Paper Title
Efficient Method for Identification of Cracks in Beams Using Fuzzy With Neural Network
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Keywords
Keywords: Cracked beam, Damage Identification, Neural Network, optimization and stiffness
Abstract
Structures like beams failure can be avoided by identifying the damage in the structure at its beginning and proper retrofitting. Recently, the researchers created a structure to recognize crack damage in beams in view of a cracked beam componentmodel, it originates from thefracture mechanicsand local flexibility rules. The present work exhibits the simulation analysis of cracked beam with machine learning model to assess the stiffness of the structure. Here Fuzzy Optimal Neural Network (FONN) is considered, in addition, the stiffness reduction technique, especially concerning thick beams, is featured in addition with a survey of other crack models. The extricated modal data are utilized to conversely recognize the cracks with the cracked beam component model through a model updating technique. The optimal NN based stiffness computation utilizes a global searching procedure utilizing Adaptive Elephant Herding Optimization (AEHO) the number of cracks identified from various beams. From the proposed model, the attained results are compared with the current research paper and other optimization, machine learning models.
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How To Cite (APA)
D.Pitchaiah, CH.Ramesh , & B.Suvarna Raju (November-2023). Efficient Method for Identification of Cracks in Beams Using Fuzzy With Neural Network. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(11), e110-e119. https://ijnrd.org/papers/IJNRD2310415.pdf
Issue
Volume 8 Issue 11, November-2023
Pages : e110-e119
Other Publication Details
Paper Reg. ID: IJNRD_208737
Published Paper Id: IJNRD2310415
Downloads: 000122253
Research Area: Mechanical EngineeringÂ
Author Type: Indian Author
Country: prakasam, andhra pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2310415.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2310415
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