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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51478

Title: Developing a PSO-Based Projection Algorithm for a Porosity Detection System Using X-Ray CT Images of Permeable Concrete
Authors: Yi-Zeng Hsieh
Mu-Chun Su
Jieh-Haur Chen
Bevan Annuerine Badjie
Yu-Min Su
Contributors: 國立臺灣海洋大學:電機工程學系
Keywords: Concrete
Asphalt
Computed tomography
Aggregates
X-ray imaging
Projection algorithms
Image reconstruction
Date: 2018-10
Issue Date: 2018-11-30T07:44:25Z
Publisher: IEEE Access
Abstract: Abstract: Permeable concrete is widely used as a road surfacing material due to its sturdiness and ability to be quickly repaired. The porosity of concrete has been used as a predictive indicator for the properties of the concrete. Traditional methods for measuring this porosity are feasible but can be time consuming. In this paper, we propose a Particle Swarm Optimization (PSO) based projection algorithm for visualization of the high-dimensional data as a two-dimensional scatter plot for detecting porosity in permeable concrete from Xray Computerized Tomography (CT) images. We regard the proposed projection algorithm as an improved version of Sammon’s nonlinear mapping. The projected scatter plot allows for straightforward analysis of the inherent structure of clusters within scanned images. Several data sets including artificial data sets and reallife imaging data were tested to demonstrate the performance of the proposed projection algorithm. The model created in this study can augment the traditional methods for examining porosity by providing visual images for decision makers to make correct decisions for future problems. With an accuracy of > 99%, the visualized images provide a clearer understanding of the inner structure of pervious concrete and enhance the study of the correlation between the properties of the concrete.
Relation: 6 pp.64406 - 64415
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51478
Appears in Collections:[電機工程學系] 期刊論文

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