Research on Fractal Method for Soft Fault Diagnosis of Nonlinear Analog Circuits

Research on Fractal Method for Soft Fault Diagnosis of Nonlinear Analog Circuits

Xinmiao LuHong Zhao Qiong Wu 

The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province, Harbin University of Science and Technology Harbin, China

Corresponding Author Email: 
lvxinmiao0611@126.com
Page: 
58-73
|
DOI: 
https://doi.org/10.18280/mmc_a.900105
Received: 
15 March 2017
|
Accepted: 
15 April 2017
|
Published: 
31 March 2017
| Citation

OPEN ACCESS

Abstract: 

The soft fault diagnosis of nonlinear analog circuits is an important guarantee of the stable and reliable operation of electronic products. In view of the low accuracy and heavy computation load of current soft fault diagnosis methods for nonlinear analog circuits, this paper presents a soft fault diagnosis method for nonlinear analog circuits based on fractal theory. Analyzing the single-fractal and generalized multi-fractal diagnosis mechanisms, and taking the fault signal as an example, the proposed method calculate the fractal dimension of the fault signal by the single-fractal box dimension and generalized multi-fractal dimension calculation method, and analyzes the influence of different frequency input signals on the features of the fault state signal through experimental simulation. It is concluded that the increasing frequency of the input signal has little effect on the fractal characteristics of the fault signal. Comparing the single-fractal and the generalized multi-fractal diagnosis method, the author discovers that the effect is better when generalized multi-fractal dimension sequence is used to diagnose the circuit fault.

Keywords: 

Single-fractal, generalized multi-fractal, feature extraction, fault diagnosis, nonlinearity

1. Introduction
2. Basic Principles of Fractal Theory
3. Research on Mechanisms of Fault Fractal Diagnosis
4. Simulation and Analysis of Fractal Dimension Feature Extraction
5. Conclusion
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