Study on the Development of the Flexural Plate Wave (FPW) Accelerometer for the Continuous Damping Control System of an Automobile
Bibliographic record
Abstract
<div class="htmlview paragraph">Recently, as a automobile becomes more electronic and intelligent, MEMS(Micro Electro Mechanical System) sensors lead the technology and market of automotive sensor by overcome limitation of size, accuracy and reliability of mechanical sensors. Accelerometer, gyro, and pressure sensor are mainly studied MEMS sensor in the automobile field. Specially, intensification of safety regulation has increased the requirement and interest of the accelerometer. There are piezoelectric, piezoresistive, capacitive type in the sensing method of the accelerometer. Among these, piezoelectric method has high sensitivity feature with a simple manufacturing process.</div> <div class="htmlview paragraph">In this paper, we fabricated Flexural Plate Wave(FPW) accelerometer which sense frequency change of the vibrating piezoplate and found a optimum condition of the piezoplate shape and manufacturing condition to improve performances by using the design of experiment. Therefore, we altered the shape of the piezoplate to rectangular, bridge and bridge with mass structure and changed thickness of a piezoplate. We produced sensor assay with each of the conditions and measured sensitivity, non-linearity, noise, bias drift, cross-axis sensitivity and durability characteristics and then we conducted vehicle test with CDC system.</div>
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 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 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".