高骏,何俊佳.量子遗传神经网络在变压器油中溶解气体分析中的应用[J].中国电机工程学报,2010,30(30):121-127.Gao Jun,He Junjia.Application of quantum genetic ANNS in transformer dissolved gas-in-oil analysis [J].Proceedings of the CSEE.2010,30(30):121-127(in Chinese).
[2]
张东波,徐瑜,王耀南.主动差异学习神经网络集成方法在变压器DGA故障诊断中的应用[J].中国电机工程学报,2010,30(22):64-70.Zhang Dongbo,Xu Yu,Wang Yaonan.Neural network ensemble method and its application in DGA fault diagnosis of power transformer on the basis of active diverse learning[J].Proceedings of the CSEE,2010,30(22):64-70(in Chinese).
[3]
朱永利,吴立增,李雪玉.贝叶斯分类器与粗糙集相结合的变压器综合故障诊断[J].中国电机工程学报,2005,25(10):159-165.Zhu Yongli,Wu Lizeng,Li Xueyu.Synthesized diagnosis on transfo rmer faults based on bayesian classifier and rough set[J].Proceedings of the CSEE,2005,25(10):159-165(in Chinese).
[4]
Zheng H B,Liao R J,Grzybowski S,et al.Fault diagnosis of power transformers using multi-class least square support vector machines classifiers with particle swarm optimisation[J].IET Electr.Power Appl.,2011,5(9):691-696.
[5]
郭创新,朱承治,张琳,等.应用多分类多核学习支持向量机的变压器故障诊断方法[J].中国电机工程学报,2010,30(13):128-134.Guo Chuangxin,Zhu Chengzhi,Zhang Lin,et al.A fault diagnosis method for power transformer based on multiclass multiple-kernel learning support vector machine[J].Proceedings of the CSEE.2010,30(13):128-134(in Chinese).
[6]
陈伟根,潘翀,云玉新,等.基于小波网络及油中溶解气体分析的电力变压器故障诊断方法[J].中国电机工程学报,2008,28(7):121-126.Chen Weigen,Pan Chong,Yun Yuxin,et al.Fault Diagnosis Method of Power Transformers Based on Wavelet Networks and Dissolved Gas Analysi[J].Proceedings of the CSEE,2008,28(7):121-126(in Chinese).
[7]
操敦奎.变压器油中气体分析诊断与故障检查[M].北京:中国电力出版社,2005:8-26.Cao Dunkui.Analysis diagnosis and fault inspection of transformer dissolved gas-in-oil[M].Beijing:China Electric Power Press,2005:8-26(in Chinese).
[8]
王昌长,李福祺,高胜友.电力设备的在线监测与故障诊断[M].北京:清华大学出版社.Wang Changchang,Li Fuqi,Gao Shengyou.On-line monitoring and diagnosis for power equipment[M].Beijing:TsingHua University Press,2011(in Chinese).
[9]
陶佳,张弘,朱国荣,等.基于优化相空间重构技术的风电场发电功率预测研究[J].中国电机工程学报,2011,31(28):9-14.Tao jia,Zhang hong,Zhu Guorong,et al.Wind power prediction based on technology of advanced phase space reconstruction[J].Proceedings of the CSEE,2011,31(28):9-14(in Chinese).
[10]
孙丹,孟濬,管宇凡,等.基于相空间重构和模糊聚类的永磁同步电机直接转矩控制系统逆变器故障诊断[J].中国电机工程学报,2007,27(16):49-53.Sun Dan,Meng Jun,Guan Yufan,et al.Invert er faults diagnosis in PMSM DTC drive using reconstructive phase space and fuzzy clustering[J].Proceedings of the CSEE,2007,27(16):49-53(in Chinese).
[11]
林卫星,文劲宇,艾小猛,等.风电功率波动特性的概率分布研究[J].中国电机工程学报,2012,32(1):38-46.Lin Weixing,Wen Jinyu,Ai Xiaomeng,et al.Probability density function of wind power variations[J].Proceedings of the CSEE,2012,32(1):38-46(in Chinese).
