Source Localization

Jochen H. Kurz, Thomas Schumacher, Lindsay Linzer, Barbara Schechinger, Christian U. Grosse

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Scopus citations

Abstract

Quantitative methods in acoustic emission (AE) analysis require localization techniques to estimate the source coordinates of the AE events as accurately as possible. There are a number of different ways to localize AE sources in practice, i.e. to obtain the desired point estimate in one, two, or three dimensions. This chapter starts with approaches for automated onset detection since the travel time information is one of the most critical input parameters for most localization approaches. In general, most localization methods presented in this chapter have in common that the travel time information from source to receiver is used for localizing an AE source. Most of the methods of AE localization discussed here were developed in the framework of earthquake seismology and GPS techniques. Array-type approaches, which were designed especially for plate-like structures, are also discussed. Different techniques for one, two and three dimensional source localization are described. Approaches based on numerical inversions as well as grid search and array localization approaches are discussed. Further concepts developed or adapted for the AE localization problem presented in this chapter use, e.g., neural networks, probabilistic approaches, or direct algebraic methods from GPS technology. Localization accuracy is influenced by various factors. Therefore, how to determine localization errors and some measures to ensure high localization accuracy are also listed and discussed.

Original languageEnglish
Title of host publicationSpringer Tracts in Civil Engineering
PublisherSpringer Science and Business Media Deutschland GmbH
Pages117-171
Number of pages55
DOIs
StatePublished - 2022

Publication series

NameSpringer Tracts in Civil Engineering
ISSN (Print)2366-259X
ISSN (Electronic)2366-2603

Keywords

  • Array localization
  • Grid search
  • Inversion
  • Iterative localization
  • Localization errors
  • Nonlinear
  • Onset determination
  • Probabilistic
  • Source localization

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