Experimental validation of LS-SVM based fault identification in analog circuits using frequency features

Lecture Notes in Mechanical Engineering

Volumn 9, Issue , 2014, Pages 629-641

  Vasan, A S ^a   Long, B ^a,b   Pecht, M ^a,c  

^a UNIVERSITY OF MARYLAND   (United States)

^b UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^c CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

SUPPORT VECTOR MACHINES; TIMING CIRCUITS;

COMPONENT VARIATIONS; DETECTION AND IDENTIFICATIONS; DIVERSE FIELDS; ELECTRONICS SYSTEM; EXPERIMENTAL VALIDATIONS; FAULT IDENTIFICATIONS; FREQUENCY FEATURES; RELIABLE ELECTRONICS; SOFT FAULTS; TOLERANCE RANGE;

ANALOG CIRCUITS;

EID: 84951055711     PISSN: 21954356     EISSN: 21954364     Source Type: Book Series    
DOI: 10.1007/978-1-4471-4993-4_54     Document Type: Chapter

References (26)

1. Birolini A (1997) Quality and reliability of technical systems. Springer, New York
2. Li F, Woo PY (2002) Fault detection for linear analog IC—the method of short-circuits admittance parameters. IEEE Trans Circuits Syst 49(1):105–108
3. Alippi C, Catelani M, Fort A, Mugnaini M (2002) SBT soft fault diagnosis in analog electronic circuits: a sensitivity-based approach by randomized algorithms. IEEE Trans Instrum Meas 51(5):1116–1125
4. Williams A, Taylor F (2006) Electronic filter design handbook. McGraw-Hill, New York
5. Yang C, Tian S, Long B, Chen F (2011) Methods of handling the tolerance and test-points selection problem for analog-circuit fault diagnosis. IEEE Trans Instrum Meas 60(1):176–185
6. Mei H, Hong W, Geng H, Shiyuan Y (2007) Soft fault diagnosis for analog circuits based on slope fault feature and BP neural network. Tsinghua Sci Technol 12(S1):26–31
7. Halgas S (2008) Multiple soft fault diagnosis of nonlinear circuits using the fault dictionary approach. Bull Pol Acad Sci 56(1):53–57
8. Zhou L, Shi Y, Zhao G, Zhang W, Tang H, Su L (2010) Soft-fault diagnosis of analog circuit with tolerance using mathematical programming. J Commun Comp 7(5):50–59
9. Cui J, Wang Y (2011) A novel approach of analog circuit fault diagnosis using support vector machines classifier. Measurement 44:281–289
10. Spina R, Upadhyaya S (1997) Linear circuit fault diagnosis using neuromorphic analyzers. IEEE Trans Circuits Syst II 44:188–196
11. Aminian M, Aminian F (2000) Neural-network based analog-circuit fault diagnosis using wavelet transform as preprocessor. IEEE Trans Circuits Syst II 47(2):151–156
12. Aminian F, Aminian M (2002) Analog fault diagnosis of actual circuits using neural networks. IEEE Trans Instrum Meas 51(3):544–550
13. Mohamed EA, Abdelaziz AY, Mostafa AS (2005) A neural network-based scheme for fault diagnosis of power transformers. Electr Power Syst Res 75(1):29–39
14. Huang J, Hu X, Yang F (2011) Support vector machine with genetic algorithm for machinery fault diagnosis of high voltage circuit breaker. Measurement 44:1018–1027
15. Mao X, Wang L, Li C (2008) SVM classifier for analog fault diagnosis using fractal features. In: Proceedings of the 2nd IEEE international symposium on intelligent information technology and application, pp 553–557
16. Scholkopf B, Smola A (2002) Learning with kernels-support vector machines, regularization, optimization and beyond. MIT Press, Cambridge
17. Suykens J, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9(3):293–300
18. Hsu CW, Lin CJ (2002) A comparison of methods for multi-class support vector machines. IEEE Trans Neural Networks 13(2):415–425
19. Long B, Tian SL, Wang HJ (2008) Least squares support vector machine based analog circuit fault diagnosis using wavelet transform as preprocessor. In: Proceedings of the international conference on communications, circuits and systems, pp 1026–1029
20. Lei Z, Ligang H, Wang Z, Wuchen W (2010) Applying wavelet support vector machine to analog circuit fault diagnosis. In: Proceedings of the 2nd workshop on education, technology and computer science, pp 75–78
21. Vapnik K (1995) The nature of statistical learning theory. Springer, New York
22. Welch P (1967) The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust 15(2):70–73
23. Aminian M, Aminian F (2007) A modular fault-diagnostic system for analog electronic circuits using neural networks with wavelet transform as preprocessor. IEEE Trans Instrum Meas 56(5):1546–1554
24. Yuan L, He Y, Huang J, Sun Y (2010) A new neural-network-based fault diagnosis approach for analog circuits by using kurtosis and entropy as a preprocessor. IEEE Trans Instrum Meas 59(3):586–595
25. Xiao Y, He Y (2011) A novel approach for analog fault diagnosis based on neural networks and improved kernel PCA. Neurocomputing 74:1102–1115
26. Toczek W, Zielonko R, Adamczyk A (1998) A method for fault diagnosis of nonlinear electronic circuits. Measurement 24:79–86