奖励与成果

荣誉与奖励

 

²  首批国家优秀青年科学基金获得者

²  国家技术发明二等奖(第二完成人)

²  教育部“长江学者奖励计划”青年学者

²  教育部青年科学奖

²  中组部万人计划青年拔尖人才

²  教育部自然科学一等奖(第一完成人)

²  德国洪堡学者

²  霍英东教育基金会青年教师奖二等奖

²  陕西青年五四奖章获得者

²  《机械工程学报》首篇明星论文

²  SCOPUS青年科学之星

²  《机械工程学报》首届高影响力论文

²  西安交通大学教书育人先进个人

²  陕西省优秀博士学位论文

 

英文专著

²  Yaguo Lei, Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery [M]. Elsevier Butterworth-Heinemann, Oxford, 2016.

²  Mohammad Fazle Azeem, Fuzzy Inference SystemTheory and Applications [M]. InTech, Croatia, 2012. (撰写其中一章)

²  Ruqiang Yan, et al., Structural Health Monitoring: Advanced Signal Processing Perspective [M]. Springer, Switzerland, 2017. (撰写其中一章)

 

代表性论文

l  机械系统动态建模

²  YaguoLei, Jing Lin, Ming J. Zuo, Zhengjia He, Condition monitoring and fault diagnosis of planetary gearboxes: A review [J]. Measurement, 2014, 48(2): 292-305.

²  Yaguo Lei, Zongyao Liu, Delong Wang, Xiao Yang, Huan Liu, Jing Lin, A probability distribution model of tooth pits for evaluating time-varying mesh stiffness of pitting gears [J]. Mechanical Systems and Signal Processing, 2018, in press.

²  Yaguo Lei, Zongyao Liu, Jing Lin, Fanbo Lu, Phenomenological models of vibration signals for condition monitoring and fault diagnosis of epicyclic gearboxes [J]. Journal of Sound and Vibration, 2016, 369: 266-281.

²  雷亚国,罗希,刘宗尧,卢帆勃,林京,汤伟. 行星轮系动力学新模型及其故障响应特性研究[J]. 机械工程学报, 2016, 52(13): 111-122

²  雷亚国,汤伟,孔德同,林京. 基于传动机理分析的行星齿轮箱振动信号仿真及其故障诊断[J]. 机械工程学报, 2014, 50(5): 17-24.

²  雷亚国,何正嘉,林京,韩冬,孔德同. 行星齿轮箱故障诊断技术的研究进展[J]. 机械工程学报, 2011, 47(19): 59-67.

l  机械信号处理与分析

²  Zijian Qiao, Yaguo Lei, Naipeng Li, Applications of stochastic resonance to machinery fault detection: A review and tutorial [J]. Mechanical Systems and Signal Processing, 2019, 122:502-536.

²  Yaguo Lei, Jing Lin, Zhengjia He, Ming J. Zuo, A review on empirical mode decomposition in fault diagnosis of rotating machinery [J]. Mechanical Systems and Signal Processing, 2013, 35(1-2): 108-126.

²  Xuefang Xu, Zijian Qiao, Yaguo Lei, Repetitive transient extraction for machinery fault diagnosis using multiscale fractional order entropy infogram [J]. Mechanical Systems and Signal Processing, 2018, 103: 312-326.

²  Yaguo Lei, Zijian Qiao, Xuefang Xu, Jing Lin, Shantao Niu, An underdamped stochastic resonance method with stable-state matching for incipient fault diagnosis of rolling element bearings [J]. Mechanical Systems and Signal Processing, 2017, 94: 148-164.

²  Yaguo Lei, Dong Han, Jing Lin, Zhengjia He, Planetary gearbox fault diagnosis using an adaptive stochastic resonance method [J]. Mechanical Systems and Signal Processing, 2013, 38(1): 113-124.

²  Zijian Qiao, Yaguo Lei, Jing Lin, Shantao Niu, Stochastic resonance subject to multiplicative and additive noise: The influence of potential asymmetries [J]. Physical Review E, 2016, 94(5): 052214-1-13.

²  Zijian Qiao, Yaguo Lei, Jing Lin, Feng Jia, An adaptive unsaturated bistable stochastic resonance method and its application in mechanical fault diagnosis [J]. Mechanical Systems and Signal Processing, 2017, 84: 731-746.

²  Yaguo Lei, Jing Lin, Zhengjia He, Yanyang Zi, Application of an improved kurtogram method for fault diagnosis of rolling element bearings [J]. Mechanical Systems and Signal Processing, 2011, 25(5): 1738-1749.

²  Yaguo Lei, Zhengjia He, Yanyang Zi, Application of the EEMD method to rotor fault diagnosis of rotating machinery [J]. Mechanical Systems and Signal Processing, 2009, 23(4): 1327-1338.

²  Yaguo Lei, Detong Kong, Jing Lin, Ming J. Zuo, Fault detection of planetary gearboxes using new diagnostic parameters [J]. Measurement Science & Technology, 2012, 23(5): 1-10.

l  大数据下智能故障诊断

²  Bin Yang, Yaguo Lei, Feng Jia, Saibo Xing, An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings [J]. Mechanical Systems and Signal Processing, 2019,122:692-706.

