Authors: H. Chelladurai, V.K. Jain, N.S. Vyas
Addresses: Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 208016, India. ' Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 208016, India. ' Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 208016, India
Abstract: Supervision or condition monitoring of the cutting tool wear is a complex phenomenon in any machining process. This paper describes an in-depth study on the development of a cutting tool condition monitoring (TCM) system for high speed turning operations. An attempt has been made to create artificial flank wear using electrical discharge machining (EDM) process. Using this (artificial worn out) cutting tool, experiments were carried out for various machining conditions. Vibration and strain data from the cutting process are recorded using two accelerometers and a strain gauge bridge. Time domain and power spectral analyses are carried out and an artificial neural networks (ANN) back propagation algorithm is used to classify and estimate the wear parameters.
Keywords: artificial flank wear; strain; vibration; artificial neural networks; ANNs; cutting tools; tool wear; condition monitoring; wear monitoring; high speed turning; electrical discharge machining; EDM; electro-discharge machining.
International Journal of Machining and Machinability of Materials, 2010 Vol.8 No.1/2, pp.87 - 113
Published online: 05 Aug 2010 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article