Ultrasonic Flaw Detection Using Signal Matching Techniques

  • Kannan Srinivasan
  • Chien-Ping Chiou
  • R. Bruce Thompson


Detection of hard-alpha inclusions in titanium has been a challenging problem for over two decades. Hard-alpha inclusions are brittle regions of microstructure usually resulting from oxygen or nitrogen contamination. During the high-stressed manufacturing process, these regions initiate cracks which are likely to grow during the service of the component, possibly leading to its failure. It becomes imperative, therefore, to detect these regions early in the manufacturing process. The detection, however, is compounded by the small contrast (consequently weak ultrasonic signal strength) of these inclusions, and the presence of high-level, correlated grain noise with spectral characteristics similar to hard-alpha inclusions. Earlier studies [1] based on model-generated simulation data have suggested that signal matching techniques are promising candidates for the detection of hard-alpha inclusions. One of the primary advantages in the use of these techniques lies in their ability to use flaw signals obtained by ultrasonic modeling as promising filter kernels.


Power Spectral Density Receiver Operating Characteristic Matched Filter Filter Kernel Ultrasonic Flaw Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Plenum Press, New York 1995

Authors and Affiliations

  • Kannan Srinivasan
    • 1
  • Chien-Ping Chiou
    • 2
  • R. Bruce Thompson
    • 3
  1. 1.Department of Aerospace Engineering and Engineering MechanicsIowa State UniversityAmesUSA
  2. 2.Center for Aviation Systems ReliabilityIowa State UniversityAmesUSA
  3. 3.Center for Nondestructive Evaluation and Department of Aerospace Engineering and Engineering MechanicsIowa State UniversityAmesUSA

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