Remaining Useful Life Estimation of Rotating Machines through Supervised Learning with Non-Linear Approaches

Remaining Useful Life Estimation In the Presence of Given Shocks

In a system, prediction of remaining useful lifetime (RUL) of servicing before reaching to a specified breakdown threshold is a very important practical issue, and research in this field is still regarded as an appreciated research gap. Operational environment of an equipment is not constant and changes regarding to stresses and shocks. These random environmental factors accelerate system deter...

Remaining useful life estimation - A review on the statistical data driven approaches

0377-2217/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.ejor.2010.11.018 ⇑ Corresponding authors at: Salford Business School M5 4WT, UK. Tel.: +44 0161 2954124; fax: +44 0161 2 010 62794461; fax: +86 010 62786911 (D.-H. Zhou). E-mail addresses: [email protected] (W. Wan (D.-H. Zhou). Remaining useful life (RUL) is the useful life left on an asset at a particular time of operation. It...

A Bayesian Framework for Remaining Useful Life Estimation

Remaining useful life estimation under degradation and shock damage

This article presents a prognostic approach to estimate remaining useful life for systems subjected to dependent competing failure processes. In the literature, shock damage is the damage to a soft failure process caused by a shock process. However, how the degradation process causes damage to a hard failure process has not been well studied. In this article, the degradation damage is modeled a...

Remaining useful life estimation based on discriminating shapelet extraction

In the Prognostics and Health Management domain, estimating the remaining useful life (RUL) of critical machinery is a challenging task. Various research topics including data acquisition, fusion, diagnostics and prognostics are involved in this domain. This paper presents an approach, based on shapelet extraction, to estimate the RUL of equipment. This approach extracts, in an offline step, di...