Back to Search
Start Over
Soft Fault Diagnosis of Analog Circuit Based on EEMD and Improved MF-DFA
- Source :
- Electronics; Volume 12; Issue 1; Pages: 114
- Publication Year :
- 2022
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2022.
-
Abstract
- Aiming at the problems of nonlinearity and serious confusion of fault characteristics in analog circuits, this paper proposed a fault diagnosis method for an analog circuit based on ensemble empirical pattern decomposition (EEMD) and improved multifractal detrended fluctuations analysis (MF-DFA). This method consists of three steps: preprocessing, feature extraction, and fault classification identification. First, the EEMD decomposition preprocesses (denoises) the original signal; then, the appropriate IMF components are selected by correlation analysis; then, the IMF components are processed by the improved MF-DFA, and the fault feature values are extracted by calculating the multifractal spectrum parameters, and then the feature values are input to a support vector machine (SVM) for classification, which enables the diagnosis of soft faults in analog circuits. The experimental results show that the proposed EEMD-improved MF-DFA method effectively extracts the features of soft faults in nonlinear analog circuits and obtains a high diagnosis rate.
- Subjects :
- ensemble empirical pattern decomposition (EEMD)
multifractal
detrended fluctuations analysis (DFA)
support vector machines (SVM)
circuit fault diagnosis
Computer Networks and Communications
Hardware and Architecture
Control and Systems Engineering
Signal Processing
Electrical and Electronic Engineering
Subjects
Details
- Language :
- English
- ISSN :
- 20799292
- Database :
- OpenAIRE
- Journal :
- Electronics; Volume 12; Issue 1; Pages: 114
- Accession number :
- edsair.doi.dedup.....18e4e9b8b8b453644aee45ea6cb49ac0
- Full Text :
- https://doi.org/10.3390/electronics12010114