ZHANG Qiang, CUI Pengfei, ZHANG Jixiong, ZHANG Hao, CHANG Tianjiao, YANG Junhui. Condition state characterization and self⁃identification control method of key equipment for intelligent solid backfilling[J]. Journal of China Coal Society, 2022, 47(12): 4237-4249.
Citation: ZHANG Qiang, CUI Pengfei, ZHANG Jixiong, ZHANG Hao, CHANG Tianjiao, YANG Junhui. Condition state characterization and self⁃identification control method of key equipment for intelligent solid backfilling[J]. Journal of China Coal Society, 2022, 47(12): 4237-4249.

Condition state characterization and self⁃identification control method of key equipment for intelligent solid backfilling

  • The most significant feature of solid backfilling mining technology is to rely on mechanical compaction to en⁃ sure the compactness of infill,which has some shortcomings of large workload,low degree of automation,and scat⁃ tered mining and backfilling processes. This restricts the large⁃scale application of solid backfilling mining technology, and urgently needs to be upgraded in the direction of intelligent solid backfilling. Based on the systematic anlysis of the research status of intelligent solid backfilling technology,it is clear that the basis of realizing intelligence is the accurate characterization and self⁃identification control of the working condition of key equipment such as backfill⁃ ing hydraulic support. By constructing a solid intelligent backfilling process flow with perception and identification as the core,and comparing the advantages and disadvantages of each characterization method and the applicable condi⁃ tions,an accurate characterization method for the working conditions of key equipment of intelligent solid backfilling based on MDH kinematics modeling is proposed. By means of combining theory with practice and parallel modeling and simulation,the working conditions of backfilling hydraulic support,multi⁃hole bottom discharge scraper conveyor and mechanism interference are defined,the discriminant function and the demodulation path of each equipment under abnormal conditions are revealed. The application and verification are carried out with the construction of intelligent solid backfilling working face in Hebei Xingdong Mine. The results show that compared with non⁃intelligent solid back⁃ filling,in a complete process cycle time,the self⁃identification and control time of working condition of single group backfilling equipment is reduced by 10 mins,and the backfilling efficiency is increased by more than 40%. The re⁃ search greatly improves the intelligent level and backfilling efficiency of solid backfilling technology,and provide a the⁃ oretical and technical basis for improving the solid backfilling system. Solid backfilling equipment has a variety of models,and the structure,size and inter⁃mechanism cooperation relationship of each model are different. The work⁃ ing condition characterization and self⁃identification control method proposed in this paper need to adjust the rele⁃ vant model structure parameters when applied to some specific models of solid backfilling equipment.
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