Reference-Free Response-Only Damage Identification in Bridges Using Relative Wavelet Entropy
Bibliographic record
Abstract
Bridges are designed and built to be safe against failure and to perform satisfactorily over their service life. To ensure safety and serviceability, it is essential to evaluate the structural performance of bridges through identification of potential damage at the earliest time possible. A vibration-based damage identification technique (DIT) that can detect structural damage, determine its location, and estimate its severity has been investigated in this research. The technique combines discrete wavelet transform (DWT) – a powerful signal processing tool for decomposition of signals – and spectral entropy in a relative procedure to detect and quantify the damage-induced disturbances in the measured dynamic response of bridges under ambient vibration. This relative wavelet entropy (RWE)-based DIT is a practical means for damage identification in in-situ cases, where the normal operation of bridges cannot be interrupted to perform dynamic excitation tests, and the data obtained from a reference (undamaged) state of the bridges are not available for comparison with the data measured from their current (damaged) state. Through its relative procedure, the technique has the advantage of mitigating undesirable effects of varying operational and environmental conditions on the damage detection process. In this research, the theoretical bases of the technique are presented, and its efficacy has been experimentally validated against false damage indications under varying operational and environmental conditions, such as the location of input dynamic excitation, location and extent of damage, support conditions, and temperature levels. The technique has also been implemented in small- and large-scale bridge specimens of various structural systems tested under different loading conditions. The test specimens included push-off columns, reinforced concrete beams, strengthened beams, precast concrete truss girders, slab-on-truss girder bridges, and post-tensioned concrete girders. The RWE-based DIT showed successful performance in identifying a wide variety of test-induced damage, including fracture in shear reinforcement, concrete cracking/crushing, debonding of strengthening sheets, rupture of truss elements’ confining tubes, and failure in truss connections. The technique has also been used to investigate the effects of pre-stressing on the dynamic behaviour of post-tensioned concrete girders to address the disagreement in the research community about the effectiveness of vibration-based DITs in pre-stress force identification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".