树脂结合Al2O3-C耐火泥料挥发分的快速测量  

Rapid Detection of Volatile Content in Resin Binding Al2O3-C Refractory Mud

作　　者：赵海 高志伟 田成川 ZHAO Hai;GAO Zhiwei;TIAN Chengchuan(Huadian Electric Power Research Institute Co., Ltd., Hangzhou 310030, China)

机构地区：[1]华电电力科学研究院有限公司,杭州310030

出　　处：《硅酸盐通报》2020年第5期1665-1669,1676,共6页Bulletin of the Chinese Ceramic Society

摘　　要：耐火泥料挥发分测量是一个受热干燥过程,由于测量仪器热惯性、蒸发过程时滞性和升温速度等限制,造成检测时间较长。采用Levenberg-Markuardt算法按照多种干燥经验模型对热失重数据进行拟合,并对结果进行了比较,确定了能够较好描述耐火泥料干燥过程的数学模型和数据段。在此基础上,采用神经元网络方法建立了热失重过程预报模型,结果表明,该方法能够实现耐火泥料挥发分的快速、准确测量,检测时间由6~8 min缩短到2 min以内,挥发分预测误差小于0.05%。The measurement of volatile content in refractory is a heating and drying process.Because of thermal inertia of instrument,time lag of evaporation and restrict of heating rate,the testing process is considerable slow.Non-linear data fitting on the basis of various drying experimental model was carried out by Levenberg-Markuardt algorithm(LMA).And the fitting results were compared.The model and data segment that better describing the drying process of refractory mud were chosen.Based on the above work,artificial neural net(ANN)method was adapt to built the prediction model for thermogravimetric(TG)process.The research indicates that quick and exact measurement of volatile contents in refractory mud can be realized by the above stated method.The testing time reduces from 6-8 min to less than 2 min,and the prediction errors are less than 0.05%.

关 键 词：挥发分 快速测量 耐火材料 人工神经元 红外水分仪 

分 类 号：TP216.1[自动化与计算机技术—检测技术与自动化装置]