神经网络在Matlab分析复合材料结构高光谱图像中的应用

M. Iskandarani
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引用次数: 4

摘要

提出并讨论了一种基于加权消除算法的神经网络建模的复合材料结构损伤检测方法——高光谱图像指数分析算法。基于矩阵带的技术允许基于序列脉冲热图像之间的相关性来监测和分析组件的结构。该技术产生由帧偏差和像素重分配计算产生的若干矩阵,具有预测能力。结果表明,该方法能够识别损伤构件,并能模拟不同条件下的各种损伤类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Neural Networks to Matlab Analyzed Hyperspectral Images for Characterization of Composite Structures
A novel approach to damage detection in composite structures using hyperspectral image index analysis algorithm with neural network modeling employing Weight Elimination Algorithm (WEA) is presented and discussed. The matrix band based technique allows the monitoring and analysis of a component’s structure based on correlation between sequentially pulsed thermal images. The technique produces several matrices resulting from frame deviation and pixel redistribution calculations with ability for prediction. The obtained results proved the technique to be capable of identifying damaged components with ability to model various types of damage under different conditions.
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