Bearing performance degradation assessment and remaining useful life prediction based on data-driven and physical model

Author:

Sheng Yuanyuan,Liu HuanyuORCID,Li Junbao

Abstract

Abstract Intelligent health maintenance of bearings usually consists of two stages: constructing effective health assessment indicators and accurate remaining useful life prediction models. However, many prediction models are available only when many constraints are met, and the health assessment indicators may not be able to accurately track the performance degradation process of bearings. This study proposes a bearing performance degradation assessment and remaining life prediction method. First, the health evaluation index family (referred to as the generalized high-order moment coefficient) was constructed based on the generalized power mean and high-order origin moments for health assessment. Subsequently, an improved Paris–Erdogan model is proposed, which uses the optimal health evaluation index as input to predict the remaining life of the bearing after the initial failure. The experimental results show that the proposed method has a higher performance degradation tracking accuracy and a smaller prediction error than the combination of traditional statistical indicators and prediction models.

Funder

National Natural Science Foundation of China

Publisher

IOP Publishing

Subject

Applied Mathematics,Instrumentation,Engineering (miscellaneous)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3