| Summary: | In view of problem of low production efficiency of artificial drawing method on fully-mechanized coal face with sublevel caving, an automatic drawing control system was studied.Sonic sensors, vibrating sensors and ash sensors are installed on hydraulic supports. Through artificial demonstration operation and machine learning to memory sensor signals, sensor signal characteristic waveform during the end of drawing process is determined, and the similarity between collected vibration sensing signal, sound sensing signal and the characteristic signal is compared; the ash sensor is used to effectively identify inclusion rate of caved top coal. According to the similarity and inclusion rate, the system execute early warning or direct control to realize automatic drawing control which taking sensor-based sensing control as main control, time control as protection value, and remote intervention control as auxiliary control. The system improves automation level and production efficiency of fully-mechanized coal face with sublevel caving.
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