An Optimal Lubrication Oil Replacement Method Based on Selected Oil Field Data

The regular replacement of lubricating oil plays a key role in improving machine reliability and reducing unexpected failures of an oil lubricated system. This paper proposes a condition-based maintenance problem with selected oil field data to determine the optimal time of the lubricating oil repla...

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Main Authors: Shufa Yan, Biao Ma, Changsong Zheng, Jianhua Chen
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8756290/
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spelling doaj-0095506aa06041fb8e28929cd629721b2021-03-29T23:25:43ZengIEEEIEEE Access2169-35362019-01-017921109211810.1109/ACCESS.2019.29274268756290An Optimal Lubrication Oil Replacement Method Based on Selected Oil Field DataShufa Yan0https://orcid.org/0000-0002-6122-146XBiao Ma1Changsong Zheng2Jianhua Chen3School of Mechanical Engineering, Beijing Institute of Technology, Beijing, ChinaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing, ChinaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing, ChinaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing, ChinaThe regular replacement of lubricating oil plays a key role in improving machine reliability and reducing unexpected failures of an oil lubricated system. This paper proposes a condition-based maintenance problem with selected oil field data to determine the optimal time of the lubricating oil replacement. The selected oil field data contain health information about the lubricating oil, so the degradation state of the oil can be predicted and the future health condition can be evaluated. The proposed lubricating oil replacement problem is modeled with the evaluated oil health condition in a Markov decision process framework and then, a method for constructing a health index for the lubricating oil is proposed based on information theory to fuse the multiple oil field data and build a degradation progression prediction model. Finally, the proposed method for condition-based lubricating oil replacement is illustrated in a practical case study. The possible applications of an optimal policy for lubricating oil replacement are much wider. For instance, the method can be used as an input to optimize an operational plan and further reduce the maintenance costs.https://ieeexplore.ieee.org/document/8756290/Lubricating oilreplacementmaterial wear and system degradationsystem degradation modelhealth indexprognostics
collection DOAJ
language English
format Article
sources DOAJ
author Shufa Yan
Biao Ma
Changsong Zheng
Jianhua Chen
spellingShingle Shufa Yan
Biao Ma
Changsong Zheng
Jianhua Chen
An Optimal Lubrication Oil Replacement Method Based on Selected Oil Field Data
IEEE Access
Lubricating oil
replacement
material wear and system degradation
system degradation model
health index
prognostics
author_facet Shufa Yan
Biao Ma
Changsong Zheng
Jianhua Chen
author_sort Shufa Yan
title An Optimal Lubrication Oil Replacement Method Based on Selected Oil Field Data
title_short An Optimal Lubrication Oil Replacement Method Based on Selected Oil Field Data
title_full An Optimal Lubrication Oil Replacement Method Based on Selected Oil Field Data
title_fullStr An Optimal Lubrication Oil Replacement Method Based on Selected Oil Field Data
title_full_unstemmed An Optimal Lubrication Oil Replacement Method Based on Selected Oil Field Data
title_sort optimal lubrication oil replacement method based on selected oil field data
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description The regular replacement of lubricating oil plays a key role in improving machine reliability and reducing unexpected failures of an oil lubricated system. This paper proposes a condition-based maintenance problem with selected oil field data to determine the optimal time of the lubricating oil replacement. The selected oil field data contain health information about the lubricating oil, so the degradation state of the oil can be predicted and the future health condition can be evaluated. The proposed lubricating oil replacement problem is modeled with the evaluated oil health condition in a Markov decision process framework and then, a method for constructing a health index for the lubricating oil is proposed based on information theory to fuse the multiple oil field data and build a degradation progression prediction model. Finally, the proposed method for condition-based lubricating oil replacement is illustrated in a practical case study. The possible applications of an optimal policy for lubricating oil replacement are much wider. For instance, the method can be used as an input to optimize an operational plan and further reduce the maintenance costs.
topic Lubricating oil
replacement
material wear and system degradation
system degradation model
health index
prognostics
url https://ieeexplore.ieee.org/document/8756290/
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