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General Information
    • ISSN: 1793-8236 (Online)
    • Abbreviated Title Int. J. Eng. Technol.
    • Frequency:  Quarterly 
    • DOI: 10.7763/IJET
    • APC: 500 USD
    • Managing Editor: Ms. Shira. Lu 
    • Abstracting/ Indexing: Inspec (IET), CNKI Google Scholar, EBSCO, ProQuest, Crossref, Ulrich Periodicals Directory, Chemical Abstracts Services (CAS), etc.
    • E-mail: ijet_Editor@126.com
IJET 2012 Vol.5(1): 57-59 ISSN: 1793-8236
DOI: 10.7763/IJET.2013.V5.510

Application of Artificial Intelligence Techniques for Detection of Cracks-A Review

D. N. Thatoi, A. A. Ojha, A. Bhanjadeo, R. Mahapatra, S. Sahoo, and S. Mohapatra

Abstract—Detection of cracks using vibration analysis employs different algorithms out of which artificial intelligence (AI) techniques is drawing a lot of attention of the engineers and scientists. This paper presents a comprehensive review of various AI techniques for determining the location, size and depth of cracks in different structures. The techniques mainly consist of fuzzy interference technique, neural network (NN), genetic algorithm (GA), hybrid models and other optimization algorithms.

Index Terms—Genetic, hybrid models, neural network, swarm optimization.

The authors are with the S„O‟A University, Department of Mechanical Engineering, I. T. E. R., Bhubaneswar, Odisha (e-mail: massthatoi@gmail.com, aam4u123@gmail.com, auroprit182@gmail.com, mahapatra.rishav@gmail.com, sssagarsahoo@gmail.com, sarthakmohapatra90@gmail.com).

[PDF]

Cite: D. N. Thatoi, A. A. Ojha, A. Bhanjadeo, R. Mahapatra, S. Sahoo, and S. Mohapatra, "Application of Artificial Intelligence Techniques for Detection of Cracks-A Review," International Journal of Engineering and Technology vol. 5, no. 1, pp. 57-59, 2013.

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