【摘要】 提出了基于EMD和VARMA模型的结构损伤识别方法。该方法首先将结构反应信号用EMD方法分解成一系列固有模态函数,然后将固有模态函数表示为时变VARMA模型并用Kalman滤波方法估计时变VARMA参数,最后根据时变VARMA参数定义一个新的损伤指标用于结构损伤识别。为检验该指标的实际性能,算例中选用ImperialCounty Services Building和Van Nuys Hotel作为基准结构。通过其实测地震反应记录的分析表明:该指标在实际的量测环境和噪声条件下具有较好的敏感性和抗噪能力,可有效地识别结构多处损伤的发生过程和严重程度;由于该指标定义在反应信号特征提取的基础上,无需其他额外的信息,它可同时用于结构整体和局部两个层次损伤的识别;同时,该指标还适于实时(在线)的结构损伤识别或健康监测,因其直接由时变VARMA参数推导得出。最后,对后续研究工作进行了展望。更多还原

【Abstract】 Based on EMD and vector autoregressive moving average(VARMA) models,a method for structural damage detection was proposed.By using the time varying VARMA model to represent the intrinsic mode functions(IMFs) obtained from the EMD of structural response signal,the Kalman filter was taken to estimate the VARMA coefficients.Then,a novel damage index derived from the VARMA coefficients was presented to detect structural damages.To investigate the real performance of the damage index,the Imperial County Services Building and Van Nuys Hotel were adopted as the benchmark structures in the examples given.The analysis of the actual response records during earthquake shows that the anti-noise ability and sensitivity of damage index are satisfactory in real environments with the presence of actual noise and it can indicate the occurrence and relative severity of structural damages at multiple locations in an efficient manner.Since the damage index is defined based on the feature extraction of a signal with no additional information required,it can be used to detect both global and local structural damages.Also,the damage index can be potentially used in real time(online) damage detection or structural health monitoring,for it is directly derived from time varying VARMA coefficients.Some recommendations for future research were provided.更多还原