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Sensors 2017, 17(11), 2440; https://doi.org/10.3390/s17112440

Defect Detection of Adhesive Layer of Thermal Insulation Materials Based on Improved Particle Swarm Optimization of ECT

1
School of Science and Technology, Yanshan University, Qinhuangdao 066004, China
2
School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
*
Author to whom correspondence should be addressed.
Received: 1 September 2017 / Revised: 10 October 2017 / Accepted: 20 October 2017 / Published: 25 October 2017
(This article belongs to the Special Issue Intelligent Sensing Technologies for Nondestructive Evaluation)
View Full-Text   |   Download PDF [5920 KB, uploaded 25 October 2017]   |  

Abstract

This paper studies the defect detection problem of adhesive layer of thermal insulation materials. A novel detection method based on an improved particle swarm optimization (PSO) algorithm of Electrical Capacitance Tomography (ECT) is presented. Firstly, a least squares support vector machine is applied for data processing of measured capacitance values. Then, the improved PSO algorithm is proposed and applied for image reconstruction. Finally, some experiments are provided to verify the effectiveness of the proposed method in defect detection for adhesive layer of thermal insulation materials. The performance comparisons demonstrate that the proposed method has higher precision by comparing with traditional ECT algorithms. View Full-Text
Keywords: thermal insulation material; electrical capacitance tomography; defect detection; image reconstruction; PSO thermal insulation material; electrical capacitance tomography; defect detection; image reconstruction; PSO
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Wen, Y.; Jia, Y.; Zhang, Y.; Luo, X.; Wang, H. Defect Detection of Adhesive Layer of Thermal Insulation Materials Based on Improved Particle Swarm Optimization of ECT. Sensors 2017, 17, 2440.

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