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Local sensitivity discriminant analysis method for defect thermal image of composite material

A locally sensitive, discriminant analysis technology, applied in image analysis, image data processing, computer components and other directions, can solve the problems of spatial information without noise, unable to deal with the non-uniform background of thermal images, etc.

Pending Publication Date: 2021-03-12
ZHEJIANG UNIV OF TECH
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

However, TSR only performs data filtering along the time direction, while spatial information is not used for noise reduction, nor can it handle the non-uniform background usually present in thermal images.

Method used

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  • Local sensitivity discriminant analysis method for defect thermal image of composite material
  • Local sensitivity discriminant analysis method for defect thermal image of composite material
  • Local sensitivity discriminant analysis method for defect thermal image of composite material

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0075] 1) Acquire defect thermal imaging sequence set:

[0076] Three defects with different positions, depths and shapes were implanted in CFRP specimens. The trapezoidal defect is located in the lower right area. Of all three flaws, this one is the shallowest and is under a layer of carbon fiber sheeting. In the middle part of the specimen, there is a circular defect covered by two layers of fibreboard. The deepest defect is located in the upper left corner, it has a diamond shape and is covered by three layers of fiberboard. The area of ​​each defect area is approximately 3 square centimeters.

[0077] For non-destructive testing of defects, we use 3000W ultrasonic pulses as energy and heat pulses to heat the test object. The duration of the heat pulse is approximately 3 milliseconds. Images related to surface temperature were captured in reflectance mode by an infrared camera (TAS-G100EXD, NEC). The resolution of the camera is 320×240 pixels, and the sampling rate is...

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Abstract

The invention discloses a local sensitivity discriminant analysis method for a defect thermal image of a composite material. The method comprises the following steps: 1) acquiring a defect thermal imaging sequence set; 2) setting initial parameters and calculating a nearest neighbor distance; 3) constructing a nearest neighborhood graph to obtain a weight matrix; 4) calculating a Laplace operatorto construct an optimal target function; 5) decomposing the eigenvalue to obtain low-dimensional embedding; and 6) defect image reconstruction and evaluation. According to the method, the features areextracted from the simulation data, the local sensitivity discrimination model of the defect thermal image of the composite material is established, the training model is evaluated, the LSDT method better processes the information, uneven backgrounds, defect features and measurement noise can be separated to a large extent, and therefore defect recognition is better facilitated.

Description

technical field [0001] The invention belongs to the technical field of composite material defect non-destructive detection, and in particular relates to a local sensitivity discrimination model method of composite material infrared thermal imaging. Background technique [0002] Composite materials have the characteristics of high specific strength, high specific modulus, high temperature resistance, corrosion resistance, and fatigue resistance, so they are widely used in important industrial fields such as aerospace and ships. Although composite materials have many advantages, due to the existence of internal defects in composite materials, the quality of products and the reliability and safety of composite material applications will be seriously reduced. [0003] All kinds of defects can lead to the degradation of various aspects of composite materials, and then affect the final performance of components. A typical example is that fiber breakage in carbon fiber composites ...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0008G06F18/2132G06F18/24147Y02P90/30
Inventor 刘凯新娄维尧杨克允马正阳蔡姚杰
Owner ZHEJIANG UNIV OF TECH
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