桁架
希尔伯特-黄变换
人工神经网络
计算机科学
振动
节点(物理)
结构工程
特征(语言学)
模式(计算机接口)
算法
模式识别(心理学)
人工智能
工程类
声学
哲学
物理
操作系统
滤波器(信号处理)
语言学
计算机视觉
作者
Menghong Wang,Huan Lu,Peiru Deng
标识
DOI:10.1088/1755-1315/267/3/032040
摘要
Abstract In this paper, a method was proposed for damage detection of truss structures under natural excitation based on the combination of radial-basis function neural network and empirical mode decomposition (EMD). Firstly, EMD method was applied to decomposing the vibration response data of the rod end node into a series of IMFs (Intrinsic Mode Functions). For the structure’s original response data, after using the EMD to decompose it, the damage information and other useful contents will be distributed into various IMFs. Using neural network’s excellent feature of linear mapping, IMFs are put as an input into the neural network, and the output was compared with the ideal output, which reveals the damage status of the structure. In this paper, experimental analysis and numerical simulation were used to detect the damage conditions of single-damage condition and two different rods in the same truss structure. Good recognition results were obtained.
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