基于数据融合和“能量-损伤”的结构多损伤模式识别

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振动与冲击 ›› 2010, Vol. 29 ›› Issue (8) : 120-123.

论文

基于数据融合和“能量-损伤”的结构多损伤模式识别

焦莉1,2;李宏男2;张海1,2;伊廷华2

作者信息 +

Structural Multi-Damage Pattern Recognition Based on Data Fusion and Energy-Damage

JIAO Li1,2;LI Hong-nan2;ZHANG hai1,2;YI Ting-hua2

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摘要

基于一致性数据融合算法和“能量-损伤”结构特征提取原理，提出一种结构多损伤模式识别方法，能够充分利用结构不同位置的不同状态信息，更好地对结构损伤做出判断。对一致性数据融合算法进行改进，使得改进后的算法能够克服一致性算法中两传感器在测量精度不同时置信距离不同的缺点，并对支持矩阵进行模糊化处理，避免人为定义阈值而产生的主观误差。利用“能量-损伤”特征提取技术，构造融合后多传感器测量数据的特征向量，以ART2神经网络作为模式识别工具进行结构多损伤识别。五层框架结构数值计算结果表明，本文提出的方法能够用于结构多损伤识别，且具有较强的鲁棒性、稳定性和适应性。

Abstract

A structural multi-damage identification method is presented based on consensus data fusion, eigenvalue extraction by energy-damage and the powerful pattern recognition function of ART2. The method can make full use of more structural status information in different site and recognize structural damage better. The traditional consensus data fusion algorithm is improved. The improved algorithm can overcomes the shortcoming of the traditional consensus algorithm with two sensors, which has different confidence distance for different measuring precision. And the supporting matrix is fuzzified, which can avoid the subjective error in determining the threshold value. Eigenvector of multi-sensor measured data after fusion are constructed using eigenvalue extraction technology of energy-damage. ART2 network is adopted as the pattern recognition to identify structural multi-damage. The numerical simulation results of a five-layer frame structure show that this method can identify structural multi-damage and it is more robust, stable and adaptive.

导出引用

焦莉;李宏男;张海;伊廷华. 基于数据融合和“能量-损伤”的结构多损伤模式识别[J]. 振动与冲击, 2010, 29(8): 120-123

JIAO Li;LI Hong-nan;ZHANG hai;YI Ting-hua. Structural Multi-Damage Pattern Recognition Based on Data Fusion and Energy-Damage[J]. Journal of Vibration and Shock, 2010, 29(8): 120-123

中图分类号： TU12 TU317.9