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首页> 外文会议>International Conference on Electronic and Mechanical Engineering and Information Technology >Monitoring of a Frame Structure Model for Damage Identification using Artificial Neural Networks
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Monitoring of a Frame Structure Model for Damage Identification using Artificial Neural Networks

机译：用人工神经网络监测造型造型模型

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摘要

A structural parameter identification and damage detection approach using displacement measurement time series is proposed, and the performance of the approach is validated experimentally with a frame structure model in a healthy condition and with joint connection damages. The proposed approach is carried out using two neural networks: one is called time-delay neural network (TDNN) and the other is called traditional neural network (TNN). The theoretical basis and the selection of the input and output of the TDNN and the TNN are explained. The performance of the proposed methodology for damage detection of the frame structure model with different joint damage scenarios is introduced by direct use of displacement measurement under base excitations. A simulation study has been carried out for the incomplete measurement data. The proposed approach provides an alternative way for damage detection of engineering structures by direct use of structural dynamic displacement measurements.
机译：提出了使用位移测量时间序列的结构参数识别和损伤检测方法，并在经过健康状态和联合连接损伤的框架结构模型实验验证该方法的性能。所提出的方法是使用两个神经网络进行的：一个被称为时延神经网络（TDNN），另一个被称为传统的神经网络（TNN）。解释了TDNN和TNN的理论基础和选择的选择和输出。通过在基础激发下直接使用位移测量来引入具有不同关节损伤情景的框架结构模型的帧结构模型的损伤方法的性能。对不完全测量数据进行了模拟研究。该方法通过直接使用结构动态位移测量，提供了一种替代方法，用于通过直接使用结构动态位移测量来损坏工程结构。

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