Output Estimation and Failure Detection in Cantilever Bimorph Actuator Using Transmissibility Operators
Bibliographic record
Abstract
Abstract In this article, we investigate how to identify faulty sensors in piezoelectric actuators used for precise positioning. Four sensors are distributed along the actuator’s cantilever structure to measure the deflection (displacement) at various points. We suggest identifying the sensor and detecting the fault in one of the sensors, which is thought to be faulty or producing a degraded signal. To address this, we suggest using transmissibility operators, which are mathematical estimators that estimate sensor measurements based on another set of sensor measurements within the same system. This estimation is highly robust against any external excitations/disturbances, as well as any unknown nonlinearities or unmodeled dynamics. The estimation robustness allows failure detection to be carried out even in significant actuator hysteresis nonlinearity and outside disturbance. Simulation results with various sensor fault conditions verified the suggested strategy.
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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 | 0.000 | 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".