Model based fault diagnosis of machine tools

A methodology for the fault diagnosis of machine tools by using a few robust sensors, dynamic process models, and parameter estimation, is described. Changes of process parameters are then symptoms, which are fed into a knowledge-based fault diagnosis component. Then, analytical and heuristic knowledge is treated via fault trees and plausibility measures. Some experimental results with a flexible machining center are given.<<ETX>>