本文選題：供水管網(wǎng) + 水力模型　； 參考：《重慶大學》2014年博士論文

【摘要】：管網(wǎng)水力模型的構建與運用是實現(xiàn)供水系統(tǒng)現(xiàn)代化管理的必要手段與途徑，它不僅有助于供水調(diào)度、優(yōu)化運營管理，還是開展管網(wǎng)漏損定位、管網(wǎng)水質(zhì)模擬、預警突發(fā)性水質(zhì)污染事件等相關研究的基礎。在構建的管網(wǎng)水力模型中，由于節(jié)點流量與管道阻力系數(shù)無法直接測量，需要通過實測的水壓與流量數(shù)據(jù)進行校核，在監(jiān)測點不足的情況下，如何有效校核水力模型并提高校核效率是管網(wǎng)研究領域的難點與熱點問題。本文以管網(wǎng)阻力系數(shù)校核、節(jié)點流量實時校核與漏損定位為主要研究內(nèi)容，取得了如下幾方面的研究成果與結論： 1）管網(wǎng)水力模型校核是復雜的非線性優(yōu)化問題，其求解方法主要有基于確定性問題的“梯度迭代算法”(Gradient-based algorithm)和基于隨機性問題的“隨機搜索算法”(Stochastic search algorithm)。雅克比矩陣的計算是利用梯度迭代算法實現(xiàn)參數(shù)校核的關鍵，目前“擾動法”被最廣泛用于計算供水管網(wǎng)雅克比矩陣，但該方法計算量大且精度低。本文應用矩陣分析法推導了供水管網(wǎng)雅克比矩陣的解析式，分別包括節(jié)點水壓與管道流量對節(jié)點流量、管道阻力系數(shù)、管徑的雅克比矩陣解析式。該式的導出不僅能提高管網(wǎng)參數(shù)校核程序的運算效率，還有利于參數(shù)敏感度分析、漏損定位、水壓監(jiān)測點優(yōu)化布置等相關研究的開展。 2）提出了基于經(jīng)驗信息的加權最小二乘管網(wǎng)阻力系數(shù)校核法。由于實際中監(jiān)測點個數(shù)小于未知量個數(shù)，管網(wǎng)阻力系數(shù)校核為欠定問題，傳統(tǒng)校核方法習慣將管道按管材與管齡進行分組以減小未知量個數(shù)，本文將管道阻力系數(shù)的經(jīng)驗值作為偽觀測值引入目標函數(shù)，相較于傳統(tǒng)方法，其優(yōu)點是能充分利用管道阻力系數(shù)的經(jīng)驗值方便地將欠定校核問題轉化為超定。 3）構建了管網(wǎng)反計算模型并用于節(jié)點流量實時校核�？紤]到通常將節(jié)點流量校核轉化為優(yōu)化問題求解需反復執(zhí)行管網(wǎng)水力平差計算（正計算），本文構建了一個新的反計算模型，該模型采用矩陣分解法分離管網(wǎng)質(zhì)量與能量方程中的變量，重新構建管網(wǎng)質(zhì)量與能量方程組。通過直接求解該模型可同時獲得管網(wǎng)中未知的節(jié)點流量、節(jié)點水壓與管道流量，且無需進行傳統(tǒng)的管網(wǎng)正計算，為管網(wǎng)水力模擬提供了一個新的算法。 4）滲漏管網(wǎng)水力特性及漏損定位研究。為研究滲漏管網(wǎng)水力特性、模擬管網(wǎng)漏損時水力狀態(tài)，構建了管道滲漏模型并利用相關實測數(shù)據(jù)論證了模型的可靠性，將管道破損形式進行分類并提出了不同形式破損口滲漏面積的計算方法。管網(wǎng)漏損可視為節(jié)點流量的異常增大，會導致監(jiān)測值的異常變化，利用一次二階矩法量化監(jiān)測值的正常波動范圍，實現(xiàn)了管網(wǎng)漏損預警。將漏損定位轉化為與節(jié)點流量校核相似的優(yōu)化問題，以最小化監(jiān)測值與管網(wǎng)水力模型計算值的差構建目標函數(shù)，通過逐個校核節(jié)點流量比較目標函數(shù)殘差實現(xiàn)了管網(wǎng)漏損定位�？紤]到對大型管網(wǎng)逐個校核節(jié)點流量計算量巨大，利用加權最小二乘回歸法對目標函數(shù)的一階泰勒展開式進行殘差計算，提高了漏損定位效率。 5）考慮管網(wǎng)漏損特征的水壓與水質(zhì)監(jiān)測點優(yōu)化布置。定位管網(wǎng)漏損需要利用監(jiān)測點提供的相關信息，優(yōu)化水壓與水質(zhì)監(jiān)測點的布置可使漏損引起的壓力變化或水質(zhì)污染盡可能被及時、準確監(jiān)測。通過計算管網(wǎng)中各管道與節(jié)點的漏損概率，利用Kmeans聚類法對水壓敏感度矩陣進行聚類分析，優(yōu)化了水壓監(jiān)測點的布置�？紤]到實際中污染物入侵管網(wǎng)的概率與管道漏損相關，，根據(jù)覆蓋集法的思想，將管道漏損概率作為權系數(shù)引入最短水流時間矩陣中，在給定的監(jiān)測等級下，通過求解目標函數(shù)極值優(yōu)化了水質(zhì)監(jiān)測點的布置。 文中所有提出的算法都在Matlab中編寫了相應程序，并利用實際管網(wǎng)結合數(shù)字仿真闡明了算法的實現(xiàn)過程、測試了算法的收斂速度、驗證了算法的正確性與可行性。
[Abstract]:The construction and application of the hydraulic model of the pipe network is the necessary means and way to realize the modern management of the water supply system. It is not only helpful to the water supply scheduling, the optimization of the operation management, but also the foundation of the related research on the leakage location of the pipe network, the water quality simulation of the pipe network, the early warning of the sudden water pollution events and so on. The point flow and pipe resistance coefficient can not be measured directly. It is necessary to check the measured water pressure and flow data. Under the condition of insufficient monitoring points, how to effectively check the hydraulic model and improve the checking efficiency is a difficult and hot issue in the field of pipe network research. This paper checks the pipe network resistance coefficient and the node flow real-time checking and leakage. Positioning is the main research content, and the following research results and conclusions are obtained.
1) the verification of the hydraulic model of the pipe network is a complex nonlinear optimization problem, and its solution methods mainly include the "gradient iterative algorithm" (Gradient-based algorithm) based on the deterministic problem and the random search algorithm (Stochastic search algorithm) based on the randomness problem. The calculation of the Jacobian matrix is to use the gradient iterative algorithm to realize the reference. At present, the "disturbance method" is the most widely used to calculate the Jacobi matrix of water supply network, but this method has large calculation and low precision. This paper derives the analytical formula of Jacobi matrix of water supply pipe network by matrix analysis method, which includes node flow, pipe resistance coefficient and Jacobi diameter of pipe diameter, respectively. The derivation of this formula can not only improve the operation efficiency of the pipe network parameter checking program, but also benefit the analysis of parameter sensitivity, leakage location, and the optimal layout of water pressure monitoring points.
