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Reseach Article

An Online System for Detecting Bending in a Pallet Car

by Ahmad Pouramini
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 152 - Number 10
Year of Publication: 2016
Authors: Ahmad Pouramini
10.5120/ijca2016911835

Ahmad Pouramini . An Online System for Detecting Bending in a Pallet Car. International Journal of Computer Applications. 152, 10 ( Oct 2016), 1-5. DOI=10.5120/ijca2016911835

@article{ 10.5120/ijca2016911835,
author = { Ahmad Pouramini },
title = { An Online System for Detecting Bending in a Pallet Car },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2016 },
volume = { 152 },
number = { 10 },
month = { Oct },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume152/number10/26352-2016911835/ },
doi = { 10.5120/ijca2016911835 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:57:47.500625+05:30
%A Ahmad Pouramini
%T An Online System for Detecting Bending in a Pallet Car
%J International Journal of Computer Applications
%@ 0975-8887
%V 152
%N 10
%P 1-5
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image processing techniques are widely used to detect defects in industrial equipment. In this paper, an online system is presented to detect bending in pallet cars of a travelling grate conveyor used in sintering machines. If bending in several pallet cars exceeds a specified limit, it can stop the production line. Therefore, an early and precise diagnosis is required. The system consists of a camera in a specific position to monitor the pallet cars and provide an online video. A method is presented to detect and extract an appropriate image of a pallet car from this video. The image is then processed to detect bending of the pallet car’s middle frame and measure the degree of bending. Particularly, edge detection methods and Hough transform are used to locate and measure the curvature. The experimental results show a precision of 98% and a recall of 100% for the detection method.

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Index Terms

Computer Science
Information Sciences

Keywords

Defect Detection Hough Transform