Remaining Useful Life Model and Assessment of Mechanical Products: A Brief Review and a Note on the State Space Model Method

论文摘要

The remaining useful life（RUL） prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety（safety awareness and safety improvement）. These studies incorporated many di erent models, algorithms, and techniques for modeling and assessment. In this paper, methods of RUL assessment are summarized and expounded upon using two major methods: physics model based and data driven based methods. The advantages and disadvantages of each of these methods are deliberated and compared as well. Due to the intricacy of failure mechanism in system, and di culty in physics degradation observation, RUL assessment based on observations of performance variables turns into a science in evaluating the degradation. A modeling method from control systems, the state space model（SSM）, as a first order hidden Markov, is presented. In the context of non-linear and non-Gaussian systems, the SSM methodology is capable of performing remaining life assessment by using Bayesian estimation（sequential Monte Carlo）. Being e ective for non-linear and non-Gaussian dynamics, the methodology can perform the assessment recursively online for applications in CBM（condition based maintenance）, PHM（prognostics and health management）, remanufacturing, and system performance reliability. Finally, the discussion raises concerns regarding online sensing data for SSM modeling and assessment of RUL.

论文目录

文章来源

类型: 期刊论文

作者: Yawei Hu,Shujie Liu,Huitian Lu,Hongchao Zhang

来源: Chinese Journal of Mechanical Engineering 2019年01期

年度: 2019

分类: 工程科技Ⅱ辑,信息科技

专业: 机械工业,自动化技术

单位: School of Mechanical Engineering,Dalian University of Technology,Department of Construction & Operations Management, South Dakota State University,Department of Industrial Engineering, Texas Tech University

基金: Supported by Fundamental Research Funds for the Central Universities of China(Grant No.DUT17GF214)

分类号: TH165.4

页码: 11-30

总页数: 20

文件大小: 1866K

下载量: 102

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