Journal Published Online: 15 July 2020
Volume 49, Issue 1

Enhancement of Defect Detectability in Pneumatic Pressure Equipment Using an Automatic Detection Technique in ECPT

CODEN: JTEVAB

Abstract

Pneumatic pressure equipment is an important component of wind tunnel test systems, which have been extensively applied in most modern industries. To guarantee the reliability and safety of pneumatic pressure equipment, a regular inspection is needed. To improve the inspections process, automating the process of identifying defects continues to receive attention in the research community. In this paper, in order to achieve automatic defect identification, an improved feature extraction algorithm in eddy current pulsed thermography is presented. The presented feature extraction algorithm contains four elements: data block selection, variable step search, relation value classification, and between-class distance decision function. The data block selection and variable step search are integrated to decrease the redundant computations in the automatic defect identification. The goal of the classification and between-class distance calculation is to select the typical features of a thermographic sequence. The main image information can be extracted by the method precisely and efficiently. Experimental results are provided to demonstrate the capabilities and benefits (i.e., increased precision, reduced processing time) of the proposed algorithm in automatic defect identification.

Author Information

Zhang, Bo
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, P. R. China
Cheng, YuHua
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, P. R. China
Yin, Chun
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, P. R. China
Huang, Xuegang
China Aerodynamics Research & Development Center, Hypervelocity Aerodynamics Institute, Mianyang, P. R. China
Dadras, Sara
Department of Electrical and Computer Engineering, Utah State University, Logan, UT, USA
Chen, Kai
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, P. R. China
Malek, Hadi
Department of Electrical and Computer Engineering, Utah State University, Logan, UT, USA
Pages: 21
Price: $25.00
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Stock #: JTE20180724
ISSN: 0090-3973
DOI: 10.1520/JTE20180724