Power Harvesting for Rotating Structure Using Piezoelectric Generators
Bibliographic record
Abstract
Conventional method of measuring the mechanical properties of rotating machinery is to couple sensors on the machine through a slip ring, which is a non-trivial, expensive, lengthy and manpower intensive process. An alternative to this is to use a contactless RF slip ring which has no physical wear and hence no maintenance. But application of contactless RF slip ring is possible only if these services are low powered and sensor signals can be multiplexed. With the advance in low powered MEMS sensors, contactless slip ring system can be used. But providing power to these sensors is an issue. One approach would be to harness power from the untapped surrounding energy which could be used to recharge and/or replace battery powered connections. One method to accomplish this is to use piezoelectric materials (PZT) to capture energy lost due to vibration and rotation of the test equipment. This captured energy can then be used to provide uninterrupted power to the appropriate sensors. Focusing our attention on blades, rotating structures will be modeled as cantilever beam. Piezoelectric bimorph attached to the rotating cantilever beam will provide an estimate for the available power that can be used for harvesting.
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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 | 0.000 | 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) | 0.003 | 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".