Signal processing research in automatic tool wear monitoring

• Authors: Larry P. Heck
• Venue: ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
• Year: 1993

Machine monitoring involves the automatic detection and identification of failure events that can occur in a mechanical system. A particularly important machine monitoring problem is the monitoring of tool wear in automatic metal drilling systems. This paper briefly discusses the role of signal processing in tool wear monitoring, and highlights several avenues of potential research in this area. These include the application and development of signal enhancement algorithms to reduce the corrupting effects of extraneous structural vibrations on the tool wear signal. This paper also discusses research directions in improved tool wear signal understanding, including detection techniques to classify a tool's condition using knowledge-based and statistical approaches.