中文摘要：

针对实测模态频率的随机性,提出了基于概率统计理论的桥梁结构模态频率异常变化的检测方法。建立桥梁实测模态频率与结构温度的BP神经网络模型,进而消除温度对模态频率的影响,在此基础上采用核密度估计方法得到消除温度影响模态频率的累积分布函数,然后采用标准正态分布的逆函数将累积分布函数转换为Q统计量,最后利用Q统计量建立用于频率异常检测的均值控制图。假设检验结果表明：Q统计量服从正态分布,从而解决了消除温度影响后的模态频率仍非正态的问题,满足了控制图对随机变量正态性的要求。分析结果表明,基于控制图的概率检测方法对桥梁模态频率的异常数据具有良好的敏感性。该方法可为大跨度桥梁健康监测数据的分析与应用提供参考。

英文摘要：

Due to the randomness within the measured modal frequencies,the present study develops the probabilistic detection method for abnormal change of bridge structures′modal frequencies based on the theories of probability and statistics.The BPNN-based correlation models between modal frequencies and structural temperature are established,so as to eliminate the temperature effects in modal frequencies.Then the cumulative distribution functions of the modal frequencies after temperature effect eliminating are estimated using Kernel density estimation method.The estimated cumulative distribution functions are converted to Q statistics based on the inverse function of standard normal distribution.At last the mean value control charts of Q statistics are constructed to detect the abnormal change of modal frequencies.The hypothesis testing results show that Q statistics follow Gaussian distributions.Accordingly,the non-normality of modal frequencies with temperature effect elimination is handled to meet the requirement of random variables′normality in control charts.The results reveal that the probabilistic detection method of control chart have good sensitivity to the abnormal data of bridge′s modal frequencies.The proposed method can provide a reference for the analysis and application of health monitoring data of long-span bridges.