Damage detection in structural elements: Using optimization of fuzzified rules. (2021)

• Record Type: Journal Article
• Authors: Bijeta Nayak, Bijaya; Sahu, Sasmita; Roy, Sudesna
• Is Part Of: Materials today. Volume 44:Part 1(2021)
• Page Start: 797
• Page End: 800
• Publication Date: 2021
• Subjects: Damage -- FuzzyLogic -- Genetic algorithm -- Structural -- Natural frequency; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2020.10.710
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Damage in forms of hairline cracks may occur during normal operations, deterioration or severe natural events. Due to the occurrence of cracks decreases lifetime of the product or system and in many large structural and machine elements, it may lead to dangerous catastrophic failure. There are various NDT methods which can be used for structural health monitoring but they take much down time and they are not cost effective also. Due to the above mentioned reasons, various researchers are getting attracted towards vibration based methods. For making the vibration based methods more efficient and effective, they can be combined with soft computing methods. In this research paper one of these types of method has been proposed. First the vibration features are collected from finite element analysis (FEA), then they are treated in the proposed method and the results are compared. Though FLS has already been used by several researchers, it has some loopholes. One of such shortcoming has been addressed in this paper while being used in the field of structural damage detection.