The Application of Deep Learning and Image Processing Technology in Laser Positioning

In this study, machine vision technology was used to precisely position the highest energy of the laser spot to facilitate the subsequent joining of product workpieces in a laser welding machine. The displacement stage could place workpieces into the superposition area and allow the parts to be join...

Full description

Bibliographic Details
Main Authors: Chern-Sheng Lin, Yu-Chia Huang, Shih-Hua Chen, Yu-Liang Hsu, Yu-Chen Lin
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Applied Sciences
Subjects:
Online Access:http://www.mdpi.com/2076-3417/8/9/1542
id doaj-5f81443152454f419048c063d901d3ea
record_format Article
spelling doaj-5f81443152454f419048c063d901d3ea2020-11-25T00:42:24ZengMDPI AGApplied Sciences2076-34172018-09-0189154210.3390/app8091542app8091542The Application of Deep Learning and Image Processing Technology in Laser PositioningChern-Sheng Lin0Yu-Chia Huang1Shih-Hua Chen2Yu-Liang Hsu3Yu-Chen Lin4Department of Automatic Control Engineering, Feng Chia University, Taichung 40724, TaiwanDepartment of Automatic Control Engineering, Feng Chia University, Taichung 40724, TaiwanDepartment of Automatic Control Engineering, Feng Chia University, Taichung 40724, TaiwanDepartment of Automatic Control Engineering, Feng Chia University, Taichung 40724, TaiwanDepartment of Automatic Control Engineering, Feng Chia University, Taichung 40724, TaiwanIn this study, machine vision technology was used to precisely position the highest energy of the laser spot to facilitate the subsequent joining of product workpieces in a laser welding machine. The displacement stage could place workpieces into the superposition area and allow the parts to be joined. With deep learning and a convolutional neural network training program, the system could enhance the accuracy of the positioning and enhance the efficiency of the machine work. A bi-analytic deep learning localization method was proposed in this study. A camera was used for real-time monitoring. The first step was to use a convolutional neural network to perform a large-scale preliminary search and locate the laser light spot region. The second step was to increase the optical magnification of the camera, re-image the spot area, and then use template matching to perform high-precision repositioning. According to the aspect ratio of the search result area, the integrity parameters of the target spot were determined. The centroid calculation was performed in the complete laser spot. If the target was an incomplete laser spot, the operation of invariant moments would be performed. Based on the result, the precise position of the highest energy of the laser spot could be obtained from the incomplete laser spot image. The amount of displacement could be calculated by overlapping the highest energy of the laser spot and the center of the image.http://www.mdpi.com/2076-3417/8/9/1542machine visionlaser spotdeep learningconvolutional neural network
collection DOAJ
language English
format Article
sources DOAJ
author Chern-Sheng Lin
Yu-Chia Huang
Shih-Hua Chen
Yu-Liang Hsu
Yu-Chen Lin
spellingShingle Chern-Sheng Lin
Yu-Chia Huang
Shih-Hua Chen
Yu-Liang Hsu
Yu-Chen Lin
The Application of Deep Learning and Image Processing Technology in Laser Positioning
Applied Sciences
machine vision
laser spot
deep learning
convolutional neural network
author_facet Chern-Sheng Lin
Yu-Chia Huang
Shih-Hua Chen
Yu-Liang Hsu
Yu-Chen Lin
author_sort Chern-Sheng Lin
title The Application of Deep Learning and Image Processing Technology in Laser Positioning
title_short The Application of Deep Learning and Image Processing Technology in Laser Positioning
title_full The Application of Deep Learning and Image Processing Technology in Laser Positioning
title_fullStr The Application of Deep Learning and Image Processing Technology in Laser Positioning
title_full_unstemmed The Application of Deep Learning and Image Processing Technology in Laser Positioning
title_sort application of deep learning and image processing technology in laser positioning
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2018-09-01
description In this study, machine vision technology was used to precisely position the highest energy of the laser spot to facilitate the subsequent joining of product workpieces in a laser welding machine. The displacement stage could place workpieces into the superposition area and allow the parts to be joined. With deep learning and a convolutional neural network training program, the system could enhance the accuracy of the positioning and enhance the efficiency of the machine work. A bi-analytic deep learning localization method was proposed in this study. A camera was used for real-time monitoring. The first step was to use a convolutional neural network to perform a large-scale preliminary search and locate the laser light spot region. The second step was to increase the optical magnification of the camera, re-image the spot area, and then use template matching to perform high-precision repositioning. According to the aspect ratio of the search result area, the integrity parameters of the target spot were determined. The centroid calculation was performed in the complete laser spot. If the target was an incomplete laser spot, the operation of invariant moments would be performed. Based on the result, the precise position of the highest energy of the laser spot could be obtained from the incomplete laser spot image. The amount of displacement could be calculated by overlapping the highest energy of the laser spot and the center of the image.
topic machine vision
laser spot
deep learning
convolutional neural network
url http://www.mdpi.com/2076-3417/8/9/1542
work_keys_str_mv AT chernshenglin theapplicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT yuchiahuang theapplicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT shihhuachen theapplicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT yulianghsu theapplicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT yuchenlin theapplicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT chernshenglin applicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT yuchiahuang applicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT shihhuachen applicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT yulianghsu applicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
AT yuchenlin applicationofdeeplearningandimageprocessingtechnologyinlaserpositioning
_version_ 1725282760888680448