[12]
张学清,梁军.风电功率时间序列混沌特性分析及预测模型研究[J].物理学报,2012,61(19):1-12.Zhang Xueqing,Liang Jun.Chaotic characteristics analysis and prediction model study on wind power time series[J].Acta Phys.Sin.,2012,61(19):1-12(in Chinese).
[13]
唐炬,陈娇,张晓星,等.用于局部放电信号定位的多样本能量相关搜索提取时间差算法[J].中国电机工程学报,2009,29(19):125-130.Tang Ju,Chen Jiao,Zhang Xiaoxing,et al.Time difference algorithm based on energy relevant search of multi-sample applied in PD location[J].Proceedings of the CSEE,2009,29(19):125-130(in Chinese).
[14]
赵彤,李庆民,陈平.OLTC振动信号特征提取的动力学分析方法[J].电工技术学报,2007,22(1):41-46.Zhao Tong,Li Qingmin,Chen Ping.Dynamic analysis method for feature extraction of mechanical vibration signals of on-load tap changers[J].Transactions of China Electrotechnical Society,22007,22(1):41-46(in Chinese).
[15]
中华人民共和国国家质量监督检验检疫总局.GB/T 7252-2001变压器油中溶解气体分析和判断导则[S].北京:中国标准出版社,2001.General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China.GB/T 7252-2001 Guide to the analysis and the diagnosis of gases dissolved in transformer oil[S].Beijing:Standards Press of China,2001(in Chinese).
[16]
肖燕彩,朱衡君,陈秀海.用灰色多变量模型预测变压器油中溶解的气体浓度[J].电力系统自动化,2006,30(13):64-67.Xiao Yancai,Zhu Hengjun,Chen Xiuhai.Concentration prediction of dissolved gas-in-oil of a transformer with the multivariable grey model[J].Automation of Electric Power Systems,2006,30(13):64-67(in Chinese).
[17]
Wang M H,Hung C P.Novel grey model for the prediction of trend of dissolved gases in oil-filled power apparatus[J].Electric Power Systems Research,2003(67):53-58.
[18]
Azadeh A,Ghaderi S F,Sohrabkhani S.A simulated- based neural network algorithm for forecasting electrical energy consumption in Iran.Energy Policy,2008,36(7):2637-2644.
[19]
Fei Shengwei,Wang Mingjun,Miao Yubin,et al.Particle swarm optimization-based support vector machine for forecasting dissolved gases content in power transformer oil[J].Energy Conversion and Management,2009,50:1604-1609.
[20]
Fei Shengwei,Sun Yu.Forecasting dissolved gases content in power transformer oil based on support vector machine with genetic algorithm[J].Electric Power Systems Research,2008,78:507-514.
[21]
杨廷方,刘沛,李浙,等.应用新型多方法组合预测模型估计变压器油中溶解气体浓度[J].中国电机工程学报,2008,28(31):108-113.Yang Tingfang,Liu Pei,Li Zhe,et al.A new combination forecasting model for concentration prediction of dissolved gases in transformer oil[J].Proceedings of the CSEE,2008,28(31):108-113(in Chinese).
[22]
赵文清,朱永利,张小奇.应用支持向量机的变压器故障组合预测[J].中国电机工程学报,2008,28(25):14-19.Zhao Wenqing,Zhu Yongli,Zhang Xiaoqi.Combinational forecast for transformer faults based on support vector machine[J].Proceedings of the CSEE,2008,28(25):14-19(in Chinese).
[23]
Michael E.Tipping.Sparse bayesian learning and the relevance vector machine[J].Journal of Machine Learning Research,2001,1:211-1244.
[24]
Tipping M E,Faul A.Fast marginal likelihood maximisation for sparse Bayesian models[C]//Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics.Key West,FL:Society for Artificial Intelligence and Statistics,2003.
李超顺,周建中,肖剑,等.基于引力搜索核聚类算法的水电机组振动故障诊断[J].中国电机工程学报,2013,33(2):98-104.Li Chaoshun,Zhou Jianzhong,Xiao Jian,et al.Vibration fault diagnosis of hydroelectric generating unit using gravitational search based kernel clustering method[J].Proceedings of the CSEE,2013,33(2):98-104(in Chinese).