A micromachined DC electric field sensor using a torsional micro mirror
Bibliographic record
Abstract
This thesis presents a MEMS dc electric field sensor with wide measurement range and adjustable sensitivity. The novel concept is applying two opposite bias voltage on the sensor surface causing to tilt, enabling operation without reference ground. The sensor mirror is mounted by torsional springs and fabricated using buck micro machining technology. With compared to earlier works with vertical moving MEMS sensors, higher sensitivity is achieved for the same bias voltage. The sensor has an adjustable linear measurement range from 10's V/m to MV/m, with no saturation. Employing on-board electronics to enable independent resonant operation, a resolution of 3.2 V/m was achieved. A portable semi automated measurement system was developed for outdoor electric field measurements. This overcomes the limit of electric field measurements for lab environments only. With the developed system, dc electric field tests were performed at University Manitoba High Voltage Laboratory, with and without corona presence to simulate an actual power line conditions. Promising results were obtained for future power industry related applications.
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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 | 0.000 | 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 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".