Volume 4 Number 5 (Oct. 2012)
Home > Archive > 2012 > Volume 4 Number 5 (Oct. 2012) >
IJCEE 2012 Vol.4(5): 722-725 ISSN: 1793-8163
DOI: 10.7763/IJCEE.2012.V4.593

Time Domain and Frequency Spectrum Analysis of Sound Signal for Drill Wear Detection

Hamed Rafezi, Mehdi Behzad, and Javad Akbari

Abstract—This paper introduces an approach for drill wear detection. Tool failure in machining processes will result in damages to workpiece. In this approach sound signal of drilling operation is recorded and analyzed in both time and frequency domains. Trend of sound signal statistical features are extracted as the drill becomes worn. Sound signal frequency spectrum is calculated using Fast Fourier Transform (FFT) to detect the effect of drill wear on frequency components of signal. In continue Wavelet Packet Decomposition (WPD) is implemented to focus on detected frequency bands. Finally a Feedforward Backpropagation Neural Network (FBNN) is designed and trained based on sound signal features extracted from wavelet packets. The FBNN classifies the tool state into three classes of wear. This approach provides a tool wear detection strategy with capability of online implementation.

Index Terms—Tool condition monitoring, sound, frequency spectrum, wavelet packets.

Hamed Rafezi is with School of Science and Engineering, Sharif University of Technology, International Campus, Kish, Iran(e-mail:h.rafezi@gmail.com)
Mehdi Behzad and Javad Akbari are with School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran (e-mail:akbari@sharif.edu, m_behzad@sharif.edu)

Cite: Hamed Rafezi, Mehdi Behzad, and Javad Akbari, "Time Domain and Frequency Spectrum Analysis of Sound Signal for Drill Wear Detection," International Journal of Computer and Electrical Engineering vol. 4, no. 5, pp. 722-725, 2012.

General Information

ISSN: 1793-8163
Frequency: Quarterly
Editor-in-Chief: Prof. Yucong Duan
Abstracting/ Indexing: EI (INSPEC, IET), Ulrich's Periodicals Directory, Google Scholar, EBSCO, ProQuest, and Electronic Journals Library
E-mail: ijcee@iap.org

What's New

  • Dec 29, 2018 News!

    IJCEE Vol. 10, No. 4 is available online now.   [Click]

  • Aug 06, 2018 News!

    IJCEE Vol. 8, No. 4 - Vol. 9, No. 1 have been indexed by EI (Inspec) Inspec, created by the Institution of Engineering and Tech.!   [Click]

  • Oct 12, 2018 News!

    IJCEE Vol. 10, No. 3 is available online now.   [Click]

  • Jul 12, 2018 News!

    IJCEE Vol. 10, No. 2 is available online now.   [Click]

  • Apr 02, 2018 News!

    IJCEE Vol. 10, No. 1 is available online now.   [Click]

  • Read more>>