Two Heuristic Algorithms for Test Point Selection in Analog Circuit Diagnoses

Pułka, Andrzej

doi:10.2478/v10178-011-0011-6

Cited by 16 publications

(9 citation statements)

References 22 publications

(125 reference statements)

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“…With the increasing integration and miniaturization of circuits in electronic systems, the testing and fault diagnosis present significant challenges to manufacturers and end users [1,2]. To resolve this problem, design for testability (DFT) has received much attention in the past few decades.…”

Section: Introductionmentioning

confidence: 99%

Research on Test Point Allocation Method Based on Multi-signal Flow Graph Using Genetic Algorithm

Wang

2013

2013 Third International Conference on Instrumentation, Measurement, Computer, Communication and Control

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During the process of design for testability (DFT), the procedure of test points addition is significantly time-consuming especially when systems become complex. To resolve this problem, an efficient method to allocate test points based on multi-signal flow graph is proposed in this paper. First, the dependency matrix that describes the relationship between signals and candidate test points is presented assuming that each output of modules in the multi-signal flow graph is considered as a candidate test point. Thus, the test point allocation problem can be formalized as searching for the optimal candidate test point set to detect and isolate the signals. Then, genetic algorithm is applied on the dependency matrix to search for the optimal test point set. Finally, the proposed method is examined by a multisignal flow graph. The result shows that the proposed method can allocate the optimal test points in acceptable time.

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Section: Introductionmentioning

confidence: 99%

Research on Test Point Allocation Method Based on Multi-signal Flow Graph Using Genetic Algorithm

Wang

2013

2013 Third International Conference on Instrumentation, Measurement, Computer, Communication and Control

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“…With the rapid development of electronic technology, many methods such as the neural network [1,11,14], the wavelet [2,15], the optimal stimulus signal selection [26,32], the support vector machine [7,12], the Mahalanobis distance model [21], the fuzzy method [6,28], the hidden Markov model (HMM) [33], the test point selection [3,24] and the coefficient-based test method [13] are studied in depth. In these methods, linear models are used.…”

Section: Introductionmentioning

confidence: 99%

Soft Fault Feature Extraction in Nonlinear Analog Circuit Fault Diagnosis

Deng

Chai

2016

Circuits Syst Signal Process

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Aiming at the problem to diagnose soft faults in nonlinear analog circuits, a novel approach to extract fault features is proposed. The approach is based on the Wigner-Ville distribution (WVD) of the subband Volterra model. First, the subband Volterra kernels of the circuit under test are cleared. Then, the subband Volterra kernels are used to obtain the WVD functions. The fault features are extracted from the WVD functions and taken as input data into the hidden Markov model (HMM). Finally, with classification of features using HMMs, the soft fault diagnosis of the nonlinear analog circuit is achieved. The simulations and experiments show that the method proposed in this paper can extract the fault features effectively and improve the fault diagnosis.

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“…The problem of test points, test stimulus, and/or measurements selection for the analog fault dictionary technique has been studied extensively [4,5,[7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. An entropybased approach was proposed by Starzyk et al [4].…”

Section: Introductionmentioning

confidence: 99%

“…Different from the traditional integer-coded table technique, faulty voltage distribution is considered in literature [19]. Under the expert system control, heuristic test points selection algorithm proposed by Pulka [20]. The application of discrete particle swarm optimization algorithm to test point selection is discussed in [21].…”

Section: Introductionmentioning

confidence: 99%

Entropy Based Test Point Evaluation and Selection Method for Analog Circuit Fault Diagnosis

Gao

Yang

Tian

et al. 2014

Mathematical Problems in Engineering

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By simplifying tolerance problem and treating faulty voltages on different test points as independent variables, integer-coded table technique is proposed to simplify the test point selection process. Usually, simplifying tolerance problem may induce a wrong solution while the independence assumption will result in over conservative result. To address these problems, the tolerance problem is thoroughly considered in this paper, and dependency relationship between different test points is considered at the same time. A heuristic graph search method is proposed to facilitate the test point selection process. First, the information theoretic concept of entropy is used to evaluate the optimality of test point. The entropy is calculated by using the ambiguous sets and faulty voltage distribution, determined by component tolerance. Second, the selected optimal test point is used to expand current graph node by using dependence relationship between the test point and graph node. Simulated results indicate that the proposed method more accurately finds the optimal set of test points than other methods; therefore, it is a good solution to minimize the size of the test point set. To simplify and clarify the proposed method, only catastrophic and some specific parametric faults are discussed in this paper.

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Two Heuristic Algorithms for Test Point Selection in Analog Circuit Diagnoses

Cited by 16 publications

References 22 publications

Research on Test Point Allocation Method Based on Multi-signal Flow Graph Using Genetic Algorithm

Research on Test Point Allocation Method Based on Multi-signal Flow Graph Using Genetic Algorithm

Soft Fault Feature Extraction in Nonlinear Analog Circuit Fault Diagnosis

Entropy Based Test Point Evaluation and Selection Method for Analog Circuit Fault Diagnosis

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