Digging force and power consumption during robotic excavation of cable shovel: experimental study and DEM simulation
Why this work is in the frame
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Bibliographic record
Abstract
Cable shovels are on the top priority of the most widely used machinery in open-pit mining industry, the automation of which offers great potential to improve both production efficiency and equipment reliability. Rational evaluations of digging force and power consumption serve as one of the fundamental techniques of realising autonomous operation of cable shovels. In this study, because of the wide range of digging parameters in theoretical calculation, the method of simulation is used to narrow the range of digging parameters in theoretical calculation, so that the digging force can be accurately and efficiently predicted by the method of theoretical calculation. Furthermore, scale-model-based experiments were taken in order to validate the effectiveness of the simulation results. Conclusively, although the theoretical calculation can numerically predict the power consumption in an acceptable extent (R2>0.85), the fitted value of unit resistance to excavation for the theoretical calculation was out of its empirical value range according to the classical theory applied to the prediction of digging resistance in the design of cable shovel. On the other hand, the simulation results were shown to be highly consistent with the experimental results (R2>0.9), which demonstrate the efficiency of the simulation method in evaluating dynamic working performance of cable shovels.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it