Paper Title:
Sensor Fusion for Condition Monitoring System of End Milling Operations
  Abstract

This paper describes the utilisation of multi sensor fusion model using force, vibration, acoustic emission, strain and sound sensors for monitoring tool wear in end milling operations. The paper applies the ASPS approach (Automated Sensor and Signal Processing Selection) method for signal processing and sensor selection [1]. The sensory signals were processed using different signal processing methods to create a wide range of Sensory Characteristic Features (SCFs). The sensitivity of these SCFs to tool wear is investigated. The results indicate that the sensor fusion system is capable of detecting machining faults in comparison to a single sensor using the suggested approach.

  Info
Periodical
Edited by
Daizhong Su, Qingbin Zhang and Shifan Zhu
Pages
267-270
DOI
10.4028/www.scientific.net/KEM.450.267
Citation
J. Abbas, A. Al-Habaibeh, D. Z. Su, "Sensor Fusion for Condition Monitoring System of End Milling Operations", Key Engineering Materials, Vol. 450, pp. 267-270, 2011
Online since
November 2010
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