Harvesting Energy From Aviation Data Lines: Implementation and Experimental Results
Bibliographic record
Abstract
Wiring is one of the main challenges in aircrafts. The avionics industry is exploring new schemes to minimize the number of power and data cables to build lighter, more reliable and fuel-efficient aircrafts. In this paper, we describe a novel integrated power harvesting interface to procure power required for avionic sensors. The implemented power harvesting approach is based on a modified power over Ethernet scheme in which the power in the ARINC 825 field (data) bus during its idle times serves as the source for the power conversion chain. A transistor-level design is carried out in CMOSP 0.35 μm (AMS) 3.3 V/5 V technology and the system performance is investigated under various conditions to improve its efficiency. From the experimental tests, an overall efficiency of 60 % was achieved and the harvesting device provided an output power of 10.08 mW for feeding sensors. Reported experimental results proved that the proposed power recovery scheme could serve as a power recovery unit to supply embedded sensors.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".