Model referenced monitoring and diagnosis - application to the manufacturing system

This paper describes "model referenced monitoring and diagnosis" a systematic method of monitoring and diagnosis. In this method, a model is used either to generate standard values for the monitoring parameters, or to derive a systematic diagnostic algorithm. As examples of the model referenced monitoring in manufacturing systems, the cutting torque prediction system and tool breakage detection system are described. In the former example, the cutting torque values at each point in time, which can be used as reference values in monitoring the abnormal cutting condition, are evaluated based on a solid modelling system. In the latter, an autoregressive (AR) model is adaptively fitted to the cutting torque signal in order to detect any sudden change in the cutting state due to tool breakage. Two examples are also described for the case of model referenced diagnosis; the diagnosis of sequentially controlled machines using the state graph model, and diagnosis by means of a failure causality model. The former method is applicable to machines controlled by sequence control. Based on the state graph of the machine and the controller, the diagnostic programme can be generated in combination with the control programme. The failure causality model represents the propagation of the effects of failures in the machine. All possible combinations of failure causes are obtained by solving the simultaneous Boolean equations derived from the model.