFT in MATLAB) were used for the fault detection in bearings and gears. A setup was built to capture the vibrational signal from three cases: healthy setup, faulty gear setup, and faulty bearing setup. The vibrational signal analysis was performed to compute the kurtosis value, peak value, RMS value, average value, standard deviation, and other statistical parameters used to estimate the system’s fault.
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Kaur, T., Gagandeep (2021). Vibration Analysis for Failure Detection of Bearing and Gear Assembly. In: Parey, A., Kumar, R., Singh, M. (eds) Recent Trends in Engineering Design. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-1079-0_5
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DOI: https://doi.org/10.1007/978-981-16-1079-0_5
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