采用组合参数的神经网络结构损伤检测分析研究

提出由结构前几阶固有频率变化率、频率变化比值和动柔度置信因子构成的组合参数作为神经网络的输入向量的方法进行结构损伤检测,全面分析了不同参数作为神经网络输入向量的损伤效果,利用数值模拟对悬臂梁、桁架结构进行分析,采用不同的输入参数进行比较·　分析结果表明,采用组合参数训练的神经网络,对结构损伤位置和程度识别较采用单一参数具有更好的识别效果·

Analyses on Structural Damage Identification Based on Combined Parameters

The relative sensitivities of structural dynamical parameters were analyzed using a directive derivation method. The neural network is able to approximate arbitrary non-linear mapping relationship,so it is a powerful damage identification tool for undnown systems.A neural network-based approach was presented for the structural damage detection. The combined parameters were presented as the input vector of the neural network, which computed with the change rates of the several former natural frequencies (C), the change ratios of the frequencies (R), and the assurance criterions of flexibilities (A). Some numerical simulation examples, such as, cantilever and truss with different damage extends and different damage locations were analyzed.The results indicate that the combined parameters are more suitable for the input patterns of neural networks than the other parameters alone.