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A Distributed Heterogeneous Inspection System for High Performance Inline Surface Defect Detection

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1 Institute of Undersea Technology, National Sun Yat-sen University, Kaohsiung, Taiwan
2 Department of Mechanical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan
3 Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan

* Corresponding Author: Yu-Cheng Chou, email

Intelligent Automation & Soft Computing 2019, 25(1), 79-90. https://doi.org/10.31209/2018.100000011

Abstract

This paper presents the Distributed Heterogeneous Inspection System (DHIS), which comprises two CUDA workstations and is equipped with CPU distributed computing, CPU concurrent computing, and GPU concurrent computing functions. Thirty-two grayscale images, each with 5,000× 12,288 pixels and simulated defect patterns, were created to evaluate the performances of three system configurations: (1) DHIS; (2) two CUDA workstations with CPU distributed computing and GPU concurrent computing; (3) one CUDA workstation with GPU concurrent computing. Experimental results indicated that: (1) only DHIS can satisfy the time limit, and the average turnaround time of DHIS is 37.65% of the time limit; (2) a good linear relationship exists between the processing speed ratio and the instruction sequence quantity ratio.

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APA Style
Chou, Y., Liao, W., Chen, Y., Chang, M., Lin, P.T. (2019). A distributed heterogeneous inspection system for high performance inline surface defect detection. Intelligent Automation & Soft Computing, 25(1), 79-90. https://doi.org/10.31209/2018.100000011
Vancouver Style
Chou Y, Liao W, Chen Y, Chang M, Lin PT. A distributed heterogeneous inspection system for high performance inline surface defect detection. Intell Automat Soft Comput . 2019;25(1):79-90 https://doi.org/10.31209/2018.100000011
IEEE Style
Y. Chou, W. Liao, Y. Chen, M. Chang, and P.T. Lin, “A Distributed Heterogeneous Inspection System for High Performance Inline Surface Defect Detection,” Intell. Automat. Soft Comput. , vol. 25, no. 1, pp. 79-90, 2019. https://doi.org/10.31209/2018.100000011



cc Copyright © 2019 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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