Journal ArticleDOI
Quantitative Recognizing Dissolved Hydrocarbons with Genetic Algorithm-Support Vector Regression
TLDR
Experimental results indicate that the GA-SVR method can effectively decrease the cross sensitivity and the regressed data is much more closed to the real values.Abstract:
Online monitoring of dissolved fault characteristic hydrocarbon gases, such as methane, ethane, ethylene and acetylene in power transformer oil has significant meaning for condition assessment of transformer. Recently, semiconductor tin oxide based gas sensor array has been widely applied in online monitoring apparatus, while cross sensitivity of the gas sensor array is inevitable due to same compositions and similar structures among the four hydrocarbon gases. Based on support vector regression (SVR) with genetic algorithm (GA), a new pattern recognition method was proposed to reduce the cross sensitivity of the gas sensor array and further quantitatively recognize the concentration of dissolved hydrocarbon gases. The experimental data from a certain online monitoring device in China is used to illustrate the performance of the proposed GA-SVR model. Experimental results indicate that the GA-SVR method can effectively decrease the cross sensitivity and the regressed data is much more closed to the real values. DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.2776read more
Citations
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Journal ArticleDOI
An effective method to improve Electronic Equipment Condition Monitoring Based on KPCA-EDA and MMSH-SVDD
Shen Yang,Chen Meng,Meng Lv +2 more
TL;DR: The result shows that this method based on KPCA-EDA and MMSH-SVDD is the effective method to improve the performance of electronic equipment condition monitoring.
References
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Journal ArticleDOI
Review of condition assessment of power transformers in service
TL;DR: In this article, an extensive review is given of diagnostic and monitoring tests, and equipment available that assess the condition of power transformers and provide an early warning of potential failure, which is a very important issue for utilities.
Journal ArticleDOI
Comparison Studies of Electrical Discharge Machining (EDM) Process Model for Low Gap Current
Azli Yahya,Trias Andromeda,Ade Erawan Minhat,Nor Hisham Haji Khamis,Kamal Kalil,Muhammad Arif Abdul Rahim +5 more
TL;DR: In this article, the authors compared a Dimensional Analysis (DA) model, an Artificial Neural Network (ANN) model and an experimental result for a low gap current of an Electrical Discharge Machining (EDM) process.
Journal ArticleDOI
Semiconducting metal oxide sensor array for the selective detection of combustion gases
TL;DR: In this article, a sensor array consisting of discrete thick-film sensors based on various semiconductor metal oxides (SMO) has been designed and fabricated for flue gas analysis purposes.
Journal ArticleDOI
Dissolved gas analysis technique for incipient fault diagnosis in power transformers: A bibliographic survey
S Singh,M N Bandyopadhyay +1 more
TL;DR: In this paper, a bibliographic survey over the last 40 years on the research and development and on the procedures for evaluating faults by dissolved gas analysis of power transformers is presented.
Journal ArticleDOI
Support vector machine with genetic algorithm for machinery fault diagnosis of high voltage circuit breaker
Jian Huang,Xiaoguang Hu,Fan Yang +2 more
TL;DR: A genetic algorithm-based SVM (GA-SVM) model is developed that can determine the optimal parameters of SVM with the highest accuracy and generalization ability and the experimental results indicate that the classification accuracy is more superior than that of the artificial neural network and the SVM.