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Sensors 2012, 12(8), 10148-10162; doi:10.3390/s120810148
Article
On-Line Estimation of Laser-Drilled Hole Depth Using a Machine Vision Method
Department of Mechanical Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan
* Author to whom correspondence should be addressed.
Received: 7 June 2012; in revised form: 23 July 2012 / Accepted: 23 July 2012 / Published: 27 July 2012
(This article belongs to the Section Physical Sensors)
Download PDF Full-Text [1867 KB, uploaded 27 July 2012 13:58 CEST]
Abstract: The paper presents a novel method for monitoring and estimating the depth of a laser-drilled hole using machine vision. Through on-line image acquisition and analysis in laser machining processes, we could simultaneously obtain correlations between the machining processes and analyzed images. Based on the machine vision method, the depths of laser-machined holes could be estimated in real time. Therefore, a low cost on-line inspection system is developed to increase productivity. All of the processing work was performed in air under standard atmospheric conditions and gas assist was used. A correlation between the cumulative size of the laser-induced plasma region and the depth of the hole is presented. The result indicates that the estimated depths of the laser-drilled holes were a linear function of the cumulative plasma size, with a high degree of confidence. This research provides a novel machine vision-based method for estimating the depths of laser-drilled holes in real time.
Keywords: machine vision; on-line estimation; laser-drilled hole depth; laser drilling; laser machining
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MDPI and ACS Style
Ho, C.-C.; He, J.-J.; Liao, T.-Y. On-Line Estimation of Laser-Drilled Hole Depth Using a Machine Vision Method. Sensors 2012, 12, 10148-10162.
AMA StyleHo C-C, He J-J, Liao T-Y. On-Line Estimation of Laser-Drilled Hole Depth Using a Machine Vision Method. Sensors. 2012; 12(8):10148-10162.
Chicago/Turabian StyleHo, Chao-Ching; He, Jun-Jia; Liao, Te-Ying. 2012. "On-Line Estimation of Laser-Drilled Hole Depth Using a Machine Vision Method." Sensors 12, no. 8: 10148-10162.