Adaptive neuro-fuzzy-based vibration approach for structural fault diagnosis

• Main Authors: Hakim, S. J. S., Kamarudin, A. F., Mokhatar, S. N., Jaini, Z. M., Umar, S., Mohamad, N., Jamaluddin, N.
• Format: Article
• Language: English
• Published: Penerbit UTHM 2022
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/99022/1/SarehatiUmar2022_AdaptiveNeuroFuzzyBasedVibrationApproach.pdf; http://eprints.utm.my/id/eprint/99022/; https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/9723
• Institution: Universiti Teknologi Malaysia

In recent times, damage identification based on vibration methods are emerging as common approaches, in which the techniques apply the vibration response of a monitored structure, such as modal frequencies and damping ratios, to evaluate its condition and detect structural damage. The basis of the vibration-based health monitoring method is that when there are alterations in the physical characteristics of a structure, there will also be changes in its vibration properties. This paper proposed a neuro-fuzzy artificial intelligence method, called adaptive neuro-fuzzy inference system (ANFIS), to detect damage using modal properties. To generate the modal characteristics of the structures, experimental study and finite element analysis of I-beams with single damage cases were performed. The results showed that the ANFIS approach was able to detect the magnitude and location of the damage with a significant degree of precision, and notably reduced computational time.