Computational simulation and experimental verification of a new vibration-based structural health monitoring approach using piezoelectric sensors
Why this work is in the frame
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Bibliographic record
Abstract
Detection of damage in vital and high-cost infrastructures has been one of the major concerns of operators of such structures in the past two decades. The growing demands in oil and gas have forced extraction of such vital fuels in deep waters. Bolted joints are widely used in pipes transporting oil and gas in deep waters. However, they do develop in-service problems, such as loosened bolts, which if remained undetected, could cause significant environmental damage and economical loss, especially in the case of pipes used in deep-water oil extraction. In this study, the energy damage index (EDI) calculated based on a novel vibration-based damage detection methodology using the empirical mode decomposition (EMD) is used to establish the existence of damage due to loosened bolts in common industrial bolted joints. A complete finite element (FE) model is established to simulate the whole process using the implicit dynamic solver of the commercial software ABAQUS © . Also, a comprehensive experimental program was designed and carried out to verify the FE results. Results show that the EDI based on the EMD method is a powerful tool for not only detecting the damage, but also the progression of the damage in bolted joints.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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