2016 IEEE International Conference on Prognostics and Health Management (ICPHM)最新文献_第6页

Simulation of ultrasonic testing for resolution of corrosion detection in pipes 管道腐蚀检测解决方法的超声检测模拟

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542836

Q. Qian, Houman Hanachi, Jie Liu, J. Gu, F. Ma, A. Koul, A. Banerjee

引用次数: 0

Implementation and verification of prognostics and health management system using a configurable system of systems architecture 使用可配置的系统架构实现和验证预后和健康管理系统

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542835

Song Han, Jinsong Yu, D. Tang, Hao Liu

{"title":"Implementation and verification of prognostics and health management system using a configurable system of systems architecture","authors":"Song Han, Jinsong Yu, D. Tang, Hao Liu","doi":"10.1109/ICPHM.2016.7542835","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542835","url":null,"abstract":"The prognostics and health management (PHM) system has been proved to be effective in failure warning and logistic support for real engineering systems. Verification of the developed PHM systems before its deployment plays an essential role in ensuring PHM functions and avoiding unexpected mistakes. To meet multidisciplinary requirements in PHM systems as well as requirements for system configurability and extensibility, this paper proposes a distributed and universal platform for the implementation and verification of PHM system using a configurable system of systems (SoS) architecture. This architecture is achieved by defining different PHM functions as different systems, and then combines them using a common runtime infrastructure (RTI) which consists of the operation manager and the functional terminal driver. Client-server framework, object-oriented technology, hierarchical structure and self-description technology are applied in the construction of the platform to support the distributed architecture and the multidisciplinary system collaboration. An implementation and verification system for PHM of a spacecraft power system is developed in this paper to demonstrate the proposed platform.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116820327","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: 2

On cross-domain feature fusion in gearbox fault diagnosis under various operating conditions based on Transfer Component Analysis 基于传递分量分析的齿轮箱多工况故障诊断跨域特征融合

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542845

Junyao Xie, Laibin Zhang, Li-xiang Duan, Jinjiang Wang

引用次数: 91

A remaining useful life prediction approach for lithium-ion batteries using Kalman filter and an improved particle filter 基于卡尔曼滤波和改进粒子滤波的锂离子电池剩余使用寿命预测方法

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542847

Baohua Mo, Jingsong Yu, D. Tang, Hao Liu

引用次数: 42

Tradeoff between energy consumption and lifetime in two tiered wireless sensor networks 两层无线传感器网络能耗与寿命的权衡

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542862

Veervrat Singh, R. Tripathi, Y. N. Singh, N. Verma

引用次数: 2

A boosting classifier for induction motor fault diagnosis 一种用于感应电动机故障诊断的boosting分类器

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542875

Wilson Q. Wang, De Z. Li

引用次数: 0

Aviation BIT optimal method for reducing false alarm rate under gust environment 阵风环境下降低航空BIT虚警率的优化方法

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542832

Y. Quo, Jiaqi Zhang, Qingdong Li, Sha Liu, Wangxu Chai

{"title":"Aviation BIT optimal method for reducing false alarm rate under gust environment","authors":"Y. Quo, Jiaqi Zhang, Qingdong Li, Sha Liu, Wangxu Chai","doi":"10.1109/ICPHM.2016.7542832","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542832","url":null,"abstract":"High false alarm rate is the major restrictive factors for the aviation built-in test (BIT) application in aircraft. This paper analyzes the environmental influence on the aviation BIT, and addresses that gust is the one of the principal reasons leading to false alarm from aviation BIT. Under the gust environment, the aero relative speed will be changed which changes the angle of incidence and lift force simultaneously. It inevitably makes the aviation BIT diagnosis data change and maybe cause false alarm in aviation BIT in some special situations. We gather the sample data influencing the BIT accuracy via the simulation experiment or actual test, and establish a decision network for the aviation BIT to confirm the influence degree under gust environment, which can comprehensively consider the change of various elements in the residual vector to distinguish the influence degree between the gust and real fault in the aircraft. This way, based on the original BIT diagnosis results and the output results of the decision network, the false alarm rate of aviation BIT can be effectively improved with weighting processing. The Monte Carlo simulation result shows the proposed aviation BIT optimal method is a good approach because it reduces the false alarm rate of aviation BIT under gust environment, and further improve the BIT diagnostic ability. The method will be useful in actual application.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122456031","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

Uncertainty quantification using evidence theory in concrete fatigue damage prognosis 证据理论在混凝土疲劳损伤预测中的不确定性量化

