【摘要】：隨著我國經(jīng)濟飛速發(fā)展,全國各地出現(xiàn)了許多大型的深基坑工程,其中很大一部分處于城市中心,基坑工程的施工必然會使周邊建筑物發(fā)生變形,同時帶來一些安全隱患。實時地對建筑物進行監(jiān)測、分析和處理實測的變形數(shù)據(jù),并針對基坑開挖運用合適的預測方法對建筑的變形進行預測,是在基坑施工期間保證周邊建筑物安全的重要手段�，F(xiàn)在對于變形分析的研究內(nèi)容一般分為變形的物理解釋和幾何分析兩部分。變形的物理解釋的任務是建立變形體的變形和變形原因之間的關(guān)系,解釋變形的原因。幾何分析的任務是在各種荷載作用下描述變形體變形的空間狀態(tài)和特性。針對深基坑開挖導致的建筑物變形問題,本文首先通過改進的灰色系統(tǒng)模型對數(shù)據(jù)進行處理；其次結(jié)合BP神經(jīng)網(wǎng)絡模型的自學習性強的特點,對改進的灰色系統(tǒng)模型的預測誤差進行改正。通過對其精度的分析可知,該組合模型對建筑物變形的預測可以達到很高的精度；最后,本文基于深基坑開挖前的地質(zhì)資料,運用有限差分軟件FLAC3D建立深基坑支護結(jié)構(gòu)、周圍土體和建筑物的簡化模型,并通過深基坑工程開挖初期建筑物的變形監(jiān)測資料對該模型參數(shù)進行優(yōu)化,并根據(jù)該模型對深基坑開挖進行模擬,對建筑物上的監(jiān)測點做預測,其預測結(jié)果稍大于實測結(jié)果。
[Abstract]:With the rapid development of economy in China, many large deep foundation pit projects have appeared all over the country, most of which are located in the center of the city. The construction of foundation pit engineering will inevitably make the surrounding buildings deform and bring some hidden dangers to safety at the same time. It is an important means to ensure the safety of surrounding buildings to monitor the buildings in real time, to analyze and process the measured deformation data, and to forecast the deformation of the buildings by using the appropriate prediction method for the excavation of the foundation pit. Now the research on deformation analysis is divided into two parts: physical interpretation and geometric analysis. The task of physical interpretation of deformation is to establish the relationship between deformation and its causes, and to explain the causes of deformation. The task of geometric analysis is to describe the spatial state and characteristics of deformation under various loads. Aiming at the problem of building deformation caused by deep foundation pit excavation, this paper deals with the data through the improved grey system model. Secondly, the prediction error of the improved grey system model is corrected based on the strong self-learning characteristic of BP neural network model. Through the analysis of its precision, it can be known that the combined model can predict the deformation of buildings with high accuracy. Finally, based on the geological data before excavation of deep foundation pit, a simplified model of supporting structure, surrounding soil and building of deep foundation pit is established by using finite difference software FLAC3D. The parameters of the model are optimized by the deformation monitoring data of the building in the early stage of excavation of deep foundation pit. According to the model, the excavation of deep foundation pit is simulated, and the monitoring points on the building are forecasted, and the prediction results are slightly larger than the measured results.
【學位授予單位】：遼寧工程技術(shù)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TU433

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