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In this paper, in order to achieve automatic defect identification for pneumatic pressure equipment, an improved feature extraction algorithm eddy current pulsed thermography (ECPT) 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 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., reducing the processing time) of the proposed algorithm in automatic defect identification.
Bo Zhang, YuHua Cheng, Chun Yin, Xuegang Huang, Sara Dadras, and Hadi Malek, “Design of an Automatic Defect Identification Method Based ECPT for Pneumatic Pressure Equipment,” Complexity, vol. 2018, Article ID 5423924, 16 pages, 2018. https://doi.org/10.1155/2018/5423924.