Application of Improved HMM Algorithm in Slag Detection System  

作　　者：TAN Da-peng LI Pei-yu PAN Xiao-hong 

机构地区：[1]College of Mechanical and Energy Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China [2]The Ministry of Education Key Laboratory of Mechanical Manufacture and Automation, Zhejiang University ofTechnology, Hangzhou 310032, Zhejiang, China

出　　处：《Journal of Iron and Steel Research International》2009年第1期1-6,共6页

基　　金：Item Sponsored by National Natural Science Foundation of China (50374061);863 National High Technology Program of China(2004AA-1Z2060)

摘　　要：To solve the problems of ladle slag detection system （SDS）, such as high cost, short service life, and inconvenient maintenance, a new SDS realization method based on hidden Markov model （HMM） was put forward. The physical process of continuous casting was analyzed, and vibration signal was considered as the main detecting signal according to the difference in shock vibration generated by molten steel and slag because of their difference in density. Automatic control experiment platform oriented to SDS was established, and vibration sensor was installed far away from molten steel, which could solve the problem of easy power consumption by the sensor. The combina- tion of vector quantization technology with learning process parameters of HMM was optimized, and its revaluation formula was revised to enhance its recognition effectiveness. Industrial field experiments proved that this system requires low cost and little rebuilding for current devices, and its slag detection rate can exceed 95%.To solve the problems of ladle slag detection system （SDS）, such as high cost, short service life, and inconvenient maintenance, a new SDS realization method based on hidden Markov model （HMM） was put forward. The physical process of continuous casting was analyzed, and vibration signal was considered as the main detecting signal according to the difference in shock vibration generated by molten steel and slag because of their difference in density. Automatic control experiment platform oriented to SDS was established, and vibration sensor was installed far away from molten steel, which could solve the problem of easy power consumption by the sensor. The combina- tion of vector quantization technology with learning process parameters of HMM was optimized, and its revaluation formula was revised to enhance its recognition effectiveness. Industrial field experiments proved that this system requires low cost and little rebuilding for current devices, and its slag detection rate can exceed 95%.

关 键 词：slag detection vibration measurement HMM vector quantization revaluation formula 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置] TN912.34[自动化与计算机技术—控制科学与工程]