發(fā)布時間：2018-04-13 12:21

  本文選題：隧道通風(fēng) + 小波神經(jīng)網(wǎng)絡(luò)　； 參考：《長安大學(xué)》2014年碩士論文

【摘要】：由“十二五”規(guī)劃中交通運輸領(lǐng)域體系，安全高效的交通運輸服務(wù)體系關(guān)乎重要的民生與經(jīng)濟意義。其中公路隧道的高效運行體系也在不斷的完善，無論從安全或節(jié)能問題上，都有研究的必要性。本文以太古西山隧道為依托，針對公路隧道通風(fēng)控制系統(tǒng)方向，克服由于非線性控制系統(tǒng)造成的滯后與多參數(shù)控制困難，就如何高效的排放隧道的(主要煙霧CO、Visibility）污染，如何實現(xiàn)在隧道中的風(fēng)機啟停控制策略，提出以上問題的研究及控制方法。 本文分為以下四方面：首先，公路隧道通風(fēng)控制系統(tǒng)的相關(guān)模型研究，包括污染物的變化動力模型、交通流的模型、確定CO/VI的需風(fēng)量的控制系統(tǒng)結(jié)構(gòu)與目標(biāo)；其次，具體到本項目的控制結(jié)構(gòu)與模型分析，說明交通預(yù)測的必要性，并結(jié)合分析確定以小波神經(jīng)網(wǎng)絡(luò)的預(yù)測方法，簡述方法過程及參考指標(biāo)等，基本實現(xiàn)了在誤差范圍內(nèi)的有效預(yù)測；再次，以實際值和控制器目標(biāo)設(shè)定偏差值，結(jié)合交通量，前饋控制等，經(jīng)過模糊原理推論，設(shè)計隧道通風(fēng)控制系統(tǒng)的模糊控制器，，仿真說明設(shè)計的可靠性，確定輸出風(fēng)機的啟�？刂茢�(shù)量；最后，建立模擬臺平，對基于模糊控制的公路隧道通風(fēng)控制系統(tǒng)實驗研究，由軟件與硬件兩部分實現(xiàn)，軟件STEP7_v5.5、組態(tài)王等，硬件是CO/VI傳感器、工控機、S7-300PLC、射流風(fēng)機等，在上位機上實時監(jiān)控控制效果目標(biāo)。 驗證結(jié)果，本文通過同時應(yīng)用小波神經(jīng)網(wǎng)絡(luò)與模糊控制原理，融合應(yīng)用于本公路隧道的通風(fēng)控制系統(tǒng)中，使得通風(fēng)控制系統(tǒng)不僅有強的學(xué)習(xí)優(yōu)勢而且能夠克服實際控制的非線性與滯后缺陷，通過理論與實際工程的相結(jié)合，同時基本滿足了安全通風(fēng)與優(yōu)化能源的要求，表明了此研究具有的切實意義。
[Abstract]:In the 12th Five-Year Plan, a safe and efficient transportation service system is of vital importance to people's livelihood and economy.The efficient operation system of highway tunnel is also improving continuously, no matter from safety or energy saving, it is necessary to study.Based on the Swire Xishan Tunnel, aiming at the direction of ventilation control system of highway tunnel, this paper overcomes the hysteresis and multi-parameter control difficulty caused by nonlinear control system, and discusses how to efficiently discharge the pollution of tunnel (main smoke COVisibility).How to realize the control strategy of fan start and stop in tunnel, the research and control method of the above problems are put forward.This paper is divided into the following four aspects: first, the study of the relevant models of highway tunnel ventilation control system, including the change of pollutant dynamics model, traffic flow model, determine the structure and objectives of the CO/VI air volume control system, secondly,The control structure and model of this project are analyzed, the necessity of traffic forecast is explained, the forecasting method based on wavelet neural network is determined, and the method process and reference index are briefly described.Finally, the fuzzy controller of tunnel ventilation control system is designed with actual value and controller target setting deviation value, combined with traffic volume, feedforward control and so on, after fuzzy principle inference, the fuzzy controller of tunnel ventilation control system is designed.Simulation shows the reliability of the design, determines the number of output fan start and stop control. Finally, the simulation platform level is established, and the experimental research of highway tunnel ventilation control system based on fuzzy control is realized by both software and hardware.Software STEP7V5.5, Kingview, hardware is CO/VI sensor, industrial control computer S7-300 PLC, jet fan and so on, real-time monitoring control effect on the upper computer.The results show that this paper applies wavelet neural network and fuzzy control principle to the ventilation control system of the highway tunnel at the same time.The ventilation control system not only has a strong learning advantage, but also can overcome the nonlinear and lag defects of practical control. Through the combination of theory and practical engineering, it basically meets the requirements of safe ventilation and energy optimization.It shows that this study has practical significance.
【學(xué)位授予單位】：長安大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U453.5

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本文編號：1744466