Characterization and autonomous control method of abnormal working conditions of super-long flexible suspended solid backfilling scraper conveyor

Abstract

Solid backfilling scraper conveyor is a key equipment of solid backfilling mining technology, and the degree of its high efficiency and intelligence restricts the development of solid intelligent backfilling mining technology. Currently, it is difficult to break through the bottleneck of high power, super-large mining and high reliability. The operating state is significantly affected by the main controlling factors such as geological conditions and filling process. The problem of autonomous control of abnormal working conditions needs to be solved urgently. The characteristics of solid backfilling scraper conveyor is summarized, and the posture and conveyance state characterization method of solid backfilling scraper conveyor is developed. By analyzing the formation principle of abnormal working conditions, selecting the discriminant index of abnormal working conditions, and combined with the characterization method of posture and conveyance state, the discriminant criteria of abnormal working conditions of the spatial posture and traction state of the scraper conveyor and the adjustment and control path of typical abnormal working conditions are given. The mechanism of conveyance control of solid backfilling scraper conveyor under multi-working conditions is revealed, and the efficient autonomous control method for abnormal working conditions is proposed to real-time control the transportation volume of backfilling materials, the straight line and horizontal extent. The first 260-meter-long solid filling project in China shows that through the autonomous control of abnormal working conditions, for every 100 mm reduction in horizontal offset, the traction is reduced by 85 kN and the transmission power loss is reduced by 55 kW, when the maximum vertical offset is reduced by 100 mm, the conveying power loss can be reduced by 7.2 kW, and for every 100 kN/m reduction in the mass of the cargo per unit length, the traction is reduced by 31.9 kN and the transmission power loss is reduced by 38.2 kW. The proposed autonomous control method of abnormal working conditions can significantly improve the conveying efficiency of solid backfilling scraper conveyor, and can help realize intelligent solid backfilling mining.

Keywords

• solid backfilling scraper conveyor
• condition characterization
• self-regulation
• condition identification
• path demodulation
• backfill mining