Predicting condition based on oil analysis - A case study

被引：19

作者：

Raposo, Hugo ^{[1
]}

Farinha, Jose Torres ^{[1
]}

Fonseca, Inacio ^{[1
]}

Galar, Diego ^{[2
]}

机构：

[1] Coimbra Univ UC, Dept Mech Engn, Ctr Mech Engn Mat & Proc CEMMPRE, Coimbra, Portugal

[2] Lulea Univ Technol LTU, Dept Civil Environm & Nat Resources Engn, Lulea, Sweden

来源：

TRIBOLOGY INTERNATIONAL | 2019年 / 135卷

关键词：

Condition monitoring; Predictive maintenance; Oil analysis; Time series; t-Student; Diesel engines; FLEET; WEAR; CONSUMPTION; MODEL; TIME;

D O I：

10.1016/j.triboint.2019.01.041

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

The paper presents and discusses a model for condition monitoring. Using data from the oil in the Diesel engines of a fleet of urban buses, it studies the evolution of degradation and develops a predictive maintenance policy for oil replacement. Based on the analysis of the oil condition, the intervals of oil replacement can be expanded, allowing increased availability. The paper links time series forecasting with the statistical behavior of some oil effluents, like soot. This exercise can be expanded to include other variables, and the model has the potential to be applied to other physical assets to achieve the best availability based on a condition monitoring policy.

引用

页码：65 / 74

页数：10

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