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Fault Classification Research of Analog Electronic Circuits Based on Support Vector Machine

D.F. Chen
2016 Chemical Engineering Transactions  
sample cloud model generation method, and the use of neural network expansion sample sets the newly created training.  ...  The results show that the new sample training practiced neural network has better noise robustness.  ...  improve the diagnosis of neural networks, they modular neural network (small scale neural network combined method) for diagnosis, and the result was 100%.  ... 
doi:10.3303/cet1651223 doaj:c6ed97a867d34583a2d9baa2b6482720 fatcat:qpvcaypwwjgcnndclyqzwyhdcq

Testability Evaluation in Time-Variant Circuits: A New Graphical Method

Marco Bindi, Maria Cristina Piccirilli, Antonio Luchetta, Francesco Grasso, Stefano Manetti
2022 Electronics  
Computer programs, based on symbolic analysis techniques, are used for both the testability analysis and the neural network training phase.  ...  DC–DC converter fault diagnosis, executed via neural networks built by exploiting the information deriving from testability analysis, is the subject of this paper.  ...  Testability analysis is fundamental for neural network-based fault diagnosis techniques. The training phase, typical of neural networks, is performed on the inputs of the network.  ... 
doi:10.3390/electronics11101589 fatcat:dlbbuwybkzdgvjnpbmhlusts4q

A Neural Network Classifier with Multi-Valued Neurons for Analog Circuit Fault Diagnosis

Igor Aizenberg, Riccardo Belardi, Marco Bindi, Francesco Grasso, Stefano Manetti, Antonio Luchetta, Maria Cristina Piccirilli
2021 Electronics  
The work combines machine learning techniques, used for classification and approximation, with testability analysis procedures for analog circuits.  ...  In this paper, we present a new method designed to recognize single parametric faults in analog circuits.  ...  MLMVN: multilayer neural network; LINFTA: linear invariant network fast testability analysis. Figure 1 . 1 Block diagram of the fault diagnosis system.  ... 
doi:10.3390/electronics10030349 fatcat:m4qq23w2z5e2xdabyh2sfxha4a

Determination of an optimum set of testable components in the fault diagnosis of analog linear circuits

G. Fedi, S. Manetti, M.C. Piccirilli, J. Starzyk
1999 IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications  
Index Terms-Analog system fault diagnosis, analog system testing, fault location.  ...  A procedure for the determination of an optimum set of testable components in the fault diagnosis of analog linear circuits is presented.  ...  For example, if a technique based on neural networks is used [9] , the presented procedure can be very useful for sizing (that is for the choice of the neuron number) and for training the neural network  ... 
doi:10.1109/81.774222 fatcat:e52fisfzxrawpahb4nomysriru

Multi Frequency Approach to Analog Fault Diagnosis using Pole Sensitivity Analysis

Venu Madhava Rao S.P.
In this paper an efficient algorithm using multi-frequency approach has been applied to fault diagnosis of analog electronic circuits using Pole Sensitivity analysis.  ...  In this paper, after application of the multi frequency approach to the pole sensitivity analysis the results show that the fault diagnosis of the circuit has increased.  ...  Baoru et. al in [10] proposed a tolerance analog circuit hard and soft fault diagnosis method based on adoptive learning rate and additional momentum algorithm BP neural network.  ... 
doi:10.24297/ijmit.v7i1.711 fatcat:6ljhzvuwonerzhceanilcchq2q

Soft Fault Clustering in Analog Electronic Circuits with the Use of Self Organizing Neural Network

Damian Grzechca
2011 Metrology and Measurement Systems  
The paper presents a methodology for parametric fault clustering in analog electronic circuits with the use of a self-organizing artificial neural network.  ...  The method proposed here allows fast and efficient circuit diagnosis on the basis of time and/or frequency response which may lead to higher production yield.  ...  However, there are known Kohonen neural network approaches to hard-fault diagnosis of analog circuits based on the observation of the power supply current [36, 37] .  ... 
doi:10.2478/v10178-011-0054-8 fatcat:fsiyqolkk5cjddkbc5mzb4rfuy

Fault Diagnosis in Analog Circuits via Symbolic Analysis Techniques [chapter]

Fawzi M, Bessam Z
2013 Analog Circuits  
Solution of Large Networks by Matrix Methods. John Wiley and Sons . [ ] Liao W, Liu J. Research on k-Fault Diagnosis and Testability in Analog Circuit.  ...  With recent sharp development of electronic design automation tools and widespread application of analog VLSI chips and mixed-signal systems in the area of wireless communication, networking, neural network  ...  The stopping criterion for the above procedure can simply be τ the testability measure found from the symbolic analysis.  ... 
doi:10.5772/53643 fatcat:jbgq7pyvtrg7rnrbedq2pokeum

Electronic Circuits Diagnosis Using Artificial Neural Networks [chapter]

Miona Andrejevi, Vano Litovski
2009 Micro Electronic and Mechanical Systems  
Neural-network based analog-circuit fault diagnosis using wavelet transform as preprocessor, IEEE Transactions on CAS -II: Analog and Digital Signal Processing, Vol. 47, No. 2, February 2000, pp. 151-156  ...  Analog Fault Diagnosis of Actual Circuits Using Neural Networks, IEEE Trans. On Instrumentation and Measurement, Vol. 51, No. 3, June 2002, pp. 544-50, ISSN 0018-9456.  ... 
doi:10.5772/7021 fatcat:ooabssht2ra55c4bncruofiqki

