Structural Deflection Measurement with a Range Camera
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Range cameras offer great potential for the measurement of structural deformations because of their ability to directly measure video sequences of three-dimensional coordinates of entire surfaces, their compactness, and their relatively low cost compared with other active imaging technologies such as terrestrial laser scanners. Identified limitations of range cameras for high-precision metrology applications such as deformation measurement include the high (centimeter level) noise level and scene-dependent errors. This paper proposes models and methodologies to overcome these limitations and reports on the use of a SwissRanger SR4000 range camera for the measurement of deflections in concrete beams subjected to flexural load-testing. Results from three separate tests show that submillimeter precision and accuracy—assessed by comparison with estimates derived from terrestrial laser scanner data—can be achieved. The high-accuracy range camera results were realized by eliminating the systematic, scene-dependent bias of internal scattering through measurement differencing and by reducing the influence of random errors with temporal and spatial filtering strategies. Additional experiments to validate some of the fundamental modeling assumptions and to explain the possible causes of residual, submillimeter biases in the deflection estimates are also reported.
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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 | 0.001 | 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 it