Sign least mean squares-based deconvolution technique for ultrasonic testing

Mohammed Siddig*, Kim Ki-Seong

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

Sign LMS algorithms, members of the simplified adaptive least-mean-squares class, have been developed to reduce computational complexity and simplify hardware implementation. These advantages make them suitable to utilize in ultrasonic testing units, a class of applications requiring simple and efficient signal processing algorithms. This paper proposes a specific sign LMS adaptive filters-based deconvolution technique for ultrasonic straight beam pulse-echo inspections. It extracts only two of the interface echoes multiple reflections for enhanced resolution and quality-enriched presentation; this technique is named "selective deconvolution". Resolution enhancement and presentation's quality enrichment performance among the different sign LMS algorithms were investigated by experiments, and based on performance, the methods themselves were compared. Computational requirements are also presented. The proposed technique with the various adaptive sign LMS filters gave satisfactory results.

Original languageEnglish
Pages (from-to)609-613
JournalRussian Journal of Nondestructive Testing
Volume48
Issue number10
DOIs
Publication statusPublished - Oct 2012
MoE publication typeA1 Journal article-refereed

Funding

This study was supported by the Ministry of Knowledge Economy (MKE) through the Regional Inno vation Centre program.

Keywords

  • adaptive LMS
  • resolution
  • selective deconvolution
  • sign LMS

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