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A solution for micro drill condition monitoring with vibration signals for PCB drilling

Qinglong An, Dapeng Dong, Xiaohu Zheng, Ming Chen, Xibin Wang

Circuit World

ISSN: 0305-6120

Article publication date: 16 August 2013

183

Abstract

Purpose

The objective of this study is to develop an automated tool condition monitoring scheme for PCB drilling.

Design/methodology/approach

Vibration signals are used to distinguish micro drill wear stages with proper features extraction and classifier design. Then a tool condition monitoring system is built up through a back propagation neural network (BPNN).

Findings

Experimental results show that BPNN is a practical method of modeling tool wear, and with this method a tool condition monitoring system is built up using energy ratio, root mean square (RMS) and kurtosis coefficient that transformed by vibration signals.

Research limitations/implications

In the further investigation, more signal samples should be computed as monitoring features for BPNN modeling. In addition, in order to build the best monitoring model, it is necessary to evaluate the performance of the BPNN model in advance, and optimize the process.

Originality/value

The paper provides a method and a system for PCB drill wear monitoring. The method and system can achieve on‐line monitoring of PCB drill condition.

Keywords

Citation

An, Q., Dong, D., Zheng, X., Chen, M. and Wang, X. (2013), "A solution for micro drill condition monitoring with vibration signals for PCB drilling", Circuit World, Vol. 39 No. 3, pp. 147-152. https://doi.org/10.1108/CW-03-2013-0009

Publisher

:

Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

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