Infrared thermal image defect feature recognition method based on dynamic multi-objective optimization

A multi-objective optimization and feature recognition technology, applied in image analysis, image data processing, character and pattern recognition, etc., can solve problems such as high time consumption and slow response

Active Publication Date: 2019-05-17
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

Under ideal conditions without considering environmental factors, representative temperature points that can fully characterize each category of information are

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  • Infrared thermal image defect feature recognition method based on dynamic multi-objective optimization
  • Infrared thermal image defect feature recognition method based on dynamic multi-objective optimization
  • Infrared thermal image defect feature recognition method based on dynamic multi-objective optimization

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[0171] In this embodiment, there are two kinds of defects on the test piece, namely defect 1 not filled with any material and defect 2 filled with material with poor thermal conductivity.

[0172] In this embodiment, the results of classifying the selected transient thermal responses using fuzzy C-means clustering are shown in figure 2 shown.

[0173] In the thermal image sequence of the specimen, three known temperature points are directly identified, namely, the transient thermal response curves of the temperature point of the material itself, the temperature point of defect 1, and the temperature point of defect 2, respectively denoted as Bac POINT, Def1 POINT and Def2 POINT, such as image 3 , 4 , 5 shown.

[0174] Using the existing method of selecting transient thermal response representatives based on differences, three transient thermal response representatives are obtained: A NFCM 23 , B NFCM 68 as well as c NFCM 79 , they respectively correspond to the te...

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Abstract

The invention discloses an infrared thermal image defect feature recognition method based on dynamic multi-objective optimization. The transient thermal response of a pixel point is selected by changing the step length of a thermal image sequence; FCM is used for classification. obtaining the category of the transient thermal response of each pixel point; the pixel value similarity of each type ofpixel points and the same type of pixel points is considered; the difference with different types of pixel points is realized; constructing a corresponding multi-objective function; meanwhile, afterthe environment is changed each time; Prediction mechanism, a guiding direction is provided for population evolution; a multi-objective optimization algorithm is helped to quickly respond to the new change; The method has the advantages that the dimension reduction result of the thermal image sequence is acquired by the aid of the feature extraction algorithm, the defect features of the infrared thermal image are extracted by the aid of the pulse coupling neural network, accordingly, accurate selection of transient heat representations (temperature points) can be realized, the accuracy of defect feature extraction can be guaranteed, and computing consumption of the transient heat representations for acquiring various types of information in dynamic environments can be reduced.

Description

technical field [0001] The invention belongs to the technical field of defect detection, and more specifically relates to a defect feature recognition method of an infrared thermal image based on dynamic multi-objective optimization. Background technique [0002] Infrared thermal image detection technology obtains structural information on and below the surface of the material by controlling the thermal excitation method and measuring the temperature field change on the surface of the material, so as to achieve the purpose of detection. When acquiring structural information, infrared thermal imaging cameras are often used to record the temperature field information of the surface or subsurface of the specimen over time, and convert it into a sequence of thermal images for presentation. Due to the huge amount of data and strong noise interference of the thermal image sequence obtained by the infrared thermal imager, in order to obtain better detection results, it is necessary...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62G06N3/04G06N3/00
Inventor 殷春薛婷程玉华黄雪刚张昊楠石安华陈凯
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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