Scanning Laser Source Technique and its Application to Turbine Disk Inspection

Kromine, Alexei K.; Fomitchov, Pavel A.; Krishnaswamy, Sridhar; Achenbach, Jan Drewes

doi:10.1007/978-1-4615-4791-4_47

Cited by 13 publications

(21 citation statements)

References 3 publications

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“…Interesting effects have also been observed in the measured frequencies during enhancement [4,12]. Preliminary results are shown in Figure 7, giving a kind of B-scan formed of fast Fourier transforms (FFTs) of the Rayleigh waves for a modelled crack of angle 10º and d/λ = 0.67.…”

Section: Scanning Laser Detectionmentioning

confidence: 86%

“…We present a study of this behaviour using two types of scanning techniques: scanning laser detection (as shown in Figure 3) and scanning laser source (SLS) [12]. Previous authors have reported enhancements for defects which are normal to the surface [2,4,6,12], while this section discusses this effect as the crack angle changes.…”

Section: Enhancement At a Defectmentioning

confidence: 97%

“…Another area of interest is the enhancement of the Rayleigh wave which occurs when scanning close to a crack edge [2,4,6,12], and whether this is also affected by crack angle. We present a study of this behaviour using two types of scanning techniques: scanning laser detection (as shown in Figure 3) and scanning laser source (SLS) [12].…”

Section: Enhancement At a Defectmentioning

confidence: 99%

“…Several authors have reported the observation of frequency changes when using the scanning laser source (SLS) technique, when the generation source is close to a surface crack [4,12]. In this type of scanning, the enhancement which occurs close to the crack is also partly due to source truncation, the free boundary conditions at the edge of the crack and interference effects.…”

Section: Scanning Laser Sourcementioning

confidence: 99%

“…For the purpose of this research we consider the use of non-contact ultrasound. Rayleigh waves are extremely useful for characterizing surface cracking [2][3][4][5][6][7][8][9][10][11][12][13], with an amplitude attenuating as r -1/2 , compared to r -1 for bulk waves, allowing measurements over a longer distance [14]. The particle motion is elliptical, with the out-of-plane (OP) component at the surface approximately 1.6 times the in-plane (IP) for aluminium [15].…”

Section: Introductionmentioning

confidence: 99%

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Defect Feature Extraction Using Surface Wave Interactions and Time-Frequency Behavior

Dutton

Rosli

Edwards

et al. 2010

AIP Conference Proceedings

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Original citation: Dutton, B., et al. (2010). Defect feature extraction using surface wave interactions and time-frequency behavior. AIP Conference Proceedings, 1211 (1) Copies of full items can be used for personal research or study, educational, or not-forprofit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. Publisher's statement:Copyright ( The following article appeared in Dutton, B., et al. (2010). Defect feature extraction using surface wave interactions and time-frequency behavior. AIP Conference Proceedings, 1211(1), pp. 647-654, and may be found at http://dx.doi.org/10.1063/1.3362455. A note on versions:The version presented here is a working paper or pre-print that may be later published elsewhere. If a published version is known of, the above WRAP url will contain details on finding it. ABSTRACT. In this paper we exploit the interaction of ultrasonic surface waves with surface cracks in order to extract defect characteristics. An experimentally validated computer model was developed to simulate laser generated surface waves interacting with defects of several depths and angles. The Rayleigh reflection coefficient vs. crack angle and depth was explored. Amplitude and frequency behaviour at the defect interface in aluminium samples was also considered. Additionally, the phase component of the FFT was used to extract similar information. Finally, we explore the time-frequency behaviour using the Wigner transform.

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Section: Scanning Laser Detectionmentioning

confidence: 86%