Abstract:
Based on radial basis function (RBF) neural networks, the
healthy working model of each subsystem of robot in FMS is
established. A new approach to fault on-line detection and
diagnosis according to neural networks model is presented. Fault
double detection based on neural network model and threshold
judgement and quick fault identification based on multi-layer
feedforward neural network model and threshold judgement and
quick fault identification based on multi-layer feedforward
neural networks are applied, which can meet quickness and
reliability of fault detection and diagnosis for robot in FMS.
Key words: Neural
networds Robot in FMS Fault detection Fault diagnosis
Manuscript received on
August 19, 1997; revised manuscript November 17, 1997
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