基于支持向量机的张弦梁损伤识别试验  

Damage Detection Experiment on Beam String Structure Using Support Vector Machine

作　　者：何浩祥[1] 闫维明[1] 张爱林[1] 王卓[1] 

机构地区：[1]北京工业大学工程抗震与结构诊治北京市重点实验室,北京100124

出　　处：《振动．测试与诊断》2011年第1期45-49,128,共5页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(编号:50878010;50978009);北京市自然科学基金重点资助项目(编号:8041002)

摘　　要：对单榀张弦梁的索力损失和腹杆损伤进行了试验研究。对拉索加载不同程度的预应力来模拟索的预应力损失,利用环境脉动和冲击激励,通过采用Fourier变换或小波变换求得索的频率来计算施加在索上的预应力值。试验结果表明,该方法可以有效地监测索预应力。对张弦梁的上部腹杆进行了环境脉动下的损伤试验,对不同的杆件沿径向进行相应程度的截面切割用以模拟不同程度的损伤状态。对加速度样本进行小波包分解得到特征向量,利用支持向量机对特征向量进行损伤分类,验证了支持向量机方法用于损失识别的有效性。当支持向量机和主成分分析结合后,试验的损伤识别效果有明显的提高。The cable prestressing loss and web members damage experiment of a beam string structure was carried out.Different prestressing forces were exerted on the cable to simulate cable prestressing loss,the prestressing forces were calculated by the frequencies which were solved by Fourier transform or wavelet transform under impulse excitation.Test results show this method is accurate and convenient.The damage cases of web members on the beam were tested to validate the efficiency of wavelet support vector machine method.Wavelet packet decomposition was applied to the structural response signals under ambient vibration,feature vectors were obtained by feature extraction method with 'energy-damage state'.The feature vectors were used for training and classification as the inputs of the compact support vector machine.The structural damage position and degree can be identified and classified,and the test result is highly accurate especially combined with principle component analysis.

关 键 词：小波包 支持向量机 损伤识别 张弦梁 主成分分析 

分 类 号：P315[天文地球—地震学] TU352[天文地球—固体地球物理学]