Fault diagnostics of roller bearing using kernel based neighborhood score multi-class support vector machine

Sugumaran, V.; Sabareesh, G. R.; Ramachandran, K. I.

doi:10.1016/j.eswa.2007.06.029

Cited by 103 publications

(39 citation statements)

References 11 publications

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“…Application of SVM for fault diagnosis in the chemical industry now is still limited, although its increasing growth in the near future is foreseeable. The neighborhood score multi-class SVM has been successfully used for roller bearing's fault diagnosis (Sugumaran et al, 2008). A fault diagnosis scheme was proposed by determining the values of unknown features and by regenerating completely described samples to diagnose the system based on SVM classifiers (Ren et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM

Zhang

2009

Chemical Engineering Science

226

116

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Section: Introductionmentioning

confidence: 99%

Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM

Zhang

2009

Chemical Engineering Science

226

116

View full text Add to dashboard Cite

“…Data classification study has been applied in decision making [1−2], fault detection [3], and pattern classification [4−5]. Classification or clustering algorithm was developed on the basis of distance-based measures between different data groups.…”

Section: Introductionmentioning

confidence: 99%

Similarity measure application to fault detection of flight system

Kim

Lee

Wang

2009

J. Cent. South Univ. Technol.

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Fault detection technique is introduced with similarity measure. The characteristics of conventional similarity measure based on fuzzy number are discussed. With the help of distance measure, similarity measure is constructed explicitly. The designed distance-based similarity measure is applicable to general fuzzy membership functions including non-convex fuzzy membership function, whereas fuzzy number-based similarity measure has limitation to calculate the similarity of general fuzzy membership functions. The applicability of the proposed similarity measure to general fuzzy membership structures is proven by identifying the definition. To decide fault detection of flight system, the experimental data (pitching moment coefficients and lift coefficients) are transformed into fuzzy membership functions. Distance-based similarity measure is applied to the obtained fuzzy membership functions, and similarity computation and analysis are obtained with the fault and normal operation coefficients.

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“…Because P (x, y) is unknown, it is impossible to calculate the expected risk of a decision function for a decision function [20], [23]. We need to find a number of indicators to replace the expected risk, it must be able to calculate, but also reflects the merits of a decision function:…”

Section: Structured Support Vector Machine (Ssvm)mentioning

confidence: 99%

Estimating Illumination Chromaticity Based on Structured Support Vector Machine

Tang¹,

Liu²,

Yuan³

et al. 2017

dtcse

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Abstract. Illumination estimation is crucial to the color constancy problem. Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimation the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an illuminant color estimate is obtained independently from distinct image main-regions. We think there is only one kind of light in each main-regions. From these main-regions a robust local illumination color is computed by consensus. So we can solve the problem of multiple illumination estimation using single illuminant color constancy method. The performance if our method is evaluated on multiple data sets. Experimental results show that we can reliably process mixed illuminant scenes.

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Fault diagnostics of roller bearing using kernel based neighborhood score multi-class support vector machine

Cited by 103 publications

References 11 publications

Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM

Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM

Similarity measure application to fault detection of flight system

Estimating Illumination Chromaticity Based on Structured Support Vector Machine

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