Title :
Machine failure detection in manufacturing systems
Author :
Yang, Chun ; Mariton, Michel
Author_Institution :
Signal & Syst. Technol., Seattle, WA, USA
Abstract :
Machine failure detection is considered in this paper, where a hybrid state space formulation is proposed to arrive at stochastic models of failure-prone manufacturing systems. Detection filters are then developed to estimate degraded regimes of machines operation. Simulation results are finally presented to assess the characteristics of the proposed models and filters
Keywords :
failure analysis; fault diagnosis; filtering theory; manufacture; state-space methods; stochastic systems; degraded regime estimation; detection filters; failure-prone manufacturing systems; hybrid state-space formulation; machine failure detection; stochastic models; Extrapolation; Filters; Manufacturing processes; Manufacturing systems; Performance evaluation; Production; Robustness; Testing;
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
DOI :
10.1109/CDC.1994.411282
