Double exposure ESPI for non-contact surface topography tracking
Bibliographic record
Abstract
In this paper, we introduce an electronic speckle pattern interferometry (ESPI) method for rapid assessment of transient deformations on an opaque object. The method records the change in speckle patterns over time, which relate to the change in phase of the reflected light. The system was capable of high-speed recordings enabled by a camera capable of double exposure and external triggering. Experiments were performed on an opaque PDMS phantom to track rapid surface movements from a piezoelectric acoustic driver located at the back of phantom. Acoustic pulses of different period and amplitude were tested. In each double exposure recording cycle, the image pair were digitally subtracted to reveal the change in the speckle pattern, which represented the change in phase of the object beam relative to the reference. We developed custom software to process the data, including an algorithm to unwrap the phase maps. Experiments revealed an ultimate sensitivity to displacements of approximately 1 nm for signals ranging in period from 50 μs to 200 μs. Future work will examine the capabilities of the system with respect to surfaces with different optical absorption and scattering characteristics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".