[1] |
Fanchiang K H, Huang Y C, Kuo C C. Power electric transformer fault diagnosis based on infrared thermal images using wasserstein generative adversarial networks and deep learning classifier[J]. Electronics, 2021, 10(10):1161-1162.
doi: 10.3390/electronics10101161
|
[2] |
Zhou Y C, Yang X H, Tao L Y, et al. Transformer fault diagnosis model based on improved gray wolf optimizer and probabilistic neural network[J]. Energies, 2021, 14(11):3029-3030.
doi: 10.3390/en14113029
|
[3] |
Zhang H R, Sun J X, Hou K N, et al. Improved informion entropy weighted vague support vector machine method for transformer fault diagnosis[J]. High Voltage, 2021, 33(19):1-13.
|
[4] |
任双赞, 徐尧宇, 李元, 等. 应用于油中溶解气体分析的深度信念网络与典型神经网络对比研究[J]. 高压电器, 2020, 56(9):39-45.
|
|
Ren Shuangzan, Xu Yaoyu, Li Yuan, et al. Comparison studies of deep belief network and typical neural network applied to analysis of dissolved gas in oil[J]. High Voltage Apparatus, 2020, 56(9):39-45.
|
[5] |
陈里里, 何颖, 董绍江. 基于深度神经网络的液压泵泄漏状态识别[J]. 仪器仪表学报, 2020, 41(4):86-94.
|
|
Chen Lili, He Ying, Dong Shaojiang. Recognition of h-ydraulic pump leakage status based on deep neural network[J]. Chinese Journal of Scientific Instrument, 2020, 41(4):86-94.
|
[6] |
杨宇, 曾国辉, 黄勃. 基于人工鱼群算法和LS_SVM的变压器故障诊断[J]. 电子科技, 2020, 33(11):36-40.
|
|
Yang Yu, Zeng Guohui, Huang Bo. A transformer fault diagnosis method integrating artificial fish swarm algorithm with least square support vector machine[J]. Electronic Science and Technology, 2020, 33(11):36-40.
|
[7] |
李恩文, 王力农, 宋斌, 等. 基于改进模糊聚类算法的变压器油色谱分析[J]. 电工技术学报, 2018, 33(19):4594-4602.
|
|
Li Enwen, Wang Linong, Song Bin, et al. Analysis of transformer oil chromatography based on improved fuzzy clustering algorithm[J]. Transactions of China Electrotechnical Society, 2018, 33(19):4594-4602.
|
[8] |
林晓宁, 蔡金锭. 基于粗糙集理论的变压器油纸绝缘状态评估[J]. 电力系统保护与控制, 2019, 47(7):22-29.
|
|
Lin Xiaoning, Cai Jinding. Evaluation of transformer oil-paper insulation based on rough set theory[J]. Power System Protection and Control, 2019, 47(7):22-29.
|
[9] |
李黄曼, 张勇, 张瑶. 基于ISSA优化SVM的变压器故障诊断研究[J]. 电子测量与仪器学报, 2021, 35(3):123-129.
|
|
Li Huangman, Zhang Yong, Zhang Yao. Study of transformer fault diagnosis based on improved sparrow search algorithm optimized support vector machine[J]. Journal of Electronic Measurement and Instrumentation, 2021, 35(3):123-129.
|
[10] |
赵文清, 严海, 周震东, 等. 基于残差BP神经网络的变压器故障诊断[J]. 电力自动化设备, 2020, 40(2):143-148.
|
|
Zhao Wenqing, Yan Hai, Zhou Zhendong, et al. Fault diagnosis of transformer based on residual BP neural network[J]. Electric Power Automation Equipment, 2020, 40(2):143-148.
|
[11] |
宋玉琴, 赵洋, 李超, 等. 基于模糊关系与自组织竞争网络的变压器故障诊断[J]. 自动化技术与应用, 2016, 35(10):131-134.
