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Study On Leakage Analysis Model Based On Mesh Resistivity

Posted on:2016-08-31Degree:MasterType:Thesis
Country:ChinaCandidate:H GaoFull Text:PDF
GTID:2208330470451338Subject:Computer software and theory
Abstract/Summary:PDF Full Text Request
With the acceleration of urbanization and economic development, solid waste prod uctioncontinues to increase, proper disposal of solid waste has become one of the key issues to beaddressed in environmental protection in China, directly related to the sustainable developmentof the national economy and people’s lives. The most commonly used approach is to landfill andlandfill costs low, currently contains95%percent of total treatment of waste in China.Landfills of solid waste often contains large amounts of toxic substances and heavy metalsions, produced chemical reactions and generate large amount of harmful material, these harmfulmaterial exists in the leach ate of garbage, once into the groundwater, the quality of water will bedestroyed, in order to prevent the leakage which cause pollution to environment, bring harm tothe health of residents, leakage detection became an urgent and extremely meaningful work. Atpresent, there has variety of leakage detection methods, but the existing leakage detectiondevices of solid waste landfill often have many difficult problems, such as high-cost, difficult todetect leakage. On the basis of nowadays detection principle, in view of the problems in them,just like high-cost, difficult to detect leakage, hard to protect, this paper develop a low-cost,automated device for landfill leakage detection. This device is suitable for solid waste landfillleakage detection during the operation, it has the function of real-time monitoring, and canlocating leakage locations timely and accurate.The principle of this paper is meshed resistivity, detection of meshed resistivity in this paperuse the crossfeed way of electrode, cycle through the entire site, we can get the whole ground’scontact resistance after sampling and processing.This paper establishes a complete set of hardware and software model. PC software is basedon Microsoft Visual Studio2010platform, using the c#language to develop a PC testingsoftware system. This system has functions like, user management, permissions settings, regularsampling, and manual sampling, data management, record inquiry. Lower computer’s centralprocessing unit is data collection box EM9336BD developed by Sino-Thai, EM9336BD usingthe Ethernet bus as the interface, it is a multifunction data acquisition devices with analog inputs and outputs,digital inputs and outputs, count and watchdog functions. The upper software makecommunication through TCP-based protocols, control lower computer hardware parts to ADsampling, acquire the contact resistance values of actual sampling. After comparative tests, theinversion model based on finite element is established, with unknown parameters of soilresistivity. In order to obtain the optimal values of the parameters, the optimization algorithm isstudied in this paper, using genetic algorithm with Newton-Raphson method, optimizing andfitting of the unknown parameters. The advantage of genetic algorithm is a global optimization,and GA algorithm is adaptable, but it has the disadvantage of slow convergence, poor accuracy,lack of local search. In order to improve the genetic algorithm, this paper is using theNewton-Raphson method embedded into genetic algorithm, which is a hybrid algorithm. Newtoniterative is a traditional method for fast convergence, it has strong ability of local search, but itcould easily fall into a local optimum. The combined use of two algorithms combines both oftheir advantages while avoiding the drawbacks of them; make the optimal process more efficientand reliable. This paper uses the improved genetic algorithms and establishes the error equationof theoretical and actual values as the objective function. Get the theoretical optimal value ofresistivity of soil.Now we have the optimal fitting data, we process the data by getting the rate of changebetween values currently and values of background, then we can obtain the changes of resistancein the situation at a given moment. The changes of resistance reflect the leakage condition of thevenue. For a more intuitive display of the leakage and meet the needs of users, this paperpositioning and displaying the leakage in a graphical format. This paper uses the technologies ofthe combination of matlab2010b and c#, to map the change rate, and show the leakage on atwo-dimensional color plane diagram.This paper is not yet complete, leak detection accuracy needs to be improved, there shouldbe more detailed in finite element division to solve this problem, but under current conditions,we first need to ensure stability and availability of sample data. In an actual landfill, there oftenhave several vulnerabilities, and the location of them will be randomly distributed throughout thewhole venue, so we should them into consideration.
Keywords/Search Tags:Leakage detection, inversion model, Finite Element, improved Genetic Algorithm
PDF Full Text Request
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