基于提升小波包和模糊模式识别的结构损伤识别

Damage Identification of Structure Based on Lifting Wavelet Packet and Fuzzy Pattern Recognition

针对网架结构的损伤特点,提出基于提升小波包特征提取的模糊模式识别的结构损伤诊断方法。该方法首先利用提升框架,将结构振动测试信号进行提升小波包分解,提取小波包信号分量能量作为损伤识别的特征向量,以此建立模糊模式识别的模糊子集,最后利用模糊C均值聚类分析与择近原则相结合的模糊模式识别方法对结构进行损伤识别,并研究噪声对该算法的影响。为了证明该方法,对一个二层网架结构模型进行数值仿真,结果表明该方法能够有效地识别损伤。

The damage identification method of truss structure based on lifting wavelet packet analysis and fuzzy pattern recognition is developed according to damage feature of the structure.Firstly,the vibration signal is decomposed using lifting wavelet packet（WP） analysis,and then the corresponding characteristic vector of damage identification is established by the lifting WP component energy,which can be used as the subset of fuzzy pattern recognition.Finally,the damage is detected based on fuzzy C-means clustering and the nearest neighbor algorithm,and the effect of noise on these algorithm is also studied.In order to verify the proposed method,the numerical simulation of a two-story truss structure model is carried out.The results show that the proposed method can be effectively used to identify the damage of structures.