Title :
Detection of discrete faults in electronics assembly
Author :
Sahinci, E. ; Kamen, E.W.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
We present an optimal estimation approach to detecting discrete faults in electronics assembly. The algorithm utilizes a nonlinear fault model whose state is a vector containing the probabilities of the process in the normal operating state and all possible fault states at a given time. The model describes the time behaviour of the process state and how the process state is related to the process measurements. An extended Kalman filter is used to obtain an estimate of the process state. This approach is applied to an electronics assembly line located at the Center for Board Assembly Research at Georgia Tech
Keywords :
Kalman filters; assembling; fault diagnosis; hidden Markov models; probability; production control; radial basis function networks; state estimation; Georgia Tech; RBF neural nets; discrete fault detection; electronics assembly; extended Kalman filter; hidden Markov model; nonlinear fault model; optimal estimation; probability; process state; state estimation; time behaviour; Assembly; Circuit faults; Computer aided manufacturing; Degradation; Electrical fault detection; Fault detection; Manufacturing systems; Pulp manufacturing; State estimation; Time measurement;
Conference_Titel :
Control Applications, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Trieste
Print_ISBN :
0-7803-4104-X
DOI :
10.1109/CCA.1998.721564
