Embedded fault diagnosis in digital systems with BIST

Ubar, Raimund; Kostin, Sergei; Raik, Jaan

doi:10.1016/j.micpro.2008.03.006

Cited by 7 publications

(6 citation statements)

References 32 publications

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“…To represent the diagnostic model of such a case of a multi-SA structure [8] where the number of SAs is less then the number of primary outputs of the network, we construct a new diagnostic matrix DM m = d m ij where j = 1,2, ... m, and m is the number of SA-s. The matrix DM m will be generated from D by merging the columns for the outputs connected to the same SA.…”

Section: Algorithmmentioning

confidence: 99%

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Investigations of the diagnosibility of digital networks with BIST

Ubar¹,

Kostin²,

Raik³

2009

2009 10th Latin American Test Workshop

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The problem of embedded fault diagnosis in digital systems based on Built-In Self-Test (BIST) facilities is discussed. A conception for diagnosis of digital circuits, which does not use fault models, and methods for calculating the diagnosibility of the given circuit are presented. The proposed measures of diagnosibility can be used for redesign of the circuit to improve the exactness of locating the faults or faulty regions in digital circuits. Experimental results provide the data which characterize the diagnosibility of circuits for the ISCAS benchmark family.

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Section: Algorithmmentioning

confidence: 99%

“…We consider the case of embedded diagnosis in digital systems based on using BIST [8]. The specific feature of using pseudorandom test sequences of BIST for fault diagnosis is the fact that majority of faults are detected repeatedly during the test.…”

Section: Introductionmentioning

confidence: 99%

Investigations of the diagnosibility of digital networks with BIST

Ubar¹,

Kostin²,

Raik³

2009

2009 10th Latin American Test Workshop

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“…There are tools to design and optimize the interface between the outputs of the system and the block of multiple SAs to achieve the best diagnostic resolution [7]. Four general strategies are implemented for fault diagnosis, which can be compared with each other and optionally modified: binary bisection of test patterns, binary bisection of detected fault sets, doubling and jumping algorithms.…”

Section: Figure 2 Gui Control Panel For Diagnozermentioning

confidence: 99%

Diagnozer: A laboratory tool for teaching research in diagnosis of electronic systems

Ubar

Jutman

Raik

et al. 2009

2009 IEEE International Conference on Microelectronic Systems Education

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In this work, we propose a multifunctional remote e-learning environment for teaching research by learning and investigating the problems of fault diagnosis in electronic systems. It is a collection of software tools which allow to simulate a system under diagnosis, emulate a pool of different methods and algorithms of fault location, analyze the efficiency of different embedded self-diagnosing architectures, and investigate the effect of real physical defects in electronic circuits. Hands-on experiments target research teaching issues. The interactive character of the environment makes the experiments attractive and helps to raise the students' curiosity for finding innovative procedures for debugging digital systems.

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“…Fault diagnosis technology has gained attention from researchers for its various applications [1][2][3]. To date, a large number of valuable approaches have been proposed for dealing with fault analysis issues, such as fuzzy theories [4,5], expert system [6], wavelet analysis [7,8], data fusion [9,10], and neural network [11,12].…”

Section: Introductionmentioning

confidence: 99%

A New Similarity Measure of Generalized Trapezoidal Fuzzy Numbers and Its Application on Rotor Fault Diagnosis

Zuo

Wang

Yin

2013

Mathematical Problems in Engineering

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Fault diagnosis technology plays a vital role in the variety of critical engineering applications. Fuzzy approach is widely employed to cope with decision-making problems because it is in the simplest and most used form. This paper proposed a new similarity measure of generalized trapezoidal fuzzy numbers used for fault diagnosis. The presented similarity measure combines concepts of the geometric distance, the center of gravity point, the perimeter, and the area of the generalized trapezoidal fuzzy numbers for calculating the degree of similarity between generalized trapezoidal fuzzy numbers. This method is proposed to deal with both standardized and nonstandardized generalized trapezoidal fuzzy numbers. Some properties of the proposed similarity measure have been proved, and 12 sets of generalized fuzzy numbers have been used to compare the calculation results of the proposed similarity measures with the existing similarity measures. Comparison results indicate that the proposed similarity measure can overcome the drawbacks of existing similarity measures. Finally, a fault diagnosis experiment is carried out in laboratory based on multifunctional flexible rotor experiment bench. Experimental results demonstrate that the proposed similarity measure is more effective than other methods in terms of rotor fault diagnosis.

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Embedded fault diagnosis in digital systems with BIST

Cited by 7 publications

References 32 publications

Investigations of the diagnosibility of digital networks with BIST

Investigations of the diagnosibility of digital networks with BIST

Diagnozer: A laboratory tool for teaching research in diagnosis of electronic systems

A New Similarity Measure of Generalized Trapezoidal Fuzzy Numbers and Its Application on Rotor Fault Diagnosis

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