【摘要】：隨著社會經(jīng)濟的發(fā)展,隧道工程已經(jīng)成為我國乃至全世界最為重要的建設(shè)項目之一。而在隧道建設(shè)過程中,容易出現(xiàn)各種工程問題,其中隧道涌水會給施工帶來極大的影響,隧道涌水不僅威脅工作人員和工程設(shè)備的安全,而且會對當?shù)丨h(huán)境帶來負面影響,因此對隧道涌水量的預測已經(jīng)成為當前隧道工程中一個亟待解決的問題。本文以化馬隧道工程為依托,基于小波分析和灰色系統(tǒng)理論,對隧道涌水進行分析和預測。重點進行了兩方面的研究工作。(1)對化馬隧道涌水在時間尺度上的變化進行分析。多時間尺度是隧道涌水過程中存在的重要特征,本文選用Morlet連續(xù)復小波變換來分析涌水時間序列的多時間尺度特征,繪制了小波方差圖和小波系數(shù)模等值線圖等,得出化馬隧道涌水的第一主周期為24個月的特征時間尺度,第二主周期為9個月的特征時間尺度,為接下來的涌水量預測提供一定指導作用。(2)對隧道涌水量進行預測。本文首先分析了灰色系統(tǒng)理論與小波分析結(jié)合的可能性,然后分別采用單一灰色GM (1, 1)模型和基于小波去噪后的GM (1,1)模型對隧道涌水量進行預測,并對結(jié)果進行分析比較,表明組合模型可以改良單一模型的局限性,從而提高預測的準確度。結(jié)果表明,小波去噪后的GM (1,1)模型預測精度更高、方法簡單可行,該方法可以為隧道涌水預測提供一種新思路,以期為隧道安全施工提供理論依據(jù)。
[Abstract]:With the development of social economy, tunnel engineering has become one of the most important construction projects in China and the world. In the process of tunnel construction, it is easy to appear various engineering problems, among which the tunnel water gushing will bring great influence to the construction. The tunnel water gushing will not only threaten the safety of the workers and engineering equipment, but also bring negative impact to the local environment. Therefore, the prediction of tunnel water inflow has become an urgent problem in current tunnel engineering. Based on the wavelet analysis and grey system theory, this paper analyzes and predicts the water gushing of the tunnel based on the Huama tunnel project. This paper focuses on two aspects of research. (1) the variation of water inrush in Huama tunnel on time scale is analyzed. Multi-time scale is an important feature in the process of tunnel water inrush. In this paper, Morlet continuous complex wavelet transform is used to analyze the multi-time scale characteristics of water inrush time series, and wavelet variance map and wavelet coefficient modulus isoline map are drawn. It is concluded that the first main period of water gushing in Huama tunnel is a characteristic time scale of 24 months and the second period is a characteristic time scale of 9 months, which provides some guidance for the prediction of water inflow in the following years. (2) forecasting the water inflow of tunnels. In this paper, the possibility of combining the grey system theory with wavelet analysis is analyzed, and then the single grey GM (1,1) model and the GM (1K1) model based on wavelet denoising are used to predict the tunnel water inflow, and the results are analyzed and compared. It shows that the combined model can improve the limitation of a single model and improve the accuracy of prediction. The results show that the prediction accuracy of the wavelet denoising GM (1 / 1) model is higher and the method is simple and feasible. This method can provide a new way for tunnel water inflow prediction and provide a theoretical basis for tunnel safety construction.
【學位授予單位】：西南交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U456.32

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