Adaptive D-based Active Power Line Filter for Industrial and Commercial Power Distribution
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
Harmonic disturbances caused by non-linear loads such as power switching devices often occur in the industrial and commercial power distribution systems and can damage sensitive equipment connected to the systems, causing tremendous productivity loss. This paper presents a novel adaptive-harmonic- detection active filter, consisting of an industry-type power electronic inverter controlled by state-of-the-art digital signal processor (DSP). This adaptive-detection DSP-based (adaptive D-based) filter provides effective elimination of power-line disturbances due to its efficient adaptive harmonic detection algorithm implemented with a fast response DSP control for various power-line conditions. The algorithm is based on a novel noise cancellation theory, originally not designed for power applications. This paper presents a practical formulation of the algorithm for utility applications that significantly simplifies the complex formulation originally for noise cancellations. Hardware and software implementations of this adaptive D-based filter are detailed. Simulation and experimental results are provided to demonstrate the effectiveness of this filter.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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