Application of genetic algorithm for crack diagnosis of a free-free aluminum beam with transverse crack subjected to axial and bending load

Authors

  • Sanjay K. Behera Institute of Technical Education and Research, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India-751030
  • Dayal R. Parhi Department of Mechanical Engineering, National Institute of Technology, Rourkela, Odisha, India
  • Harish C. Das Mechanical Engineering Department, National Institute of Technology, Shillong, Meghalaya, India-793003

DOI:

https://doi.org/10.15282/jmes.12.3.2018.6.0337

Keywords:

Crack, natural frequency, mode shapes, numerical analysis, genetic algorithm

Abstract

A beam structure in presence of crack subjected to both bending and axial load has been investigated for damage diagnosis to predict crack location and crack depth based on an optimized intelligent technique using genetic algorithms approach. Numerical with experimental investigations have been conducted in a free-free beam model to calculate natural frequencies. In this work, genetic algorithm as an optimized artificial intelligent technique has been used which employs first three relative modal parameters like natural frequencies as input data taken from numerical and experimental results to obtain optimized crack locations and crack depths as output parameters. This methodology has been found to be quite reliable for fault diagnosis by monitoring the possible variations in the relative natural frequencies of a free-free beam element in presence of crack. This paper also gives an insight into the deviation of the results of the proposed methodology from the experimental result.

References

He Y, Guo D, Chu F. Using genetic algorithms and finite element methods to detect shaft crack for rotor-bearing system. Mathematics and computers in simulation. 2001;57(1-2):95-108.

Hao H, Xia Y. Vibration-based damage detection of structures by genetic algorithm. Journal of computing in civil engineering. 2002;16(3):222-229.

Krawczuk M. Application of spectral beam finite element with a crack and iterative search technique for damage detection. Finite Elements in Analysis and Design. 2002;38(6):537-548.

He RS, Hwang SF. Damage detection by an adaptive real-parameter simulated annealing genetic algorithm. Computers & Structures. 2006;84(31-32):2231-2243.

Perera R, Torres R. Structural damage detection via modal data with genetic algorithms. Journal of Structural Engineering. 2006;132(9):1491-1501.

Chen HG, Yan YJ, Chen WH, Jiang JS, Yu L, Wu ZY. Early damage detection in composite wingbox structures using Hilbert-Huang transform and genetic algorithm. Structural Health Monitoring. 2007;6(4):281-297.

Panigrahi SK, Chakraverty S, Mishra BK. Vibration based damage detection in a uniform strength beam using genetic algorithm. Meccanica. 2009;44(6):697.

Vakil-Baghmisheh MT, Peimani M, Sadeghi MH, Ettefagh MM. Crack detection in beam-like structures using genetic algorithms. Applied soft computing. 2008;8(2):1150-1160.

Saridakis KM, Chasalevris AC, Papadopoulos CA, Dentsoras AJ. Applying neural networks, genetic algorithms and fuzzy logic for the identification of cracks in shafts by using coupled response measurements. Computers & Structures. 2008;86(11-12):1318-1338.

Meruane V, Heylen W. A hybrid real genetic algorithm to detect structural damage using modal properties. Mechanical Systems and Signal Processing. 2011;25(5):1559-1573.

Nobahari M, Seyedpoor SM. Structural damage detection using an efficient correlation-based index and a modified genetic algorithm. Mathematical and Computer modelling. 2011;53(9-10):1798-1809.

Buezas FS, Rosales MB, Filipich CP. Damage detection with genetic algorithms taking into account a crack contact model. Engineering Fracture Mechanics. 2011;78(4):695-712.

Zhang Y, Randall RB. Rolling element bearing fault diagnosis based on the combination of genetic algorithms and fast kurtogram. Mechanical Systems and Signal Processing. 2009;23(5):1509-1517.

Agarwalla DK, Parhi DR. Effect of crack on modal parameters of a cantilever beam subjected to vibration. Procedia Engineering. 2013;51:665-669.

