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。 The static displacement curvature confidence factor used for damage identification is combined with artificial neural network technology to establish a gray network system for structural damage identification. The system is used to identify and analyze the damage location and degree of the cantilever structure. It can be seen that this method is very effective for the structural damage identification. The proposed method not only has the advantages of simple static displacement curvature confidence factor calculation, Higher advantage, but also has a high degree of parallel neural network computing power and good fault tolerance.