A MLMVN with Arbitrary Complex-Valued Inputs and a Hybrid Testability Approach for the Extraction of Lumped Models Using FRA

Igor Aizenberg, Antonio Luchetta, Stefano Manetti, Maria Cristina Piccirilli
2019 Journal of Artificial Intelligence and Soft Computing Research  
The fundamental brick of this architecture is a multi-valued neuron (MVN), used in a multilayer neural network (MLMVN); the neuron is modified in order to use arbitrary complex-valued inputs, which represent  ...  A Frequency Response Analysis (FRA) of the device to be modeled is performed, executing repeated measurements or intensive simulations. The method can be used to extract the values of the components.  ...  The combined use of different concepts developed by the authors (testability, symbolic analysis and representation, MVN-based neural networks with complex inputs) allows a rigorous and straightforward  ... 
doi:10.2478/jaiscr-2018-0021 fatcat:wcjdyvl2ijc43ev23v5nmz2o24

A Hierarchical Modeling and Fault Diagnosis Technique for Complex Electronic Devices

Bing Long, Zhi-Jian Dai, Shu-Lin Tian, Hou-Jun Wang
2009 2009 IEEE Circuits and Systems International Conference on Testing and Diagnosis  
Abstract⎯Due to the shortcomings of the diagnosis systems for complex electronic devices such as failure models hard to build and low fault isolation resolution, a new hierarchical modeling and diagnosis  ...  method is proposed based on multisignal model and support vector machine (SVM).  ...  Hu [9] proposed an approach of soft fault diagnosis for analog circuits based on slope fault feature and back propagation neural network.  ... 
doi:10.1109/cas-ictd.2009.4960745 fatcat:sugsjgx6rzdpdkv7tkoqz36pgi

2019 Index IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems Vol. 38

2019 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems  
., +, TCAD Aug. 2019 1385-1398 Analog multipliers An Analog Neural Network Computing Engine Using CMOS-Compatible Charge-Trap-Transistor (CTT).  ...  Chan, C.S., +, TCAD Sept. 2019 1689-1702 CMOS analog integrated circuits An Analog Neural Network Computing Engine Using CMOS-Compatible Charge-Trap-Transistor (CTT).  ... 
doi:10.1109/tcad.2020.2964359 fatcat:qjr6i73tkrgnrkkmtjexbxberm

Application of Artificial Neural Networks in Electronics

Miona Andrejević Stošović, Vančo Litovski
2018 Electronics  
Artificial neural networks are shown to be universal approximators, so they were successfully used in applications in modelling of electronic circuits, as well as in fault diagnosis and classification.  ...  In this paper we will give short overview of different applications of artificial neural networks in electronics.  ...  An artificial neural network (ANN) was used to capture the fault dictionary and perform the diagnosis.  ... 
doi:10.7251/els1721087a fatcat:vlxr5tn2qrd6hcrwne2uljgaie

A new adaptive analog test and diagnosis system

E.F. Cota, M. Negreiros, L. Carro, M. Lubaszewski
2000 IEEE Transactions on Instrumentation and Measurement  
This paper presents a low-cost analog test system with diagnosis capabilities.  ...  The diagnosis method consists on injecting probable faults in a mathematical model of the circuit, and later comparing its output with the output of the real faulty circuit.  ...  Its ability of classifying component faults is comparable to existing methods based on neural networks.  ... 
doi:10.1109/19.843053 fatcat:e3ly67yp7faufjhyaiar2pquyy

Ic bridge fault modeling for ip blocks using neural network-based vhdl saboteurs

D.B. Shaw, D. Al-Khalili, C.N. Rozon
2003 IEEE transactions on computers  
This through h sabo- > analog a digital vn later eneral’s is being ‘iven to rrent to SHAW ET AL.: IC BRIDGE FAULT MODELING FOR IP BLOCKS USING NEURAL NETWORK-BASED VHDL SABOTEURS Neural Network Mapping  ...  .: IC BRIDGE FAULT MODELING FOR IP BLOCKS USING NEURAL NETWORK-BASED VHDL SABOTEURS 1291 training.  ... 
doi:10.1109/tc.2003.1234526 fatcat:komef6tyvjb5xhgaxh65wjmuru

Table of Contents

2020 2020 11th International Conference on Prognostics and System Health Management (PHM-2020 Jinan)  
Diagnosis Method for Rotating Machinery Based on Multi-representation Adaptation Neural Network 210 Kaifeng Zhang (Huazhong University of Science and Technology), Guannan Cao (Huazhong University of Science  ...  Circuit Incipient Fault Diagnosis from Raw Signals Using Multi-layer Extreme Distributed Fault Diagnosis for Electro-Hydraulic Suspension by Model Decomposition 355 Dun Lan (Hefei University of Technology  ... 
doi:10.1109/phm-jinan48558.2020.00004 fatcat:m2bsdulg2fhqrfj6imw4rd7h5e
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