Progress in high-efficiency and energy-saving technologies for large-scale intelligent equipment in coal mines
Bibliographic record
Abstract
High-efficiency and energy-saving technologies for large-scale intelligent equipment in coal mines are a key driving force for industrial transformation and upgrading. Focusing on high-efficiency and energy-saving technologies in systems such as fully mechanized mining, transportation, hoisting, and power supply, this paper analyzes the latest research progress and key technologies across four areas: 10 kV voltage upgrades at fully mechanized working faces, intelligent high-efficiency variable frequency drive integrated units, electrification and underground charging/swap systems for mobile coal mine equipment, and shaft hoists with shaftless magnetic coupling drives. ① 10 kV power supply system upgrades at fully mechanized working faces can reduce voltage and electric energy losses. This requires optimized power system design, enhanced electrical safety and high-voltage equipment protection, and the application of safety performance testing technologies to ensure reliable operation. ② The intelligent high-efficiency variable frequency drive integrated unit combines variable frequency control and permanent magnet direct drive motor technology with intelligent control and predictive maintenance, improving operational efficiency, reliability, and energy savings while reducing equipment failure rates and maintenance costs. ③ Electrification of underground equipment relies on high-performance lithium batteries, digital drive-by-wire systems, autonomous driving, and intelligent dispatching. This achieves zero emissions, low noise, and high efficiency. Supported by standardized explosion-proof lithium battery power, rapid battery swapping, vehicle-charger coordination with full-time management, and emergency response mechanisms at charging/swap stations, the technology helps alleviate range anxiety in underground operations. ④ The shaftless magnetic coupling drive hoist enhances mine transport efficiency and equipment stability through an integrated magnetic coupling drive system, a multi-channel anti-shock safety braking system, and health management technologies for key components—addressing the low efficiency and high failure rates of traditional hoists.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".