2017 Second International Conference on Reliability Systems Engineering (ICRSE)最新文献_第9页

Application of machine learning method in bridge health monitoring 机器学习方法在桥梁健康监测中的应用

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030793

Jiafan Peng, Shunong Zhang, Dongmu Peng, Kan Liang

引用次数: 10

Finite element analysis based on sequential coupling method for a glass product under temperature and vibration conditions 基于序贯耦合法的温度振动条件下玻璃制品有限元分析

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030808

Chenqi Lv, Shunong Zhang, P. Gao, Fashan Li, Wenqiang Li, J. Xie

引用次数: 0

Sequential preventive maintenance interval determination based on Monte Carlo method for deteriorating systems 基于蒙特卡罗方法的劣化系统序贯预防性维修间隔确定

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030777

Yukui Zhu, Linhan Guo

引用次数: 3

A response-based method for analyzing data from Taguchi experiments 基于响应的田口实验数据分析方法

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030735

R. Jiang, Xing Yao

引用次数: 1

Product assembling quality risk analysis approach based on RQR chain 基于RQR链的产品装配质量风险分析方法

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030731

Fengdi Liu, Yihai He, Jiaming Cui

{"title":"Product assembling quality risk analysis approach based on RQR chain","authors":"Fengdi Liu, Yihai He, Jiaming Cui","doi":"10.1109/ICRSE.2017.8030731","DOIUrl":"https://doi.org/10.1109/ICRSE.2017.8030731","url":null,"abstract":"The assembling process is the final production step, its quality is the decisive factor of the reliability of the finished product. Along with the release of ISO 9001: 2015, the risk of thinking is firstly cited, and the risk oriented quality analysis should be extended to the assembling process. Therefore, in order to improve the reliability of the final product, the risk thinking is needed to be introduced into the management and analysis of the assembling quality. Therefore, based on the proposed RQR chain, a reliability oriented quality risk analysis method is presented for the product assembling process. Firstly, the RQR assembling chain is introduced in this paper, and its three basic management objects of system reliability (R), assembling process quality (Q) and product reliability (R) are expounded. Secondly, based on the co-effect in the RQR chain, a quality framework of risk control is put forward. Thirdly, the impact of noncritical quality characteristic variations on key quality characteristics (KQC) is analyzed, and then the decline degree of the assembling product reliability caused by the KQCs variation is quantified. Then, according to the impact of the proportion, the risk factor K is determined, and then the quantitative relationship between assembling variation and product quality accident risk is established. Finally, a quality risk analysis case of a lifting equipment assembling process is given to verify the availability of the approach.","PeriodicalId":317626,"journal":{"name":"2017 Second International Conference on Reliability Systems Engineering (ICRSE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124654633","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

Reliability assessment of the Missile system based on Bayesian network 基于贝叶斯网络的导弹系统可靠性评估

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030741

Yadong Guan, Xiaogang Li, Min Wang, Jianhua Ye

{"title":"Reliability assessment of the Missile system based on Bayesian network","authors":"Yadong Guan, Xiaogang Li, Min Wang, Jianhua Ye","doi":"10.1109/ICRSE.2017.8030741","DOIUrl":"https://doi.org/10.1109/ICRSE.2017.8030741","url":null,"abstract":"The Tactical Missile is a complex system with a large number of components, with characteristics of high reliability, long storage life. Due to the limitation of the samples of the missile, the traditional method of modeling and evaluating based on mathematical statistics has a lot of shortcomings. Therefore, according to the Bayesian network method, we use the principle of physics of failure analysis to establish the assessment model from the components to the system. The work of the paper mainly includes the following contents. First, the failure modes and the sensitive environmental stress are qualitatively and quantitatively analyzed to determine the main influencing factors of the system failure at work. Second, according to the system function to establish the system function flow chart, the data is divided into different styles based on the physics of failure. According to the test results, the likelihood function is established. Third, based on the Bayesian network and combined with the system function, the paper establishes the qualitative and quantitative Bayesian network model from the component to the system, from the bottom node to the high node. According to the test data, the evaluation and verification of the system life parameters are carried out.","PeriodicalId":317626,"journal":{"name":"2017 Second International Conference on Reliability Systems Engineering (ICRSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127519646","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

