Minimization of ambiguity in parametric fault diagnosis of analog circuits: A complex network approach

2012 ◽  
Vol 219 (1) ◽  
pp. 408-415 ◽  
Author(s):  
Hu Tan ◽  
Minfang Peng
Keyword(s):  
Fault Diagnosis ◽  
Complex Network ◽  
Analog Circuits ◽  
Network Approach ◽  
Parametric Fault

COMPLEX NETWORK APPLICATION IN FAULT DIAGNOSIS OF ANALOG CIRCUITS

2011 ◽  
Vol 21 (05) ◽  
pp. 1323-1330 ◽  
Author(s):  
MINFANG PENG ◽  
JIAJIA WANG ◽  
CHI K. TSE ◽  
MEIE SHEN
Keyword(s):  
Fault Diagnosis ◽  
Complex Network ◽  
Analog Circuits ◽  
Large Scale ◽  
Fault Simulation ◽  
Small World ◽  
Main Task ◽  
Electronic Circuits ◽  
Successful Isolation ◽  
High Degree

Fault diagnosis has played an important role in the identification of fault mechanisms and the subsequent successful isolation of faults in electronic circuits. In this paper, we propose a novel procedure for fault diagnosis in analog circuits. We first generate a set of fault patterns from fault simulation, and our main task is to develop a practical description of the way in which these fault patterns interact. Our approach is based on the construction of a complex network that describes the inter-dependence of the various fault patterns. Analysis of this complex network shows that the degree distribution is scalefree-like and the connectivity is small-world. We henceforth identify a small number of fault patterns that are most highly connected (of highest degrees) with other fault patterns. Furthermore, we study the connection between this network of fault patterns and the original circuit, the purpose being to relate the information of the high-degree fault patterns with the physical circuit topology, thus allowing the physical fault locations and circuit elements to be identified. Our proposed approach will find applications in automatic fault diagnosis of large-scale electronic circuits.

scholarly journals Parametric Fault Diagnosis of Analog Circuits Based on a Semi-Supervised Algorithm

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 228 ◽  
Author(s):  
Ling Wang ◽  
Dongfang Zhou ◽  
Hui Tian ◽  
Hao Zhang ◽  
Wei Zhang
Keyword(s):  
Fault Diagnosis ◽  
Analog Circuits ◽  
Health Management ◽  
Learning Algorithm ◽  
Training Model ◽  
Supervised Machine Learning ◽  
Fault Classification ◽  
Linear Discriminant ◽  
Diagnosis Rate ◽  
Parametric Fault

The parametric fault diagnosis of analog circuits is very crucial for condition-based maintenance (CBM) in prognosis and health management. In order to improve the diagnostic rate of parametric faults in engineering applications, a semi-supervised machine learning algorithm was used to classify the parametric fault. A lifting wavelet transform was used to extract fault features, a local preserving mapping algorithm was adopted to optimize the Fisher linear discriminant analysis, and a semi-supervised cooperative training algorithm was utilized for fault classification. In the proposed method, the fault values were randomly selected as training samples in a range of parametric fault intervals, for both optimizing the generalization of the model and improving the fault diagnosis rate. Furthermore, after semi-supervised dimensionality reduction and semi-supervised classification were applied, the diagnosis rate was slightly higher than the existing training model by fixing the value of the analyzed component.

scholarly journals Construction of an Expert System Based on Fuzzy Logic for Diagnosis of Analog Electronic Circuits

2015 ◽  
Vol 61 (1) ◽  
pp. 77-82 ◽  
Author(s):  
Damian E. Grzechca
Keyword(s):  
Fuzzy Logic ◽  
Fault Diagnosis ◽  
Expert System ◽  
Analog Circuits ◽  
Fuzzy Rule ◽  
Sensitivity Matrix ◽  
Fault Dictionary ◽  
Common Strategy ◽  
Parametric Fault ◽  
Rule System

Abstract The paper presents construction of the fuzzy logic system to analog circuits parametric fault diagnosis. The classical dictionary construction is replaced by fuzzy rule system. The first part refers to analog fault diagnosis, its techniques, approaches and goals. It clarifies common strategy and define differences between detecting, locating and identifying a fault in analog electronic circuit. The second part is focused on a creation of fuzzy rule expert system with use of sensitivity functions and known circuit topology. To detect, locate and identify a faulty element in a circuit the sensitivity matrix is used. The advantage of the method is its utilization in all, AC, DC and time domain. The fuzzy system, like the classical fault dictionary, can detect and locate single catastrophic faults and, on the contrary to the classical one, it also detects and locates parametric faults. Moreover, it allows identification of these faults, such that sign of the faulty parameter deviation is designated. The method has deterministic character as well as it can be applied on the verification and production stage

scholarly journals New Aspects of Fault Diagnosis of Nonlinear Analog Circuits

2015 ◽  
Vol 61 (1) ◽  
pp. 83-93 ◽  
Author(s):  
Michał Tadeusiewicz ◽  
Stanisław Hałgas ◽  
Andrzej Kuczyński
Keyword(s):  
Fault Diagnosis ◽  
Analog Circuits ◽  
Multiple Solutions ◽  
Analytical Form ◽  
Homotopy Continuation ◽  
Technological Parameters ◽  
Mathematical Algorithms ◽  
Parametric Fault ◽  
Nonlinear Analog Circuits ◽  
Nonlinear Analog

