中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2016, Vol. 35 ›› Issue (4): 20-24.DOI: 10.3969/j.issn.1674-0696.2016.04.05

• 桥梁与隧道工程 • 上一篇    下一篇

高速公路隧道通风系统的多参量模糊控制研究

张晓松,金涛,林东   

  1. (西安公路研究院,陕西 西安 710065)
  • 收稿日期:2015-12-28 修回日期:2016-03-03 出版日期:2016-08-20 发布日期:2016-08-20
  • 作者简介:第一作者:张晓松(1965—),男,陕西西安人,高级工程师,主要从事智能交通及应用方面的研究。E-mail:1286743765@qq.com。
  • 基金资助:
    交通运输部科技成果推广项目(2012 318 361 110);陕西省交通建设科技项目(08-16K)

Research on Multi-parameter Fuzzy Control Algorithm of Highway Tunnel Ventilation System

ZHANG Xiaosong, JIN Tao, LIN Dong   

  1. (Xi’an Highway Research Institute, Xi’an 710065, Shaanxi, P.R.China)
  • Received:2015-12-28 Revised:2016-03-03 Online:2016-08-20 Published:2016-08-20
  • Contact: 金涛(1978—),男,上海嘉定人,高级工程师,主要从事交通信息技术及ITS方面的研究。E-mail:xgyjt@qq.com。

摘要: 为解决隧道通风系统能耗较高、智能化程度较低的问题,将隧道烟雾浓度、车流量、风速等多种数据作为参量,预测未来多个连续时刻的烟雾浓度,并以预测结果序列的变化程度及趋势为依据,采用模糊控制方法对隧道通风实现智能化提前控制。通过仿真实验证明,与分档控制方法相比,该方法能够根据烟雾浓度变化趋势而调整风机开启数量,避免了因个别采样点的影响而频繁启停风机,有利于延长风机寿命。由于根据预测结果对风机进行了提前控制,在更好地改善隧道环境的同时,缩短了风机开启的总时长,节约能源,降低隧道运营成本。

关键词: 隧道工程, 智能交通, 隧道通风, 模糊控制, 风机控制, 多参量多步预测

Abstract: In order to solve the problems of high energy consumption and low intelligence in tunnel ventilation system, it was proposed that using fuzzy control algorithm for achieving the target of controlling tunnel ventilation intelligently in advance, according to the sequence of change and trends in smoke concentration data, which is predicted in multiple consecutive time in the future based on the parameters of smoke concentration, vehicle flow, and wind speed. The simulation results prove that the fuzzy control algorithm can adjust the number of working fans by the change and trends in smoke concentration data compared with step control method, which can avoid frequent start-stop of fans because of the influence of individual sample and also extend the service life of fans. The method for controlling fans in advance by the result of prediction can improve the environment of tunnel, shorten total working time of fans, save energy and reduce the operating cost of tunnel.

Key words: tunnel engineering, intelligent transportation, tunnel ventilation, fuzzy control, fan control, multivariate and multistep prediction

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