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Composite material defect depth prediction method

A depth prediction and defect technology, applied in image data processing, instruments, calculations, etc., to achieve the effect of high prediction accuracy and simple method

Pending Publication Date: 2020-03-13
四川沐迪圣科技有限公司
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Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method for predicting the depth of defects in composite materials. By extracting defect thermal contrast characteristic time and combining Gaussian transformation, the nonlinear relationship between characteristic time and defect depth is mapped by Gaussian transformation Linear relationship, so as to achieve accurate estimation of defect depth

Method used

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  • Composite material defect depth prediction method
  • Composite material defect depth prediction method

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Embodiment

[0033] figure 1 It is a flow chart of a method for predicting the depth of composite material defects in the present invention.

[0034] In this example, if figure 1 Shown, the present invention a kind of depth prediction method of composite material defect, comprises the following steps:

[0035] S1. Image acquisition

[0036] Thermally load the test piece with a halogen lamp, and collect the infrared thermal image sequence of the test piece;

[0037] S2, image preprocessing

[0038] Use the matrix sparse decomposition algorithm to conduct qualitative defect analysis on infrared thermal image sequences, so as to determine all defect areas;

[0039] In this embodiment, for the obtained defect-containing infrared thermal image sequence, in order to reduce the number of thermal image frames and improve the accuracy of defect detection, preprocessing is performed by commonly used feature extraction algorithms, such as principal component analysis (PCA), independent Component...

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Abstract

The invention discloses a depth prediction method for defects of a composite material. The method comprises the steps of carrying out qualitative analysis based on a sparse matrix decomposition algorithm; utilizing Gaussian Transform, extracting the thermal contrast temperature curves of the defect area and the non-defect area, and through taking the peak time of the thermal contrast curve as thecharacteristic time of different depths, remapping the nonlinear relationship between the theoretically characteristic time and the defect depth into the linear relationship, so that the defect depthis accurately predicted, and the method has the characteristics of simplicity, convenience, high prediction precision and the like.

Description

technical field [0001] The invention belongs to the technical field of non-destructive testing, and more specifically relates to a method for predicting the depth of defects in composite materials. Background technique [0002] Non-destructive testing is an applied technical discipline based on modern science and technology. On the premise of not destroying the internal structure of the object to be tested, it uses physical methods to detect the physical properties, state characteristics and internal structure of the object inside or on the surface. Whether there are defects inside, so as to judge whether the tested part is qualified. The detection of defects is mainly divided into qualitative analysis and quantitative analysis. Qualitative analysis is used to determine whether the tested part contains defects, while quantitative analysis determines the size and depth of defects. [0003] Carbon fiber composite materials have the advantages of low density, high strength, hi...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/543
CPCG06T7/0004G06T7/543G06T2207/10048Y02P90/30
Inventor 高斌汪美伶
Owner 四川沐迪圣科技有限公司
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