2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)最新文献_第3页

Monte Carlo simulation of dendrite growth due to contaminant deposition on a printed circuit board 印制板上污染物沉积引起的枝晶生长的蒙特卡罗模拟

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050142

Z. Ren, C. Teng, Yonghong Li, Yun Fu, Yun Wang, W. Ouyang

{"title":"Monte Carlo simulation of dendrite growth due to contaminant deposition on a printed circuit board","authors":"Z. Ren, C. Teng, Yonghong Li, Yun Fu, Yun Wang, W. Ouyang","doi":"10.1109/ICRMS.2016.8050142","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050142","url":null,"abstract":"The reliability of electronic devices depends not only on the quality of components but also on the environmental condition, such as the humidity and the density of contaminants. For example, electrostatically enhanced dust deposition typically produces a dendritic deposit which induces a short circuit in adjacent conductors. In order to investigate contaminant deposition mechanisms on a printed circuit board (PCB), a Monte Carlo simulation is developed in the present paper to discover the dendrite growth features of contaminants under different conditions. It is found that, under the simulation parameters, the contaminant particles will diffuse, gather and grow up to form a dendrite configuration after they are deposited on the solid surface. The size of the dendrite increases as the number of contaminant particles increases. Finally, the dendrite connects the two conductors on both sides and this is why the dendrite induces a short circuit. These findings could shed light on the understanding of the dendrite growth mechanisms on printed circuit boards. It is helpful to design proper protection methods in order to reduce the malfunction of the devices as much as possible.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121942152","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

Online estimation of state-of-health for lithium ion batteries based on charge curves 基于充电曲线的锂离子电池健康状态在线估计

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050034

N. Yang, Jing Feng, Quan Sun, Tianyu Liu, Dao Zhong

引用次数: 11

Fault diagnosis for railway track circuit based on wavelet packet power spectrum and ELM 基于小波包功率谱和ELM的轨道电路故障诊断

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050089

Zicheng Wang, Jin Guo, Yadong Zhang, Rong Luo

{"title":"Fault diagnosis for railway track circuit based on wavelet packet power spectrum and ELM","authors":"Zicheng Wang, Jin Guo, Yadong Zhang, Rong Luo","doi":"10.1109/ICRMS.2016.8050089","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050089","url":null,"abstract":"For enhancing the troubleshooting efficiency of a track circuit, a fault diagnosis method for the track circuit is proposed in this paper. First, a locomotive signal induced voltage model is established based on the transmission-line theory. Then, cases of the induced voltage envelope signals, when the track circuits are in the normal and fault conditions, respectively, are simulated. Next, a three-layer wavelet packet is adopted to decompose the induced voltage envelope signals and power spectrum analysis for the detail signal is realized. 16 time-domain indices of the β power spectrum including the standard deviation, variance, kurtosis value, and the variable coefficient are used as the failure features. Then, the information fusion of the time domain features is implemented using the principal component analysis (PCA) technology. Finally, the fusion features are input to an extreme learning machine (ELM) model to identify the failures. Case analyses show that the fault diagnosis method proposed in this paper can obtain a high accuracy and provide a scientific basis for the on-site maintenance of the track circuit.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129480285","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: 1

Reliability and performance modeling for mission-oriented k-out-of-n system under common cause failures 共因故障下面向任务的k-out- n系统的可靠性和性能建模

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050159

Xiujie Zhao, M. Xie, Qiang Feng

引用次数: 1

Step-stress accelerated degradation modeling based on nonlinear Wiener process 基于非线性Wiener过程的阶跃应力加速退化模型

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050041

Lin Deng, Zegui Huang, Zhongyi Cai, Yunxiang Chen

引用次数: 0

Research on fault injection technology for embedded software based on JTAG interface 基于JTAG接口的嵌入式软件故障注入技术研究

