An Efficient Cuckoo Search Algorithm for System-Level Fault Diagnosis

XUAN Hengnong; ZHANG Runchi; SHI Shengsheng

doi:10.1049/cje.2016.06.035

Volume 25 Issue 6

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XUAN Hengnong, ZHANG Runchi, SHI Shengsheng, “An Efficient Cuckoo Search Algorithm for System-Level Fault Diagnosis,” Chinese Journal of Electronics, vol. 25, no. 6, pp. 999-1004, 2016, doi: 10.1049/cje.2016.06.035

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XUAN Hengnong, ZHANG Runchi, SHI Shengsheng, “An Efficient Cuckoo Search Algorithm for System-Level Fault Diagnosis,” Chinese Journal of Electronics, vol. 25, no. 6, pp. 999-1004, 2016, doi: 10.1049/cje.2016.06.035

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An Efficient Cuckoo Search Algorithm for System-Level Fault Diagnosis

doi: 10.1049/cje.2016.06.035

1.
School of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210046, China;
2.
Department of Computer Science and Technology, Nanjing University, Nanjing 210023, China

Funds: This work is supported by the National Natural Science Foundation of China (No.90718008, No.61133015).

Received Date: 2014-10-10
Rev Recd Date: 2015-08-14
Publish Date: 2016-11-10

Abstract

Abstract

We propose a new efficient algorithm named Cuckoo search fault diagnosis (CSFD) to solve system-level fault diagnosis problem. KMP algorithm is proposed for initialization based on the K-means partition algorithm; a fitness function is designed according to the equation constraints satisfied by the test model; the binary mapping method is advanced by optimizing existing binary mapping algorithm. Experiments show that KMP algorithm significantly reduces the disparity between the initial solution and the actual solution, and CSFD algorithm improves the efficiency and correctness significantly compared with existing typical swarm intelligence diagnosis algorithm.
- System-level fault diagnosis,
- Equation model,
- Cuckoo search,
- K-means clustering,
- Cuckoo search fault diagnosis algorithm (CSFD)

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References(15)

References

R. Zuech, et al., "Intrusion detection and big heterogeneous data: A Survey", Journal of Big Data, Vol.2, No.1, pp.1-41, 2015.

M. Chen, S. Mao and Y. Liu, "Big data: A survey", Mobile Networks and Applications, Vol.19, No.2, pp.171-209, 2014.

K. Kambatla, G. Kollias, V. Kumar, et al., "Trends in big data analytics", Journal of Parallel and Distributed Computing, Vol.74, No.7, pp.2561-2573, 2014.

FP. Preparata, G. Metze and RT. Chien, "On the connection assignment problem of diagnosable system", IEEE Trans on Electronic Computer, Vol.16, No.12, pp.848-854, 1967.

D.F. Zhang, G.G. Xie and Y.H. Min, "Node grouping in systemlevel fault diagnosis", Journal of Computer Science and Technology, Vol.16, No.5, pp.474-479, 2001.

H.N. Xuan, D.F. Zhang and M. Zhang, "The equation diagnosis on PMC fault model", Chinese Journal of Electronics, Vol.31, No.05, pp.694-697, 2003.

H.N. Xuan, M. Zhang, D.F. Zhang and T.X. Zhang, "Theoretical basis of equation diagnosis about Chwa & Hakimi fault models", Computer Applications, Vol.23, No.04, pp.16-18, 2003.

H.N. Xuan, et al., "The fault diagnosis algorithm and it's application about PMC model based on ex-test", Chinese Journal of Electronics, Vol.35, No.5, pp.987-990, 2007.

M. Elhadef, et al., "An evolutionary algorithm for identifying faults in t-diagnosable systems", Reliable Distributed Systems the 19th IEEE Symposium, Nurnberg, Germany, pp.74-83, 2000.

W. Deng, X.F. Yang and Z.F. Wu, "An efficient genetic algorithm for system-level diagnosis", Chinese Journal of Computers, Vol.30, No.7, pp.1115-1124, 2007.

R. Falcon, M. Almeida and A. Nayak, "A binary particle swarm optimization approach to fault diagnosis in parallel and distributed systems", Evolutionary Computation 2010 IEEE Congress, Barcelona, Spain, pp.1-8, 2010.

R. Falcon, et al., "Fault identification with binary adaptive fireflies in parallel and distributed systems", Evolutionary Computation 2011 IEEE Congress, New Orleans, USA, pp.1359-1366, 2011.

H.N. Xuan, R.C. Zhang, M. Zuo and T.T. Liu, "A hierarchical fault diagnosis algorithm for data center networks", Chinese Journal of Electronics, Vol.42, No.12, pp.2536-2542, 2014.

X.S. Yang and S. Deb, "Cuckoo search via Lévy flights", Nature & Biologically Inspired Computing 2009 World Congress, Coimbatore, India, pp.210-214, 2009.

X.S. Yang and S. Deb, "Engineering optimisation by cuckoo search", International Journal of Mathematical Modelling and Numerical Optimisation, Vol.1, No.4, pp.330-343, 2010.

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