Infrared technology defect reconstruction and feature extraction method based on additive fuzzy

Abstract

The invention discloses an infrared technology defect reconstruction and feature extraction method based on additive fuzziness, and the method comprises the steps of building a multi-region defect reconstruction model through an infrared thermal image sequence of a test piece to be detected, and reconstructing the defects in different space regions through variational Bayes inference. In the collected data, the signals representing internal defects are weak, and the noise may be introduced by the parameter hypothesis during a defect reconstruction process, so that we need to highlight the internal defect information, and remove the noise interference, and accordingly the color features and the contour features of the images are extracted through a color extraction filter and an edge contour extraction filter, then by carrying out optimization processing on the defect color image, and finally fusing the optimized color image and contour features through inverse transformation, the defects of different space-time regions can be described clearly.

Description

technical field [0001] The invention belongs to the technical field of defect detection, and more specifically relates to a defect reconstruction and feature extraction method based on additive fuzzy infrared technology. Background technique [0002] Infrared thermal imaging technology has been widely used in the automotive industry, shipbuilding industry, petrochemical industry and aerospace fields. Due to its features such as no need to directly contact the test piece to be tested, fast and efficient detection, and portability, it can effectively realize the nondestructive detection of damage. [0003] Infrared technology can be roughly divided into two categories, namely active heating and passive heating. For active heating, energy or heat is required to be artificially given to the test piece to be tested. According to the differences in heating methods, active heating can be divided into: optical excitation, electromagnetic excitation and mechanical excitation. Opti...

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Problems solved by technology

[0006] Secondly, the traditional defect method is mainly aimed at the defect characteristics of different regions in the same space, so the damage information in different spaces will be ignored, which will make a wrong judgment on the defect type of the material. In order to judge the defect situation of the material more accurately, The invention proposes an effective detection method, which can not only judge the damage of the surface space of the material to be detected, remove noise interference, but more importantly, obtain the damage situation of the inner space more accurately

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