Title: Tool wear prediction by using wavelet transform

Authors: Sarvesh Kumar Mishra; U. Srinivas Rao; Sandeep Kumar

Addresses: Department of Mechanical Engineering, Indian Institute of Technology Delhi, New Delhi, 110016, India ' Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India ' Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India

Abstract: Tool wear has been a potential problem that costs high for the manufacturing industry. In the past there has been application of signal processing techniques to cutting operation and monitor the tool wear. This paper relates the suitability of application of wavelet transform to tool wear prediction. The suitability of fast Fourier transform (FFT) and discrete wavelet transform (DWT) to process the signals from machining was investigated. To accomplish this objective, experiments were carried out to collect signals from machining experiments and thereafter signals were processed using FFT and wavelet transform. It is observed that at higher cutting speeds, wavelet transform is a more effective signal processing technique compared to FFT as signal gets corrupted by high frequency noise at higher speeds. Effect of wavelet packet decomposition for de-noising and filtering was also studied to remove high frequency noise from the accelerometer signals.

Keywords: tool condition monitoring; FFT; fast Fourier transform; discrete wavelet transform; DWT; tool wear; machining; vibration signals; wear prediction; cutting speed; signal processing; wavelet packet decomposition; de-noising; filtering; high frequency noise.

DOI: 10.1504/IJPTECH.2016.080000

International Journal of Precision Technology, 2016 Vol.6 No.3/4, pp.216 - 230

Received: 06 Apr 2016
Accepted: 26 Aug 2016
Published online: 26 Oct 2016 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article