An Improved KFCM Clustering Method Used for Multiple Fault Diagnosis of Analog Circuits

Khanlari, Masoumeh; Ehsanian, Mehdi

doi:10.1007/s00034-016-0479-0

Cited by 19 publications

(8 citation statements)

References 24 publications

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“…The multiple fault diagnosis method that can diagnose CPS within the range of (0,∞) is much less. Double faults are diagnosed in literatures [7,15,16]. But the faults are few fixed parameter values.…”

Section: A Fault Locationmentioning

confidence: 99%

Genetic Algorithm Based Faulty Parameter Identification for Linear Analog Circuit

Yang

2020

IEEE Access

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Faulty parameter identification is vital to prediction of remaining useful life of circuit under test (CUT). Based on the transfer function of the CUT, we use measured faulty response to reversely deduce the possible faulty parameters. It is known that the response is the function of the analog parameters. Usually, the number of independent response is much fewer than that of the analog component. The underdetermined equations have infinite solutions. In other words, there are lots of combinations of analog parameters that can generate the same faulty response. Hence, it is more valuable to deduce the possible fault parameter range within which all faults can generate the same measured response. The deduction is accomplished by using genetic algorithm. The length of chromosome equals to the number of analog component. Each gene represents a component's parameter value. Based on the gene values and the transfer function, each individual has a simulated response. Our target is to find all possible individuals viz., parameter combinations, which minimize the difference between the simulated and measured faulty response. In the final solutions, it is easy to find the minimal and maximum fault parameters, viz., extreme points. The possible faulty parameter rage is determined by these two extreme points because that the transfer function and parameters of analog element are continuous. The effectiveness of the proposed method is examined by using filter circuit examples.

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Section: A Fault Locationmentioning

confidence: 99%

Genetic Algorithm Based Faulty Parameter Identification for Linear Analog Circuit

Yang

2020

IEEE Access

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“…Only several components are selected as the potential faults of analog circuits in many researches [1][2][3][4][5][6]. This is inappro-priate, because they often selected the components which were easy to locate.…”

Section: Fault Features Analysis Of Output Voltagementioning

confidence: 99%

“…Analog circuits' diagnosis is the bottleneck of electronic circuits at present. It is an active area of research with significant work carried out at the system, board, and chip level [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Fault features analysis for soft faults of analog circuits with tolerance

Zhang¹,

Guo

et al. 2018

MATEC Web Conf.

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Soft faults of analog circuits are more difficult to diagnose than hard faults because the soft faults are caused by the deviations of component parameters. Node voltages were traditionally used as the testing signals to diagnose analog circuits. With the rapid development of integrated circuits technology, fewer and fewer circuit nodes are accessible. Only the output voltage can be tested in many cases. This cries for other new accessible signal except for the traditional voltage signal. In this paper, the fault features of testing signal in both time-domain and frequency-domain are analysed. The output voltage was acquired firstly. Its fault features were extracted and used for fault diagnosis. The results show that the soft faults of Tow-Thomas filter cannot be uniquely located by using this output voltage only. Then a new accessible signal, which named dynamic power supply current, was acquired and its fault features were analysed. And the results were compared with those using output voltages. The comparing results show the validity of dynamic power supply current. This signal contains information related with the circuits’ topology and can be used for fault diagnosis of analog circuits.

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“…To simplify the problem, only few special fixed parameter shifting (such as ±25% or ±50% deviation from the nominal value) are considered in literatures [3]- [11]. An overdetermined equations fitting [9] based iterative method is proposed to estimate values of the considered set of the parameters.…”

Section: Introductionmentioning

confidence: 99%

“…The method that can diagnose the multiple parameter shifting within the range of (0,∞) is much less. Methods in literatures [5], [11], [13]can handle some double faults. But the faults are still fixed parameter values.…”

Section: Introductionmentioning

confidence: 99%

Multiple Soft Fault Diagnosis of Analog Filter Circuit Based on Genetic Algorithm

Yang

2020

IEEE Access

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Hard (open and short) faults and discrete parameter faults (DPF) are the mostly used fault models in simulation-before-test (SBT) method. Because that the parameter of analog element is continuous, the DPF can not elaborately characterize all possible continuous parameter faults (CPF) occurring in analog circuit, let alone the double soft fault. To address such problem, a genetic algorithm (GA) based simulation after test (SAT) fault diagnosis method is proposed in this paper. The fault diagnosis is transformed into an optimization problem. The genes represent the parameter values of potential faulty components. Our target is to minimize the difference between the actual faulty response and the GA simulated response. The chromosome that minimize the difference gives the solution. This method does not save all possible faults in advance whereas it can diagnosis single and double continuous faults. The effectiveness of the proposed method is examined by using filter circuit examples.

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An Improved KFCM Clustering Method Used for Multiple Fault Diagnosis of Analog Circuits

Cited by 19 publications

References 24 publications

Genetic Algorithm Based Faulty Parameter Identification for Linear Analog Circuit

Genetic Algorithm Based Faulty Parameter Identification for Linear Analog Circuit

Fault features analysis for soft faults of analog circuits with tolerance

Multiple Soft Fault Diagnosis of Analog Filter Circuit Based on Genetic Algorithm

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