光谱学与光谱分析 |
|
|
|
|
|
Infrared Spectroscopy Analysis of SF6 Using Multiscale Weighted Principal Component Analysis |
PENG Xi1, WANG Xian-pei1, HUANG Yun-guang2 |
1. Laboratory of System Integrated and Fault Diagnosis, Wuhan University, Wuhan 430079, China 2. Guangxi Research Institute of Electric Power, Nanning 530023, China |
|
|
Abstract Infrared spectroscopy analysis of SF6 and its derivative is an important method for operating state assessment and fault diagnosis of the gas insulated switchgear (GIS). Traditional methods are complicated and inefficient, and the results can vary with different subjects. In the present work, the feature extraction methods in machine learning are recommended to solve such diagnosis problem, and a multiscale weighted principal component analysis method is proposed. The proposed method combines the advantage of standard principal component analysis and multiscale decomposition to maximize the feature information in different scales, and modifies the importance of the eigenvectors in classification. The classification performance of the proposed method was demonstrated to be 3 to 4 times better than that of the standard PCA for the infrared spectra of SF6 and its derivative provided by Guangxi Research Institute of Electric Power.
|
Received: 2012-03-18
Accepted: 2012-05-02
|
|
Corresponding Authors:
PENG Xi
E-mail: pengxi@whu.edu.cn
|
|
[1] Zhou Q, Tang J, Tang M, et al. IEEE Transactions on Dielectrics and Electrical Insulation, 2007, 14: 30. [2] Chang C, Chang C S, Jin J, et al. IEEE Transactions on Dielectrics and Electrical Insulation, 2005, 12: 374. [3] Beyer C, Jenett H, Klockow D. IEEE Transactions on Dielectrics and Electrical Insulation, 2000, 7: 234. [4] Youshi M, Robin-Jouan Ph, Kanzari Z. IEEE Transactions on Dielectrics and Electrical Insulation, 2005, 12: 1193. [5] Derdouri A, Casanovas J, Hergli R J. Appl. Phys., 1989, 65: 1852. [6] Soppart O, Pilzecker P, Baumbach J I. IEEE Transactions on Dielectrics and Electrical Insulation, 2000, 7: 229. [7] Braun J M, Chu F Y. IEEE Transactions on Power Delivery, 1986, 1: 81. [8] Kurte R, Beyer C, Heise H M. Anal. Bioanal. Chem., 2002, 373. [9] Kirby M, Sirovich L. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(1): 103. [10] Turk M, Pentland A. J. Cognitive Neuroscience, 1991, 13(1): 71. [11] Belhumeur P N, Hespanha J P, Kriegman D J. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(5): 711. [12] Martnez A M, Kak A C. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(2): 228-233. [13] Bartlett M S, Movellan J R, and Sejnowski T J. IEEE Transactions on Neural Networks, 2002, 13(6): 1450. [14] Yuen P C, Lai J H. Pattern Recognition, 2002, 35(6): 1247. [15] Yang M H. Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition, 2002. 215. [16] Rellier G, Descombes X, Falzon F, et al. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(7): 1543. [17] Mallat S G. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7): 674. [18] Bhavik R B. AIChE Journal, 1998, 44(7): 1596. [19] Ding W, Hayashi R, Ochi K. IEEE Transactions on Dielectrics and Electrical Insulation, 2006, 13: 1200.
