【摘要】 裂缝等损伤在振动时常具有变刚度的时域非线性特征，且损伤前的数据难以获取。针对此问题，通过采集检测结构各位置的加速度时间序列，建立待检测层和基层响应数据的广义自回归条件异方差（generalized autoregressive conditional heteroskedasticity in the mean，简称GARCH-M）模型，分析两模型系数的切比雪夫距离，提出了基于GARCH-M模型和切比雪夫距离的归一化损伤识别组合指标。仿真和实验结果表明：基于上述组合指标，仅利用损伤后的加速度响应数据进行损伤识别，即能够有效识别出非线性损伤层位置；相较于GARCH模型，GARCH-M模型对结构的非线性损伤加速度响应时间序列具有更好的适应性；模型计算过程简单，精度较高，在输电塔等工程结构的非线性损伤识别领域具有较好的工程应用价值。更多还原

【Abstract】 Damages such as cracks often have time-domain nonlinear characteristics of variable stiffness during vibration,and the data before damage is difficult to obtain. In response to the above problems,the acceleration time series of each position of the inspection structure are collected. The generalized autoregressive conditional heteroskedasticity in the mean(GARCH-M)model of the lay response data is established for the inspect and base layers. Furthermore,the Chebyshev distance between the two model coefficients is analyzed,and a combined index of normalized damage recognition based on GARCH-M model and Chebyshev distance is proposed.The simulation and experimental results show that based on the above combined indicators,only the acceleration response data after damage can be used for damage identification,that is,the location of the nonlinear damage layer can be effectively identified. Compared with the GARCH model,the GARCH-M model is nonlinear to the structure,and the damage acceleration response time series has better adaptability. Moreover,the calculation process of the above model is simple and accurate,and it has good engineering application value in the field of nonlinear damage identification of engineering structures such as transmission towers.更多还原