Experimental verification of improved probability of detection model considering the effect of sensor's location on low frequency electromagnetic monitoring signals

Haicheng Song, Noritaka Yusa

研究成果: Article査読

2 被引用数 (Scopus)

抄録

Structural health monitoring (SHM) is a promising method for maintaining the integrity of structures. A reasonable approach is necessary to quantify its detection uncertainty by taking into account the effect of random sensor locations on inspection signals. Recent studies of the authors proposed a model that adopts Monte Carlo simulation to numerically obtain the distribution of inspection signals influenced by random sensor locations. This model can evaluate the effect not only of multiple defect dimensions but also of the placement of sensors on the detection uncertainty. However, its effectiveness has only been confirmed using pseudo-experimental signals generated by artificial pollution. This study aims to examine the effectiveness of the proposed model in quantifying the detection uncertainty of SHM methods using the experimental signals of low frequency electromagnetic monitoring for inspecting wall thinning in pipes. The results confirm the capability of the proposed model to correctly characterize the distribution of inspection signals affected by random sensor locations and to determine the reasonable probability of detection.

本文言語English
ページ(範囲)377-384
ページ数8
ジャーナルInternational Journal of Applied Electromagnetics and Mechanics
64
1-4
DOI
出版ステータスPublished - 2020

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • 材料力学
  • 機械工学
  • 電子工学および電気工学

フィンガープリント

「Experimental verification of improved probability of detection model considering the effect of sensor's location on low frequency electromagnetic monitoring signals」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル