This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Sensory-Based Prognostics and Life Prediction for Components with Exponential Degradation
Technical Paper
2006-01-1419
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
Research on interpreting sensory data communicated by smart sensors and distributed sensor networks, and utilizing these data streams in making critical decisions stands to provide significant advancements across a wide range of application domains such as maintenance management. In this paper, a stochastic degradation modeling framework is developed for computing and continuously updating residual life distributions of partially degraded components. The methodology combines sensory data acquired through condition monitoring technology with reliability and degradation characteristics using novel sensory updating techniques. A sensory updating procedure is developed and validated using real world degradation data from rolling element thrust bearings.
Recommended Content
Authors
Topic
Citation
Gebraeel, N., "Sensory-Based Prognostics and Life Prediction for Components with Exponential Degradation," SAE Technical Paper 2006-01-1419, 2006, https://doi.org/10.4271/2006-01-1419.Also In
Reliability and Robust Design in Automotive Engineering, 2006
Number: SP-2032; Published: 2006-04-03
Number: SP-2032; Published: 2006-04-03
References
- Licht T. Deshmukh A. “Hierarchically organized Bayesian networks for distributed sensor networks” American Society of Mechanical Engineers Dynamic Systems and Control Division 71 1059 1066 2003
- Akyildiz I. F. Su W Sankarasubramaniam Y Cayirci E. “A survey on sensor networks” IEEE Communications Magazine 40 8 102 105 2002
- Tseng S. Hamada M. Chiao C. “Using degradation data to improve fluorescent lamp reliability” Journal of Quality Technology 27 363 369 1995
- Yang K. Jeang A. “Statistical surface roughness checking procedure based on a cutting tool wear model” Journal of Manufacturing Systems 13 1 8 1994
- Yang K. Yang G. “Degradation reliability assessment using severe critical values” International Journal of Reliability, Quality and Safety Engineering 5 85 95 1998
- Goode K. Roylance B. Moore J. “Development of a predictive model for monitoring condition of a hot strip mill” Ironmaking and Steelmaking 25 42 46 1998
- Swanson D. C. “A general prognostic tracking algorithm for predictive maintenance” IEEE Aerospace Conference Proceedings 6 62971 62977 2001
- Doksum K. A. Hoyland, A. “Models for variable-stress accelerated life testing experiments based on Wiener processes and the inverse Gaussian distribution” Technometrics 34 74 82 1992
- Whitmore G. “Estimating degradation by a Wiener diffusion process subject to measurement error Lifetime Data Analysis 1 307 319 1995
- Lee J. “Measurement of machine performance degradation using a neural network model” Computers in Industry 30 3 193 209 1996
- Gebraeel N. Lawley M. Liu R. Parmeshwaran V. “Life distributions from component degradation signals: A Neural Net Approach” IEEE Transactions on Industrial Electronics 51 3 694 700 2004
- Chinnam R. B. Baruah P. “A neuro-fuzzy approach for estimating mean residual life in condition-based maintenance systems” International Journal of Materials and Product Technology 20 1-3 166 179 2003
- Chinnam R. B. Mohan P. “Online reliability estimation of physical systems using neural networks and wavelets” International Journal of Smart Engineering System Design 4 4 253 264 2002
- Shao Y. Nezu K. “Prognosis of remaining bearing life using neural networks” Proceedings of the Institute of Mechanical Engineer, Part I, Journal of Systems and Control Engineering 214 3 217 230 2000
- Lu C. Meeker W. “Using degradation measures to estimate a time-to-failure distribution” Technometrics 35 2 161 174 1993
- Gebraeel, N. Lawley, M. Li, R. Ryan, J. K. “Life distributions from component degradation signals: A Bayesian Approach” IIE Transactions on Reliability 2005
- Harris T. A. “Rolling Bearing Analysis” Wiley New York 2001
- Nelson, W. Accelerated Testing Statistical Models, Test Plans, and Data Analysis Wiley New York 1990
- Blake M. P. Mitchel W. S. “Vibration & Acoustic Measurement Handbook, Spartan Books” New York New York 1972