权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Prediction of ground vibration caused by road traffic using neural network

利用神经网络预测道路交通引起的地面振动

基本信息

批准号：
10650464
负责人：
KITAMURA Yasutoshi
金额：
$ 2.24万
依托单位：
Kobe University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1998
资助国家：
日本
起止时间：
1998 至 2000
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-10650464/
关键词：
traffic induced vibration ground vibration attenuation with distance neural network visco-elastic half space soil parameter prediction of vibration 実測調査シミュレーション

项目摘要

This research consists of two subjects.In the first subject, an estimation method of soil properties is proposed to predict simply the attenuation with distance on ground vibration caused by road traffic. This method is based on neural network in which a real ground is idealized by a half space. In the first year, the fundamental study is performed to build the neural network and it is shown that its system is useful. In the second year, viscous damping of ground is introduced to improve the precision of the prediction and it is cleared that the proposed neural network is fitted for practical use. In the third year, the proposed neural network is improved again to increase the usefulness. Moreover, a falling weight impactor is examined as excitation source, because an easy exciting method is necessary to apply the proposed method to real ground.In the second subject, the introduction of an analytical technique is intended to build a neural network for the prediction of ground vibration at the shoulder of road. In the first year, the neural network is built only by measured data in the field. However, it is seen on the accumulation process of measured data that there is a limit to the neural network based on only measured data. In the second and third years, the introduction of a unit pattern method is considered by referring the case of noise. A simulation method is developed to calculate ground vibration caused by a running vehicle under the consideration of road roughness before the unit pattern is introduced. The characteristics of the unit pattern are made clear by comparison of numerical unit patterns and measured ones. Moreover, a computer simulation method considered traffic flow is developed for the prediction of traffic induced vibration. A neural network for estimation of road roughness is also proposed.

本研究由两个课题组成。第一个课题提出了一种土壤性质的估计方法，以简单地预测道路交通引起的地面振动随距离的衰减。该方法基于神经网络，其中真实地面由半空间理想化。第一年，进行了构建神经网络的基础研究，并表明其系统是有用的。第二年，引入地面粘性阻尼以提高预测精度，并表明所提出的神经网络适合实际使用。第三年，所提出的神经网络再次得到改进，以增加实用性。此外，还研究了落锤冲击器作为激励源，因为需要一种简单的激励方法才能将所提出的方法应用于实际地面。在第二个主题中，引入分析技术旨在建立一个神经网络来预测路肩处的地面振动。第一年，神经网络仅根据现场测量数据构建。但从实测数据的积累过程可以看出，仅基于实测数据的神经网络存在局限性。第二年和第三年，参考噪声的情况考虑引入单元模式方法。在引入单元模式之前，开发了一种模拟方法来计算在考虑道路粗糙度的情况下行驶车辆引起的地面振动。通过数值单位模式与实测单位模式的比较，明确了单位模式的特征。此外，还开发了一种考虑交通流的计算机模拟方法来预测交通引起的振动。还提出了一种用于估计道路粗糙度的神经网络。