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Structural health monitoring using modal strain energy damage indicator coupled with teaching-learning-based optimization algorithm and isogoemetric analysis
- Source :
- Journal of Sound and Vibration. 448:230-246
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- This paper proposes a two-stage approach for damage assessment in beam-like structures using two-dimensional Isogeometric Analysis (IGA) and Finite Element Method (FEM) combined with optimization techniques. In the first stage, the Local Frequencies Change Ratio (LFCR) indicator and a newly developed damage indicator based on normalized Modal Strain Energy Indicator (nMSEDI) are introduced to locate effectively the potential damaged elements. In order to verify nMSEDI, different scenarios based on single and multiple damages are studied using numerical experiments. In the second stage, the Teaching-Learning-Based Optimization Algorithm (TLBO) is utilized and its performance is compared with that of Particle Swarm Optimization (PSO) and Bat Algorithm (BA). The three optimizations techniques are combined with IGA using nMSEDI as objective function. In addition, experimental vibration tests using laboratory steel been are conducted to validate the proposed technique. The obtained results clearly indicate that the proposed approach can be used to determine accurately and efficiently both damage location and severity in beam-like structures.
- Subjects :
- Acoustics and Ultrasonics
Optimization algorithm
Computer science
Mechanical Engineering
Particle swarm optimization
02 engineering and technology
Isogeometric analysis
Inverse problem
Condensed Matter Physics
01 natural sciences
Finite element method
Vibration
020303 mechanical engineering & transports
0203 mechanical engineering
Mechanics of Materials
0103 physical sciences
Structural health monitoring
010301 acoustics
Algorithm
Bat algorithm
Subjects
Details
- ISSN :
- 0022460X
- Volume :
- 448
- Database :
- OpenAIRE
- Journal :
- Journal of Sound and Vibration
- Accession number :
- edsair.doi...........5ce205312afe40f23c9af61d59301892
- Full Text :
- https://doi.org/10.1016/j.jsv.2019.02.017