中文摘要：

为了有效地进行大跨结构的损伤识别，提出随机车载作用下利用BP-AdaBoost(BackPropagationneuralnetwork，AdaptiveBoosting)模型对大跨斜拉桥拉索进行损伤识别的方法。该方法首先依据交通调查数据，建立随机交通荷载模型，再运用提升框架，对结构损伤前后的振动测试信号进行提升小波包分解，将小波包信号分量能量累积变异值作为特征值，识别斜拉索损伤位置，然后以此建立BP-AdaBoost模型，利用AdaBoost算法和BP神经网络相结合的方法对大跨斜拉桥拉索的损伤程度进行识别，并研究噪声对该算法的影响。数值分析结果表明，该方法有较强的抗噪声干扰能力，在随机车载作用下，运用BP-AdaBoost模型能够有效识别大跨斜拉桥拉索损伤。

英文摘要：

The cable damage identification method of long-span cable-stayed bridges is proposed using BP-AdaBoost(Back Propagation neural network,Adaptive Boosting)model under random vehicle’s load.Firstly,the random traffic loadmodel is established according to the traffic survey data,and the vibration signal is decomposed using lifting wavelet packet(WP)analysis based on lifting scheme.Then,the corresponding characteristic vector is constructed by the energyaccumulating variation value of the lifting WP component energy.And this vector is used to identify the damage locationof cables of the cable-stayed bridge.Finally,the BP-AdaBoost model is established.Combining AdaBoost algorithm with BPneural network,the damage degree of the cable of the long-span cable-stayed bridge can be identified.The effect of noise onthe algorithm is studied.The numerical results show that the proposed method can be used to effectively identify the cabledamage of long-span cable-stayed bridges under random vehicle’s load.