DocumentCode
643606
Title
A novel image-based method for conveyor belt rip detection
Author
Xiaoming Peng
Author_Institution
Sch. of Autom., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear
2013
fDate
5-8 Aug. 2013
Firstpage
1
Lastpage
4
Abstract
Conveyor belts of all types are prone to rips from impact by sharp objects in the flow path, which can lead to expensive belt failure. In this paper, we present a novel method for detecting conveyor belt rips. In contrast to previous work on conveyor belt rip detection, the proposed method has a built-in real/false rip classification mechanism, which we believe will serve as a quite useful reference to designers of vision-based conveyor belt monitoring systems who wish to reduce false rip detection rates.
Keywords
belts; condition monitoring; conveyors; fault diagnosis; image classification; mechanical engineering computing; conveyor belt rip detection; failure; image-based method; rip classification mechanism; vision-based conveyor belt monitoring systems; Belts; Educational institutions; Eigenvalues and eigenfunctions; Feature extraction; Image edge detection; Support vector machine classification; Training; conveyor belt rip detection; digital image processing; pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location
KunMing
Type
conf
DOI
10.1109/ICSPCC.2013.6663878
Filename
6663878
Link To Document