發(fā)布時(shí)間：2018-04-26 08:05

  本文選題：自動(dòng)化監(jiān)測(cè) + 靜力水準(zhǔn)儀　； 參考：《成都理工大學(xué)》2017年碩士論文

【摘要】：隨著經(jīng)濟(jì)的發(fā)展和城市化的推進(jìn),越來越多的人涌入了城市。過大的人口密度給地面交通造成了巨大壓力,交通擁堵成為制約城市發(fā)展的一大頑疾。為了減輕地面交通壓力,許多大城市把發(fā)展地下軌道交通作為解決之道。隨著城市的建設(shè)發(fā)展,地鐵隧道附近出現(xiàn)了越來越多的高層建筑,可能對(duì)隧道的安全性和穩(wěn)定性造成嚴(yán)重的影響,從而危及整個(gè)城市的交通系統(tǒng)。為確保運(yùn)營(yíng)地鐵隧道的結(jié)構(gòu)安全,保障地鐵線路的安全運(yùn)行,確保廣大乘客的人身安全,對(duì)運(yùn)營(yíng)地鐵隧道進(jìn)行安全監(jiān)測(cè)具有重大意義。傳統(tǒng)的地鐵隧道監(jiān)測(cè)方法,由于成本、精度、時(shí)效、可行性等因素,對(duì)比于新興的監(jiān)測(cè)手段,已經(jīng)逐漸失去優(yōu)勢(shì)。在運(yùn)營(yíng)地鐵隧道的監(jiān)測(cè)中,為及時(shí)了解地鐵隧道變形情況,實(shí)現(xiàn)信息化監(jiān)測(cè),保證地鐵隧道的絕對(duì)安全,以及對(duì)突發(fā)狀況及時(shí)做出反應(yīng),一般采取人工監(jiān)測(cè)與自動(dòng)化監(jiān)測(cè)相結(jié)合的作業(yè)模式。在運(yùn)營(yíng)地鐵隧道自動(dòng)化監(jiān)測(cè)中使用的靜力水準(zhǔn)儀和激光測(cè)距儀等監(jiān)測(cè)儀器進(jìn)行隧道沉降與收斂?jī)身?xiàng)監(jiān)測(cè)指標(biāo)的測(cè)量。此種儀器具有高分辨率、高精度、高穩(wěn)定性、高可靠性、響應(yīng)時(shí)間快,工作壽命長(zhǎng)等優(yōu)點(diǎn);所有自動(dòng)化數(shù)據(jù)通過無線網(wǎng)絡(luò)傳輸至數(shù)據(jù)采集監(jiān)控平臺(tái),通過網(wǎng)頁形式發(fā)布。用戶可以對(duì)項(xiàng)目實(shí)時(shí)進(jìn)行管理、維護(hù)等操作。大量經(jīng)驗(yàn)表明,運(yùn)營(yíng)地鐵隧道自動(dòng)化監(jiān)測(cè)系統(tǒng)具有良好的精度,極佳的時(shí)效性,合理的成本等優(yōu)點(diǎn),已成為現(xiàn)在運(yùn)營(yíng)地鐵隧道監(jiān)測(cè)的主要手段。但在實(shí)踐中也發(fā)現(xiàn)在隧道收斂較大的區(qū)間段,沉降自動(dòng)化監(jiān)測(cè)的數(shù)據(jù)與人工測(cè)量的數(shù)據(jù)有較大偏差;而在收斂較小的區(qū)間段,沉降自動(dòng)化監(jiān)測(cè)的數(shù)據(jù)與人工測(cè)量數(shù)據(jù)又比較吻合。所以,本文試圖從地鐵隧道的數(shù)學(xué)幾何模型和監(jiān)測(cè)數(shù)據(jù)的數(shù)理統(tǒng)計(jì)模型入手,根據(jù)造成沉降數(shù)據(jù)不一致的原因,提出修正模型,對(duì)運(yùn)行地鐵隧道自動(dòng)化監(jiān)測(cè)數(shù)據(jù)進(jìn)行修正,使地鐵沉降自動(dòng)化監(jiān)測(cè)數(shù)據(jù)達(dá)到更高的精度。結(jié)果表明,兩種修正模型都可以提高沉降自動(dòng)化監(jiān)測(cè)數(shù)據(jù)的精度。其中幾何修正模型的適應(yīng)性最好,局部修正后的數(shù)據(jù)精度雖然也能滿足要求,但是不如回歸模型的修正精度高。回歸模型的局部修正精度雖然很高,但是適用性較差。通過本文研究,不僅可以提高地鐵隧道沉降自動(dòng)化數(shù)據(jù)的精度,而且還能提升地鐵隧道自動(dòng)化監(jiān)測(cè)系統(tǒng)的穩(wěn)定性,適用性,對(duì)完善數(shù)據(jù)處理流程,拓展系統(tǒng)功能,有著很大意義。
[Abstract]:With the development of economy and urbanization, more and more people pour into the city. The excessive population density has brought great pressure to the ground traffic, and traffic congestion has become a serious problem restricting the development of the city. In order to reduce the ground traffic pressure, many big cities take the development of underground rail transit as the solution. With the development of urban construction, more and more high-rise buildings appear near the subway tunnel, which may have a serious impact on the safety and stability of the tunnel, thus endangering the traffic system of the whole city. In order to ensure the structural safety of the subway tunnel, ensure the safe operation of the subway line, and ensure the safety of the passengers, it is of great significance to monitor the safety of the operating subway tunnel. The traditional subway tunnel monitoring method has gradually lost its advantage compared with the new monitoring methods because of the factors of cost, precision, aging, feasibility and so on. In the monitoring of subway tunnel operation, in order to understand the deformation of subway tunnel in time, realize information monitoring, ensure the absolute safety of subway tunnel, and make timely response to the unexpected situation, In general, manual monitoring and automatic monitoring combined with the operation model. The static level and laser rangefinder used in the automatic monitoring of subway tunnel are used to measure the settlement and convergence of the tunnel. This instrument has the advantages of high resolution, high precision, high stability, high reliability, fast response time, long working life, etc. All the automatic data are transmitted to the data acquisition and monitoring platform through wireless network and published through the form of web pages. Users can manage and maintain the project in real time. A great deal of experience shows that the automatic monitoring system of subway tunnel has the advantages of good precision, excellent timeliness, reasonable cost and so on, which has become the main means of subway tunnel monitoring. However, in practice, it is also found that in the section where the tunnel converges greatly, there is a big deviation between the data of automatic monitoring of settlement and that of manual measurement, while in the section where the convergence is small, The data of automatic settlement monitoring are in good agreement with the data of manual measurement. Therefore, this paper attempts to start with the mathematical geometry model of subway tunnel and the mathematical statistical model of monitoring data. According to the causes of the inconsistency of settlement data, this paper puts forward a modified model to correct the automatic monitoring data of running subway tunnel. The automatic monitoring data of subway settlement can achieve higher accuracy. The results show that both modified models can improve the accuracy of automatic monitoring data. The geometric correction model has the best adaptability, and the data precision after local correction can meet the requirements, but it is less accurate than the regression model. Although the local correction accuracy of the regression model is very high, the applicability of the regression model is poor. Through the research of this paper, not only the precision of the automatic data of subway tunnel settlement can be improved, but also the stability and applicability of the automatic monitoring system of subway tunnel can be improved, and the data processing flow can be improved and the system function can be expanded. It means a lot.
【學(xué)位授予單位】：成都理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U456

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