基于高效神经网络的框架结构节点损伤的多重分步识别方法

提出了基于神经网络的框架结构节点损伤的多重分步识别方法,建立了用于框架结构节点损伤识别的高效神经网络法。根据节点损伤的多重分步识别思路,把节点损伤识别主要分为四步:第一步利用神经网络建立损伤异常过滤器对节点损伤进行预警;第二步以频率构造的组合指标作为神经网络输入向量,对节点损伤进行初步定位;第三步以归一化的应变模态差绝对值作为神经网络输入向量,对节点损伤进行具体定位;第四步以应变模态差绝对值作为神经网络输入向量,对节点损伤程度进行识别。针对三跨四层的框架结构进行了节点损伤识别数值模拟,结果表明:应用神经网络技术,采用多重分步识别方法,简化了网络的结构,能够有效地对框架结构节点损伤进行预警、定位和定量。

The Multi-stage Damage Identification Approach for Frame Structural Joints Based on me High Efficient Neural Network

The multi-stage damage identification approach for frame structural joints based on the neural network has been raised in this paper. Under the foundation of this approach, a kind of high efficient neural network methods to identify damage in fome structural joints has been established by compiling APDL and MATLAB programs. This approach is divided into four steps. Firstly, damage anomalous filter which is set up by BP neural network has been used to alarm the damage in stucmral joints. Secondly, the primary location ofthejoint damage is determined by the neural network with inputing the combined damage indext. At the third step, the specific location of the member damage is determined by the neural network with inputing the damage indexNSMC. Finally, the damage degree of the joint is determined by the neural network with inputing the damage indexSMC.