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针对水泥生料分解过程中易煅烧工况、难煅烧工况和异常工况不能及时准确判断的难题,将局部线性神经模糊模型和规则推理相结合,提出了基于局部线性神经模糊模型和规则推理的工况识别模型。局部线性神经模糊模型预测预热器C5出口温度,规则推理使用输入变量判断当前工况。该模型已经成功应用到某水泥厂水泥生料分解过程,降低了预热器C5下料管堵塞的概率。
In view of the difficult calcination condition, difficult calcination condition and abnormal working condition which can not be timely and accurately judged in the process of cement raw meal decomposition, the local linear neural fuzzy model and the rule reasoning are combined to propose the local linear neural fuzzy model and rule reasoning The condition identification model. Local Linear Neuro-Fuzzy Model Predict Preheater C5 Outlet Temperature, Rule Inference Use input variables to determine current operating conditions. The model has been successfully applied to a cement plant raw meal decomposition process, reducing the probability of preheater C5 under the tube blockage.