A High Performance Voice Coil Actuator for Optomechatronic Applications
Bibliographic record
Abstract
Voice coil actuators (VCAs) are simple electro-mechanical devices, which are capable of generating linear motion in response to an electrical input. The generic cylindrical design of commercially available actuators imposes a large variety of limitations on the end user. The most prominent is the requirement to design and fit extra components to the actuator in order to increase functionality. To solve this issue, a novel voice coil actuator was created, which reconfigures the standard cylindrical design with one of a rectangular structure. The novel actuator incorporates planar magnets in a modified Halbach array configuration to ensure compactness and an exceptionally intense, uniform magnetic field. The moving coil is substituted with a printed circuit board (PCB) encompassing numerous current conducting traces. The board contains a miniature linear rail and bearing system, unified drive electronics, and highly adaptive position feedback circuitry resulting in a compact, highly dynamic and accurate device. In pursuit of optomechatronic applications, two distinct parallel kinematic mechanisms (PKMs) were developed to utilize the high dynamics and accuracy of the novel actuator. These devices were configured to function in only rotational degrees-of-freedom (DOF) and because of their underlying kinematic structures can be referred to as parallel orientation manipulators (POMs). In particular, two structures were defined, 2-PSS/U and 3-PSS/S, in order to constrain their payloads to two and three degrees of rotational freedom, respectively. The resultant manipulators are highly dynamic, precise and fulfill size, weight, and power requirements for many applications such as sense and avoidance and visual tracking.
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.
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".