Replacing coal with gangue and achieving zero gangue discharge is one of the core goals of green mine construction in China. A research team led by Professors Yang Kang and Zhang Qiang from China University of Mining and Technology published a landmark study in the international academic journal Applied Sciences, systematically proposing for the first time a new model for solid backfill coal mining based on a fully closed-loop intelligent architecture of "perception-decision-execution." Targeting the pain points of traditional solid backfill mining technology—low production efficiency, high labor intensity, and high costs—the study deploys six core subsystems across the entire chain from the surface to the underground, successfully achieving a synergistic closed loop between intelligent underground jig separation (coal content in rejects <4%) and intelligent backfilling at the working face. This has doubled the monthly output of the working face and increased backfilling efficiency by 50%, marking China's leap from "following" to "leading" in the global field of green and intelligent backfill mining.

The Dual Dilemma of Green Intelligent Backfilling

Solid backfill mining technology has demonstrated significant advantages in solid waste disposal, mining of coal under buildings, railways, and water bodies ("three unders"), and dynamic disaster control. However, the large-scale promotion and application of this technology have long been constrained by three major bottlenecks: low production efficiency, high unit production costs, and high labor intensity. Traditional solid backfill mining technology suffers from core bottlenecks such as a low degree of autonomous operation and insufficient adaptive regulation capabilities, resulting in a low level of intelligence that severely impacts its application effectiveness and scope. Meanwhile, traditional gangue backfilling also struggles to meet the dual requirements of backfill quality and efficiency for intelligent working faces in terms of gangue separation accuracy and efficiency, necessitating a technological leap through systematic intelligent upgrades.

Four Intelligent Subsystems Precisely Deconstruct the Entire Backfilling Chain

Using a combination of literature review, theoretical analysis, and field measurements, the research team proposed for the first time an intelligent architecture based on the entire chain of "surface—feeding—underground separation—working face," constructing a closed-loop energy control architecture centered on "perception-decision-execution," equipped with six core subsystems. Among these, the technological breakthroughs in four key intelligent subsystems constitute the core innovative pillars of this study.

1. Intelligent Surface Gangue Preprocessing System: Source Control and Process Digitalization

Traditional surface backfill material preparation has long suffered from low automation, heavy dust, and excessive human intervention. The self-developed intelligent surface gangue preprocessing system integrates four functions: automatic washing of autonomous vehicles, intelligent spray dust suppression at transfer points, dynamic metering during conveying, and adaptive adjustment of the feeding system. This system not only achieves full digitalization and transparency of material sources but also eliminates dust pollution at the source, providing a solid "first threshold" for the stable operation of underground processes.

2. Intelligent Underground Jig Separation System: Coal Content in Rejects <4%, Unlocking the Key to "Zero-Waste" Mines

In-situ underground gangue separation is a critical link in green backfill mining. The research team successfully developed an intelligent underground jig separation system featuring intelligently adjustable jigging frequency, intelligently measurable and controllable bed thickness, and intelligently proportioned air volume. This core subsystem achieves two revolutionary effects. First, a revolutionary improvement in separation accuracy: the system stably controls the coal content in rejects below 4%, reaching the internationally recognized advanced level of underground gangue discharge and effectively avoiding the waste of coal resources. Second, it completes the "mine cycle" closed loop: combined with the full-bin alarm and level adjustment functions of the surface-to-underground vertical gangue feeding system, it truly achieves the core green mining goal of gangue not being lifted to the surface or discharged above ground, fundamentally eliminating the long-term ecological hazards of surface gangue dumps.

3. Intelligent Solid Backfilling System for the Working Face: Monthly Output Doubled, Efficiency Increased by 50%

The team constructed a fully closed-loop intelligent control architecture for the backfilling working face, coupling PLC control with PID algorithms. Engineering practice data shows that this system doubles the monthly output of the working face, increases backfilling efficiency by 50%, and reduces the number of operators per shift by 8 to 10 people. This significant achievement is primarily attributed to the automatic organization of mining and backfilling processes, intelligent judgment of the interference state of the tamping mechanism, and real-time perception and decision optimization of backfilling parameters, greatly shortening the ratio of backfilling efficiency to fully mechanized mining efficiency and successfully resolving the fundamental contradiction of "mining-backfilling imbalance" in traditional backfill mining.

4. Intelligent Backfilling Effect and Mine Pressure Monitoring System: Controllable Mine Pressure and Zero Surface Subsidence

The ultimate goal of intelligent backfilling is to achieve effective control of strata movement and surface subsidence. The integrated intelligent backfilling effect monitoring platform and mine pressure feedback network achieve precise mine pressure control at the working face and accurate prediction of surface deformation through real-time monitoring of backfill bearing capacity and roof activity. Engineering practice indicates that the weighted mine pressure coefficient at the working face is only 1.12, and surface subsidence is precisely controlled within the allowable range of the national first-level building (structure) protection standard. This fundamentally solves the industry problem of "backfill design based on experience and uncontrollable surface subsidence" in traditional backfill mining.

Reshaping the Global Logic of Green Intelligent Mining in the Coal Industry

The breakthrough significance of this research goes far beyond the efficiency improvement of a single working face or a single coal mine; it will profoundly reshape the future landscape of the coal industry from three strategic dimensions.

First, establishing a "closed-loop ecosystem" industrial paradigm for coal mining. By intelligently separating and in-situ backfilling underground gangue, this technology constructs a complete closed-loop system of "replacing coal with gangue and zero gangue discharge," signifying that coal mining is no longer a simple resource consumption process but a circular industry of solid waste disposal and resource replacement. This model completely solves the long-standing ecological problem of surface gangue storage that has plagued hundreds of large mines in China for decades.

Second, overcoming the technical barriers to large-scale safe mining of coal under "three unders." A vast amount of high-quality coal resources in eastern China has long been covered by buildings, water bodies, and railways. Through intelligent precision backfilling and roof control, this technology controls surface subsidence below the limit standard, providing a strictly engineering-verified complete set of solutions for the economic, safe, and green development of massive "three unders" coal resources, offering crucial technical reserves for national energy security.

Third, defining the "China Standard" for global intelligent green mines. This achievement has established an intelligent standard architecture covering the entire chain of "surface preprocessing—underground separation—working face backfilling—mine pressure monitoring," and has systematized the configuration schemes and key technical frameworks of the six core subsystems under different backfilling modes. China has taken the lead in completing the critical leap from "mechanization" to "intelligence" in this field, exporting a replicable and scalable "China Solution" for the sustainable transformation of the global coal industry.

The modular and replicable advantages of this technology mean it has extremely high adaptability potential for coal mines under various production and geological conditions. The research team points out that with the deep integration of cutting-edge technologies such as image recognition and machine learning in backfill mining (e.g., visual prediction of gangue volume and intelligent compaction rate control), as well as the realization of full-process self-driving capabilities for intelligent backfill support robots, coal mine backfill mining is about to enter a new phase of "fully unmanned, fully adaptive" smart mines, providing key strategic technical support for the green and low-carbon transformation of the coal industry under the guidance of carbon neutrality goals.