Remaining useful life prediction model of the space station
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Liming Ren | Li Xiaopeng | Hong-Zhong Huang | Fuqiu Li | Hongzhong Huang | Fuqiu Li | Lin Xiaopeng | Liming Ren
[1] Francesco Corman,et al. Integrated optimization on train scheduling and preventive maintenance time slots planning , 2017 .
[2] Zhen Liu,et al. A method for remaining useful life prediction of crystal oscillators using the Bayesian approach and extreme learning machine under uncertainty , 2018, Neurocomputing.
[3] Jie Yang,et al. Early prediction of remaining discharge time for lithium-ion batteries considering parameter correlation between discharge stages , 2018, Eksploatacja i Niezawodnosc - Maintenance and Reliability.
[4] Jan Lundberg,et al. Remaining useful life estimation: review , 2014, Int. J. Syst. Assur. Eng. Manag..
[5] Xinhong Li,et al. Risk-based operation safety analysis during maintenance activities of subsea pipelines , 2019, Process Safety and Environmental Protection.
[6] Hongru Li,et al. Prognostic for hydraulic pump based upon DCT-composite spectrum and the modified echo state network , 2016, SpringerPlus.
[7] Xin Li,et al. Optimal Bayesian control policy for gear shaft fault detection using hidden semi-Markov model , 2018, Comput. Ind. Eng..
[8] Osama Moselhi,et al. Assessment of Remaining Useful Life of Pipelines Using Different Artificial Neural Networks Models , 2016 .
[9] Mariusz Zieja,et al. Outline of a method for estimating the durability of components or device assemblies while maintaining the required reliability level , 2018 .
[10] Weiwen Peng,et al. Reliability analysis of complex multi-state system with common cause failure based on evidential networks , 2018, Reliab. Eng. Syst. Saf..
[11] Hui Ye,et al. Remaining useful life assessment of lithium-ion batteries in implantable medical devices , 2018 .
[12] Michael G. Pecht,et al. Prognostics and health management based refurbishment for life extension of electronic systems , 2014, 2014 IEEE International Conference on Information and Automation (ICIA).
[13] Gautam Biswas,et al. Methodologies for system-level remaining useful life prediction , 2016, Reliab. Eng. Syst. Saf..
[14] Hong-Zhong Huang,et al. Physics of failure-based reliability prediction of turbine blades using multi-source information fusion , 2018, Appl. Soft Comput..
[15] Sharareh Taghipour,et al. Optimisation of non-periodic inspection and maintenance for multicomponent systems , 2018 .
[16] Xingyu Gu,et al. Estimation and uncertainty analysis of energy consumption and CO2 emission of asphalt pavement maintenance , 2018 .
[17] Adrian Gill,et al. Optimisation of the technical object maintenance system taking account of risk analysis results , 2017 .
[18] Weiwen Peng,et al. Reliability assessment of complex electromechanical systems under epistemic uncertainty , 2016, Reliab. Eng. Syst. Saf..
[19] Robert X. Gao,et al. Deep Learning for Improved System Remaining Life Prediction , 2018 .
[20] Bin Liang,et al. Remaining useful life prediction of aircraft engine based on degradation pattern learning , 2017, Reliab. Eng. Syst. Saf..
[21] Jian Shuai,et al. The energy source based job safety analysis and application in the project , 2017 .
[22] Tiedo Tinga,et al. Improving failure analysis efficiency by combining FTA and FMEA in a recursive manner , 2018, Reliab. Eng. Syst. Saf..
[23] Jin Cui,et al. Multi-bearing remaining useful life collaborative prediction: A deep learning approach , 2017 .
[24] Wim J. C. Verhagen,et al. Predictive maintenance for aircraft components using proportional hazard models , 2018, J. Ind. Inf. Integr..
[25] Shaoping Wang,et al. An adaptive-order particle filter for remaining useful life prediction of aviation piston pumps , 2017 .
[27] Yang Zhang,et al. Maintenance processes modelling and optimisation , 2017, Reliab. Eng. Syst. Saf..
[28] Luo Ya,et al. The Comparison of Personalization Recommendation for E-Commerce , 2012 .
[29] Hong-Zhong Huang,et al. Reliability analysis of phased mission system with non-exponential and partially repairable components , 2018, Reliab. Eng. Syst. Saf..
[30] Bin Xu,et al. Failure prognosis of multiple uncertainty system based on Kalman filter and its application to aircraft fuel system , 2016 .
[31] Pham Luu Trung Duong,et al. Heuristic Kalman optimized particle filter for remaining useful life prediction of lithium-ion battery , 2018, Microelectron. Reliab..
[32] Hong-Zhong Huang,et al. Reliability assessment of multi-state phased mission system with non-repairable multi-state components , 2018, Applied Mathematical Modelling.
[33] An Jinwen. Geostationary Satellite's End-of-Life Predication Based on Propellant-Remaining Estimation , 2006 .
[34] R. Batley. Guest editor's preface. Symposium on non‐state provision of basic services , 2006 .
[35] Cher-Hiang Goh,et al. A framework for the casualty risk assessment and lifetime determination of small satellites , 2016, 2016 IEEE Region 10 Conference (TENCON).
[36] Shiyu Zhou,et al. Remaining useful life prediction based on noisy condition monitoring signals using constrained Kalman filter , 2016, Reliab. Eng. Syst. Saf..
[37] Xin Zhang,et al. An improved unscented particle filter approach for lithium-ion battery remaining useful life prediction , 2018, Microelectron. Reliab..
[38] Wenhai Wang,et al. Remaining useful life prediction for an adaptive skew-Wiener process model , 2017 .
[39] Dong Wang,et al. Battery remaining useful life prediction at different discharge rates , 2017, Microelectron. Reliab..