Changchun Institute of Optics,Fine Mechanics and Physics,CAS
Application of Optimized Parameters SVM Based on Photoacoustic Spectroscopy Method in Fault Diagnosis of Power Transformer | |
Y. X. Zhang; Z. F. Cheng; Z. P. Xu and J. Bai | |
2015 | |
发表期刊 | Spectroscopy and Spectral Analysis |
卷号 | 35期号:1 |
文章类型 | 期刊 |
其他摘要 | In order to solve the problems such as complex operation,consumption for the carrier gas and long test period in traditional power transformer fault diagnosis approach based on dissolved gas analysis(DGA),this paper proposes a new method which is detecting 5types of characteristic gas content in transformer oil such as CH4,C2H2,C2H4,C2H6and H2based on photoacoustic spectroscopy and C2H2/C2H4,CH4/H2,C2H4/C2H6three-ratios data are calculated.The support vector machine model was constructed using cross validation method under five support vector machine functions and four kernel functions, heuristic algorithms were used in parameter optimization for penalty factor c and g,which to establish the best SVM model for the highest fault diagnosis accuracy and the fast computing speed.Particles swarm optimization and genetic algorithm two types of heuristic algorithms were comparative studied in this paper for accuracy and speed in optimization.The simulation result shows that SVM model composed of C-SVC,RBF kernel functions and genetic algorithm obtain 97.5%accuracy in test sample set and 98.333 3%accuracy in train sample set,and genetic algorithm was about two times faster than particles swarm optimization in computing speed.The methods described in this paper has many advantages such as simple operation,non-contact measurement, no consumption for the carrier gas,long test period,high stability and sensitivity,the result shows that the methods described in this paper can instead of the traditional transformer fault diagnosis by gas chromatography and meets the actual project needs in transformer fault diagnosis. |
收录类别 | sci |
语种 | 英语 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ciomp.ac.cn/handle/181722/55945 |
专题 | 中科院长春光机所知识产出 |
推荐引用方式 GB/T 7714 | Y. X. Zhang,Z. F. Cheng,Z. P. Xu and J. Bai. Application of Optimized Parameters SVM Based on Photoacoustic Spectroscopy Method in Fault Diagnosis of Power Transformer[J]. Spectroscopy and Spectral Analysis,2015,35(1). |
APA | Y. X. Zhang,Z. F. Cheng,&Z. P. Xu and J. Bai.(2015).Application of Optimized Parameters SVM Based on Photoacoustic Spectroscopy Method in Fault Diagnosis of Power Transformer.Spectroscopy and Spectral Analysis,35(1). |
MLA | Y. X. Zhang,et al."Application of Optimized Parameters SVM Based on Photoacoustic Spectroscopy Method in Fault Diagnosis of Power Transformer".Spectroscopy and Spectral Analysis 35.1(2015). |
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