2013 IEEE Conference on Prognostics and Health Management (PHM)最新文献_第2页

Model-based diagnosis of gear fault under variable loading condition 变载荷条件下齿轮故障的模型诊断

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621410

S. Leem, Jooho Choi

引用次数: 2

Online condition monitoring and remaining useful life prediction of particle contaminated lubrication oil 颗粒污染润滑油在线状态监测及剩余使用寿命预测

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621415

Junda Zhu, Jae Yoon, D. He, Bin Qiu, Eric Bechhoefer

{"title":"Online condition monitoring and remaining useful life prediction of particle contaminated lubrication oil","authors":"Junda Zhu, Jae Yoon, D. He, Bin Qiu, Eric Bechhoefer","doi":"10.1109/ICPHM.2013.6621415","DOIUrl":"https://doi.org/10.1109/ICPHM.2013.6621415","url":null,"abstract":"To increase wind energy production rate, there is a pressing need to improve the wind turbine availability and reduce the operational and maintenance costs. The safety and reliability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive train subassemblies such as gearbox and means for lubrication oil condition monitoring and degradation detection. The purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oil has deteriorated to such a degree that it no longer fulfills its function. In this paper, particle contamination of lubrication oil and the remaining useful life (RUL) of the particle contaminated lubrication oil are investigated. Physical models are developed to quantify the relationship between particle contamination level and the outputs of commercially available online oil dielectric and viscosity sensors. The effectiveness of the developed models is then validated using laboratory experiments. In particular, the remaining useful life prediction of degraded lubrication oil with viscosity and dielectric constant data using particle filtering is presented. A simulation case study is provided to demonstrate the effectiveness of the developed technique.","PeriodicalId":178906,"journal":{"name":"2013 IEEE Conference on Prognostics and Health Management (PHM)","volume":"822 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122399595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Cost Benefit Analysis for condition based maintenance 基于状态维修的成本效益分析

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621451

N. Verma, Sreevidya Khatravath, A. Salour

引用次数: 15

Towards systems level prognostics in the Cloud 迈向云中的系统级预测

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621449

Budhaditya Deb, Mohak Shah, S. Evans, Manoj Mehta, Anthony Gargulak, Tom Lasky

{"title":"Towards systems level prognostics in the Cloud","authors":"Budhaditya Deb, Mohak Shah, S. Evans, Manoj Mehta, Anthony Gargulak, Tom Lasky","doi":"10.1109/ICPHM.2013.6621449","DOIUrl":"https://doi.org/10.1109/ICPHM.2013.6621449","url":null,"abstract":"Many application systems are transforming from device centric architectures to cloud based systems that leverage shared compute resources to reduce cost and maximize reach. These systems require new paradigms to assure availability and quality of service. In this paper, we discuss the challenges in assuring Availability and Quality of Service in a Cloud Based Application System. We propose machine learning techniques for monitoring systems logs to assess the health of the system. A web services data set is employed to show that variety of services can be clustered to different service classes using a k-means clustering scheme. Reliability, Availability, and Serviceability (RAS) logs and Job logs dataset from high performance computing system is employed to show that impending fatal errors in the system can be predicted from the logs using an SVM classifier. These approaches illustrate the feasibility of methods to monitor the systems health and performance of compute resources and hence can be used to manage these systems for high availability and quality of service for critical tasks such as health care monitoring in the cloud.","PeriodicalId":178906,"journal":{"name":"2013 IEEE Conference on Prognostics and Health Management (PHM)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127949187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Uncertainty quantification of fusion prognostics for lithium-ion battery remaining useful life estimation 锂离子电池剩余使用寿命估算融合预测的不确定性量化

