Advanced Signal Processing for Thermal Flaw Detection

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Description

Dynamic thermography is a promising technology for inspecting metallic and composite structures used in high-consequence industries. However, the reliability and inspection sensitivity of this technology has historically been limited by the need for extensive operator experience and the use of human judgment and visual acuity to detect flaws in the large volume of infrared image data collected. To overcome these limitations new automated data analysis algorithms and software is needed. The primary objectives of this research effort were to develop a data processing methodology that is tied to the underlying physics, which reduces or removes the data interpretation requirements, and ... continued below

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92 pages

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VALLEY, MICHAEL T.; HANSCHE, BRUCE D.; PAEZ, THOMAS L.; URBINA, ANGEL & ASHBAUGH, DENNIS M. September 1, 2001.

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This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 26 times . More information about this report can be viewed below.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM, and Livermore, CA
    Place of Publication: Albuquerque, New Mexico

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Description

Dynamic thermography is a promising technology for inspecting metallic and composite structures used in high-consequence industries. However, the reliability and inspection sensitivity of this technology has historically been limited by the need for extensive operator experience and the use of human judgment and visual acuity to detect flaws in the large volume of infrared image data collected. To overcome these limitations new automated data analysis algorithms and software is needed. The primary objectives of this research effort were to develop a data processing methodology that is tied to the underlying physics, which reduces or removes the data interpretation requirements, and which eliminates the need to look at significant numbers of data frames to determine if a flaw is present. Considering the strengths and weakness of previous research efforts, this research elected to couple both the temporal and spatial attributes of the surface temperature. Of the possible algorithms investigated, the best performing was a radiance weighted root mean square Laplacian metric that included a multiplicative surface effect correction factor and a novel spatio-temporal parametric model for data smoothing. This metric demonstrated the potential for detecting flaws smaller than 0.075 inch in inspection areas on the order of one square foot. Included in this report is the development of a thermal imaging model, a weighted least squares thermal data smoothing algorithm, simulation and experimental flaw detection results, and an overview of the ATAC (Automated Thermal Analysis Code) software that was developed to analyze thermal inspection data.

Physical Description

92 pages

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  • Other Information: PBD: 1 Sep 2001

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  • Report No.: SAND2001-2959
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/787641 | External Link
  • Office of Scientific & Technical Information Report Number: 787641
  • Archival Resource Key: ark:/67531/metadc718833

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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Creation Date

  • September 1, 2001

Added to The UNT Digital Library

  • Sept. 29, 2015, 5:31 a.m.

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  • April 11, 2016, 1:20 p.m.

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VALLEY, MICHAEL T.; HANSCHE, BRUCE D.; PAEZ, THOMAS L.; URBINA, ANGEL & ASHBAUGH, DENNIS M. Advanced Signal Processing for Thermal Flaw Detection, report, September 1, 2001; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc718833/: accessed November 15, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.