Behera RK, Parhi DR, Sahu SK. Vibration analysis of a cracked rotor surrounded by viscous liquid. Journal of Vibration and Control. 2006;12(5):465-494.

Das HC, Parhi DR. Online fuzzy logic crack detection of a cantilever beam. International Journal of Knowledge-based and Intelligent Engineering Systems. 2008;12(2):157-171.

Dash AK, Parhi DR. Analysis of an intelligent hybrid system for fault diagnosis in cracked structure. Arabian Journal for Science and Engineering. 2014;39(2):1337-1357.

Perera R, Ruiz A, Manzano C. Performance assessment of multicriteria damage identification genetic algorithms. Computers & Structures. 2009;87(1-2):120-127.

Friswell MI, Penny JE, Garvey SD. A combined genetic and eigensensitivity algorithm for the location of damage in structures. Computers & Structures. 1998;69(5):547-556.

Xiang J, Zhong Y, Chen X, He Z. Crack detection in a shaft by combination of wavelet-based elements and genetic algorithm. International Journal of Solids and Structures. 2008;45(17):4782-4795.

Zhang L, Jack LB, Nandi AK. Fault detection using genetic programming. Mechanical Systems and Signal Processing. 2005;19(2):271-289.

Singh SK, Tiwari R. Identification of a multi-crack in a shaft system using transverse frequency response functions. Mechanism and machine theory. 2010;45(12):1813-1827.

Nguyen N, Lee H. Bearing fault diagnosis using adaptive network based fuzzy inference system. In: International Symposium on Electrical & Electronics Engineering. Vietnam 2007;24-25.

Jena PK, Thatoi DN, Nanda J, Parhi DR. Effect of damage parameters on vibration signatures of a cantilever beam. Procedia engineering. 2012;38:3318-3330.

Parhi DR, Dash AK. Faults detection by finite element analysis of a multi cracked beam using vibration signatures. International Journal of Vehicle Noise and Vibration. 2010;6(1):40-54.

Parhi DR, Kumar DA. Analysis of methodologies applied for diagnosis of fault in vibrating structures. International Journal of Vehicle Noise and Vibration. 2009;5(4):271-286.

Parhi DR, Singh MK. Navigational strategies of mobile robots: a review. International Journal of Automation and Control. 2009;3(2-3):114-134.

Pothal JK, Parhi DR. Navigation of multiple mobile robots in a highly clutter terrains using adaptive neuro-fuzzy inference system. Robotics and Autonomous Systems. 2015;72:48-58.

Singh MK, Parhi DR. Path optimisation of a mobile robot using an artificial neural network controller. International Journal of Systems Science. 2011;42(1):107-120.

Pawar PM, Ganguli R. Genetic fuzzy system for online structural health monitoring of composite helicopter rotor blades. Mechanical Systems and Signal Processing. 2007;21(5):2212-2236.

Das HC, Parhi DR. Detection of the crack in cantilever structures using fuzzy gaussian inference technique. AIAA Journal. 2009;47(1):105-115.

Das HC, Parhi DR. Application of neural network for fault diagnosis of cracked cantilever beam. In: World Congress on Nature & Biologically Inspired Computing (NaBIC). 2009;1303-1308.

Sahu S, Parhi DR. An inverse approach of damage detection of beam like structure using intelligent hybrid fuzzy rule base system. Perspective in science. 2016.

Sahu S, Parhi DR. Performance comparison of genetic algorithm and differential evolution algorithm in the field of damage detection in crack structures. Journal of vibration engineering and technology. 2017;5(2).

Deepak BBVL, Parhi DR. Control of an automated mobile manipulator using artificial immune system. Journal of Experimental & Theoretical Artificial Intelligence. 2016;28(1-2):417-439.

Mohanty PK, Parhi DR. A new intelligent motion planning for mobile robot navigation using multiple adaptive neuro-fuzzy inference system. Applied Mathematics & Information Sciences. 2014;8(5):2527.

Pham DT, Parhi DR. Navigation of multiple mobile robots using a neural network and a Petri Net model. Robotica. 2003;21(1):79-93.

