Analysis of Order Statistic Filters Applied to Ultrasonic Flaw Detection Using Split-Spectrum Processing

Jafar Saniie, Daniel T. Nagle, Kevin D. Donohue

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

Split-spectrum processing of broadband ultrasonic signals coupled with order statistic filtering has proven to be effective in improving the flaw-to-clutter ratio of backscattered signals. It has been shown that an optimal rank can be obtained with a prior knowledge of flaw-to-clutter ratio and the underlying distributions. The order statistic filter performs well where the flaw and clutter echoes have good statistical separation in a given quantile region representing a particular rank (e.g., minimum, median, maximum). Order statistic filters are analyzed for the situation in which the observations do not contain equivalent statistical information. Through simulation and experimental studies applied to ultrasonic flaw detection, the robustness of order statistic filters is evaluated.

Original languageEnglish
Pages (from-to)133-140
Number of pages8
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Volume38
Issue number2
DOIs
StatePublished - Mar 1991

Bibliographical note

Funding Information:
Manuscript received March 22, 1990; revlsed September 4, 1990; accepted September 27, 1990. This work was supported inpart by SDlOiIST funds managed under contract no. S40000RB01 by the Office of Naval Re-search Research. J. Saniie and D. T. Nagle are with the Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago. IL 60616. K. D. Donohue is with the Department of Electrical and Computer Engineering, Drexel University. Philadelphia, PA 19104. IEEE Log Number 9041515.

ASJC Scopus subject areas

  • Instrumentation
  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering

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