【作者】 杨津灵；

【导师】 杨洁明；

【作者基本信息】 太原理工大学 ， 机械电子工程， 2012， 博士

【摘要】 煤泥水处理是选煤厂非常重要的工艺环节,其处理效果直接影响洗水复用与闭路循环的指标,而且对选煤厂其他环节如分选效率、产品的数质量指标等都影响很大,甚至是制约全厂经济效益和社会效益的一个重要系统。因此,如何处理好煤泥水一直是国内外选煤界非常重视的研究内容。在煤泥水处理过程中实现有效的絮凝沉降是保证循环水质量的重要条件,但目前国内仍有许多选煤厂主要靠人工调节絮凝剂的添加量,导致循环水浊度不稳定。部分选煤厂虽已实现药剂自动添加,但对于絮凝沉降过程的复杂性,尤其是具有大惯性、大滞后的特点,均未能给出针对性的控制策略。因此,研究先进的控制方法,改善控制效果,对选煤厂具有很重要的意义。本文主要做了以下几方面的工作：1、通过对煤泥水性质的测定,详细分析了煤泥水的特点和难处理的原因；研究了煤泥水的沉降特性和影响煤泥水沉降的各种因素；分析了煤泥水絮凝沉降过程这样一个复杂的受多因素影响的大惯性、大滞后和非线性过程目前在控制上存在的问题和难点,如目前采用的控制算法对大滞后问题考虑不足,被控对象难以用精确的数学模型描述等。2、本文在前馈加反馈联合控制的控制模式下,对如何克服系统大滞后的影响,提高系统的稳定性进行了重点研究,首先提出了一种沿浓缩机深度方向的三点式浊度分布检测方法,用以替代在溢流总管上的浊度检测,以提前和直接反映沉降效果；同时采用灰色预测算法,根据现在和过去浊度数据及其变化行为,对溢流水未来的浊度值进行了超前预测,从而大大降低了过程滞后对控制性能造成的影响。3、基于改进的灰色预测-模糊PID控制原理,提出了一种改进的煤泥水絮凝沉降过程前馈加反馈控制策略,其改进之处在于：(1)用模糊PID算法替代了目前采用的常规模糊控制算法,即根据模糊规则在线整定PID参数,既克服了模糊控制难以消除稳态误差和实现精确控制的弱点,又克服了PID参数整定的困难,使它们的结合形成优势互补；(2)用沉降区的浊度变化矢量代替了澄清区浊度偏差的微分作为模糊控制器的第二维输入,将浊度的变化趋势提前输入模糊控制器,对大滞后过程起到了提前控制的作用。该控制策略是一种简单、易于实现、而且鲁棒性强、控制有效的模式,适合于在环境恶劣的工业过程控制中应用。4、本文仿真分析了灰色预测模型维数、原始数据序列的波动性以及预测步长对预测精度的影响,研究了PID参数的模糊推理规则,进行了论域分析和隶属度函数设计,并用实验方法建立了某种条件假设下的絮凝沉降过程的输入输出关系,通过系统辨识得到了煤泥水沉降过程的模拟模型。在此基础上进行了控制性能的仿真分析,结果表明灰色预测模糊PID控制对大滞后过程具有较好控制特性和抗干扰能力。5、设计并实现了由现场显示与调节单元、下位机PLC控制器和远程上位机控制器组成的煤泥水絮凝沉降控制系统。借助上位机的运算能力应用MATLAB与组态软件的混合编程,实现灰色预测的过程；下位机PLC完成对系统传感器数据的采集和加药量的模糊控制。上、下位机通过工业以太网络交换数据和控制信息。更多还原

【Abstract】 In coal preparation plant, slime water treatment system plays a very important role for the reason that the process water must be recycled. Generally, the turbidity of overflow water in thickening tank should below the required level. Unqualified recycled water will have impact on the production quotas such as separating effect, heavy medium consumption and product moisture. Especially, the severe disorder of slime water treatment system will result in anomaly, even shut down, of the overall coal separating system. Due to the great environmental concerns and potential economic reward, in the past decades many efforts have been made by both here and abroad researcher to study the methods of slime water treatment. However, most plants still rely on experienced workers’manual adjustment to control the addition of flocculant nowadays, which may lead to unstable water turbidity. In some factories, the automatic dosing has adopted, but the efficient control schemes to the great inertia and long delay of flocculating sedimentation process is lacking. Therefore, it is required to further study the advanced control methods for the specific problem.In this paper, we make the following contributions:1. We do some experiments on the samples of the coal slime water. From the parameters measured in the experiments, we analyze the properties of coal clime water and the multiple factors related to its sedimentation process. Based on such observations, we conclude that the particular challenges in effective control:large inertia and long latency. It is found that the existing schemes underestimate these problems.2. To solve the system’s large latency problem, we propose a novel turbidity detection method, which senses the turbidity at three locations in the vertical direction along the thickener. Compared with the traditional method only observing the turbidity at the overflow pipe, the new scheme is able to discover the sedimentation’s situation with reduced delay. We develop grey prediction algorithm to foretell the turbidity in advance so that the delay problem is much alleviated.3. Based on theories about grey prediction and fuzzy PID, we present a new flocculating sedimentation strategy with feed-forward and feedback. The scheme is different from the existing schemes in two ways. Firstly, the traditional fuzzy control method is substituted by the fuzzy PID algorithm, which can adjust the PID parameters in an online manner according to the fuzzy rules. The advantages are twofold:it could avoid the steady state error problem for fuzzy control methods; and it makes the PID parameter setting convenient. Secondly, the turbidity variation vector in the sinking region replaces the turbidity error differentials at clarity region as the second input for the fuzzy controller. Since the trend of turbidity change could be inferred, the large-delay system can be controlled in advance. Besides, the control strategy is practical to implement in harsh industrial environment.4. Through extensive simulations, we study the impacts of a number of settings on the accuracy of prediction, like the grey prediction model dimensions, the fluctuation of data sequence, and prediction step size. Based on PID fuzzy deduction rules, we make domain analysis and design member functions. A virtual model of coal slime water sedimentation has been derived by experiments and system identification method, which discloses an input-output relation of sedimentation process. The results show that the proposed control method is effective for large-delay system, even with interference signals.5. Finally, we design and implement the automatic control system of flocculating sedimentation process which is composed of the display and adjusting unit on-site, lower machine PLC and upper machine PC. With operation ability of PC, grey forecasting process is realized by Mingled-Programming between MATLAB and configuration software. System Sensor data acquisition and the dosage of the fuzzy control were done by PLC. Upper machine and lower machine can exchange data and control information through the industrial Ethernet network.更多还原