Drill wear monitoring using cutting force signals
Monitoring of tool wear condition for the drilling process, which is one of the major cutting process in machining, is very considerable for the sake of avoiding tool failures, increasing machine utilization and decreasing production cost in an automated manufacturing environment. In the literature, many tool wear condition monitoring techniques have been investigated using a variety of sensors including dynamometers for force and torque, accelerometers for mechanical vibrations, AE sensors for acoustic emission and current probes for current/power measurement of spindle and feed motors. New techniques are proposed in this paper for real time identification of tool wear status based on cutting force and torque measurements from dynamometer during metal drilling. These techniques utilize hidden Markov models (HMM), phase plane method, transient time method and mechanistic approach. (C) 2003 Elsevier Ltd. All rights reserved.
drilling process tool wear condition monitoring hidden markov models monitoring systems