Wear Prediction of Earth-Moving Machinery Joint Bearing via Correlation between Wear Coefficient and Film Parameter: Experimental Study

润滑 方位(导航) 润滑油 磨损系数 材料科学 相关系数 线性回归 摩擦学 机械工程 结构工程 复合材料 法律工程学 工程类 计算机科学 数学 统计 人工智能
作者
Hong-Gyu Jeon,Dae‐Hyun Cho,Jae-Hyeong Yoo,Young-Ze Lee
出处
期刊:Tribology Transactions 卷期号:61 (5): 808-815 被引量:14
标识
DOI:10.1080/10402004.2017.1418036
摘要

A wear life prediction of a grease-lubricated bearing in earth moving machinery has to be made based on actual wear data for its accuracy, but much effort should be devoted to obtain the wear data from the actual bearing. Currently, manufacturers provide a very conservative maintenance guide to schedule the replacement of the bearings to prevent the mechanical failure due to wear, causing economic losses, and the market requires finding optimal maintenance cycles to reduce maintenance costs. In this study, an economical wear prediction methodology for the grease-lubricated bearing based on typical pin-on-disk (POD) tests is proposed. POD tests were performed under boundary and mixed lubrication regimes considering the actual operating conditions of the bearings. It was found that there is a linear relation between the lubrication film parameter and the wear coefficient in log-log scale. The amount of wear of actual bearings was estimated by the wear coefficient from the linear regression analysis based on the POD test. The wear tests were further performed with the actual bearing under two loading cases and then the lubrication film parameter and wear coefficient were calculated, respectively. The estimated amount of wear shows good agreement with the measurement of wear depth. This leads us to conclude that it is possible to economically predict the wear amount in an actual bearing from POD wear test results by analysis of the correlation between the wear coefficient and the lubrication film parameter.
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