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水泥熟料生产过程热效率监测、评估与优化方法研究
其他题名Thermal Efficiency Monitoring, Evaluation and Optimization Methods for the Cement Clinker Manufacturing Process
刘钊1,2
导师于海斌
分类号O224
关键词水泥熟料生产过程 热效率模型 在线监测 煤炭消耗预测 热效率优化
索取号O224/L76/2016
页数119页
学位专业机械电子工程
学位名称博士
2016-05-30
学位授予单位中国科学院沈阳自动化研究所
学位授予地点沈阳
作者部门信息服务与智能控制技术研究室
摘要水泥熟料生产过程是一个复杂的热量转换与消耗过程,具有热集成与热耦合、气-液-固多相共存、化学反应与传递现象伴生、生产工况变化频繁等复杂特性。此外,在生产条件方面,存在热能相关参数的检测元件少且其所处工作环境恶劣、测量精度差等问题。上述因素导致现有的能源管理系统难以真正实现水泥熟料生产过程热效率的监测、评估和优化,生产过程普遍存在热耗高、热能利用率低等问题。本文针对水泥熟料生产过程中存在的热效率问题,开展了热能平衡分析、热效率建模与在线监测、热能节能潜力评估、煤炭消耗预测和热效率优化方面的研究。主要研究内容和创新性成果如下:(1) 针对水泥熟料生产过程,建立了全流程及生料预热分解、熟料煅烧和熟料冷却三个子工序的热能平衡模型,提出了工序能耗分数的概念,进而基于工序能耗分数建立了全流程热效率解析模型。利用热效率解析模型证明了稳态工况下全流程热效率与子工序热效率之间存在线性正相关关系,通过分析热效率影响因素得到提高全流程热效率的有效途径。水泥熟料生产过程热效率模型的建立为该过程热效率在线监测与优化奠定了基础。(2) 针对水泥熟料生产过程热效率无法在线监测的问题,建立了一种可用于在线辨识的热能平衡模型。在稳态工况下,由现场数据构成的输入输出矩阵接近奇异矩阵,因此,采用递推奇异值分解辨识算法并改进了递推算法的初始值用于在线模型参数估计,克服了线性回归算法中出现的病态问题,避免了递推过程中参数向量进入复数域范围。实验结果证明了所建立的热能平衡模型和改进的辨识算法能有效地计算水泥熟料生产过程热效率。(3) 针对大时间尺度下水泥熟料生产过程煤炭消耗水平因工况变化和噪声数据而无法直接准确计算的问题,采用基于数据密度聚类的算法剔除了煤炭消耗数据中的噪声数据和异常值,建立了反映水泥熟料生产实际煤炭消耗水平的数据指标。提出了一种结构化的热能节能潜力评估方法来对标分析水泥熟料生产过程中的各热能支出,并绘制了用于展示水泥熟料生产过程节能潜力的热能支出分布直方图。(4) 针对水泥熟料生产过程中生料预热分解环节煤炭消耗时间序列的固有复杂性和不规律性,基于“分解-预测-集成”的原则,提出了一种基于经验模态分解的混合集成预测模型,用于生料预热分解环节的煤炭消耗。该模型有效地集成了经验模态分解,滑动平均滤波,最小二乘支持向量回归和二次指数平滑算法。实验结果证明了本文提出的混合预测模型可以发挥各算法的优势,并且在各种预测指标测试中优于其他五种主流的预测模型。(5) 针对目前水泥熟料生产过程各环节热效率优化技术缺乏相互协调的问题,根据水泥熟料生产过程热能收支平衡关系及内部热交换关系,建立了基于能量转换模型的水泥熟料生产过程热效率优化模型,通过协调分解炉和回转窑的喂煤速率来减少水泥熟料生产过程的热能损失,提高了生产过程整体热效率。实验结果表明基于水泥熟料生产过程热能转换关系的热效率优化方法可以显著降低该生产过程的煤炭消耗。
其他摘要The cement clinker manufacturing process is a complex thermal energy conversion and consumption process, which has complex characteristics, such as thermal integration, thermal coupling, gas-liquid-solid multiphase coexistence, chemical reactions and transport phenomena concomitance, frequently changed production conditions. Additionally, in terms of production conditions, there are many problems, such as less detecting elements of thermal energy related parameters, the harsh environment and poor measurement accuracy. The above factors lead the existing energy management system difficult to realize the monitoring, evaluation and optimization of thermal efficiency of the cement clinker manufacturing process. The problems of high thermal energy consumption and low utilization rate of energy generally exist in the manufacturing process. In order to solve the thermal efficiency problems existing in the cement clinker manufacturing process, the studies of thermal energy balance analysis, thermal efficiency modeling and on-line monitoring, thermal energy saving potential evaluation, coal consumption forecasting and thermal efficiency optimization are carried out in this paper. The main research contents and innovative achievements are as follows: (1) For the cement clinker manufacturing process, the thermal energy balance models of the whole process and its three sub procedures of raw material preheating decomposition, clinker calcination and clinker cooling are established. The concept of procedure energy consumption fraction is proposed, and then the thermal efficiency analytical model is established and quantitatively described based on this concept. The thermal efficiency analytical model proves that there is a positive linear correlation between the thermal efficiency of the whole process and the thermal efficiencies of the three sub procedures under the steady-state condition. Effective ways to improve the thermal efficiency of the whole process is obtained by analyzing the influence factors of