基于灰色网络的结构损伤识别研究

RESEARCH ON STRUCTURAL DAMAGE IDENTIFICATION USING GREY NETWORK

将用于损伤识别的静态位移曲率置信因子与人工神经网络技术相结合,建立了结构损伤识别的灰色网络系统。利用该系统对悬臂梁结构损伤位置和程度进行了识别分析和判断,可以看出,利用此方法对结构的损伤识别是非常有效的,且该方法不仅具有静态位移曲率置信因子计算简单、准确度高等优点,而且还具有神经网络高度并行运算能力和良好的的容错性。

Combining the static displacement curvature assurance coefficient used for damage identification with artificial neural network technology, the system of structural damage identification based on the grey network was set up. Using the system to judge the location and extent of structural damage on cantilever beam, it can be seen that this method is very effective, and the calculation on the static displacement curvature assurance coefficient is simple, the accuracy is high , and it also has a highly parallel computing power and good fault tolerance.