石油化工高等学校学报

石油化工高等学校学报 ›› 2012, Vol. 25 ›› Issue (5): 71-75.DOI: 10.3969/j.issn.1006-396X.2012.05.018

• 控制工程 • 上一篇    下一篇

基于神经网络的沥青路面实际老化预测系统的研究

张海涛1,姜海洋2   

  1. (1.东北林业大学土木工程学院,黑龙江哈尔滨150040;2.中国科学院力学研究所,北京100190)
  • 收稿日期:2012-04-09 出版日期:2012-10-25 发布日期:2012-10-25
  • 作者简介:张海涛(1963-),男,黑龙江哈尔滨市,教授,博士
  • 基金资助:
    黑龙江省交通厅重点项目(T1102)。

Predicting System of Asphalt Aging in Field Based on the Neural Network

  1. 1. College of Civil Engineering, Northeast Forestry University, Harbin Heilongjiang 150040, P.R.China;  2. Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, P.R.China
  • Received:2012-04-09 Published:2012-10-25 Online:2012-10-25

摘要: 在实验室测定沥青短期老化数据基础上,利用MATLAB建立BP神经网络系统,通过沥青路面实际老化数据调查与处理,用国内几个地区不同使用年限的沥青路面实际老化25 ℃针入度数据训练,预测得到寒区沥青路面不同使用年限的沥青25 ℃针入度等沥青路面实际老化数据,为建立沥青模拟老化与实际老化的关系提供理论依据。

关键词: 沥青路面 , 沥青老化 , BP神经网络 , 针入度

Abstract: Based on the data of the asphalt aging simulated in lab, through the data collection of the asphalt aging in the field, the BP neural network system was established by MATLAB to train the data of the asphalt 25 ℃ penetration in the different using time asphalt pavement from different regions in China, and predicted the 25 ℃ penetration of the different using time asphalt pavement aging in the field in cold zone. The theoretical method for the relationships between asphalt aging simulated in lab and aging in field has been put forward.

Key words: Asphalt pavement,    ,  Asphalt aging,     ,  BP neural network,    ,  Penetration

引用本文

张海涛,姜海洋. 基于神经网络的沥青路面实际老化预测系统的研究[J]. 石油化工高等学校学报, 2012, 25(5): 71-75.

ZHANG Hai-tao,JIANG Hai-yang. Predicting System of Asphalt Aging in Field Based on the Neural Network[J]. Journal of Petrochemical Universities, 2012, 25(5): 71-75.

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