Low cost Design for Current Regulator with High Capacity and Precision
Bibliographic record
Abstract
In many industrial and research applications, devices need to operate under constant current (CC) conditions, where voltage precision is not required. For some applications such as reliability testing of solder joints needed in electronics, we aim to maximize the number of devices-under-test (DUTs). In contrast to testing these DUTs in series using one CC supply, the DUTs need to be tested with individual current sources so that the failure of one DUT does not disturb the testing of the others. This makes the scaling of CC power supplies a necessary but expensive endeavor. To address this issue, we present a low cost solution for an adjustable constant current regulator (CCR) device with high current capacity. The final build cost of the current regulator was CAD 56.14. Specifications include 10 A maximum current, an accuracy of ±25 mA, and a precision of ± 50 uA. The maximum power output of the device is found to be 15.925 W.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".