2017 Prognostics and System Health Management Conference (PHM-Harbin)最新文献

Predictive maintenance of moving systems 移动系统的预测性维护

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079111

Nathalie Herr, J. Nicod, C. Varnier, N. Zerhouni, P. Dersin

引用次数: 6

Damage estimation and reconfigurable control for a PMSM-Inverter system under demagnetization fault 永磁同步电机-逆变器系统退磁故障的损伤估计与可重构控制

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079109

Liu Senyi, N. Gang

引用次数: 0

Remaining useful life prediction for nonlinear degrading systems with maintenance 有维护的非线性退化系统的剩余使用寿命预测

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079119

Hanwen Zhang, Maoyin Chen, Donghua Zhou

{"title":"Remaining useful life prediction for nonlinear degrading systems with maintenance","authors":"Hanwen Zhang, Maoyin Chen, Donghua Zhou","doi":"10.1109/PHM.2017.8079119","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079119","url":null,"abstract":"Remaining useful life (RUL) prediction is one of the most critical procedures of the prognostics and health management (PHM). In the existing literature, most RUL prediction methods are under the assumption that there is no maintenance activity during the whole life time of the degrading system. However, most practical systems experience various kinds of maintenance activities when they are in operation. This article presents an approach to predict the RUL of a class of nonlinear degrading systems with stochastic maintenance. To predict the RUL for systems with stochastic maintenance, a wiener process based degradation model is proposed. The switches between states of normal operation and maintenance are described by a continuous time Markov chain (CTMC). In addition, the maximum likelihood estimation (MLE) is adopted to estimate both unknown parameters in the degradation model and the transition probability between normal operation and maintenance. The analytical form of first hitting time (FHT) of degradation process is difficult to derive with the presence of maintenance activities. To avoid complicated mathematical derivation of stochastic differential, Monte Carlo method is used to obtain a numerical result of the RUL distribution. A numerical study is presented to illustrate and validate the proposed method.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129564612","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: 3

Reliability modeling for multi-component systems subject to multiple dependent competing failure processes with shifting hard failure threshold 具有可变硬失效阈值的多依赖竞争失效过程多部件系统可靠性建模

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079117

Xiaomeng Guan, Guangyan Zhao, Jie Xuan

{"title":"Reliability modeling for multi-component systems subject to multiple dependent competing failure processes with shifting hard failure threshold","authors":"Xiaomeng Guan, Guangyan Zhao, Jie Xuan","doi":"10.1109/PHM.2017.8079117","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079117","url":null,"abstract":"For complex multi-unit systems whose sub-unit suffering multiple dependent competing failure processes (MDCFP) with shifting hard failure threshold, new multiple-component system models were developed in this paper. The previous studies about reliability analysis have focused on a single unit or simple system with s-independent failure processes and failure times. The new models are different from previous studies by extending unit-level degradation model to the system level. In this paper, each component in the system can be invalid owing to a hard failure process or a soft failure process. These failure processes mentioned-above are not only competing but also dependent and whichever happens first, the component fails. Moreover, the hard failure threshold can change due to the increment of the total degradation. Then, the reliability models for series, parallel, series-parallel system were derived respectively. Finally, numerical examples about Micro-electro-mechanical System (MEMS) are illustrated to verify the developed models and the results are effective. These models could be applied in MEMS or used in many other similar systems.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121503159","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: 4

Blade health monitoring of gas turbine using online crack detection 基于在线裂纹检测的燃气轮机叶片健康监测

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079211

Bai Liu, Longli Tang, Tong Liu, Zijian Liu, Kening Xu

{"title":"Blade health monitoring of gas turbine using online crack detection","authors":"Bai Liu, Longli Tang, Tong Liu, Zijian Liu, Kening Xu","doi":"10.1109/PHM.2017.8079211","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079211","url":null,"abstract":"Gas turbine engine blades are subjected to severe fatigue which is caused by complex in-service environment. In fact, blade crack is one of the costliest sources of damage in gas turbine. Detection of cracks of blades is important to ensure safe and reliable operation of gas turbine engine. A vibration-based damage-detection methodology is presented in this paper to monitor the health condition of gas turbine rotor blade. In order to simulation the real-time dynamic crack propagation of rotor blades, model analysis was performed using a finite element model to calculate the natural frequencies and mode shapes of gas turbine blade, the possible crack initiation location was determined, the natural frequencies and mode shapes changed as the crack growing, indicating the feasibility of the methodology to capture the dynamic health condition of blade on-line. Simulation results have indicated the capability of the methodology in evaluating the changes of blade vibration signals once damage is initiated of growing, and in consistently detecting cracks of damaged blade to monitor the health condition. Additionally, the results indicated that blade natural frequency decays slightly when crack propagating, providing the potential for reliable diagnosis of the gas turbine blades with crack fault, thus the implementation of blade health monitoring system will be the approach to achieve condition-based maintenance.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114981567","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: 3

