Clonal fuzzy intelligent system for fault diagnosis of cracked beam. (June 2018)

• Record Type: Journal Article
• Authors: Parhi, Dayal R; Sahu, Sasmita
• Is Part Of: International journal of damage mechanics. Volume 27:Number 6(2018)
• Page Start: 840
• Page End: 858
• Publication Date: 2018-06
• Subjects: Crack -- fuzzy logic -- antibody -- antigen -- natural frequency; Fracture mechanics -- Periodicals; 620.1126
• DOI: 10.1177/1056789517708019
• Languages: English
• ISSNs: 1056-7895

Abstract

Cracks, faults, or damages are serious threat to the current and future performance of the system. For decades, research work is being carried out on the dynamic behavior of the structural elements for fault diagnosis. The modern types of damage detection methods use the dynamic response from the signals of the beams. In this article, a robust fault diagnostic tool based on clonal selection algorithm and fuzzy logic has been proposed. Theoretical and finite element analyses are done to model the crack and to find the effect of the presence of cracks changes on the vibrational characteristic (natural frequencies) of a fixed–fixed beam. The inputs to (Clonal Selection Algorithm-Fuzzy Logic) system are the first three relative natural frequencies and the outputs from the system are the relative crack depth and relative crack location. Experimental validations with the theoretical results have been carried out to check the robustness of the predicted algorithm.