CFP last date
20 December 2024
Reseach Article

Automatic Fault Identification of a Mechanical System using Genetic Algorithm

by Abhishek Bal, Nilima Paul, Sonali Sen
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 104 - Number 9
Year of Publication: 2014
Authors: Abhishek Bal, Nilima Paul, Sonali Sen
10.5120/18232-9201

Abhishek Bal, Nilima Paul, Sonali Sen . Automatic Fault Identification of a Mechanical System using Genetic Algorithm. International Journal of Computer Applications. 104, 9 ( October 2014), 25-31. DOI=10.5120/18232-9201

@article{ 10.5120/18232-9201,
author = { Abhishek Bal, Nilima Paul, Sonali Sen },
title = { Automatic Fault Identification of a Mechanical System using Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 104 },
number = { 9 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 25-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume104/number9/18232-9201/ },
doi = { 10.5120/18232-9201 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:35:44.008066+05:30
%A Abhishek Bal
%A Nilima Paul
%A Sonali Sen
%T Automatic Fault Identification of a Mechanical System using Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 104
%N 9
%P 25-31
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper describes a fault identification technique for mechanical system which is based on genetic algorithm using training set. The real-world application of Genetic Algorithm (GA) to the key of engineering problem becomes a rapidly emerging approach in the field of control engineering and signal processing. Genetic algorithms are convenient for searching a space in multi-directional way from large spaces and poorly defined space. In this paper Genetic Algorithm is used to identify and evaluate the fault cases. Several methods are employed in the state of art in fault identification. Here one class of efficient method are investigated which is based on optimization technique. Here it is shown that Genetic Algorithm can be used to select smaller subset of features from the large set which together form a new set that can be successful for fault identification and classification tasks. The performance of this present proposed method has been verified through two types of fitness function, namely, square function and polynomial function. Finally, fault detection exercises are performed based on the training set to verify the feasibility of this proposed method. Experimental results show that the fault is distinguished with a high precision through this present work.

References
  1. Abhishek Bal, Nilima Paul, Suvasree Chakraborty, Sonali Sen, "Voice Matching using Genetic Algorithm", International Journal of Advanced Computer Research, Volume-4 Number-1 Issue-14,pages 305-312 March-2014.
  2. Georges R. Harik, Fernando G. Lobo, and David E. Goldberg ,"The Compact Genetic Algorithm", University of Illinois at Urbana-Champaign Urbana,IL 61801,IlliGAL Report No. 97006,August 1997.
  3. K. F. Man, Member, IEEE, K. S. Tang, and S. Kwong, "Genetic Algorithms: Concepts and Applications", Member, IEEE Transaction on Industrial Electronics, Vol-43, No-5, October 1996.
  4. Kumara Sastry(2), David Goldberg(2), Graham Kendall(3), "GENETIC ALGORITHMS",Springer,2. University of Illinois, USA, 3. University of Nottingham, UK, ?2005.
  5. Davis, L. D. (ed)," Genetic Algorithms and Simulated Annealing, Pitman publishing", London,1987.
  6. Sastry, K. , "Evaluation-relaxation schemes for genetic and evolutionary algorithms", Master's Thesis, General Engineering Department, University of Illinois at Urbana-Champaign, Urbana, IL,2001.
  7. Sastry, K. and Goldberg, D. E. , 2, Let's get ready to rumble: Crossover versus mutation head to head, in: Proc. 2004 Genetic and Evolutionary Computation Conf. II, Lecture Notes in Computer Science, Vol. 3103, Springer, Berlin, pp. 126–137,2004.
  8. Srivastava, R. and Goldberg, D. E. , Verification of the theory of genetic and evolutionary continuation, in: Proc. Genetic and Evolutionary Computation Conf. , pp. 551–558, 2001.
  9. David E. Goldberg, Addison-Wesley, "Genetic Algorithms in Search Optimization and Machine Learning", chapter 1-8, page 1-432, 1989.
  10. Randy L Haupt, "Practical genetic Algorithm", John Wiley and Sons Inc, chapter 1-7, page 1-251,2004.
  11. Artificial Intelligence: Course Content, Lecture hours– 42, RC Chakraborty, June 01, 2010. Available: http://www. myreaders. info/html/artificialintelligence. html.
  12. Goldberg, D. E. , "Genetic algorithms in Search, Optimization & Machine Learning", Addison-Wesley, New York, 1999.
  13. L. D. Goh, N. Bakharya, A. A. Rahmana, B. H. Ahmada, "Prediction of Unmeasured Mode Shape Using Artificial Neural Network for Damage Detection ",Goh et al. / Jurnal Teknologi (Sciences & Engineering) 61:1,vol 61 ,No 1,pages 57–66,12 February 2013 .
  14. F. T. K Au,Y. S Cheng,L. G. Tham,Z. Z. Bai, "Structural Damage Detection Based on a Micro-genetic Algorithm Using Incomplete and Noisy Model Test Data", Journal of Sound and Vibration. 259:1081-1094,2003.
  15. S. S. Law, T. H. T. Chan, D. Wu, "Efficient numerical model for the damage detection of large scale structure", Engineering Structures, Volume 23, Issue 5, Pages 436-451,2001.
  16. Chou, J. H. and Ghaboussi, J. , "Genetic Algorithm in Structural Damage Detection", Computers and Structures, Vol. 79, pp. 1335-1353, 2001.
  17. Raich, A. M. and Liszkai, T. R. , "Benefits of Applying and Implicit Redundant Representation Genetic Algorithm for Structural Damage Detection in Noisy Environments", Genetic and Evolutionary Computation Conference, Vol. 2724, pp. 2418-2419, 2003
  18. Mares, C. and Surace, C. , "An application of genetic algorithms to identify damage in elastic structures", Journal of Sound and Vibration, Vol. 195, No. 2, pp. 195-215, 1996.
  19. Mehul A. Shah,Joseph M. Hellerstein,Eric Brewer. ,"Highly Available, Fault-Tolerant, Parallel Dataflows",SIGMOD 2004 June 13-18, 2004.
  20. Klaus Echtle , Irence Eusgeld, "A Genetic Algorithm for Fault-Tolerant System Design",springer,LNCS 2847,pp. 197-213,2003
  21. Abhinav Saxena ,Ashraf Saad,"Genetic Algorithms for Artificial Neural Net-based Condition Monitoring System Design for Rotating Mechanical Systems",Journal of Applied Soft Computing, Volume 34,pp 135-149,2006.
Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm Fault identification Optimization Fitness Function Training set.