|
|
Song Yuqin, Zhao Yang, Li Chao, et al. Transformer fault diagnosis based on fuzzy relations and self-organizing competitive network[J]. Techniques of Automationand Applications, 2016, 35(10):131-134.
|
[12] |
吴杰康, 覃炜梅, 梁浩浩, 等. 基于自适应极限学习机的变压器故障识别方法[J]. 电力自动化设备, 2019, 39(10):181-186.
|
|
Wu Jiekang, Qin Weimei, Liang Haohao, et al. Transformer fault identification method based on self-adaptive extreme learning machine[J]. Electric Power Automation Equipment, 2019, 39(10):181-186.
|
[13] |
刘彬, 刘永记, 刘浩然, 等. 基于贝叶斯改进结构算法的回转窑故障诊断模型研究[J]. 中国机械工程, 2017, 28(18):2143-2151.
|
|
Liu Bin, Liu Yongji, Liu Haoran, et al. A study of fault diagnosis model of rotary kiln based on improved structural algorithm of Bayesian[J]. China Mechanical Engineering, 2017, 28(18):2143-2151.
|
[14] |
仝兆景, 秦紫霓, 赵运星, 等. 基于贝叶斯网络的变压器故障诊断研究[J]. 电子科技, 2021, 34(3):43-47.
|
|
Tong Zhaojing, Qin Zini, Zhao Yunxing, et al. Research on transformer fault diagnosis based on Bayesian network[J]. Electronic Science and Technology, 2021, 34(3):43-47.
|
[15] |
白翠粉, 高文胜, 金雷, 等. 基于3层贝叶斯网络的变压器综合故障诊断[J]. 高电压技术, 2013, 39(2):330-335.
|
|
Bai Cuifen, Gao Wensheng, Jin Lei, et al. Integrated diagnosis of transformer faults based on three-layer Bayesian network[J]. High Voltage Engineering, 2013, 39(2):330-335.
|
[16] |
吕启深, 曾辉雄, 姚森敬, 等. 基于贝叶斯网络和粗糙集约简的变压器故障诊断[J]. 中国电力, 2013, 46(9):75-79.
|
|
Lü Qishen, Zeng Huixiong, Yao Senjing, et al. Transformer fault diagnosis based on Bayesian network and rough set reduction theory[J]. Electric Power, 2013, 46(9):75-79.
|
[17] |
王金鑫, 王忠巍, 马修真, 等. 基于贝叶斯网络的柴油机润滑系统多故障诊断[J]. 控制与决策, 2019, 34(6):1187-1194.
|
|
Wang Jinxin, Wang Zhongwei, Ma Xiuzhen, et al. Diagnosis of multiple faults of diesel engine lubrication system based on Bayesian networks[J]. Control and Decision, 2019, 34(6):1187-1194.
|
[18] |
张娜, 赵泽丹, 包晓安, 等. 基于改进的Tent混沌万有引力搜索算法[J]. 控制与决策, 2020, 35(4):893-900.
|
|
Zhang Na, Zhao Zedan, Bao Xiaoan, et al. Gravitational search algorithm based on improved Tent chaos[J]. Control and Decision, 2020, 35(4):893-900.
|
[19] |
Xue J K, Shen B. A novel swarm intelligence optimization approach: Sparrow search algorithm[J]. Systems Science & Control Engineering, 2020, 8(1):22-34.
|
[20] |
李本锌. 智能算法在油浸式变压器故障诊断中的应用研究[D]. 南昌: 华东交通大学, 2015.
|
|
Li Benxin. Application research of oil-immersed transformer fault diagnosis based on intelligent algorithms[D]. Nanchang: East China Jiaotong University, 2015.
|
[21] |
尹金良. 基于相关向量机的油浸式电力变压器故障诊断方法研究[D]. 北京: 华北电力大学, 2013.
|
|
Yin Jinliang. Study on oil-immersed power transformer fault diagnosis based on relevance vector machine[D]. Beijing: North China Electric Power University, 2013.
|