:The debonding of non-metallic materials can affect their performance, and infrared nondestructive testing can identify adhesive defects effectively. The boundary feature of adhesive defects is first investigated in this study based on infrared non-destructive testing; subsequently, a quantitative analysis method for identifying the boundary position of adhesive defects using the extreme value of a temperature gradient is obtained. Next, the Canny edge detection algorithm is used to identify the defect boundary of an adhesive defect model by numerical simulations and to identify experimental data simultaneously. For problems such as blurred boundaries and noise for recognition results, an improved algorithm for filtering out all "suspected boundaries" to preserve the "weak boundary" is proposed. The results show that the improved Canny algorithm can improve the integrity and accuracy of identifying adhesive defects from infrared non-destructive testing. Key words:infrared nondestructive testing, adhesive defects, recognition algorithm, quantitative analysis of defects 收稿日期:2019-06-14;修订日期:2019-11-12. 作者简介:牛奕(1986-) ,男,博士,主要从事热安全科学机理,安全仿真与模拟的研究工作。E-
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