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Lamb wave line sensing for crack detection in a welded stiffener.

ABSTRACT: This paper proposes a novel Lamb wave line sensing technique for crack detection in a welded stiffener. The proposed technique overcomes one of the biggest technical challenges of Lamb wave crack detection for real structure applications: crack-induced Lamb waves are often mixed with multiple reflections from complex waveguides. In particular, crack detection in a welded joint, one of the structural hot spots due to stress concentration, is accompanied by reflections from the welded joint as well as a crack. Extracting and highlighting crack-induced Lamb wave modes from Lamb wave responses measured at multi-spatial points along a single line can be accomplished through a frequency-wavenumber domain analysis. The advantages of the proposed technique enable us not only to enhance the crack detectability in the welded joint but also to minimize false alarms caused by environmental and operational variations by avoiding the direct comparison with the baseline data previously accumulated from the pristine condition of a target structure. The proposed technique is experimentally and numerically validated in vertically stiffened metallic structures, revealing that it successfully identifies and localizes subsurface cracks, regardless of the coexistence with the vertical stiffener.

SUBMITTER: An YK

PROVIDER: S-EPMC4168411 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Lamb wave line sensing for crack detection in a welded stiffener.

An Yun-Kyu YK Kim Jae Hong JH Yim Hong Jae HJ

Sensors (Basel, Switzerland) 20140718 7

This paper proposes a novel Lamb wave line sensing technique for crack detection in a welded stiffener. The proposed technique overcomes one of the biggest technical challenges of Lamb wave crack detection for real structure applications: crack-induced Lamb waves are often mixed with multiple reflections from complex waveguides. In particular, crack detection in a welded joint, one of the structural hot spots due to stress concentration, is accompanied by reflections from the welded joint as wel ...[more]

PMID: 25046014

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Project description:BackgroundOcclusions of intravenous (IV) tubing can prevent vital and time-critical medication or solutions from being delivered into the bloodstream of patients receiving IV therapy. At low flow rates (≤ 1 ml/h) the alarm delay (time to an alert to the user) can be up to 2 h using conventional pressure threshold algorithms. In order to reduce alarm delays we developed and evaluated the performance of two new real-time occlusion detection algorithms and one co-occlusion detector that determines the correlation in trends in pressure changes for multiple pumps.MethodsBench-tested experimental runs were recorded in triplicate at rates of 1, 2, 4, 8, 16, and 32 ml/h. Each run consisted of 10 min of non-occluded infusion followed by a period of occluded infusion of 10 min or until a conventional occlusion alarm at 400 mmHg occurred. The first algorithm based on binary logistic regression attempts to detect occlusions based on the pump's administration rate Q(t) and pressure sensor readings P(t). The second algorithm continuously monitored whether the actual variation in the pressure exceeded a threshold of 2 standard deviations (SD) above the baseline pressure. When a pump detected an occlusion using the SD algorithm, a third algorithm correlated the pressures of multiple pumps to detect the presence of a shared occlusion. The algorithms were evaluated using 6 bench-tested baseline single-pump occlusion scenarios, 9 single-pump validation scenarios and 7 multi-pump co-occlusion scenarios (i.e. with flow rates of 1 + 1, 1 + 2, 1 + 4, 1 + 8, 1 + 16, and 1 + 32 ml/h respectively). Alarm delay was the primary performance measure.ResultsIn the baseline single-pump occlusion scenarios, the overall mean ± SD alarm delay of the regression and SD algorithms were 1.8 ± 0.8 min and 0.4 ± 0.2 min, respectively. Compared to the delay of the conventional alarm this corresponds to a mean time reduction of 76% (P = 0.003) and 95% (P = 0.001), respectively. In the validation scenarios the overall mean ± SD alarm delay of the regression and SD algorithms were respectively 1.8 ± 1.6 min and 0.3 ± 0.2 min, corresponding to a mean time reduction of 77% and 95%. In the multi-pump scenarios a correlation > 0.8 between multiple pump pressures after initial occlusion detection by the SD algorithm had a mean ± SD alarm delay of 0.4 ± 0.2 min. In 2 out of the 9 validation scenarios an occlusion was not detected by the regression algorithm before a conventional occlusion alarm occurred. Otherwise no occlusions were missed.ConclusionsIn single pumps, both the regression and SD algorithm considerably reduced alarm delay compared to conventional pressure limit-based detection. The SD algorithm appeared to be more robust than the regression algorithm. For multiple pumps the correlation algorithm reliably detected co-occlusions. The latter may be used to localize the segment of tubing in which the occlusion occurs. Trial registration Not applicable.

Dataset Information

Lamb wave line sensing for crack detection in a welded stiffener.

Publications

Lamb wave line sensing for crack detection in a welded stiffener.

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