Title :
Jam Detector for Steel Pickling Lines Using Machine Vision
Author :
Usamentiaga, Ruben ; Molleda, Julio ; Garcia, Diego ; Bulnes, Francisco G. ; Perez, J.M.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Oviedo, Viesques, Spain
Abstract :
High efficiency and availability in industrial processing lines are requirements to produce top-grade steel at a minimum cost. One of the most important aspects in achieving these goals is efficient automation, which ensures high performance and reduces the cost of production. This work proposes a new system to improve the automation of a steel processing line: a jam detector based on machine vision. The proposed system is designed to detect jams in a crucial step in steel production: pickling. The proposed machine-vision application acquires images from the pickling line and detects the jam based on the number of pieces ejected from the side trimmers. State-of-the-art methods are used for image processing, providing a fast and robust detector for the industrial line. Tests and the results obtained after more than one year of operation in a steel processing plant indicate that the proposed system meets production needs.
Keywords :
automation; computer vision; cost reduction; industrial plants; object detection; pickling (materials processing); production engineering computing; steel industry; steel manufacture; automation; efficient automation; image processing; industrial processing lines; jam detector; machine vision application; production cost reduction; side trimmers; steel pickling lines; steel processing line; steel processing plant; steel production; Jam detection; machine vision; pickling line;
Journal_Title :
Industry Applications, IEEE Transactions on
DOI :
10.1109/TIA.2013.2259786