本文選題：大壩 + 變形監(jiān)測�。� 參考：《西南石油大學》2016年碩士論文

【摘要】：隨著我國水電能源的大力發(fā)展,更多的大壩、高壩被修建。大壩所處環(huán)境復(fù)雜,在其運行過程中可能受到多方面未知因素的不利影響而發(fā)生安全事故,因此,對大壩進行變形監(jiān)測很有必要性,利用原型監(jiān)測資料分析大壩變形的規(guī)律,科學分析大壩各效應(yīng)量及其影響量之間的關(guān)系,及時掌握其運行狀態(tài)及演變趨勢,及時發(fā)現(xiàn)危及安全的異常因素,在社會、經(jīng)濟效益乃至科學研究上面都具有重要的意義。目前,大壩監(jiān)測數(shù)據(jù)采集方法已較成熟,但監(jiān)測數(shù)據(jù)建模分析仍處于半理論、半經(jīng)驗階段,各類分析模型均有所發(fā)展。本文在對變形監(jiān)測技術(shù)及變形監(jiān)測數(shù)據(jù)分析模型系統(tǒng)研究的基礎(chǔ)上,以桐子壕航電樞紐工程為例,詳細論述了大壩變形監(jiān)測方案、監(jiān)測數(shù)據(jù)的處理與分析,并對幾種典型統(tǒng)計分析模型進行比較分析研究。論文主要包括以下幾個部分：(1)調(diào)研國內(nèi)外關(guān)于大壩變形監(jiān)測的文獻、資料,系統(tǒng)梳理和總結(jié)大壩變形監(jiān)測方法及變形監(jiān)測數(shù)據(jù)分析方法,并比較分析了各類方法的優(yōu)劣及發(fā)展趨勢。(2)深入研究各類典型大壩變形監(jiān)測統(tǒng)計分析模型原理、方法,包括多元線性回歸分析模型、逐步回歸分析模型、偏最小二乘回歸分析模型、時間序列分析模型、灰色系統(tǒng)分析模型Kalman濾波模型及人工神經(jīng)網(wǎng)絡(luò)模型等。(3)以桐子壕航電工程為例,確定大壩外部變形監(jiān)測方案及實施方法,并分析了方案的可靠性等；簡單分析桐子壕航電工程大壩水平位移基準網(wǎng)和垂直位移基準網(wǎng)的三期監(jiān)測數(shù)據(jù)成果,通過比較各點的相對年變化量和差異情況,來判斷基準點的穩(wěn)定性。同時,對變形監(jiān)測成果進行初步整理,利用大量的監(jiān)測數(shù)據(jù),繪制大壩變形的時間位移過程線圖,并對大壩變形體態(tài)進行了相應(yīng)的分析。(4)應(yīng)用統(tǒng)計模型進行桐子壕航電工程大壩變形預(yù)測分析；建立多元線性回歸分析模型、逐步回歸分析模型、偏最小二乘回歸分析模型,分析大壩水位、氣溫及時效與監(jiān)測點變形的相關(guān)性,獲得了大壩壩體變形主要與溫度相關(guān)的結(jié)論。(5)變形監(jiān)測數(shù)據(jù)統(tǒng)計模型分析方法的比較和討論。比較多元線性回歸分析模型、逐步回歸分析模型、偏最小二乘回歸分析模型三類統(tǒng)計模型的適應(yīng)性及準確度。通過對大壩變形監(jiān)測數(shù)據(jù)典型統(tǒng)計分析方法比較研究,對大壩變形規(guī)律的深入分析,為更好地選擇變形監(jiān)測方法及揭示大壩變形規(guī)律提供參考。
[Abstract]:With the development of hydropower energy in China, more dams have been built. The dam is in a complex environment and may be adversely affected by many unknown factors during its operation. Therefore, it is necessary to monitor the dam deformation, and analyze the deformation law of the dam by using the prototype monitoring data. It is of great significance in society, economic benefit and even scientific research to analyze scientifically the relationship between the effect quantity of dam and its influence quantity, to grasp its running state and evolution trend in time, and to discover the abnormal factors that endanger safety in time. At present, dam monitoring data collection method has been more mature, but monitoring data modeling and analysis is still in the semi-theoretical, semi-empirical stage, all kinds of analysis models have been developed. Based on the research of deformation monitoring technology and deformation monitoring data analysis model system, taking Tongzi trench navigation and power project as an example, this paper discusses in detail the dam deformation monitoring scheme, the processing and analysis of monitoring data. Several typical statistical analysis models are compared and studied. This paper mainly includes the following parts: 1) investigating the literature and data of dam deformation monitoring at home and abroad, systematically combing and summing up dam deformation monitoring methods and analysis methods of deformation monitoring data. The advantages and disadvantages of each method and its development trend are compared and analyzed. (2) the principle of statistical analysis model of various typical dam deformation monitoring is studied in depth, including multivariate linear regression model, stepwise regression model, and so on. Partial least square regression analysis model, time series analysis model, grey system analysis model Kalman filter model and artificial neural network model etc. The reliability of the scheme is analyzed, and the results of the three periods monitoring data of the horizontal displacement datum network and the vertical displacement reference network of Tongzi trench avionics engineering dam are simply analyzed, and the relative annual variation and the difference of each point are compared. To judge the stability of the reference point. At the same time, the deformation monitoring results are preliminarily sorted out, and a lot of monitoring data are used to draw the time displacement process diagram of dam deformation. The deformation of the dam is analyzed by the statistical model, the multivariate linear regression model, the stepwise regression model and the partial least square regression model are established. Based on the analysis of the correlation between dam water level, temperature, aging and deformation at monitoring points, the conclusion that the deformation of dam body is mainly related to temperature is obtained. The comparison and discussion of statistical model analysis methods of deformation monitoring data are given. The adaptability and accuracy of three statistical models are compared among multivariate linear regression model stepwise regression model and partial least square regression model. Through the comparative study of typical statistical analysis methods of dam deformation monitoring data, this paper makes a deep analysis of dam deformation law, and provides a reference for selecting better deformation monitoring method and revealing dam deformation law.
【學位授予單位】：西南石油大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TV698.11

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