Title :
Jam detector for steel pickling lines using machine vision
Author :
Usamentiaga, Rubén ; Molleda, Julio ; Garcia, Daniel F. ; Bulnes, Francisco G. ; Pérez, Jesus M.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Oviedo, Gijon, Spain
Abstract :
High efficiency and availability in industrial processing lines is a requirement 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 in operation in a steel processing plant indicate that the proposed system meets production needs.
Keywords :
computer vision; industrial plants; object detection; pickling (materials processing); production engineering computing; steel industry; image processing; industrial processing lines; jam detector; machine vision; production cost reduction; side trimmers; steel pickling lines; steel processing line automation; steel processing plant; steel production; Belts; Cameras; Machine vision; Steel; Strips; Jam detection; Machine Vision; Pickling Line;
Conference_Titel :
Industry Applications Society Annual Meeting (IAS), 2012 IEEE
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4673-0330-9
Electronic_ISBN :
0197-2618
DOI :
10.1109/IAS.2012.6374071