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Development of an intelligent structural testing system utilizing neural networks

利用神经网络开发智能结构测试系统

基本信息

批准号：
07555467
负责人：
OHI Kenichi
金额：
$ 1.28万
依托单位：
University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (A)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1996
项目状态：
已结题

项目摘要

The on-line or pseudo dynamic test has been considered as a powerful tool for the earthquake simulation of building. The method computes the displacements of the structural system based on the dynamic analysis and drives the actuators with that response to measure the restoring force directly from the test specimen. This criteria is perfectly applied to middle or high rise buildings with concrete stiff slabs or shear wall panels. In such a case the masses of the system are concentrated at the floor levels and the displacement of the elements are considered as a function of the mass associated lateral displacement. But in the case of steel frames composed of flexible beam-columns unbalanced forces appear in the non mass assosiated degree of freedom, and the representation of displacements as function of the lateral ones is not valid. In the present report a general scheme for on-line hybrid substructuring simulation is presented, to achieve the deformed position of testing steel beam-column. This scheme uses a predictor of the incremental forces on the specimen. Four predictors are presented, the elastic beam element predictor, the two component bilinear beam element predictor, the artificial neural network predictor, and the multi-spring inelastic beam-column element predictor. A brief description of the applicability of the scheme in the hybrid analysis is presented. Also the transformations required to reach the general deformed configuration are shown. Three series tests are presented to evaluate the different predictors and the applicability of the scheme, tests under controlled rotation and varying or constant axial load are described. From the report is conclude : the neural netwark predictor is applied successfully in the removal scheme of the unbalance moment, which is reduced to a negligible level.

在线或拟动力测试被认为是建筑物地震模拟的有力工具。该方法根据动态分析计算结构系统的位移，并根据该响应驱动执行器，直接测量测试样本的恢复力。该标准完全适用于采用混凝土刚性板或剪力墙板的中高层建筑。在这种情况下，系统的质量集中在地板水平处，并且元件的位移被视为与质量相关的横向位移的函数。但在由柔性梁柱组成的钢框架的情况下，不平衡力出现在非质量相关自由度中，并且位移作为横向位移的函数的表示是无效的。在本报告中，提出了一种在线混合子结构模拟的总体方案，以实现测试钢梁柱的变形位置。该方案使用样本上增量力的预测器。提出了四种预测器：弹性梁单元预测器、二分量双线性梁单元预测器、人工神经网络预测器和多弹簧非弹性梁柱单元预测器。简要描述了该方案在混合分析中的适用性。还显示了达到一般变形构型所需的变换。提出了三个系列试验来评估不同的预测变量和该方案的适用性，描述了受控旋转和变化或恒定轴向载荷下的试验。报告得出的结论是：神经网络预测器成功地应用于不平衡力矩的消除方案中，将不平衡力矩降低到可以忽略不计的水平。