ONLINE TOOL BREAKAGE DETECTION IN TURNING - A MULTISENSOR METHOD

A multi-sensor tool breakage detection system is introduced that chara cterizes the state of measurements during normal (no-fault) condition and at tool breakage by the two columns of a multi-valued influence ma trix (MVIM). In this system the measurements are monitored on-line and flagged upon the detection of abnormalities. Tool breakage detection is performed by matching this vector of flagged measurements against t he two columns of MVIM, which are estimated during a training session so as to minimize the error in detection. The detection system is impl emented in turning. Experimental results indicate that this system pro vides excellent detection when the full range of tool breakage effect on the measurements is included in training, and that its performance is less dependent upon the training set than a multilayer neural net.