本文選題：城市 + 供水管網(wǎng)　； 參考：《蘇州科技學院》2013年碩士論文

【摘要】：隨著國內(nèi)城市的迅速發(fā)展以及基礎(chǔ)設(shè)施的不斷建設(shè),人們的生活水平不斷提高,城市供水規(guī)模也在不斷擴大。各大城市雖然根據(jù)自身發(fā)展需要改建和新建了許多供水管道,但不容忽視的是,仍有許多應(yīng)該更換的管道仍在運行。這樣的現(xiàn)象直接導(dǎo)致了我國城市供水管網(wǎng)漏損現(xiàn)象非常嚴重。在水資源彌足珍貴的當今社會,降低供水管網(wǎng)漏損率已成為城市供水行業(yè)一項重要課題。本文以蘇州市高新區(qū)供水管網(wǎng)為研究對象,在構(gòu)建蘇州市高新區(qū)供水管網(wǎng)水力模型、全面了解供水管網(wǎng)水力狀況的基礎(chǔ)上,對蘇州市高新區(qū)供水管網(wǎng)漏損管理關(guān)鍵技術(shù)展開了研究。在全面收集歷史漏損統(tǒng)計資料的基礎(chǔ)上,引入時間序列分析法自回歸移動平均混合模型(ARMA),建立了蘇州市高新區(qū)供水管網(wǎng)漏損預(yù)測模型,對蘇州市高新區(qū)供水管網(wǎng)短期內(nèi)漏損水量和漏損件數(shù)進行了預(yù)測。通過量化導(dǎo)致管道漏損的主要因素,選取管道管徑、管道埋深、管道壓縮模量、管道上方平均日交通流量、管網(wǎng)運行壓力5大影響因子作為模型的輸入?yún)?shù),采用神經(jīng)網(wǎng)絡(luò)BP結(jié)構(gòu)對蘇州市高新區(qū)已更換的灰口鑄鐵管和鍍鋅鋼管使用時間進行了擬合,并對區(qū)域內(nèi)未更換的老舊管道安全使用時間進行了預(yù)測。以月平均漏損控制總費用最小為目標函數(shù),對蘇州市高新區(qū)供水管網(wǎng)“經(jīng)濟漏水量”進行了求解,并對供水管網(wǎng)漏損檢測周期進行了優(yōu)化。利用建立的蘇州市高新區(qū)供水管網(wǎng)水力模型模擬了現(xiàn)階段及供水量增大時的運行工況,并對管網(wǎng)現(xiàn)階段存在的問題進行了分析,提出了遠期規(guī)劃的建議。通過建立管道爆管危險函數(shù),結(jié)合模擬出的管網(wǎng)壓力狀況,對蘇州市高新區(qū)供水管網(wǎng)爆管概率進行了模擬。本論文的目的旨在為供水管網(wǎng)漏損管理提供一些新的優(yōu)化思路,為供水企業(yè)管理工作提供決策支持與技術(shù)參考。
[Abstract]:With the rapid development of domestic cities and the continuous construction of infrastructure, people's living standards have been improved, and the scale of urban water supply is expanding. Although many large cities have built and built many water supply pipelines according to their own development, there are still many pipes that should be replaced. The leakage of water supply pipe network in China is very serious. In the precious modern society of water resources, reducing the leakage rate of water supply network has become an important issue in the urban water supply industry. This paper takes the water supply network of Suzhou hi tech Zone as the research object, and constructs a hydraulic model of water supply network in Suzhou high and new zone. On the basis of the hydraulic condition of the water supply network, the key technology of leakage management in the water supply network of Suzhou high tech Zone is studied. On the basis of collecting the historical leakage statistics, the time series analysis method of autoregressive moving average mixed model (ARMA) is introduced, and the leakage prediction model of the water supply network in Suzhou hi tech Zone is established, and the Suzhou city is established. In the short term, the leakage of water and the number of leakage in the water supply network of the high and new zone are predicted. By quantifying the main factors leading to the leakage of the pipeline, the 5 influencing factors of the pipe pipe diameter, the buried depth of the pipe, the pipeline compression modulus, the average daily traffic flow above the pipeline, and the operating pressure of the pipe network are used as the input parameters of the model, and the BP structure of the neural network is adopted to the Soviet Union. The use time of gray cast iron pipe and galvanized steel pipe has been fitted, and the safe use time of old and old pipes in the region is predicted. The objective function is to minimize the total cost of the monthly mean leakage control. The "economic leakage" of the water supply pipe network in Suzhou high tech Zone is solved, and the water supply pipe is applied to the water supply pipe. The leakage detection cycle of the network is optimized. Using the hydraulic model of the water supply network of Suzhou high tech Zone, the operating conditions of the current stage and the increase of water supply are simulated, and the existing problems in the current phase of the pipe network are analyzed, and the suggestion of the forward planning is put forward. By establishing the risk function of the pipe burst, the simulated pressure of the pipe network is combined. In this paper, the purpose of this paper is to provide some new optimization ideas for the leakage management of the water supply network and provide the decision support and technical reference for the management of the water supply enterprises in Suzhou.
【學位授予單位】：蘇州科技學院
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TU991.33

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相關(guān)期刊論文 前1條

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本文編號：2073077