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542857

He-sheng Tang, Dawei Li, Wei Chen, S. Xue

{"title":"Uncertainty quantification using evidence theory in concrete fatigue damage prognosis","authors":"He-sheng Tang, Dawei Li, Wei Chen, S. Xue","doi":"10.1109/ICPHM.2016.7542857","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542857","url":null,"abstract":"Fatigue failure is the main failure mode of mechanical components in the research of engineering structures. As fatigue life may be a basis for the fatigue reliability design, it is very important to predict it for the normal usage of the structure. Uncertainties rooted in physical variability, data uncertainty and modeling errors of the fatigue life prediction analysis. Furthermore, the predicted life of concrete structures in civil engineering field will be more obviously uncertain than other engineering structures. Due to lack of knowledge or incomplete, inaccurate, unclear information in the modeling, there are limitations in using only one framework (probability theory) to quantify the uncertainty in the concrete fatigue life prediction problem because of the impreciseness of data or knowledge. Therefore the study of uncertainty theory in the prediction of fatigue life is very necessary. This study explores the use of evidence theory for concrete fatigue life prediction analysis in the presence of epistemic uncertainty. The empirical formula S-N curve and the Paris law based on the fracture mechanics are selected as the fatigue life prediction models. The evidence theory is used to quantify the uncertainty present in the models' parameters. The parameters in fatigue damage prognosis model are obtained by fitting the available sparse experimental data and then the uncertainty in these parameters is taken into account. In order to alleviate the computational difficulties in the evidence theory based uncertainty quantification (UQ) analysis, a differential evolution (DE) based interval optimization method is used for finding the propagated belief structure. The object of the current study is to investigate uncertainty of concrete fatigue damage prognosis using sparse experimental data in order to explore the feasibility of the approach. The proposed approach is demonstrated using the experimental results of the plain concrete beams and the steel fibred reinforced concrete beams.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128547307","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: 5

A fault diagnosis method of engine rotor based on Random Forests 基于随机森林的发动机转子故障诊断方法

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542838

Q. Yao, Jian Wang, Lu Yang, Haixia Su, Guigang Zhang

{"title":"A fault diagnosis method of engine rotor based on Random Forests","authors":"Q. Yao, Jian Wang, Lu Yang, Haixia Su, Guigang Zhang","doi":"10.1109/ICPHM.2016.7542838","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542838","url":null,"abstract":"Rotor is the main part of the engine, the vibration fault is very common in the process of running, it must be monitored, checked, excluded in a timely manner for improving the reliability of engine and aircraft safety. This paper mainly studies four kinds of rotor fault, including unbalance, misalignment, surge, bearing failure. The frequency spectrum of the vibration signal of a rotor system is an important basis for rotor fault diagnosis, using the spectrum of rotor to build decision tree analysis is an important method for rotor fault detection. As the single decision tree's anti-interference ability is very poor, this paper presents an engine rotor fault diagnosis method based on Random Forests. Experimental results show that the accuracy of this diagnosis method is high, the failures can be diagnosed timely and effectively to keep the engine in normal operation. To evaluate the validity of Random Forests, a SVM classifier is trained for comparison. Compare with SVM, we obtain better classification in Random Forests algorithm. This result demonstrates that Random Forests algorithm is a valid method for engine rotor.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117145376","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

Developing machine learning-based models to estimate time to failure for PHM 开发基于机器学习的模型来估计PHM的故障时间

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542876

Chunsheng Yang, Takayuki Ito, Yubin Yang, Jie Liu

{"title":"Developing machine learning-based models to estimate time to failure for PHM","authors":"Chunsheng Yang, Takayuki Ito, Yubin Yang, Jie Liu","doi":"10.1109/ICPHM.2016.7542876","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542876","url":null,"abstract":"The core of PHM (Prognostic and Health Monitoring) technology is prognostics which is able to estimate time to failure (TTF) for the monitored components or systems using the built-in predictive models. However the development of predictive models for TTF estimation remains a challenge. To address this issue, we proposed to develop machine learning-based models for TTF estimation by using the techniques from machine learning and data mining. In the past decade, we have been working on the development of machine learning-based models for estimating TTF and applied the developed technology to various real-world applications such as train wheel prognostics, and aircraft engine prognostics. In this paper, we report two kinds of machine learning-based models for estimating TTF, including multistage classification, on-demand regression. The multistage classification improves the TTF estimation over one stage classification by dividing the time window into more small narrow time windows. A case study, APU prognostics, demonstrates the usefulness of the developed methods. The results from the case study show that the machine learning-based modeling method is an effective and feasible way to develop predictive models to estimate TTF for PHM.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125867563","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: 7