Optimal Method for Identification of Cracks in Different Beams using Fuzzy with Elephant Based Neural Network
D. Pitchaiah1, Putti Srinivasa Rao2

1Dasaripalli.Pitchaiah*, Research Scholar, Mechanical Engineering Department, Andhra University, Visakhapatnam, India.
2Dr. Putti Srinivasa Rao, Professor of Mechanical Engineering, Andhra University College of Engineering, Andhra University, Visakhapatnam, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 3357-3364 | Volume-9 Issue-2, December 2019. | Retrieval Number: A5013119119/2019©BEIESP | DOI: 10.35940/ijitee.A5013.129219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Failure of Structures i.e., beams 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 using a cracked beam component model that originates from the fracture mechanics and local flexibility rules. The present work exhibits the analysis of cracked beam with a 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 with a survey of other crack models. The extricated model data are utilized to conversely recognize the cracks with the cracked beam component model through a model updating technique. The optimal Neural Network based stiffness computation utilizes a global searching procedure using Adaptive Elephant Herding Optimization (AEHO) to identify the number of cracks in various beams. From the proposed model, the attained results are compared with the existing research work, and other optimization and machine learning models. 
Keywords: Cracked Beam Component Model, Neural Network, Adaptive Elephant Herding Optimization, Machine Learning models.
Scope of the Article:  Machine learning