Detection of deterioration of furnace walls using large-scale point-clouds. Issue 4 (4th July 2018)

• Record Type: Journal Article
• Authors: Shinozaki, Yuki; Kohira, Keisuke; Masuda, Hiroshi
• Is Part Of: Computer-aided design and applications. Volume 15:Issue 4(2018)
• Page Start: 575
• Page End: 584
• Publication Date: 2018-07-04
• Subjects: Point-Cloud -- Deterioration Diagnosis -- Terrestrial Laser Scanner; Computer-aided design -- Congresses; Computer-aided design -- Periodicals; Engineering design -- Data processing -- Congresses; Engineering design -- Periodicals; 620.00420285
• DOI: 10.1080/16864360.2017.1419645
• Languages: English
• ISSNs: 1686-4360

Abstract

ABSTRACT: Blast furnaces are large industrial structures to produce iron. Since scaffolding and wearing of furnace walls are caused in their long lifecycle, furnaces have to be repeatedly inspected and renovated. In this paper, we discuss methods for detecting scaffolding and wearing on furnace walls using point-clouds. We detect scaffolding and wearing as differences between the original wall surface and measured points. However, it is not easy to estimate wall shapes with no scaffolding and wearing, because most blast furnaces were not precisely built as designed in drawings. Therefore, we introduce three different methods for estimating the original wall surfaces, and verify whether these methods can appropriately detect scaffolding and wearing regions from point-clouds. GRAPHICAL ABSTRACT: