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Structural Health Monitoring: Latest Applications and Data Analysis, 2nd Edition

This special issue belongs to the section “Civil Engineering“.

Special Issue Information

Dear Colleagues,

Following the positive reception of our previous Special Issue entitled "Structural Health Monitoring: Latest Applications and Data Analysis," we are delighted to present its continuation in the form of a second edition. Similar to the previous edition, this particular Special Issue is dedicated to the topic of Structural Health Monitoring (SHM), with a specific focus on its latest applications and corresponding data analysis. The surveillance of engineering structures is undoubtedly a key matter; however, it encompasses a vast and multidisciplinary scope. In this context, both novel sensor systems and techniques for measurement, data collection, and processing are relevant. Structural Health Monitoring (SHM) techniques comprise a range of technical diagnostic and nondestructive testing methods that are widely utilized. These methods include electromagnetic, high frequency, thermovision, radiography, ultrasound, and various others. Each of the aforementioned techniques poses distinctive challenges, not only in relation to the methodology of measurement but also with regard to data processing. Consequently, the processing of signals or images for the purpose of qualitative and quantitative evaluation of the structures being examined is of particular interest in this context.

Researchers in the broad domain of technical diagnostics and nondestructive testing are cordially invited to present their innovative contributions pertaining to the above-mentioned topics. All types of research are welcome, including theoretical and experimental studies, as well as comprehensive reviews and surveys.

Prof. Dr. Grzegorz Psuj
Dr. Barbara Grochowalska (Szymanik)
Guest Editors

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Keywords

  • structural health monitoring
  • electromagnetic nondestructive evaluation
  • technical diagnostics
  • magnetic methods
  • thermovision
  • high-frequency electromagnetic methods
  • ultrasound methods
  • radiography
  • multi-sensor measuring systems
  • sensors network
  • multi-source data mining and fusion
  • data processing
  • image processing
  • numerical modelling
  • optimisation
  • neural networks
  • machine vision
  • machine learning

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Appl. Sci. - ISSN 2076-3417