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Identification of Active and Passive Sources Using Elastic Waves and Computational Intelligence
Abstract
The application of structural health monitoring is determined by the received sensor data and the interaction between structure and environment. Due to this interaction, the raw signal will always include scattering and noise, which has to be processed and filtered efficiently. In this study, computational intelligence is used to recognize patterns in the sensor signal. To train the system and predict the location precisely, numerical simulations and physical experiments of various scenarios are performed in order to create a large database. Once the training process with numerical data is completed, the trained system is applied to new numerical and experimental data and will predict the impact and damage location. The result proves that computational intelligence is a promising method to localize arbitrary sources in real applications. Furthermore, the proposed work can be easily applied for various damage cases and structures and is supported by the strongly growing field of computational intelligence and big data analysis.
DOI
10.12783/shm2019/32381
10.12783/shm2019/32381