CASE-BASED REASONING INTELLIGENT PREDICTION MODEL OF ROTARY KILN TEMPERATURE

Gongfa Li^{1, 2}, Jia Liu¹, Guozhang Jiang¹, Honghai Liu², Wentao Xiao¹

1College of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081 China

2Intelligent Systems and Biomedical Robotics Group, School of Creative Technologies, University of Portsmouth, PO1 2DJ, United Kingdom

Temperature is a key technical index in rotary kiln combustion process, which is so difficult to measure directly online. The offline analysis has large-time delay and poor precision. An intelligent prediction model of rotary kiln temperature based on case-based reasoning was developed, which consists of four modules: data collection and pre-treatment, prediction, online modification and effect estimate. The practical data of some rotary kiln were simulated. The industrial application results show that the prediction model can reflect the actual operation condition and meet the requirement of real-time control .Its effectiveness is proved evidently.