煤炭是中国能源的主体，选煤是煤炭工业现代化生产的基础和前提。选煤厂技术管理过程的主要任务是对选煤厂各个环节的生产效果进行分析和评定。可选性曲线和分配曲线是对选煤厂生产效果评定、预测、优化最基本的曲线。因此，对选煤厂曲线绘制技术的研究具有重要的现实意义和应用价值。 本文以某大型煤业集团下辖的选煤厂为应用对象，针对实际需求，对选煤曲线绘制技术进行了研究，实现了集生产信息和数据管理相结合的选煤曲线自动绘制系统。 文章首先介绍了选煤厂生产过程流程和数据传输技术，研究了基于jQuery的Ajax异步调用技术；接着介绍了选煤曲线模拟理论及主要方法，包括系统规划法、数学模拟法以及用最优化方法作模型参数估计，进而说明了数学模拟法建立经验模型的实用性和粒子群优化算法(PSO)做非线性拟合的优越性。 随后，重点研究了选煤过程中曲线模拟技术，包括基于二次Bezier曲线的整体插值拟合和粒子群优化算法在曲线拟合中的应用。通过试验进行比较分析，结果表明插值法有保留试验误差，绘制的曲线不光滑的缺点；而用数学模拟法建立经验模型，然后用粒子群优化算法对模型参数进行拟合，利用拟合出的数学模型绘制的曲线不仅拟合误差小而且光滑，能够满足实际的生产需要。 最后，系统采用J2EE编程框架，Oracle 9i数据库，同时运用数学模拟法和粒子群优化算法，设计并实现了选煤曲线的自动绘制系统，继而对整个系统进行了专业的功能测试和压力测试。 上线运行的情况表明，本系统集稳定性、安全性、可扩展性、可移植性于一体，具有很高的实用性。

Coal is the main energy in China, and coal cleaning is foundation and premise for modern production of coal industry. Main task in technology management process of coal preparation plant is to analyze and evaluate production effect of every link in coal preparation plants. Washability curve and distribution curve are the most basic curves for assessing, forecasting and optimizing of coal preparation plant’s production effect. Therefore, the study of technology for coal curve drawing has important practical significance and application value. In the thesis, coal preparation plants belonging to a certain large coal group serve as the application object. According to factual demands, drawing-curve technology for coal preparation is researched. It realized automatic drawing system of coal curves which combines production information and data management. Production processing and transmitting data technology of coal preparation plants are firstly introduced and technology for asynchronous invoke based on jQuery and Ajax is researched. Then theories and main methods of coal cleaning curve simulation are introduced, including system planning method, mathematical simulation method and optimization method of model parameter estimation. Moreover, it explains practical value of building experienced models by applying the method of mathematical simulation and advantages of particle swarm optimization algorithm (PSO) for non-linear fitting. As following, technology of curve simulation during coal process is mainly researched, including conic Bezier overall curve interpolation fitting and particle swarm optimization algorithm applied in curve fitting techniques. By doing experiment and analyzing, result shows that interpolation method has the deficiency that it keeps experimental errors and the drawn curves are not smooth. However, by applying mathematical simulation method for establishing experience model and then using particle swarm optimization algorithm to fit the model parameter, the fitting error of drawn curves is small and the curves are smooth, which can satisfy the practical production demands. Finally, J2EE programming framework is applied for developed the system, and Oracle 9i is used for establishing database. Meanwhile, mathematical simulation method and particle swarm optimization algorithm are applied to design and realize the automatic drawing system of coal curves. At last, professional function test and stress test of the whole system are done. The operation results indicate that stability, safety, expansibility and transportability are integrated in this system. Hence, this system has very high practicability.