Remaining useful life prediction based on nonlinear state space model

2011 Prognostics and System Health Management Conference, PHM-Shenzhen 2011

Volumn , Issue , 2011, Pages

  Zhao, Jianmin ^a   Feng, Tianle ^a  

^a MECHANICAL ENGINEERING COLLEGE   (China)

Author keywords

prediction; remaining useful life; state space model

Indexed keywords

EXPECTATION-MAXIMIZATION ALGORITHMS; HEALTH DEGRADATION; INDUSTRY ASSETS; NONLINEAR STATE SPACE MODELS; PARTICLE FILTERING; REMAINING USEFUL LIFE PREDICTIONS; REMAINING USEFUL LIVES; STATE SPACE MODEL;

ALGORITHMS; FORECASTING; HEALTH;

STATE SPACE METHODS;

EID: 79960915573     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PHM.2011.5939528     Document Type: Conference Paper

References (11)

1. Zhou Yifan, Ma Lin, Mathew, Joseph, "Non-gaussian continuous state space model for asset degradation," Proceedings 3rd World Congress on Engineering Asset Management and Intelligent Maintenance Systems Conference1, Beijing, China, 2008, pp.1981-1992.
2. Richard K. Kunz, "Characterization of solid propellant for linear cumulative damage modeling," Joint Propulsion Conference & Exhibit, Denver, Colorado, Aug. 2009, pp.1-10.
3. Nagi Gebraeel, Mark Lawley, R. Liu, and Vijay Panneshwaran, "Residual life predictions from vibration-based degradation signals: a neural network approach," IEEE Transactions on Industrial, vol. 51, no. 3, Jun. 2004, pp.694-700.
4. Shunfeng Cheng and Michael Pecht, " Multivariate state estimation technique for remaining useful life prediction of electronic products," Advancement of Artificial Intelligence, 2007.
5. S. Barone, M. Guida, and G. Pulcini, "A stochastic degradation model of catalytic converters performances."
6. Deng Chao, Wu Jun, and Wan Zijuan, "Performance degradation model based on support vector machine," Computer Integrated Manufacturing Systems, vol. 15, no. 4, Apr. 2009, pp.685-698.
7. Nagi Gebraeel, Alaa Elwany, and Jing Pan, "Residual Life Predictions in the absence of prior degradation knowledge," IEEE Transactions on Reliability, vol.58, no.1, Mar. 2009, pp.106-116.
8. Jorgensen B., Lundbye C.S., Song PX-K et aI, "A state space model for multivariate longitudinal count data," Biometrika, vo1.86, no. 1. 1999, pp.169-181.
9. Marcos E. Orchard, "A particle filtering-based framework for on-line fault diagnosis and failure prognosis," Georgia Institute of Technology, Georgia, 2006.
10. Argon Chen, and G. S. Wu, "Real-time health prognosis and dynamic preventive maintenance policy for equipment under ageing Markovian deterioration," International Journal of Production Research, vol.45, no.15,Aug. 2007, pp.3351-3379.
11. Hashemi R., Jacqmin-Gadda H., and Commenges D., "A latent process model for joint modeling of events and marker," Lifetime Data Analysis, vol 9, no.4, 2003, pp.331-343. (Pubitemid 39015635)