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Journal of Statistical Computation and Simulation Volume 85, 2015 - Issue 9
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Original Articles

Residual life estimation based on nonlinear-multivariate Wiener processes

Xiaolin WangDepartment of System Engineering, College of Information System and Management, National University of Defense Technology, Changsha, People's Republic of ChinaCorrespondence[email protected]
,
Narayanaswamy BalakrishnanDepartment of Mathematics and Statistics, McMaster University, Hamilton, Canada
&
Bo GuoDepartment of System Engineering, College of Information System and Management, National University of Defense Technology, Changsha, People's Republic of China
Pages 1742-1764 | Received 30 Jan 2013, Accepted 24 Feb 2014, Published online: 18 Mar 2014

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Tianyu Liu, Quan Sun, Jing Feng, Zhengqiang Pan & Qizi Huangpeng. (2017) Residual life estimation under time-varying conditions based on a Wiener process. Journal of Statistical Computation and Simulation 87:2, pages 211-226.
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Articles from other publishers (25)

Bingxin Yan, Han Wang & Xiaobing Ma. (2022) Correlation‐driven multivariate degradation modeling and RUL prediction based on Wiener process model. Quality and Reliability Engineering International 39:8, pages 3203-3229.
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Xin Wu, Tingting Huang & Jie Liu. (2023) Common stochastic effects induced multivariate degradation process with temporal dependency in degradation characteristic and unit dimensions. Reliability Engineering & System Safety 239, pages 109505.
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Katarzyna Maraj-Zygmąt, Aleksandra Grzesiek, Grzegorz Sikora, Janusz Gajda & Agnieszka Wyłomańska. (2023) Testing of two-dimensional Gaussian processes by sample cross-covariance function. Chaos: An Interdisciplinary Journal of Nonlinear Science 33:7.
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Xin Wu, Tingting Huang, Kun Zhou & Wei Dai. (2022) Degradation modeling and reliability prediction of products with indicators influenced by clusters in a dynamic environment. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 237:1, pages 80-97.
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Bo Guo. 2023. Advances in Reliability and Maintainability Methods and Engineering Applications. Advances in Reliability and Maintainability Methods and Engineering Applications 445 474 .
Xiangang Cao, Zhuo Lei, Yanchuan Li, Mengyuan Zhang & Xinyu Duan. (2022) Prediction Method of Equipment Remaining Life Based on Self-Attention Long Short-Term Memory Neural Network. Journal of Shanghai Jiaotong University (Science).
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Guanqi Fang, Rong Pan & Yukun Wang. (2022) Inverse Gaussian processes with correlated random effects for multivariate degradation modeling. European Journal of Operational Research 300:3, pages 1177-1193.
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Yumei Liu, Ting Hu, Yun Chen, Zixu Hao & Ming Liu. (2022) Dynamic Fatigue Analysis of High-Speed Trains Gearbox Using Copula Function. Mathematical Problems in Engineering 2022, pages 1-15.
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Diyin Tang, Mengtong Gong, Jinsong Yu, Liwei Guo & Junwei Di. (2022) System-Level Performance Prediction for Infrared Systems Based on Energy Redistribution in Infrared Images. IEEE Transactions on Industrial Electronics 69:2, pages 2000-2011.
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Kunsong Lin, Yutong Wang & Yunxia Chen. (2021) A Kernel-Density based Semi-Parametric stochastic degradation model with dependent increments. Mechanical Systems and Signal Processing 161, pages 107978.
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Jingdong Lin, Zheng Lin, Guobo Liao & Hongpeng Yin. (2021) A Novel Product Remaining Useful Life Prediction Approach Considering Fault Effects. IEEE/CAA Journal of Automatica Sinica 8:11, pages 1762-1773.
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Zhenyu Wu & Yanting Li. (2021) An integrated maintenance strategy of wind turbine based on statistic process control. An integrated maintenance strategy of wind turbine based on statistic process control.
Guanqi Fang & Rong Pan. (2021) On multivariate copula modeling of dependent degradation processes. Computers & Industrial Engineering 159, pages 107450.
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Jiawen Hu, Qiuzhuang Sun, Zhi-Sheng Ye & Qiang Zhou. (2021) Joint Modeling of Degradation and Lifetime Data for RUL Prediction of Deteriorating Products. IEEE Transactions on Industrial Informatics 17:7, pages 4521-4531.
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Hanwen Zhang, Maoyin Chen, Jun Shang, Chunjie Yang & Youxian Sun. (2021) Stochastic process-based degradation modeling and RUL prediction: from Brownian motion to fractional Brownian motion. Science China Information Sciences 64:7.
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Bingxin Yan, Xiaobing Ma, Guifa Huang & Yu Zhao. (2021) Two-stage physics-based Wiener process models for online RUL prediction in field vibration data. Mechanical Systems and Signal Processing 152, pages 107378.
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Kai Song, Jian Shi & Xiaojian Yi. (2020) A time-discrete and zero-adjusted gamma process model with application to degradation analysis. Physica A: Statistical Mechanics and its Applications 560, pages 125180.
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Qinglai Dong, Lirong Cui & Shubin Si. (2020) Reliability and availability analysis of stochastic degradation systems based on bivariate Wiener processes. Applied Mathematical Modelling 79, pages 414-433.
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Jianchun Zhang, Xiaobing Ma & Yu Zhao. (2019) Degradation-Based State Reliability Modeling for Components or Systems With Multiple Monitoring Positions. IEEE/ASME Transactions on Mechatronics 24:6, pages 2453-2464.
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Weiwen Peng, Zhi-Sheng Ye & Nan Chen. (2019) Joint Online RUL Prediction for Multivariate Deteriorating Systems. IEEE Transactions on Industrial Informatics 15:5, pages 2870-2878.
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Shanlin YANG, Jianmin WANG, Leyuan SHI, Yuejin TAN & Fei QIAO. (2018) Engineering management for high-end equipment intelligent manufacturing. Frontiers of Engineering Management 5:4, pages 420.
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Dong Wang & Kwok-Leung Tsui. (2018) Brownian motion with adaptive drift for remaining useful life prediction: Revisited. Mechanical Systems and Signal Processing 99, pages 691-701.
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Fuqiang Sun, Ning Wang, Xiaoyang Li & Wei Zhang. (2017) Remaining Useful Life Prediction for a Machine With Multiple Dependent Features Based on Bayesian Dynamic Linear Model and Copulas. IEEE Access 5, pages 16277-16287.
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Weiwen Peng, Lanqing Hong & Zhisheng Ye. 2017. Statistical Modeling for Degradation Data. Statistical Modeling for Degradation Data 81 103 .
Weiwen Peng, Yan-Feng Li, Yuan-Jian Yang, Shun-Peng Zhu & Hong-Zhong Huang. (2016) Bivariate Analysis of Incomplete Degradation Observations Based on Inverse Gaussian Processes and Copulas. IEEE Transactions on Reliability 65:2, pages 624-639.
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