Crack Identification at the Welding Joint with Frequency Comparison Function Method
Bibliographic record
Abstract
A methodology named Frequency Comparison Function (FCF) is developed and studied to realize the crack identification with high sensitivity in the welding joint area for a beam-type structure. This method is derived from Frequency Response Function (FRF) by replacing the excitation data with the response signal recorded from a designated point of the test structure, then the standard deviation value of the FCF is calculated to detect and evaluate the possible crack or local damage-induced vibration signal perturbations. Finite element analysis of a welded beam structure is first conducted in ANSYS to obtain the vibration responses on two sides of the weld joint, which are then analyzed with FCF algorithm. It is concluded that FCF is applicable with breathing crack identification and it is fast and efficient with no required data pre-progressing, like the filtering and smoothing functions, and hence can be used for real-time crack detection. By employing the smart coating sensor composed of piezoelectric patches, a high sensitivity crack identification is realized, and the crack is detectable at its very early stage (3% of the beam thickness).
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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".