Machine anomaly detection and diagnosis incorporating operational data applied to feed axis health monitoring

ASME 2011 International Manufacturing Science and Engineering Conference, MSEC 2011

Volumn 2, Issue , 2011, Pages 289-296

  Liao, Linxia ^a   Pavel, Radu ^b  

^a SIEMENS CORPORATE RESEARCH   (United States)

^b Techsolve   (United States)

Author keywords

Anomaly detection; Diagnosis; Operating conditions; Principal component analysis; Self organizing maps

Indexed keywords

ACCURATE ANALYSIS; ANOMALY DETECTION; DATA SETS; EXTERNAL SENSORS; HEALTH MONITORING; MACHINE HEALTH; OPERATING CONDITION; OPERATIONAL DATA; PRINCIPAL COMPONENTS; SELF ORGANIZING; USAGE PATTERNS;

CONFORMAL MAPPING; DATA HANDLING; DIAGNOSIS; MACHINERY; MANUFACTURE; SENSORS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 82455205901     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/MSEC2011-50211     Document Type: Conference Paper

References (14)

1. Luo, M., Wang, D., Pham, M., Low, C. B., Zhang, J. B., Zhang, D. H., et al. (2005). "Model-based fault diagnosis/prognosis for wheeled mobile robots: a review." Industrial Electronics Society, 2005. IECON 2005. 31st Annual Conference of IEEE.
2. Li, Y., Kurfess, T. R., & Liang, S. Y. (2000). "Stochastic prognostics for rolling element bearings." Mechanical Systems and Signal Processing, 14 (5), 747-762.
3. Markou, M., & Singh, S. (2003). "Novelty detection: a review - part 1: Statistical approaches." Signal Processing, 83 (12), 2481-2497.
4. Markou, M., & Singh, S. (2003). "Novelty detection: a review - part 2: neural network based approaches." Signal Processing, 83 (12), 2499-2521.
5. Djurdjanovic, D., Lee, J., & Ni, J. (2003). "Watchdog Agent-an infotronics-based prognostics approach for product performance degradation assessment and prediction." Advanced Engineering Informatics, 17 (3-4), 109-125.
6. Kothamasu, R., Huang, S. H., & VerDuin, W. H. (2006). "System health monitoring and prognostics - a review of current paradigms and practices." International Journal of Advanced Manufacturing Technology, 28, 1012-1024.
7. Wang, W. (2007). "An adaptive predictor for dynamic system forecasting." Mechanical Systems and Signal Processing, 21 (2), 809-823.
8. Kasabov, N. K., & Song, Q. (2002). "DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction." IEEE TRANSACTIONS ON FUZZY SYSTEMS, 10 (2).
9. Cormen, T., Leiserson, C., Rivest, R., & Stein, C. (2002). "Introduction to Algorithms". The MIT Press.
10. Duda, R., Hart, P., & Stork, D. (2000). Pattern Classification (2 ed.). Wiley-Interscience.
11. Wang, S., & Cui, J. (2005). "Sensor-fault detection, diagnosis and estimation for centrifugal chiller systems using principal-component analysis method." Applied Energy, 82 (3), 197-213.
12. Kohonen, T. (1990). "The self-organizing map." Proceeding of the IEEE, 78 (9), 1464-1480.
13. Fukunaga, K. (1990). "Introduction to statistical pattern recognition (2nd ed.)." Boston: Academic Press.
14. Li, G., Qin, S.Z., Ji, Y.D., & Zhou D.H., "Total PLS based contribution plots for fault diagnosis," Acta Automatica Sinica, 35 (6), 759-765.