基于BP网络的结构损伤识别

Identification of Structure Damage Based on BP Neural Network

结构的动力特性和结构参数直接相关 ,结构的损伤将引起相应动力特性的改变 ,因此 ,如果能建立结构动力特性变化与结构损伤之间的映射关系 ,则可以利用结构振动测试信息实现结构损伤诊断。神经网络方法因其具有非线性映射能力强、计算速度快、容错性好等优点 ,正越来越多的用于基于振动的结构损伤识别 ,但是对于大型复杂结构 ,普遍存在网络结构复杂 ,识别效率低下的问题。以框架结构为例 ,应用 BP网络分阶段的进行损伤位置、损伤程度的识别 ,这有效降低了网络的复杂性 ,减少了学习样本 。

The dynamic characteristic of structures has a direct relationship with structural parameters and structural damage will cause dynamic characteristics shifts correspondently. Therefore, if the mapping relationship between structural damage and dynamic characteristic shifts can be established, the damage can be diagnosed using dynamic measurements of the structures. With the merits of its strong non-linear mapping ability, rapid computation and anti-interference capability, artificial neural network (ANN) is becoming more popularly used in the identification of structure damage based on vibration. However for large-scale complicated structure, there is a general problem as the network structure is complicated and identification efficiency is low. Frame structure is used as an example and using BP Neural network gradually identifies the damage location and damage degree. The results showed that this method can reduce the complexity of the network and improve learning efficiency effectively.