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050155

Mengmeng Liu, Zhaoyang Zeng, F. Su, Jueping Cai

{"title":"Research on fault injection technology for embedded software based on JTAG interface","authors":"Mengmeng Liu, Zhaoyang Zeng, F. Su, Jueping Cai","doi":"10.1109/ICRMS.2016.8050155","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050155","url":null,"abstract":"Fault injection is an effective method for PHM and testability validation. However, with the increasing complexity of structures and functions, and with the promotion of integration levels for airborne prognostics and health management (PHM) and integrated modular avionics (IMA) systems, fault injection is often difficult to use in conventional “plug,” “probe,” or “adaptor plate” methods. Fault injection based on software also presents a bottleneck for engineering applications in terms of controllability and operability. Seeking to solve the problem of applying software fault injection to testability validation, a fault injection technique based on the Joint Test Action Group (JTAG) interface is proposed in this study. The proposed technique is based on the demands of testability validation, takes into account the development trend in avionics of modularization and integration, and adopts aspects of the JTAG boundary-scan technique. Through use of the boundary-scan technique and chip debugging functions, noncontacted hardware fault injection can be realized. Accurate and controllable fault injection of embedded chip pins/functions can then be achieved that satisfies the requirements of fault simulation and injection effect/time. The problems of fault injection implementations for equipment-oriented IMA architecture can thus be overcome, and a new direction for implementing testability validation of airborne PHM and integrated avionics equipment, thereby effectively promoting and ensuring the achievement of testability indices and PHM functions.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116447661","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

High availability verification framework for OpenStack based on fault injection 基于故障注入的OpenStack高可用性验证框架

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050168

Qingfeng Du, J. Qiu, Kanglin Yin, Huan Li, Kun Shi, Yue Tian, Tiandi Xie

引用次数: 6

Challenges and opportunities of complex equipment operational reliability technology in industrial big data age 工业大数据时代复杂设备运行可靠性技术的挑战与机遇

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050134

Hongbo Ma, Xianguang Kong, Yiping Zhong, Changqi Yang, Zhongquan Li, Yang Fu

{"title":"Challenges and opportunities of complex equipment operational reliability technology in industrial big data age","authors":"Hongbo Ma, Xianguang Kong, Yiping Zhong, Changqi Yang, Zhongquan Li, Yang Fu","doi":"10.1109/ICRMS.2016.8050134","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050134","url":null,"abstract":"Large and complex equipment reliability evaluation is extremely dependent on equipment reliability experiment data, maintenance records, and failure data. With the informationalization and intellectualization of equipment (such as CNC machine tools, shield machines, and weaponry), large amounts of data (big data) will be produced during the equipment's operation. Abundant data provide a strong support for equipment operational reliability analysis in the industrial big data age, but also pose a huge challenge for reliability analysis. This paper first explores the opportunities provided by big data to promote the reliability analysis and assessment of complex equipment. Then, we mainly focus on the remaining challenges of equipment operational reliability assessment using the industrial big data method, such as the fact that most of the data reflect an intermediate state (incomplete failure state) of the equipment. We also consider a way to analyze the multiple-states of the equipment operation and correlate the multiple failure modes of the equipment operation using the big data. Moreover, a big data analysis method for calculating the reliability and predicting the residual life of gradual systems is discussed, along with a method for combining the traditional reliability calculation theory with the big data theory. All of these issues provide a significant challenge for the reliability analysis of complex equipment in the big data age.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126894632","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: 1

A safety evaluation method for heavy-duty CNC machine tools for the total life cycle based on an entropy weight method 基于熵权法的重型数控机床全生命周期安全评价方法

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050055

Guofa Li, Yongchao Huo, Jialong He, Zhaojun Yang, Jian Wang, Guofei Liu

引用次数: 0

Research on fault diagnosis training simulation technology based on MCGS 基于MCGS的故障诊断训练仿真技术研究

2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050094

Xin Guo, Lizi Chen, N. Zhao

引用次数: 1