Online Burning Material Pile Detection on Color Clustering and Quaternion based Edge Detection in Boiler
2015 (English)In: KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, ISSN 1976-7277, Vol. 9, no 1, 190-207 p.Article in journal (Refereed) Published
In the combustion engineering, to decrease pollution and increase production efficiency, and to optimally keep solid burning material amount constant in a burner online, it needs a smart method to detect the amount variation of the burning materials in a high temperature environment. This paper presents an online machine vision system for automatically measuring and detecting the burning material amount inside a burner or a boiler. In the camera-protecting box of the system, a sub-system for cooling is constructed by using the cooling water circulation techqique. In addition, the key and intelligent step in the system is to detect the pile profile of the variable burning material, and the algorithm for the pile profile tracing was studied based on the combination of the gey level (color) discontinuity and similarity based image segmentation methods, the discontinuity based sub-algorithm is made on the quaternion convolution, and the similarity based sub-algorithm is designed according to the region growing with multi-scale clustering. The results of the two sub-algoritms are fused to delineate the final pile profile, and the algorithm has been tested and applied in different industrial burners and boilers. The experiements show that the proposed algorithm works satisfactorily.
Place, publisher, year, edition, pages
2015. Vol. 9, no 1, 190-207 p.
Boiler, burning material pile, color clustering, quaternion convolution
Computer Science Telecommunications
IdentifiersURN: urn:nbn:se:kth:diva-165233DOI: 10.3837/tiis.2015.01.011ISI: 000351719000011ScopusID: 2-s2.0-84922227652OAI: oai:DiVA.org:kth-165233DiVA: diva2:809737
QC 201505052015-05-052015-04-242015-05-05Bibliographically approved