Application of Improved HMM Algorithm in Slag Detection System

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 combination 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%.