Cutting tool condition monitoring using eigenfaces

Abstract

AbstractEffective monitoring of the tool wear condition within a machining process can be very challenging. Depending on the sensors used, often only a part of the relevant wear information can be detected. In the case of milling processes data acquisition is made even more difficult by the fact that the process working point is inaccessible for sensor applications due to the physical tool, the machining process itself, the chipping and used cooling-lubricants. By using a variety of sensors and different measuring principles, sensor data fusion strategies can counteract this problem. An approach to this is the eigenface algorithm. This approach, a face recognition technique, is tested for its suitability on tool condition monitoring in milling processes by using multi-sensor process data.