波信号的解调和人工神经网络的损伤识别算法

S. Saravanan; F. Ju; N.Q. Guo

波信号的解调和人工神经网络的损伤识别算法

1.
School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore
2.
School of Engineering, Monash University, Bandar Sunway 46150, Selangor, Malaysia

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中图分类号: TG115.28
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- 刊出日期: 2010-08-09

Wave Signal Demodulation and Artificial Neural Networks for Damage Identification

摘要

摘要: 讨论了基于波信号的解调和人工神经网络的损伤识别算法, 以及其在Lamb波信号的应用。Lamb波与损伤相互作用, 将修改回波信号, 从该信息提取相关的损害信息可用于自动损伤检测。然而, 由于该波与损害相互作用的复杂性, 波信号的反应是不容易解释。反应的波信号被认为是一个高频率载波信号调制的低频信号。基线减法后, 频域卷积和滤波, 原来的信号解调成一个新的简单的信号, 其与因损伤发生的能量变化有关。随后进行特征提取, 通过寻找新信号的局部极大值和所取得的峰值和位置将作为人工神经网络的损伤特性的输入。这种损伤检测验证算法的有效性, 通过一个带缺口复合材料层压板缺损模型利用有限元进行验证。对不同缺口深度和位置的反应波信号用于模拟和训练和测试的样本。最后, 对网络的精度和泛化能力进行评估, 结果是令人满意的。
- 兰姆波 /
- 损伤探测 /
- 解调 /
- 神经网络
Abstract: This presentation will discuss the Lamb wave-based damage detection using wave signal demodulation and artificial neural networks. The interaction between Lamb wave and damage will modify the response wave signal from which information related to damage can be extracted for automated damage detection. However, the interpretation of the response wave signal is not easy due to the complex nature of the wave-damage interaction. This paper discusses a damage detection algorithm based on wave signal demodulation and artificial neural networks(ANNs). The response wave signal is considered as a low-frequency signal modulated by a high-frequency carrier signal. After baseline subtraction, frequency domain convolution and filtering, the original signal is demodulated and transformed into a new simplified signal related to the energy change due to damage. Subsequently feature extraction is carried out by finding the local maxima in the new signal and the obtained peak values and locations are used as inputs into the ANNs for damage characterization. The validity of this damage detection algorithm is then verified using a finite element(FE) model of a composite laminate with notch defects. The response wave signals of different notch depths and locations are acquired from the simulations and used as the training and testing samples. Finally the assessment of the networks accuracy and generalization ability is performed and the result is satisfactory.
- Lamb Wave /
- Damage Detection /
- Demodulation /
- Neural Networks

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参考文献(15)

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波信号的解调和人工神经网络的损伤识别算法

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出版历程

Wave Signal Demodulation and Artificial Neural Networks for Damage Identification

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出版历程

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