Design of a hybrid proportional electromagnetic dynamic vibration absorber for control of idling engine vibration
Bibliographic record
Abstract
A hybrid proportional electromagnetic dynamic vibration absorber consisting of an electromagnetic actuator and an elastic element is proposed for control of engine vibration during idling. The design of the proportional electromagnetic actuator is realized considering the geometric parameters of the core to achieve nearly constant magnetic force over a broad range of its dynamic displacement but proportional to square of the current. The dynamic characteristics of the electromagnetic dynamic vibration absorber are analyzed analytically and experimentally. The effects of various geometric parameters of the actuator such as the slopes and width/height, and the air gaps on the resulting magnetic force characteristics are evaluated using a finite element model and verified experimentally. A methodology is proposed to achieve magnetic force proportional to current and consistent with the disturbance frequency. The hybrid proportional electromagnetic dynamic vibration absorber is subsequently applied to a single-degree-of-freedom primary system with an acceleration feedback control algorithm for attenuation of primary system vibration in a frequency band around the typical idling vibration frequencies. The effectiveness of the hybrid proportional electromagnetic dynamic vibration absorber is evaluated through simulations and laboratory experiments under harmonic excitations in the 20–30 Hz frequency range. Both the simulation and measurements show that the hybrid proportional electromagnetic dynamic vibration absorber can yield effective attenuation of periodic idling vibration in the frequency range considered.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".