Method for automatic identification and detection of defect in composite material

Abstract

The invention relates to a method for automatic identification and detection of defects in a composite material. The method comprises steps of: detecting the composite material to generate an infrared image by using infrared thermal wave nondestructive testing equipment; conducting phase space reconstruction on the infrared sequence image to determine defect position of the composite material and segment defect area of the image; conducting phase space reconstruction on the infrared sequence image with defect area and carrying out singular value decomposition to obtain a singular matrix, and left and right projection matrixes; carrying out matrix reconstruction again on the two projection matrixes; extracting algebraic characteristics of time information and space information of the defect through singular value decomposition; constructing mixing characteristic vector as characteristic symptom of the defect; and utilizing results from a nerve network classifier to complete the identification and classification determination. The method of the invention can realize automatic identification and detection on defect in the composite material, carry out rapid detection on damage type of the composite material and provide rapid detection means according to usage condition of the composite material, and has critical reality meaning and research value.

Description

technical field [0001] The invention relates to an infrared thermal wave non-destructive testing technology, in particular to a method for automatic identification and detection of internal defect types of composite materials. Background technique [0002] Infrared thermal wave non-destructive testing technology is an emerging discipline, its principle is to heat the test piece to be tested through a heat source, and use an infrared thermal imager to collect real-time image signals of the surface temperature of the test piece. During the heat conduction process, when there are defects such as fractures, pores, and delamination inside the specimen, the heat conduction performance of the material will change, and the surface temperature of the specimen will be unevenly distributed. By processing the collected temperature signal, the internal defect information of the test piece can be judged. Infrared thermal wave non-destructive testing has the advantages of non-contact meas...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is aimed at the shortcomings of the existing technology for detecting internal defects of composite materials, such as the need to establish a complete material heat transfer model and measure a large number of material physical parameters, and the relatively large limitations in actual engineering applications. It provides a method for automatic identification and detection of internal defect types in composite materials that does not require the establishment of physical models to quickly analyze defect information in infrared sequence images

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