Gaussian Variance Filtering for Automatic Inspection of Gas Pipelines using Magnetic Flux Leakage Signal

가스 배관 자동 검사를 위한 자기 누설 신호의 가우시안 분산 필터링

  • Han, Byung-Gil (School of Electrical Engineering & Computer Science, Kyungpook National University) ;
  • Lee, Min-Ho (School of Electrical Engineering & Computer Science, Kyungpook National University) ;
  • Cho, Sung-Ho (KOGAS) ;
  • Rho, Young-Woo (KOGAS) ;
  • Choi, Doo-Hyun (School of Electrical Engineering & Computer Science, Kyungpook National University)
  • 한병길 (경북대학교 전자전기컴퓨터학부) ;
  • 이민호 (경북대학교 전자전기컴퓨터학부) ;
  • 조성호 (한국가스공사) ;
  • 노용우 (한국가스공사) ;
  • 최두현 (경북대학교 전자전기컴퓨터학부)
  • Published : 2006.06.21

Abstract

Magnetic Flux Leakage (MFL) inspection is a general non-destructive testing (NDT) method to detect the corrosion of natural gas pipelines. Currently, it is subjectively analyzed by trained analysts. In spite of investing much time and human resources, the inspection results may be different according to the analysts' expertise. So, many gas suppliers are keenly interested in the automation of the interpretation process. This paper presents a Gaussian variance filtering method of MFL signals, which is taken from MFL pigging of underground pipelines. In the proposed algorithm the original MFL signals are filtered by multiple Gaussians with different variance. Experimental results show that this approach does not need to align bias and to use explicit noise reduction algorithm.

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