2) a weighted least square pipe network resistance coefficient checking method based on empirical information is proposed. Due to the fact that the number of monitoring points is less than the number of unknown quantities, the resistance coefficient of the pipe network is checked into an underdetermined problem. The traditional checking method is used to group pipes and pipe age to reduce the number of unknown quantities. The empirical value of pipe resistance coefficient is given in this paper. As a pseudo observation value, the objective function is introduced. Compared with the traditional method, the advantage of this method is that it can make full use of the empirical value of the pipe resistance coefficient to convert the underdetermined proofreading problem into overdetermination.
3) the inverse calculation model of the pipe network is constructed and used to check the node flow in real time. Considering that the calculation of the hydraulic adjustment of the pipe network is often carried out, a new inverse calculation model is built in this paper. This model uses the matrix decomposition method to separate the variables in the quality and energy equation of the pipe network. The quality and energy equations of the pipe network are rebuilt. By directly solving the model, the unknown node flow, node water pressure and pipe flow can be obtained at the same time, and the traditional pipe network is not required to be calculated, which provides a new algorithm for the hydraulic simulation of the pipe network.
4) research on hydraulic characteristics and leakage location of leakage pipe network. In order to study the hydraulic characteristics of leakage pipe network, simulate the hydraulic state of pipeline leakage, build the pipeline leakage model and demonstrate the reliability of the model by using the related measured data, classify the pipe breakage form and put forward the calculation method of the leakage area of different forms of damaged mouth. The leakage can be seen as an abnormal increase of node flow, which can lead to abnormal changes in monitoring values. The two order moment method is used to quantify the normal fluctuation range of the monitoring value, and the leakage early warning of the pipe network is realized. The leakage location is transformed into an optimization problem similar to the node flow checking, in order to minimize the difference between the monitoring value and the calculation value of the hydraulic model of the pipe network. The standard function is used to check the leakage location of the pipe network by checking the residual error of the target function by checking the flow rate of the node by one by one. Considering the huge calculation amount of the flow of the large pipe network, the first order Taylor expansion of the target function is calculated by the weighted least square regression method, and the leakage location efficiency is improved.
5) the optimal layout of water pressure and water quality monitoring point considering the leakage characteristics of the pipe network. The leakage loss of the pipe network needs to use the relevant information provided by the monitoring point. The optimization of the layout of water pressure and water quality monitoring points can make the pressure change caused by the leakage or the water pollution as far as possible and accurately. Through the calculation of the leakage of the pipes and nodes in the pipe network The Kmeans clustering method is used to cluster analysis of water pressure sensitivity matrix, and the layout of water pressure monitoring points is optimized. Considering that the probability of the intrusion pipe network is related to the leakage of the pipeline, the leakage probability of the pipeline is introduced into the shortest flow time matrix by the idea of the cover set method, and under the given monitoring grade, the leakage probability of the pipeline is introduced. The layout of water quality monitoring points is optimized by solving the extremum of the objective function.
All the proposed algorithms in this paper have written the corresponding program in Matlab, and use the actual pipe network and digital simulation to illustrate the implementation process of the algorithm, test the convergence speed of the algorithm, and verify the correctness and feasibility of the algorithm.

【學位授予單位】：重慶大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TU991.33

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