thermal efficiency. The establishment of the thermal efficiency model of the cement clinker manufacturing process provides the basis for the on-line monitoring and optimization of the thermal efficiency of the whole process. (2) An thermal energy balance model of the cement clinker manufacturing process that can be used for on-line identification is established, aiming at solving the problem that the thermal efficiency can’t be on-line monitored. Considering that the input and output matrix is close to a singular matrix under steady working conditions, the recursive singular value decomposition (RSVD) identification algorithm is adopted for the on-line estimation of model parameters, which overcomes the ill-conditioned problem in linear regression algorithm. In order to avoid the parameter vectors entering the complex number domain in the recursive process, the initial value of the recursive algorithm is improved. The experimental results prove that the established model and the improved identification can effectively calculate the thermal efficiency of the cement clinker manufacturing process. (3) To solve the problem that the coal consumption level can not be accurately calculated in large time scale due to the changes of working condition and the noise data, data density based clustering algorithm is adopted to eliminate the noise data and outliers of the coal consumption data, and then the data index that can reflect the actual coal consumption level of the cement clinker manufacturing process is established. Meanwhile, a structured energy saving potential evaluation method is proposed to benchmark thermal energy expenditures of the cement clinker manufacturing process, and the thermal energy expenditure distribution histogram of the cement clinker manufacturing process which is used to display the energy saving potential is drew. (4) In consideration of the intrinsic complexity and irregularity of coal consumption time series of the raw material preheating and decomposition process, a hybrid ensemble model that integrates is proposed, based on the “decomposition-prediction-integration” methodology, to forecast the coal consumption of this process. The hybrid ensemble model effectively integrates empirical mode decomposition (EMD), moving average filter (MAF), least squares support vector regression (LSSVR), and quadratic exponential smoothing (QES). The experimental results prove that the proposed hybrid ensemble model can give full play to the advantages of each algorithm and outperform other five popular forecasting models in forecasting performance tests. (5) Aiming at the deficiency of mutual coordination of the thermal efficiency optimization technology, and according to the thermal energy balance and internal thermal coupling relationship of the cement clinker manufacturing process, the thermal efficiency optimization model of the cement clinker manufacturing process is proposed based on the energy conversion model. The thermal energy loss is reduced by coordinating the coal feeding rate of the furnace and rotary kiln, and the overall thermal efficiency is improved. The experimental results show that the thermal energy conversion relations based thermal efficiency optimization method can significantly reduce the coal consumption.
语种中文
产权排序1
文献类型学位论文
条目标识符http://ir.sia.cn/handle/173321/19659
专题信息服务与智能控制技术研究室
作者单位1.中国科学院沈阳自动化研究所
2.中国科学院大学
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刘钊. 水泥熟料生产过程热效率监测、评估与优化方法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2016.
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