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621441

Datong Liu, Yue Luo, Limeng Guo, Yu Peng

{"title":"Uncertainty quantification of fusion prognostics for lithium-ion battery remaining useful life estimation","authors":"Datong Liu, Yue Luo, Limeng Guo, Yu Peng","doi":"10.1109/ICPHM.2013.6621441","DOIUrl":"https://doi.org/10.1109/ICPHM.2013.6621441","url":null,"abstract":"The uncertainty of prognostics and remaining useful life (RUL) estimation for the lithium-ion battery is emphasized in the battery management system (BMS). Many machine learning algorithms and statistical methods can not only realize the RUL prediction but also provide the probability density function (PDF) as the prognostic uncertainty representation, involving particle filter (PF), Relevance Vector Machine (RVM), etc. This paper presents a fusion RUL prediction approach with PF algorithm and data-driven autoregression (AR) algorithm for lithium-ion battery. Moreover, a framework to quantitatively analyze and evaluate the PDF distribution of the lithium-ion battery RUL prediction is presented. The probability confidence interval estimation, PDF histogram and distribution hypothesis test are included in quantifying the uncertainty. These quantitative analysis results can be meaningful for lithium-ion battery health management and maintenance. The experimental results with the battery data of NASA Ames Prognostics Data Repository show that the proposed framework can achieve the quantification of PDF to introduce the reference for the corresponding maintenance and management. The proposed work also shows potential prospective for industrial application.","PeriodicalId":178906,"journal":{"name":"2013 IEEE Conference on Prognostics and Health Management (PHM)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131838448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Prognosis for insulated gate bipolar transistor based on Gaussian Process Regression 基于高斯过程回归的绝缘栅双极晶体管预测

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621456

Sheng Hong, Zheng Zhou, Chuan Lv, Hongyi Guo

引用次数: 8

Simulation on missile availability with consideration to storage process 考虑存储过程的导弹可用性仿真

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621443

Yaqiu Li, Guangyan Zhao, Yufeng Sun, Weiwei Hu

引用次数: 0

A liquid contact indicator model for warranty abuse detection in portable electronics 便携式电子产品保修期滥用检测的液体接触指示器模型

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621435

Seunghyuk Choi, B. Youn, M. Pecht

引用次数: 0

Remaining useful life based maintenance decision making for deteriorating systems with both perfect and imperfect maintenance actions 基于剩余使用寿命的完善和不完善维护系统的维护决策

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621442

P. D. Van, A. Voisin, E. Levrat, B. Iung

{"title":"Remaining useful life based maintenance decision making for deteriorating systems with both perfect and imperfect maintenance actions","authors":"P. D. Van, A. Voisin, E. Levrat, B. Iung","doi":"10.1109/ICPHM.2013.6621442","DOIUrl":"https://doi.org/10.1109/ICPHM.2013.6621442","url":null,"abstract":"This paper deals with a proactive condition-based maintenance (CBM) considering both perfect and imperfect maintenance actions for deteriorating systems. Perfect maintenance actions restore completely the system to the `as good as new' state. Their related cost are however often high. Imperfect preventive maintenance restores partially the system with reduced maintenance cost. Nevertheless, the restoration quality may depend not only on the allocated maintenance cost, the system age but also on the total number of imperfect maintenance actions executed since the last replacement time of the system. The first objective of the paper is to model imperfect maintenance actions. The second objective is to propose an adaptive maintenance policy which can help to select optimally maintenance actions (perfect or imperfect actions), if needed, at each inspection time using the remaining useful life (RUL) prognosis. To illustrate the use and the advantages of the proposed maintenance policy, different sensitivity studies are analyzed and discussed through a numerical example.","PeriodicalId":178906,"journal":{"name":"2013 IEEE Conference on Prognostics and Health Management (PHM)","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123397538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Requirements for prognostic health management of passive components in advanced small modular reactors 先进小型模块化反应堆中无源元件的预测健康管理要求

2013 IEEE Conference on Prognostics and Health Management (PHM) Pub Date : 2013-06-24 DOI: 10.1109/ICPHM.2013.6621425

R. Meyer, J. Coble, P. Ramuhalli

引用次数: 5