Enhanced Ultrasonic Flaw Detection using an Ultra-high Gain and Time-dependent Threshold

Yongfeng Song, Joseph A Turner, Zuoxiang Peng, Chen Chao, Xiongbing Li

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In an attempt to improve the ultrasonic testing capability of a conventional C-scan system, a flaw detection method using an ultra-high gain is developed in this paper. A time-dependent threshold for image segmentation is applied to identify automatically material anomalies present in the sample. A singly-scattered response (SSR) model is used with extreme value statistics to calculate the confidence bounds of grain noise. The result is a time-dependent threshold associated with the grain noise that can be used for segmentation. Ultrasonic imaging experiments show that the presented method has advantages over a traditional fixed threshold approach with respect to false positives and missed flaws. The results also show that a low gain is adverse to the detection of micro-flaws with subwavelength dimensions. The forward model is expected to serve as an effective tool for the probability of detection (POD) of flaws and the inspection of coarse-grained materials in the future.

Original languageEnglish (US)
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
DOIs
StateAccepted/In press - Apr 17 2018

Fingerprint

ultrasonic flaw detection
high gain
Ultrasonics
Defects
thresholds
defects
ultrasonics
nondestructive tests
Ultrasonic imaging
Ultrasonic testing
inspection
confidence
Image segmentation
Acoustic noise
statistics
anomalies
Inspection
Statistics
Experiments

Keywords

  • Acoustics
  • Backscatter
  • Extreme value theory
  • Grain noise statistics
  • Image segmentation
  • Inspection
  • Microstructure
  • Scattering
  • Solids
  • Time-dependent threshold
  • Transducers
  • Ultra-high gain
  • Ultrasonic C-scan

ASJC Scopus subject areas

  • Instrumentation
  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering

Cite this

Enhanced Ultrasonic Flaw Detection using an Ultra-high Gain and Time-dependent Threshold. / Song, Yongfeng; Turner, Joseph A; Peng, Zuoxiang; Chao, Chen; Li, Xiongbing.

In: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 17.04.2018.

Research output: Contribution to journalArticle

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