[1] SMET V, FOREST F, HUSELSTEIN J J, et al. Aging and failure modes of IGBT modules in high-temperature power cycling[J]. IEEE Transactions on Industrial Electronics, 2011, 58(10): 4931–4941. [2] 王希平, 丁祥宽, 姚芳, 等. IGBT模块失效机理及状态监测研究综述[J]. 中国电力, 2019, 52(9): 61–72 WANG Xiping, DING Xiangkuan, YAO Fang, et al. Review of failure mechanism and state monitoring technology for IGBT modules[J]. Electric Power, 2019, 52(9): 61–72 [3] YANG S, BRYANT A, MAWBY P, et al. An industry-based survey of reliability in power electronic converters[J]. IEEE Transactions on Industry Applications, 2011, 47(3): 1441–1451. [4] 刘嘉诚. 基于机器学习算法的IGBT寿命预测研究[D]. 合肥: 合肥工业大学, 2020. LIU Jiacheng. Research on IGBT life prediction based on machine learning algorithm[D]. Hefei: Hefei University of technology, 2020. [5] RAJAGURU P, LU H, BAILEY C, et al. Impact of underfill and other physical dimensions on silicon lateral IGBT package reliability using computer model with discrete and continuous design variables[J]. Microelectronics Reliability, 2018, 83: 146–156. [6] LI L L, LIU Z F, TSENG M L, et al. Prediction of IGBT power module remaining lifetime using the aging state approach[J]. Microelectronics Reliability, 2019, 102: 113–476. [7] 张经纬, 邓二平, 赵志斌, 等. 压接型IGBT器件单芯片子模组疲劳失效的仿真[J]. 电工技术学报, 2018, 33(18): 4277–4285 ZHANG Jingwei, DENG Erping, ZHAO Zhibin, et al. Simulation on fatigue failure of single IGBT chip module of press-pack IGBTs[J]. Transactions of China Electrotechnical Society, 2018, 33(18): 4277–4285 [8] 冯静波, 吕铮, 邓卫华, 等. 柔性直流换流阀IGBT过流失效研究[J]. 中国电力, 2021, 54(1): 70–77 FENG Jingbo, LV Zheng, DENG Weihua, et al. Study on the IGBT overcurrent failure of VSC-HVDC converter valve[J]. Electric Power, 2021, 54(1): 70–77 [9] 陈剑, 王海风. 模型-数据混合驱动的直驱风机VSC等效建模方法[J]. 电力系统保护与控制, 2021, 49(2): 10–17 CHEN Jian, WANG Haifeng. A model-data hybrid driven method of VSC equivalent modeling of a permanent magnetic synchronous generator[J]. Power System Protection and Control, 2021, 49(2): 10–17 [10] 高伟, 张琼洁, 李长留, 等. 基于LSTM网络的牵引变流器IGBT故障预测方法研究[J]. 电子器件, 2020, 43(4): 804–808 GAO Wei, ZHANG Qiongjie, LI Changliu, et al. A fault prediction method of IGBT in traction converter based on LSTM[J]. Chinese Journal of Electron Devices, 2020, 43(4): 804–808 [11] CHEN M, XU S, RAN L, et al. Prediction of case temperature for monitoring IGBT power module using artificial neural network[J]. International Review of Electrical Engineering (IREE), 2012, 7(1): 3240–3247. [12] HAQUE M S, CHOI S, BAEK J. Auxiliary particle filtering-based estimation of remaining useful life of IGBT[J]. IEEE Transactions on Industrial Electronics, 2018, 65(3): 2693–2703. [13] ASTIGARRAGA D, IBANEZ F M, GALARZA A, et al. Analysis of the results of accelerated aging tests in insulated gate bipolar transistors[J]. IEEE Transactions on Power Electronics, 2016, 31(11): 7953–7962. [14] SONNENFELD G, GOEBEL K, CELAYA J R. An agile accelerated aging, characterization and scenario simulation system for gate controlled power transistors[C]//2008 IEEE AUTOTESTCON. IEEE, 2008: 208–215. [15] CHOI U M, J?RGENSEN S, BLAABJERG F. Advanced accelerated power cycling test for reliability investigation of power device modules[J]. IEEE Transactions on Power Electronics, 2016, 31(12): 8371–8386. [16] 吴广宁, 袁海满, 高波, 等. 基于特征评估与核主元分析的电力变压器故障诊断[J]. 高电压技术, 2017, 43(8): 2533–2540 WU Guangning, YUAN Haiman, GAO Bo, et al. Fault diagnosis of power transformer based on feature evaluation and kernel principal component analysis[J]. High Voltage Engineering, 2017, 43(8): 2533–2540 [17] MIRJALILI S, LEWIS A. The whale optimization algorithm[J]. Advances in Engineering Software, 2016, 95: 51–67. [18] BRATLEY P, FOX B L. Implementing sobols quasirandom sequence generator (algorithm 659)[J]. ACM Transactions on Mathematical Software, 2003, 29(1): 49–57. [19] 张顶学, 关治洪, 刘新芝. 一种动态改变惯性权重的自适应粒子群算法[J]. 控制与决策, 2008(11): 1253–1257 ZHANG Dingxue, GUAN Zhihong, LIU Xinzhi. An adaptive particle swarm optimization algorithm with dynamically changing inertia weight[J]. Control and Decision, 2008(11): 1253–1257 [20] BEN SALEM S, BACHA K, CHAARI A. Support vector machine based decision for mechanical fault condition monitoring in induction motor using an advanced Hilbert-Park transform[J]. ISA Transactions, 2012, 51(5): 566–572.
|