Structural health monitoring for intelligence structure: Damage feature

F. E. Gunawan*, Budiyan Mariyadi, Y. Kanto, T. H. Nhan, I. Kamil, Sutikno

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Structural Health Monitoring or SHM is a system to monitor and assess an engineering structure's integrity. It is crucial to avoid catastrophic failure, which often leads to material and immaterial loss. For the system to work, sensors should be placed on the structure to measure its deformation: strain, acceleration, velocity, or displacement. Then, the recorded data are analyzed to obtain damage-sensitive features, quantities for predicting structural reliability. Up to the present time, the widely used attributes are natural frequency and periodically deformation shapes. Vast engineers and scientists understand both. However, empirical evidence suggests the damage should have grown significantly to alter the natural frequency and mode shape to a detectable amount. This work intends to propose a damage attribute sensible to structural damages and better than the natural frequency. We derive the attribute from the classical theory of Euler-Bernoulli Beam and assess its performance empirically for the case involving a cracked beam. The beam responses with and without crack subjected to loads are computed numerically by the finite-element method. The assessed damage attribute is computed in the time domain at some observation points around the damaged area. The results are compared to those predicted by the change of natural frequency.

Original languageEnglish
Article number070013
JournalAIP Conference Proceedings
Issue number1
Publication statusPublished - 8 Aug 2023
Event13th International Seminar on Industrial Engineering and Management, ISIEM 2021 - Bandung, Indonesia
Duration: 28 Jul 2021 → …


  • Damage Feature
  • Euler-Bernoulli Beam
  • Machine Learning
  • Mode Shapes. Beam Deformation
  • Natural Frequency
  • Structural Health Monitoring (SHM)


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