Application of vibration analysis of mining shovels for diggability assessment in open-pit operations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the past decades, technological advances and mining requirements have led to larger, more complex and more costly equipment. This trend in mining equipment has resulted in changing maintenance strategies from unplanned and scheduled maintenance to a condition-based maintenance (CBM) strategy. However, condition monitoring techniques used in CBM programmes are more than a maintenance management tool; they can provide the means to improve machine performance, production capacity and overall mine production. Vibration monitoring is usually the dominant technique of CBM programmes for critical machines such as electric rope shovels. It has been demonstrated that abnormal machine behaviour can be diagnosed using vibration monitoring techniques. However, this article aims to show the applicability of vibration monitoring of electric rope shovels for post-blast assessment rather than maintenance management. As a result, an electric rope shovel’s vibrations experienced by its boom during different operating ...
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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 | 0.001 | 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