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首页> 外文期刊>International Journal of Chemistry and Chemical Engineering >Modelling and Forecasting of Detention Period of Coal Rakes in Low Capacity Thermal Power Plants
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Modelling and Forecasting of Detention Period of Coal Rakes in Low Capacity Thermal Power Plants

机译：低容量热电厂煤炭滞后拘留期的建模与预测

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摘要

Material handling has been an important consideration for any industrial unit in this age of nanotechnology indispensably requiring harmony in the constituents of E-triad (Energy, Economy and Ecology). The thermal power plants producing usable and easily transmissible form of energy for industrial growth as well as domestic happiness invariably depend on rakes of coal received and their unloading for its smooth operation. The detention period of coal rakes in the plant is an important factor which affects its operation and controls its economics. A model has been developed to forecast detention period of coal rakes in the thermal power plant having capacity around 500 MW. The knowledge of 3-point moving average has been applied and repetitively used to smoothen the haphazardly distributed and enormously large number of data collected from the plants and that of multiple linear regression analysis has been used for developing the model. The knowledge of multiple linear regression analysis and 3-point moving average and its iteration applied on the irregularly placed and haphazardly distributed data finds the model suggested for the system variable, detention period giving higher value of coefficient of determination and passing F-test for its validity.
机译：物料处理对于该纳米技术的任何工业单位都是一个重要的考虑因素在E-TRIAD（能源，经济和生态学）的组分中不可或缺地需要和谐。热电厂生产可用于工业增长以及国内幸福的可用且易于传播的能量形式，因此总是取决于所接受的煤炭耙子及其平稳运行。植物中煤炭灾难的拘留期是影响其运作并控制其经济学的重要因素。已经开发了一种模型，以预测煤炭脱落的拘留期，其热电厂的容量约为500兆瓦。 3点移动平均的知识已被应用和重复地用于平滑从植物中收集的随意分布和大量的大量数据以及多元线性回归分析的数据已用于开发模型。多元线性回归分析的知识和3点移动平均值及其在不规则放置和随意分布的数据上应用的迭代发现了对系统变量，滞留期的模型，使其测定系数较高，并通过F-Test有效性。

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