Failure prediction of diesel engine based on occurrence of selected wear particles in oil

被引：29

作者：

Valis, David ^{[1
]}

Zak, Libor ^{[2
]}

Pokora, Ondrej

机构：

[1] Univ Def, Brno, Czech Republic

[2] Brno Univ Technol, CS-61090 Brno, Czech Republic

来源：

ENGINEERING FAILURE ANALYSIS | 2015年 / 56卷

关键词：

System failure prediction; Material wear; System and material deterioration; System residual technical life estimation; Diffusion processes; ONLINE RELIABILITY ESTIMATION; RESIDUAL-LIFE DISTRIBUTIONS; INDIVIDUAL COMPONENTS; MAINTENANCE; MODELS;

D O I：

10.1016/j.engfailanal.2014.11.020

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

When assessing reliability, the principles of system failure prognostic are basic requirements. Condition-based maintenance is more demanding when estimating a system failure and residual/remaining technical life time (RTL). This paper introduces analytical and prognostic methods used for assessing system material wear to predict a failure occurrence. The principles presented in the article are based on indirect but real diagnostic oil data. We concentrate on wear metal particles such as iron (Fe) and lead (Pb) as potential failure indicators. Our approach is very different from other papers published in this area as their data were often artificial or viewed as potentially useful, but they never existed. The advantage and novelty of the outcomes presented in the article are that they might be used mainly for predicting failure occurrence and also for optimising intervals of preventive maintenance (PM), analyzing cost-benefit and planning operation/mission. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：501 / 511

页数：11

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