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Record W1624804537 · doi:10.1184/r1/6724094

Ultrasonic Techniques for Baseline-Free Damage Detection in Structures

2010· article· en· W1624804537 on OpenAlex
Debaditya Dutta

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResearch Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2010
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsnot available
FundersNational Research FoundationNational Research Foundation of KoreaCarnegie Mellon UniversityBombardierMinistry of Education, Science and TechnologyNational Science Foundation
KeywordsBaseline (sea)Ultrasonic sensorComputer scienceAcousticsArtificial intelligenceGeologyPhysics

Abstract

fetched live from OpenAlex

This research presents ultrasonic techniques for baseline-free damage detection in structures in the context of structural health monitoring (SHM). Conventional SHM methods compare signals obtained from the pristine condition of a structure (baseline signals) with those from the current state, and relate certain changes in the signal characteristics to damage. While this approach has been successful in the laboratory, there are certain drawbacks of depending on baseline signals in real field applications. Data from the pristine condition are not available for most existing structures. Even if they are available, operational and environmental variations tend to mask the effect of damage on the signal characteristics. Most important, baseline measurements may become meaningless while assessing the condition of a structure after an extreme event such as an earthquake or a hurricane. Such events may destroy the sensors themselves and require installation of new sensors at different locations on the structure. Baselinefree structural damage detection can broaden the scope of SHM in the scenarios described above. A detailed discussion on the philosophy of baseline-free damage detection is provided in Chapter 1. Following this discussion, the research questions are formulated. The organization of this document and the major contributions of this research are also listed in this chapter. Chapter 2 describes a fully automated baseline-free technique for notch and crack detection in plates using a collocated pair of piezoelectric wafer transducers for measuring ultrasonic signals. Signal component corresponding to the damage induced mode-converted Lamb waves is extracted by processing the originally measured ultrasonic signals. The damage index is computed as a function of this mode-converted Lamb wave signal component. An over-determined system of Lamb wave measurements is used to find a least-square estimate of the measurement errors. This error estimate serves as the damage threshold and prevents the occurrences of false alarms resulting from imperfections and noise in the measurement system. The threshold computation from only the measured signals is they key behind baseline-free damage detection in plates. Chapters 3 and 4 are concerned with nonlinear ultrasonic techniques for crack detection in metallic structures. Chapter 3 describes a nonlinear guided wave technique based on the principle of super-harmonic production due to crack induced nonlinearity. A semi-analytical method is formulated to investigate the behavior of a bilinear crack model. Upon comparing the behavior with experimental observations, it is inferred that a bilinear model can only partially capture the signal characteristics arising from a fatigue crack. A correlation between the extents of nonlinear behavior of a breathing crack with the different stages of the fatigue crack growth is also made in Chapter 3. In Chapter 4, a nonlinear system identification method through coherence measurement is proposed. A popular electro-magnetic impedance circuit was used to detect acoustic nonlinearity produced by a crack. Chapters 5 and 6 comprise the final part of this thesis where wavefield images from a scanning laser vibrometer are digitally processed to detect defects in composite structures. Once processed, the defect in the scanned surface stands out as an outlier in the background of the undamaged area. An outlier analysis algorithm is then implemented to detect and localize the damage automatically. In Chapter 5, exploratory groundwork on wavefield imaging is done by obtaining wave propagation images from specimens made of different materials and with different geometries. In Chapter 6, a hitherto unnoted phenomenon of standing wave formation in delaminated composite plates is observed and explained. Novel signal and image processing techniques are also proposed in this chapter, of which the isolation of standing waves using wavenumber-frequency domain manipulation and the use of Laplacian image filtering technique deserve special mention.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.254
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it