钢筋混凝土梁裂纹故障分析

Crack fault analysis in reinforced concrete beam

应用人工神经网络模型,对钢筋混凝土梁结构上出现的裂纹损伤对于结构固有频率下降率的影响进行了诊断和预测研究,并与传统的诊断和预测结果进行了比较,结果表明采用神经网络技术对工程结构进行裂纹损伤故障的联合诊断和预测比传统诊断结果精确,能够更好地反映结构损伤与特征参数之间的非线性特征.

This paper analyzed the influence of the crack damage fault occurred in reinforced concrete beam on the ratios of inherent frequency drops by applying artificial neural network (ANN), and compared with the traditional method of diagnosis and prediction. It showed that it is feasible to synthetically diagnose and forecast the crack damage fault in structure using artificial neural network, and the results of diagnosis and prediction are more precise than traditional one . It can reflect the nonlinear between the damage fault and parameters better.