A novel approach for analog fault diagnosis based on neural networks and improved kernel PCA

Xiao, Yao; He, Yigang

doi:10.1016/j.neucom.2010.12.003

Cited by 81 publications

(27 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PCA [5], improved KPCA [10] and KLDA [12] have been used to reduce the dimension of features in recent analog circuit fault diagnosis works [5,10,12]. The proposed diagnosis approach in our work is compared with the approaches in [5,10,12].…”

Section: Comparison Of Simulation Resultsmentioning

confidence: 99%

“…The proposed diagnosis approach in our work is compared with the approaches in [5,10,12]. The energy features of example 1 and example 2 are used to test the referenced approaches and compare the simulation results for performed incipient fault diagnoses under the same simulation conditions.…”

Section: Comparison Of Simulation Resultsmentioning

confidence: 99%

“…The wavelet transform was introduced to the diagnosis [3−9], and coefficients [3−7] and coefficient energies [8,9] were generated as features. The principal component analysis (PCA) [5], kernel principal component analysis (KPCA) [10], linear discriminant analysis (LDA) [11] and kernel linear discriminant analysis (KLDA) [12] were proposed to reduce the dimension of high-dimensional features for the purpose of simplifying the workload, and positive results were obtained. With regard to the successive classifier, an artificial neural network has been normally and widely used, for it can implement the fault diagnosis by using the extracted CUTs' performance data [13−16].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Approach To Diagnosis Of Analog Circuit Incipient Faults Based On KECA And OAO LSSVM

Zhang¹,

He²,

Zuo³

et al. 2015

Metrology and Measurement Systems

Self Cite

View full text Add to dashboard Cite

Correct incipient identification of an analog circuit fault is conducive to the health of the analog circuit, yet very difficult. In this paper, a novel approach to analog circuit incipient fault identification is presented. Time responses are acquired by sampling outputs of the circuits under test, and then the responses are decomposed by the wavelet transform in order to generate energy features. Afterwards, lower-dimensional features are produced through the kernel entropy component analysis as samples for training and testing a one-against-one least squares support vector machine. Simulations of the incipient fault diagnosis for a Sallen-Key band-pass filter and a two-stage four-op-amp bi-quad low-pass filter demonstrate the diagnosing procedure of the proposed approach, and also reveal that the proposed approach has higher diagnosis accuracy than the referenced methods.

show abstract

Section: Comparison Of Simulation Resultsmentioning

confidence: 99%

Section: Comparison Of Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Approach To Diagnosis Of Analog Circuit Incipient Faults Based On KECA And OAO LSSVM

Zhang¹,

He²,

Zuo³

et al. 2015

Metrology and Measurement Systems

Self Cite

View full text Add to dashboard Cite

show abstract

“…Therefore, designing an intelligent fault diagnosis method has attracted considerable attention. Various intelligent techniques have been put forward, such as expert system 1, principal component analysis (PCA) 2–5, wavelet transform 6, 7, rough set theory 8 etc. Artificial neural network (ANN) can approximate the nonlinear relations for continuous or discrete systems 9–11 and has been widely applied in fault diagnosis 12–16 in recent years.…”

Section: Introductionmentioning

confidence: 99%

Stationäre Siebklassierung

Hennig

Teipel

2016

Chemie Ingenieur Technik

View full text Add to dashboard Cite

Eines der wichtigsten mechanischen Trennverfahren ist die Siebklassierung. Zur Untersuchung der Trenncharakteristik soll diese modelliert werden. Der Trenngrad wird aus den gemessenen Partikelverteilungen und den Gesamtmassen der einzelnen Fraktionen bestimmt. Die Modelle sind von jeweils drei bzw. vier Funktionsparametern abhängig. Dazu gehören der Bypass‐Parameter a, der Parameter xcut, der die Median‐Trenngrenze definiert, sowie der Parameter α als die Trennschärfe der Klassierung. Zusätzlich wird ein dritter Schärfeparameter β eingeführt. Als Parameterstudie stehen durchgeführte Siebversuchsreihen an zwei Taumelsiebmaschinen zur Verfügung.

show abstract

“…For example, reference [16] offers a method for parametric and catastrophic fault detection and location of linear circuits in the frequency domain, whereas the papers [14,20,21,29] bring diagnostic methods using the time-domain features.…”

Section: Introductionmentioning

confidence: 99%

Catastrophic Fault Diagnosis of a Certain Class of Nonlinear Analog Circuits

Tadeusiewicz

Kuczyński

Hałgas

2014

Circuits Syst Signal Process

View full text Add to dashboard Cite

This paper deals, for the first time, with catastrophic fault diagnosis of nonlinear analog circuits containing bipolar and MOS transistors having multiple operating points (DC solutions). The faults are cuts of some connecting paths and short-circuits of some pairs of points. Simulation-before-test approach is applied for detection and identification of a single catastrophic fault. To build a fault dictionary, a diagnostic test is arranged based on DC analysis. In the discussed circuits having multiple DC solutions, the tested output voltage may assume different values for fixed value of the input voltage. This fact considerably complicates the fault diagnosis. The crucial point of the proposed approach is tracing large number of nonlinear multivalued input-output characteristics at different values of circuit parameters within their tolerance ranges. For this purpose an efficient and fast algorithm is developed, based on the theory known under the name a linear complementarity problem. To illustrate the proposed approach and show its efficiency, four numerical examples are given.

show abstract

A novel approach for analog fault diagnosis based on neural networks and improved kernel PCA

Cited by 81 publications

References 19 publications

A Novel Approach To Diagnosis Of Analog Circuit Incipient Faults Based On KECA And OAO LSSVM

A Novel Approach To Diagnosis Of Analog Circuit Incipient Faults Based On KECA And OAO LSSVM

Stationäre Siebklassierung

Catastrophic Fault Diagnosis of a Certain Class of Nonlinear Analog Circuits

Contact Info

Product

Resources

About