Fault Diagnosis Method for Analog Circuits Based on Matrix Perturbation Analysis

被引：0
|
作者：
Zhou Q. [1 ,2 ]
Xie Y. [2 ]
机构：
[1] School of Physics and Electronic Engineering, Yibin University, Yibin
[2] School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu
来源：
| 1600年 / Science Press卷 / 52期
关键词：
Analog circuit; Fault diagnosis; Fault model; Matrix perturbation; Parameter identification;
D O I：
10.3969/j.issn.0258-2724.2017.02.022
中图分类号：
学科分类号：
摘要：
To integrate the fault detection, fault localization and parameter identification of analog circuits in one system and reduce the cost and facilitate the engineering implementation of fault diagnosis, an fault diagnosis and parameter identification method for analog circuits based on matrix perturbation theory was proposed. First, curve fitting for the sampled time series of the faulty circuit was conducted, and the phase deviation of the circuit was treated as one fault signature. Then, a matrix was built using the sampled time series, and the trace of this matrix was used as the other fault signature. Finally, the phase deviation and trace were used as joint fault signatures, and the fault diagnosis model was established according to the correspondence between the changes of the fault signatures and the fault device parameter variations. The experimental results of two international standard circuits show that the accuracy of fault location ranges from 98.5% to 100% and the error of fault parameter identification is in the range of -1.2% to 1.72%. © 2017, Editorial Department of Journal of Southwest Jiaotong University. All right reserved.
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页码：369 / 378
页数：9
相关论文
共 19 条
  • [11] Zhang C., He Y., Yuan L., Approach for analog circuit incipient fault diagnosis based on KECA, Chinese Journal of Scientific Instrument, 36, 3, (2015)
  • [12] Ma C., Chen X., Analog circuit fault diagnosis based on attribute reduct ensemble of support vector machine, Chinese Journal of Scientific Instrument, 32, 3, pp. 660-666, (2011)
  • [13] Tadeusiewicz M., Halgas S., A new approach to multiple soft fault diagnosis of analog BJT and CMOS circuits, IEEE Transactions on Instrumentation and Measurement, 64, 10, pp. 2688-2695, (2015)
  • [14] Wang K., Wang N., A novel RNA genetic algorithm for parameter estimation of dynamic systems, Chemical Engineering Research and Design, 88, 1, pp. 1485-1493, (2010)
  • [15] Dionysios C., Scott D., Brian T., Genetic algorithm-based parameter identification of a hysteretic brushless exciter model, IEEE Transactions on Energy Conversion, 21, 1, pp. 148-154, (2006)
  • [16] Teng F., Lin X., Zhang C., Parameter identification and verification of dynamic P model based on nonlinear genetic algorithm, Chinese Journal of Scientific Instrument, 36, 5, pp. 1124-1130, (2015)
  • [17] Wilkinson J.H., The Algebraic Eigenvalue Problem, pp. 62-64, (1988)
  • [18] Griffiths D.J., Introduction to Quantum Mechanics, pp. 96-98, (2004)
  • [19] Kaminska B., Arabi K., Bell I., Analog and mixed-signal benchmark circuits: first release, Proc. ITC, pp. 183-190, (1997)
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