Version 1
: Received: 14 August 2023 / Approved: 17 August 2023 / Online: 18 August 2023 (09:04:20 CEST)
How to cite:
Bhatti, S.; Shaikh, A.A.; Mansoor, A.; Hussain, M. Applying Stochastic Models to Analyze Vibration Features of Roller Bearings. Preprints2023, 2023081287. https://doi.org/10.20944/preprints202308.1287.v1
Bhatti, S.; Shaikh, A.A.; Mansoor, A.; Hussain, M. Applying Stochastic Models to Analyze Vibration Features of Roller Bearings. Preprints 2023, 2023081287. https://doi.org/10.20944/preprints202308.1287.v1
Bhatti, S.; Shaikh, A.A.; Mansoor, A.; Hussain, M. Applying Stochastic Models to Analyze Vibration Features of Roller Bearings. Preprints2023, 2023081287. https://doi.org/10.20944/preprints202308.1287.v1
APA Style
Bhatti, S., Shaikh, A.A., Mansoor, A., & Hussain, M. (2023). Applying Stochastic Models to Analyze Vibration Features of Roller Bearings. Preprints. https://doi.org/10.20944/preprints202308.1287.v1
Chicago/Turabian Style
Bhatti, S., Asif Mansoor and Murtaza Hussain. 2023 "Applying Stochastic Models to Analyze Vibration Features of Roller Bearings" Preprints. https://doi.org/10.20944/preprints202308.1287.v1
Abstract
Machinery parts gradually wear out over time due to regular usage. To improve machinery health and prevent critical issues, a reliable prognosis framework can be implemented by monitoring the behaviour of machinery parts and issuing warnings before they reach a critical state. To achieve this, vibration data from roller bearings experiencing various fault conditions have been collected. Different techniques from the literature were combined to analyze the distinct configurations in the vibration data sets and identify the main defects in roller bearings. The significant features extracted from this analysis were then used to create optimized stochastic model equations, separately regressing inner and outer race fault features to healthy bearing features under random conditions. These models can help engineers design more dependable systems, optimize their performance, and minimize the risk of failures and downtime.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
