A Detection Sensitivity Analysis Model for Structural Health Monitoring to Inspect Wall Thinning considering Random Sensor Location

Haicheng Song, Noritaka Yusa

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Structural health monitoring (SHM), which allows the detection of defects at an early stage by attaching sensors to the target, is an effective method of enhancing the reliability and the safety of important engineering structures. One of the practical difficulties of SHM is that usually a large area must be monitored using a limited number of sensors fixed at certain locations. And the sensor placement is a decisive contributor to the detection capability of SHM because measured signals generally depend on the location of a defect with respect to a sensor. In order to quantify the detection sensitivity more reasonably, this study proposes an analytical method based on a closed-form probability density function and a numerical method based on Monte Carlo simulation to quantify the detection sensitivity, taking into account the randomness of sensor location. The effectiveness of the proposed detection sensitivity analysis model has been examined using simulated inspection signals of low frequency electromagnetic monitoring for detecting full circumferential pipe wall thinning.

Original languageEnglish
Pages (from-to)74-87
Number of pages14
JournalResearch in Nondestructive Evaluation
Volume32
Issue number2
DOIs
Publication statusPublished - 2021

Keywords

  • detection sensitivity
  • Finite element simulation
  • sensor placement

ASJC Scopus subject areas

  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering

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