Abstract The paper is focused on nonlinear analog circuits, with the special attention paid to circuits comprising bipolar and MOS transistors manufactured in micrometer and submicrometer technology. The problem of fault diagnosis of this class of circuits is discussed, including locating faulty elements and evaluating their parameters. The paper deals with multiple parametric fault diagnosis using the simulation after test approach as well as detection and location of single catastrophic faults, using the simulation before test approach. The discussed methods are based on diagnostic test, leading to a system of nonlinear algebraic type equations, which are not given in explicit analytical form. An important and new aspect of the fault diagnosis is finding multiple solutions of the test equation, i.e. several sets of the parameters values that meet the test. Another new problems in this area are global fault diagnosis of technological parameters in CMOS circuits fabricated in submicrometer technology and testing the circuits having multiple DC operating points. To solve these problems several methods have been recently developed, which employ different concepts and mathematical tools of nonlinear analysis. In this paper they are sketched and illustrated. All the discussed methods are based on the homotopy (continuation) idea. It is shown that various versions of homotopy and combinations of the homotopy with some other mathematical algorithms lead to very powerful tools for fault diagnosis of nonlinear analog circuits. To trace the homotopy path which allows finding multiple solutions, the simplicial method, the restart method, the theory of linear complementarity problem and Lemke’s algorithm are employed. For illustration four numerical examples are given

scholarly journals A Tool for Single-Fault Diagnosis in Linear Analog Circuits with Tolerance Using the T-Vector Approach

VLSI Design ◽  
2008 ◽  
Vol 2008 ◽  
pp. 1-8
Author(s):  
José A. Soares Augusto ◽  
Carlos Beltrán Almeida
Keyword(s):  
Fault Diagnosis ◽  
Analog Circuits ◽  
Active Filter ◽  
Single Frequency ◽  
Single Fault ◽  
Parametric Faults ◽  
Linear Analog ◽  
Parametric Fault ◽  
Vector Approach

In previous works of these authors, a technique for doing single-fault diagnosis in linear analog circuits was developed. Under certain conditions, one of them assuming nominal values for the circuit parameters, it was shown that only two measurements taken on two selected circuit nodes, at a single frequency, were needed to detect and diagnose any parametric fault. In this paper, the practical value of the technique is improved by extending the application to the diagnosis of faults in circuits with parameters subject to tolerance. With this in mind, single parametric faults with several strengths are randomly injected in the circuit under study and, afterwards, these faults are diagnosed (or the diagnosis fails). Results are reported on a simple active filter. Conclusions are drawn about the robustness and effectiveness of the technique.

scholarly journals Complex network approach for detecting tropical cyclones

2021 ◽  
Author(s):  
Shraddha Gupta ◽  
Niklas Boers ◽  
Florian Pappenberger ◽  
Jürgen Kurths
Keyword(s):  
Sea Level ◽  
Tropical Cyclones ◽  
Complex Network ◽  
Time Scales ◽  
Southern Oscillation ◽  
Volcanic Eruptions ◽  
Network Approach ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Climate Networks

AbstractTropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the interactions among climate variables at different locations on the Earth’s surface, and in particular, time-evolving climate networks have been successfully applied to study different climate phenomena at comparably long time scales, such as the El Niño Southern Oscillation, different monsoon systems, or the climatic impacts of volcanic eruptions. Here, we develop and apply a complex network approach suitable for the investigation of the relatively short-lived TCs. We show that our proposed methodology has the potential to identify TCs and their tracks from mean sea level pressure (MSLP) data. We use the ERA5 reanalysis MSLP data to construct successive networks of overlapping, short-length time windows for the regions under consideration, where we focus on the north Indian Ocean and the tropical north Atlantic Ocean. We compare the spatial features of various topological properties of the network, and the spatial scales involved, in the absence and presence of a cyclone. We find that network measures such as degree and clustering exhibit significant signatures of TCs and have striking similarities with their tracks. The study of the network topology over time scales relevant to TCs allows us to obtain crucial insights into the effects of TCs on the spatial connectivity structure of sea-level pressure fields.

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