Big-data-driven based intelligent prognostics scheme in industry 4.0 environment 工业4.0环境下基于大数据驱动的智能预测方案

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079310

Jihong Yan, Yue Meng, Lei Lu, Chao-zhong Guo

引用次数: 18

Application of large-data-driven PHM technology in satellite test and on-orbit management 大数据驱动PHM技术在卫星试验与在轨管理中的应用

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079214

Qinyi Li, Xin Peng

引用次数: 8

Tutorial: Data-driven diagnostics and prognostics 教程:数据驱动的诊断和预测

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079098

Bin Zhang

{"title":"Tutorial: Data-driven diagnostics and prognostics","authors":"Bin Zhang","doi":"10.1109/PHM.2017.8079098","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079098","url":null,"abstract":"Fault diagnosis and prognosis (FDP) plays an important role in the modern complex industrial systems. Diagnosis aims to monitor the fault state in real-time while prognosis predicts the evolution of fault state and remaining useful life (RUL). Traditional Riemann sampling-based FDP (RS-FDP) takes samples and executes algorithms periodically and, in most cases, requires significant computational resources, which makes it difficult to be implemented on hardware with very limited computational capabilities. To overcome this bottleneck, a Lebesgue sampling-based FDP (LS-FDP), in which FDP algorithms are implemented “as-needed”. In LS-FDP, a set of Lebesgue states are defined on the state axis. The computation of LS-based diagnosis is triggered only when the value of measurements changes from one Lebesgue state to another, or “event-triggered#x201D;. This method significantly reduces the computation demands by eliminating unnecessary computation. This LS-FDP design is generic and able to accommodate different FDP algorithms. In this presentation, the design of LS-FDP and its application to engineering systems will be discussed in details. The efficiency of LS-FDP is verified by comparison with those of its RS-FDP counterparts.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"2018 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128046871","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: 0

A case study on health prediction of an industrial diesel motor using particle filtering 粒子滤波技术在工业柴油机健康预测中的应用研究

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079245

H. Vu, P. Do, B. Iung, F. Peysson

引用次数: 1

Design of the prognostics and health management platform of high-speed railway traction power supply equipment 高速铁路牵引供电设备预测与健康管理平台的设计

2017 Prognostics and System Health Management Conference (PHM-Harbin) Pub Date : 2017-07-09 DOI: 10.1109/PHM.2017.8079110

Mingzhou Luo, Sheng Lin, D. Feng, Zhengyou He, Lihua Chen

{"title":"Design of the prognostics and health management platform of high-speed railway traction power supply equipment","authors":"Mingzhou Luo, Sheng Lin, D. Feng, Zhengyou He, Lihua Chen","doi":"10.1109/PHM.2017.8079110","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079110","url":null,"abstract":"Traction power supply system, as the only power source of high-speed railway, the safety and reliability of its equipment's operation are very important. The effective integration and usage of the operation data of traction power supply equipment has been a hot research topic during recent years. In order to improve the utility of equipment's operation data, it is necessary to build a comprehensive platform to store, organize, calculate and display the operation data and put the prognostic and health management (PHM) algorithms of the equipment into application. This paper introduces the system structure and function realization of the prognostics and health management platform for high-speed railway traction power supply equipment. The core part of the platform is the PHM software, it can show the equipment monitoring and detection information on the interface. Besides, by combining the algorithms for fault prediction, fault diagnosis, health assessment, reliability assessment, risk assessment and maintenance strategy decision-making, it can also show the results calculated according to the PHM algorithms. Thus fault detection and prediction, health diagnosis and evaluation, maintenance decision-making and optimization can be well achieved by making full use of the operation data.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121470379","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: 8