本文選題：基坑沉降監(jiān)測(cè) + 灰色系統(tǒng)模型　； 參考：《安徽理工大學(xué)》2017年碩士論文

【摘要】：按照設(shè)計(jì)的要求以一定的時(shí)間周期對(duì)基坑沉降進(jìn)行監(jiān)測(cè),根據(jù)對(duì)這些監(jiān)測(cè)數(shù)據(jù)的處理及分析,準(zhǔn)確預(yù)測(cè)基坑沉降的趨勢(shì),以便能夠及時(shí)采取措施,防止災(zāi)害事故的發(fā)生,確�；蛹爸苓吔ㄖ锖腿藛T的安全。本文利用小波降噪的方法,來(lái)處理基坑沉降監(jiān)測(cè)數(shù)據(jù)并對(duì)觀測(cè)數(shù)據(jù)的變化趨勢(shì)進(jìn)行預(yù)測(cè)研究。以某市一處招待所基坑沉降觀測(cè)為例,選取有代表性的監(jiān)測(cè)點(diǎn)用來(lái)分析研究。首先,根據(jù)實(shí)際觀測(cè)數(shù)據(jù)利用灰色系統(tǒng)和時(shí)間序列預(yù)測(cè)模型分別計(jì)算,根據(jù)不同模型的預(yù)測(cè)結(jié)果,分析比較其各自的優(yōu)缺點(diǎn);其次,應(yīng)用軟閾值小波降噪的方法,對(duì)實(shí)例中原始監(jiān)測(cè)數(shù)據(jù)進(jìn)行預(yù)處理;最后,分別采用經(jīng)典的灰色系統(tǒng)和時(shí)間序列模型、時(shí)間序列—灰色系統(tǒng)組合模型對(duì)小波降噪后得到的數(shù)據(jù)進(jìn)行預(yù)測(cè),對(duì)其預(yù)測(cè)的結(jié)果進(jìn)行分析比較。對(duì)比結(jié)果表明,利用經(jīng)典灰色系統(tǒng)模型預(yù)測(cè)得到的結(jié)果優(yōu)于時(shí)間序列模型,利用時(shí)間序列—灰色系統(tǒng)組合模型預(yù)測(cè)得到的結(jié)果均優(yōu)于經(jīng)典的灰色系統(tǒng)和時(shí)間序列模型;小波降噪灰色系統(tǒng)模型預(yù)測(cè)得到的結(jié)果優(yōu)于未經(jīng)降噪時(shí)間序列—灰色系統(tǒng)組合模型,且優(yōu)于小波降噪時(shí)間序列模型。最后發(fā)現(xiàn)小波降噪時(shí)間序列—灰色系統(tǒng)組合模型預(yù)測(cè)效果最優(yōu)。該文研究?jī)?nèi)容對(duì)基坑工程施工設(shè)計(jì)及監(jiān)測(cè)方案設(shè)計(jì)具有指導(dǎo)作用。
[Abstract]:According to the design requirements, the foundation pit settlement is monitored in a certain period of time. According to the processing and analysis of these monitoring data, the trend of foundation pit settlement can be accurately predicted, so that timely measures can be taken to prevent the occurrence of disasters and accidents. Ensure the safety of the foundation pit and surrounding buildings and personnel. In this paper, wavelet denoising method is used to deal with foundation pit settlement monitoring data and forecast the trend of observation data. Taking the settlement observation of foundation pit of a guesthouse in a city as an example, representative monitoring points are selected for analysis and research. Firstly, according to the actual observation data, the grey system and time series prediction model are used to calculate respectively, and the advantages and disadvantages of different models are analyzed and compared according to the prediction results of different models. Secondly, the soft threshold wavelet denoising method is applied. The pre-processing of the original monitoring data is carried out. Finally, the data obtained by wavelet denoising are predicted by using the classical grey system and time series model, and the combination model of time series and grey system respectively. The predicted results are analyzed and compared. The results show that the results obtained by using the classical grey system model are superior to those of the time series model, and the results obtained by using the combined time series-grey system model are superior to those of the classical grey system model and the time series model. The prediction result of wavelet denoising grey system model is better than that of unnoised time series grey system combined model and wavelet denoising time series model. Finally, it is found that the prediction effect of wavelet denoising time series-grey system combined model is optimal. The research contents of this paper can be used to guide the design of foundation pit construction and the design of monitoring scheme.
【學(xué)位授予單位】：安徽理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TU433

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