Feature Analysis and Reconstruction Method of Exponential Entropy Multiplicative Fuzzy Defects Based on Infrared Thermal Imaging

Abstract

The invention discloses an exponential entropy multiplicative fuzzy defect feature analysis and reconstruction method based on infrared thermal imaging. Through the reconstruction model and the optimized fuzzy algorithm, the defects of different degrees in different spaces are extracted and characterized, so that different degrees of defects in different spaces can be extracted and analyzed. The defect features can be accurately divided; at the same time, in the optimized fuzzy algorithm, a new objective function is constructed, part of which includes the product of approval and hesitation, which enriches the feature information of the element, and the other part includes exponential fuzzy entropy. The uncertainty of the feature information is described, the correlation of the damage area gain function is enhanced, the features are emphasized, and the defects are effectively distinguished. Such a design and structure have good stability and high efficiency. It plays a prominent role in the description of the characteristic texture of defects and the characterization of characteristic color differences, and can reasonably and accurately evaluate and analyze defects of different degrees in different spaces.

Description

technical field [0001] The invention belongs to the technical field of defect detection, and more particularly relates to an exponential entropy multiplicative fuzzy defect feature analysis and reconstruction method based on infrared thermal imaging. Background technique [0002] In recent years, infrared thermal imaging detection technology has developed rapidly. It does not damage the body, fast and efficient, and can effectively solve the problems of high labor intensity, long cycle, low efficiency, and poor safety in traditional non-destructive testing methods, realize large-scale rapid testing, and save a lot of manpower and material resources. [0003] If there are defects on the surface of the test piece to be tested, it will affect its heat distribution. The test piece to be tested is heated, resulting in a high temperature area and a low temperature area. Due to the difference in temperature, the heat in the high temperature area is transferred to the low temperatu...

AI Technical Summary

Problems solved by technology

However, the traditional FCM algorithm cannot completely express the characteristics of each element, and many useful pixel features will be lost during the processing of defect information in different spaces and in different degrees. In order to solve this kind of problem, the present invention proposes a new objective function, including It not only improves the information of feature elements, but also handles the mutual interference between different degrees of defects.

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