Pothal JK, Parhi DR. Navigation of multiple mobile robots in a highly clutter terrains using adaptive neuro-fuzzy inference system. Robotics and Autonomous Systems. 2015;72:48-58.

Parhi DR, Behera AK. Dynamic deflection of a cracked shaft subjected to moving mass. Transactions of the Canadian Society for Mechanical Engineering. 1997;21(3):295-316.

Jena PK, Thatoi DN, Nanda J, Parhi DRK. Effect of damage parameters on vibration signatures of a cantilever beam. Procedia engineering. 2012;38:3318-3330.

Behera RK, Pandey A, Parhi DR. Numerical and experimental verification of a method for prognosis of inclined edge crack in cantilever beam based on synthesis of mode shapes. Procedia Technology. 2014;14:67-74.

Thatoi DN, Das HC, Parhi DR. Review of techniques for fault diagnosis in damaged structure and engineering system. Advances in Mechanical Engineering. 2012;4:327569.

Parhi DR, Behera AK. Dynamic deflection of a cracked beam with moving mass. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 1997;211(1):77-87.

Pandey A, Sonkar RK, Pandey KK, Parhi DR. Path planning navigation of mobile robot with obstacles avoidance using fuzzy logic controller. IEEE 8th International Conference on Intelligent Systems and Control: Green Challenges and Smart Solutions. 2014;36-41.

Mohanty PK, Parhi DR. Cuckoo search algorithm for the mobile robot navigation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2013;8297 LNCS (PART 1):527-536.

Singh MK, Parhi DR, Bhowmik S, Kashyap SK. Intelligent controller for mobile robot: Fuzzy logic approach. In: The 12th International Conference of International Association for Computer Methods and Advances in Geomechanics (IACMAG). 2008;3:1755-1762.

Mohanty PK, Parhi DR. Optimal path planning for a mobile robot using cuckoo search algorithm. Journal of Experimental & Theoretical Artificial Intelligence. 2016;28(1-2):35-52.

Shaari MS, Ariffin AK, Takahashi A, Abdullah S, Kikuchi M, Akramin MRM. Fatigue crack growth analysis on square prismatic with embedded cracks under tension loading. Journal of Mechanical Engineering and Sciences. 2017;11(1):2511-2526.

Lau KT, Ahsan Q, Shueb MI, Othman R. Vibrational damping behaviors of graphene nanoplatelets reinforced NR/EPDM nanocomposites. Journal of Mechanical Engineering and Sciences. 2017;11(4):3274-3287.

Er-raoudi, M, Diany M, Aissaoui H, Mabrouki M. Gear fault detection using artificial neural networks with discrete wavelet transform and principal component analysis. Journal of Mechanical Engineering and Sciences. 2016;10(2):2006-2019.

Tezara C, Siregar JP, Lim HY, Fauzi FA, Yazdi MH, Moey LK, Lim JW. Factors that affect the mechanical properties of kenaf fiber reinforced polymer: A review. Journal of Mechanical Engineering and Sciences. 2016;10(2):2159-2175.

Yusof MFM, Kamaruzaman MA, Zubair M, Ishak M. Detection of defects on weld bead through the wavelet analysis of the acquired arc sound signal. Journal of Mechanical Engineering and Sciences. 2016;10(2):2031-2042.

Fauzi F, Ghazalli Z, Siregar J. Effect of various kenaf fiber content on the mechanical properties of composites. Journal of Mechanical Engineering and Sciences. 2016;10:2226-33.

Tada H, Paris PC, Irwin GR. The stress analysis of cracks. Handbook, Del Research Corporation. 1973.

Downloads

Published

2018-09-30

How to Cite

[1]
S. K. Behera, D. R. Parhi, and H. C. Das, “Application of genetic algorithm for crack diagnosis of a free-free aluminum beam with transverse crack subjected to axial and bending load”, J. Mech. Eng. Sci., vol. 12, no. 3, pp. 3825–3851, Sep. 2018.