DeepSHM: A deep learning approach for structural health monitoring based on guided Lamb wave technique

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Abstract

In our previous work, we demonstrated how to use inductive bias to infuse a convolutional neural network (CNN) with domain knowledge from fatigue analysis for aircraft visual NDE. We extend this concept to SHM and therefore in this paper, we present a novel framework called DeepSHM which involves data augmentation of captured sensor signals and formalizes a generic method for end-to-end deep learning for SHM. The study case is limited to ultrasonic guided waves SHM. The sensor signal response from a Finite-Element-Model (FEM) is pre-processed through wavelet transform to obtain the wavelet coefficient matrix (WCM), which is then fed into the CNN to be trained to obtain the neural weights. In this paper, we present the results of our investigation on CNN complexities that is needed to model the sensor signals based on simulation and experimental testing within the framework of DeepSHM concept.

Original languageEnglish
Title of host publicationSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019
EditorsJerome P. Lynch, Hoon Sohn, Kon-Well Wang, Haiying Huang
PublisherSPIE
Volume10970
ISBN (Electronic)9781510625952
DOIs
Publication statusPublished - 2019
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019 - Denver, United States
Duration: 4 Mar 20197 Mar 2019

Publication series

NameSENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2019
ISSN (Print)0277-786X

Conference

ConferenceSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019
CountryUnited States
CityDenver
Period4/03/197/03/19

Keywords

  • convolutional neural network (CNN)
  • damage classification
  • deep learning
  • Finite-Element-Modelling (FEM)
  • guided Lamb wave
  • signal processing
  • Structural Health Monitoring (SHM)

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  • Cite this

    Ewald, V., Groves, R. M., & Benedictus, R. (2019). DeepSHM: A deep learning approach for structural health monitoring based on guided Lamb wave technique. In J. P. Lynch, H. Sohn, K-W. Wang, & H. Huang (Eds.), Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019 (Vol. 10970). [109700H] (SENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2019). SPIE. https://doi.org/10.1117/12.2506794