|
[1] |
CHENG Jia-wei1, 2,LIU Xin-xing1, 2*,ZHANG Juan1, 2. Application of Infrared Spectroscopy in Exploration of Mineral Deposits: A Review[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 15-21. |
[2] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
[3] |
GUO Ge1, 3, 4, ZHANG Meng-ling3, 4, GONG Zhi-jie3, 4, ZHANG Shi-zhuang3, 4, WANG Xiao-yu2, 5, 6*, ZHOU Zhong-hua1*, YANG Yu2, 5, 6, XIE Guang-hui3, 4. Construction of Biomass Ash Content Model Based on Near-Infrared
Spectroscopy and Complex Sample Set Partitioning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3143-3149. |
[4] |
ZHANG Mei-zhi1, ZHANG Ning1, 2, QIAO Cong1, XU Huang-rong2, GAO Bo2, MENG Qing-yang2, YU Wei-xing2*. High-Efficient and Accurate Testing of Egg Freshness Based on
IPLS-XGBoost Algorithm and VIS-NIR Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1711-1718. |
[5] |
WU Mu-lan1, SONG Xiao-xiao1*, CUI Wu-wei1, 2, YIN Jun-yi1. The Identification of Peas (Pisum sativum L.) From Nanyang Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1095-1102. |
[6] |
SHANG Chao-nan1, XIE Yan-li2, GAO Xiao3, ZHOU Xue-qing2, ZHAO Zhen-dong2, MA Jia-xin1, CUI Peng3, WEI Xiao-xiao3, FENG Yu-hong1, 2*, ZHANG Ming-nan2*. Research on Qualitative and Quantitative Analysis of PE and EVA in Biodegradable Materials by FTIR[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3380-3386. |
[7] |
HU Yun-you1, 2, XU Liang1*, XU Han-yang1, SHEN Xian-chun1, SUN Yong-feng1, XU Huan-yao1, 2, DENG Ya-song1, 2, LIU Jian-guo1, LIU Wen-qing1. Adaptive Matched Filter Detection for Leakage Gas Based on Multi-Frame Background[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3307-3313. |
[8] |
GENG Ying-rui1, SHEN Huan-chao1, NI Hong-fei2, CHEN Yong1, LIU Xue-song1*. Support Vector Machine Optimized by Near-Infrared Spectroscopic
Technique Combined With Grey Wolf Optimizer Algorithm to
Realize Rapid Identification of Tobacco Origin[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2830-2835. |
[9] |
WANG Yue1, 3, 4, CHEN Nan1, 2, 3, 4, WANG Bo-yu1, 5, LIU Tao1, 3, 4*, XIA Yang1, 2, 3, 4*. Fourier Transform Near-Infrared Spectral System Based on Laser-Driven Plasma Light Source[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1666-1673. |
[10] |
ZHA Ling-ling1, 2, 3, WANG Wei2*, XIE Yu1, SHAN Chang-gong2, ZENG Xiang-yu2, SUN You-wen2, YIN Hao2, HU Qi-hou2. Observation of Variations of Ambient CO2 Using Portable FTIR
Spectrometer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1036-1043. |
[11] |
LI Yan-yan1, 2, LUO Hai-jun1, 2*, LUO Xia1, 2, FAN Xin-yan1, 2, QIN Rui1, 2. Detection of Craniocerebral Hematoma by Array Scanning Sensitivity Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 392-398. |
[12] |
CUI Fang-xiao1, ZHAO Yue2, MA Feng-xiang2, WU Jun1*, WANG An-jing1, LI Da-cheng1, LI Yang-yu1. Optimization of FTIR Passive Remote Sensing Signal-to-Noise Ratio and Its Application in SF6 Leak Detection in Transform Substation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(05): 1436-1440. |
[13] |
WANG Chao1, LI Peng-cheng2, YANG Kai1, ZHANG Tian-tian2, LIU Yi-lin2, LI Jun-hui2*. Rapid Detection of Tobacco Quality Grade and Analysis of Grade Characteristics by Using Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(03): 943-947. |
[14] |
NING Jia-lian1, TANG Jin1, HU Tian-you1, LIU Qiang2, WANG Hao-wen1, CHEN Zhi-li1*. Study on Spectral Radiation Characteristics of Carbon Disulfide Flame Based on Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(05): 1377-1381. |
[15] |
HU Rong1,2,LIU Wen-qing2,XU Liang2*,JIN Ling2,YANG Wei-feng2,SHEN Xian-chun2,CHENG Xiao-xiao2, WANG Yu-hao2,HU Kai2,LIU Jian-guo2. Near Infrared Spectroscopic Modeling Method for Cement Raw Meal Components by Eliminating Background Moisture[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(04): 1051-1055. |
|
|
|
|