【作者】 李明；

【导师】 崔宝侠；

【作者基本信息】 沈阳工业大学 ， 控制理论与控制工程， 2007， 硕士

【摘要】 双进双出磨煤机是火力电厂中广泛采用的一种制粉设备。它具有能耗低、生产效率高、研磨煤种范围广和不受异物影响等优殿，但是磨煤机运行时也存在一定的问题，有时出力不均匀，功耗变大，甚至发生堵煤和乏煤现象。这是由煤位检测设备精度低造成的，而国外的煤位检测设备虽然检测精度高，但进口价格昂贵。因此自主进行检测设备的研发对于降低整体成本，具有重要意义。论文首先介绍了双进双出磨煤机的工作原理、特点及传统的煤位检测方法，分析了传统的煤位检测方法的不足，即煤位检测精度较低的问题。为了解决此问题，论文首次提出了压差法与噪声法相结合的分段煤位检测方法。当磨煤机工作在乏煤和堵煤的情况下，噪声法很难准确测量煤位，此时采用压差法进行煤位检测可以取得良好的效果；而当磨煤机工作在正常煤位情况下时，压差法精度降低，不再适合此状态，而此段是噪声法测量精度最高的煤位段，因此采用噪声法。为了提高噪声法正常工作时的检测精度，在原有方法的基础上，对其进行算法的改进。将现场收集的磨煤机的噪声，利用小波变换的方法进行频率分解，并找到反映磨煤机简体内煤位的特征频率段，之后对分解后的特征向量采用智能分析的方法，利用神经网络建立磨煤机煤位的统计模型，最终实现煤位检测。在优化控制方面，为了使双进双出磨煤机制粉系统在低功耗的前提下，研磨效果理想，出力均匀，需要对磨煤机的煤位进行优化控制，使磨煤机工作在最佳的煤位段。煤位控制方法采用内模控制，有效的抑制了系统滞后时间长、惯性大的问题。内模控制模型由神经网络训练生成，在数据量大的情况下此方法建立系统模型要优于传统的机理建模。最后采用MATLAB进行仿真分析，验证了算法的有效性。更多还原

【Abstract】 BBD Ball Mill is well used in power plant, and it has advantages of low energy consumption, high efficiency, wide application in grinding mill and stable running. However, when the equipment is running, problems such as occasionally asymmetric power, energy consumption becoming larger, even the phenomena that the equipment is jammed or lacked, exist in the Mill because of low precision of the material level detecting equipment. While foreign equipments have higher precision, but the price is high simultaneously. Therefore, it is very meaningful to develop detecting equipment independently to decrease entire cost. The thesis will study on this question.Firstly, the thesis introduces working principle, characteristics of BBD Ball Mill and traditional coal level measuring method, then analyses shortage of low precision of traditional coal level measurement. Therefore, the thesis put forward the subsection measuring method through pressure difference method mixed with noise measuring method. When the Mill works under condition that coal is lacked or jammed, it’s difficult for noise method to measure the coal level exactly. And pressure difference measuring method can get well result under this condition. But when the Mill works under the condition that coal level is normal, pressure difference method precision decreases and isn’t appropriate for the condition. As in normal level, the noise method gets the highest precision. Therefore, the noise method is adopted. In order to acquire better control effect, the noise measure method needs to be improved. The wavelet packet transformation, which is used to decompose the noise frequency, is adopted to process the Mill noise from the field to find characteristic frequency segment inside the Mill. After that, the decomposed eigenvector is processed by intelligent analysis method, and statistics model of the coal level is built using nerve network. Finally, coal level measurement is achieved.Secondly, in optimum control part, for the consideration of low power consumption, the mill pulverizing optimum control system of BBD Ball Mill is presented in the thesis to guarantee the asymmetric power and the machine to work under best coal level. The coal level control method effectively restrains the shortages of long lagging time and large inertia of the system. Because internal model is obtained by nerve network, and if data are plenty, the system model from above method is better than traditional mechanism modeling. And simulation results demonstrate effectiveness of the method.更多还原