Abstract
In this paper, it is discussed about the condition monitoring of rolling element bearing as a preventive measure taken so as to do preventive maintenance of bearing. By conducting condition monitoring, it provides us with the present condition of bearing. To do so “Acoustic analysis method” is used, where the acoustic data of bearing is collected on a real-time basis using sensors MAX4466 and MAX9812 with the help of NI-DAQ 9008 and Arduino UNO microcontroller. The acoustic data of the bearing is collected at various shaft speeds by the use of variable speed motor. FFT analysis method is used for the real-time acoustic data analysis by means of LabVIEW software. This paper also focuses on the application of sound pressure and vibration signals to detect the presence of defect in rolling element bearing using acoustic data analysis method and statistical method using kurtosis value analysis.
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Nadar, A., Sangam, R. (2019). Condition Monitoring of Rolling Element Bearing by Acoustic Analysis Using LabVIEW. In: Vasudevan, H., Kottur, V., Raina, A. (eds) Proceedings of International Conference on Intelligent Manufacturing and Automation. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-2490-1_65
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DOI: https://doi.org/10.1007/978-981-13-2490-1_65
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