The inspection strategy of the subsea gas boosting system considering imperfect test effect 考虑试验效果不完美的海底气体增压系统检测策略

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030760

Jin-yong Yao, Zhiping Pang, Yiliu Liu

引用次数: 0

Fault diagnosis for hydraulic system of naval gun based on BP-Adaboost model 基于BP-Adaboost模型的舰炮液压系统故障诊断

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030739

Xiangkun Liu, Yanguang Hu, Zhijun Xu, Yingjie Ren, Tingfo Gao

{"title":"Fault diagnosis for hydraulic system of naval gun based on BP-Adaboost model","authors":"Xiangkun Liu, Yanguang Hu, Zhijun Xu, Yingjie Ren, Tingfo Gao","doi":"10.1109/ICRSE.2017.8030739","DOIUrl":"https://doi.org/10.1109/ICRSE.2017.8030739","url":null,"abstract":"There is strong nonlinearity between the fault states and performance parameters of naval gun hydraulic system. The BP neural network can be trained to represent the nonlinear relationship between variables effectively. But it is sensitive to the initial weights of the network, so the training results are relatively unstable. To solve the problem, this paper presents a new approach to the naval gun hydraulic system fault diagnosis based on BP-Adaboost model. Firstly, the BP neural network is used as a weak classifier, which can fit the relationship between the fault states and the parameters. By training the BP neural network repeatedly, several weak classifiers are obtained. Then by using the Adaboost algorithm, a strong classifier is obtained by merging the multiple BP neural network weak classifiers. The strong classifier can finally be used to diagnose the fault of naval gun hydraulic system. The simulation results demonstrate that the fault diagnosis model has a higher convergence speed and diagnosis accuracy, which can meet the requirements of hydraulic system fault diagnosis.","PeriodicalId":317626,"journal":{"name":"2017 Second International Conference on Reliability Systems Engineering (ICRSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130306433","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

Quality variation control oriented product infant failure risk mitigation strategy based on risk chain 面向质量变异控制的基于风险链的产品缺陷风险缓解策略

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030784

Chunling Zhu, Yihai He, Jiaming Cui, Fengdi Liu

{"title":"Quality variation control oriented product infant failure risk mitigation strategy based on risk chain","authors":"Chunling Zhu, Yihai He, Jiaming Cui, Fengdi Liu","doi":"10.1109/ICRSE.2017.8030784","DOIUrl":"https://doi.org/10.1109/ICRSE.2017.8030784","url":null,"abstract":"Infant failure seriously affects customer satisfaction, which is mainly determined by quality variations in manufacturing process, and it is the most critical part of product quality risk. However, most of manufacturers subject to lack of targeted quality variation controlling for infant failure risk, which causes neglecting of preventing and mitigating infant failure risk. Therefore, in this paper, first, an infant failure risk chain is put forward to clarify the formation mechanism from process variation to infant failure. And second, based on forward analysis of the chain, infant failure risk is quantitatively modeled. Third, according to the analysis results, the key process variations are identified by backward analysis of the chain. And variation controlling costs and infant failure losses costs are comprehensively considered to optimize process variation controlling. Finally, a case study of a level control system is introduced to verify the applicability of the proposed method. The final result shows that the proposed method has a good performance in infant failure risk mitigation.","PeriodicalId":317626,"journal":{"name":"2017 Second International Conference on Reliability Systems Engineering (ICRSE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128693480","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

Influence of work motivation and task difficulty on human reliability 工作动机和任务难度对人的可靠性的影响

2017 Second International Conference on Reliability Systems Engineering (ICRSE) Pub Date : 2017-07-01 DOI: 10.1109/ICRSE.2017.8030722

Zekun Wu, Xing Pan, Huixiong Wang, Jize Chen

引用次数: 2