²  Liang Guo, Yaguo Lei, Saibo Xing, Tao Yan, Naipeng Li, Deep convolutional transfer learning network: A new method for intelligent fault diagnosis of machines with unlabeled data [J]. IEEE Transactions on Industrial Electronics, 2019, in press.

²  Feng Jia, Yaguo Lei, Na Lu, Saibo Xing, Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization [J]. Mechanical Systems and Signal Processing, 2018, 110: 349-367.

²  Yaguo Lei, Feng Jia, Jing Lin, Saibo Xing, Steven X. Ding, An intelligent fault diagnosis method using unsupervised feature learning towards mechanical big data [J]. IEEE Transactions on Industrial Electronics, 2016, 63(5): 3137-3147.

²  Feng Jia, Yaguo Lei, Liang Guo, Jing Lin, Saibo Xing, A neural network constructed by normalized sparse autoencoder and its application to intelligent fault diagnosis of machines [J]. Neurocomputing, 2018, 272: 619-628.

²  Feng Jia, Yaguo Lei, Jing Lin, Xin Zhou, Na Lu, Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data [J]. Mechanical Systems and Signal Processing, 2016, 72-73: 303-315.

²  Yaguo Lei, Zongyao Liu, Xionghui Wu, Naipeng Li, Wu Chen, Jing Lin, Health condition identification of multi-stage planetary gearboxes using a mRVM-based method[J]. Mechanical Systems and Signal Processing, 2015, 60-61: 289-300.

²  Yaguo Lei, Zhengjia He, Yanyang Zi, and Qiao Hu, Fault diagnosis of rotating machinery based on multiple ANFIS combination with GAs [J]. Mechanical Systems and Signal Processing, 2007, 21(5): 2280-2294.

²  Yaguo Lei, Zhengjia He, Yanyang Zi, Xuefeng Chen, New clustering algorithm based fault diagnosis using compensation distance evaluation technique [J]. Mechanical Systems and Signal Processing, 2008, 22(2): 419-435.

²  Yaguo Lei, Zhengjia He, Yanyang Zi, A combination of WKNN to fault diagnosis of rolling element bearings [J]. Transactions of the ASME, Journal of Vibration and Acoustics, 2009, 131(6): 1-6.

²  Yaguo Lei, Ming J Zuo, Zhengjia He, Yanyang Zi, A multidimensional hybrid intelligent method for gear fault diagnosis [J]. Expert Systems with Applications, 2010, 37(2): 1419-1430.

²  雷亚国,杨彬,杜兆钧,吕娜. 大数据下机械装备故障的深度迁移诊断方法[J]. 机械工程学报, 2019, 录用.

²  雷亚国,贾峰,孔德同,林京,邢赛博. 大数据下机械智能故障诊断的机遇与挑战[J]. 机械工程学报, 2018, 54(5): 94-104.

²  雷亚国,贾峰,周昕,林京. 基于深度学习理论的机械装备大数据健康监测方法[J]. 机械工程学报, 2015, 51(21): 49-56.

l  机械装备剩余寿命预测

²  Biao Wang, Yaguo Lei, Naipeng Li, Ningbo Li, A hybrid prognostics approach for estimating remaining useful life of rolling element bearings [J]. IEEE Transactions on Reliability, 2019, in press.

²  Naipeng Li, Yaguo Lei, Tao Yan, Ningbo Li, Tianyu Han, A wiener process model-based method for remaining useful life prediction considering unit-to-unit variability [J]. IEEE Transactions on Industrial Electronics, 2019, 66(3): 2092-2101.

²  Liang Guo, Yaguo Lei, Naipeng Li, Tao Yan, Ningbo Li, Machinery health indicator construction based on convolutional neural networks considering trend burr [J]. Neurocomputing, 2018, 292: 142-150.

²  Yaguo Lei, Naipeng Li, Liang Guo, Ningbo Li, Tao Yan, Jing Lin, Machinery health prognostics: A systematic review from data acquisition to RUL prediction [J]. Mechanical Systems and Signal Processing, 2018, 104: 799-834.

²  Yaguo Lei, Naipeng Li, Szymon Gontarz, Jing Lin, Stanislaw Radkowski, Jacek Dybala, A model-based method for remaining useful life prediction of machinery [J]. IEEE Transactions on Reliability, 2016, 65(3): 1314-1326.

²  Yaguo Lei, Naipeng Li, Jing Lin, A new method based on stochastic process models for machine remaining useful life prediction [J]. IEEE Transactions on Instrumentation and Measurement, 2016, 65(12): 2671-2684.

²  Naipeng Li, Yaguo Lei, Jing Lin, Steven X. Ding, An improved exponential model for predicting remaining useful life of rolling element bearings [J]. IEEE Transactions on Industrial Electronics, 2015, 62(12): 7762-7773.

²  Naipeng Li, Yaguo Lei, Liang Guo, Tao Yan, Jing Lin, Remaining useful life prediction based on a general expression of stochastic process models [J]. IEEE Transactions on Industrial Electronics, 2017, 64(7): 5709-5718.

²  Liang Guo, Naipeng Li, Feng Jia, Yaguo Lei, Jing Lin, A recurrent neural network based health indicator for remaining useful life prediction of bearings [J]. Neurocomputing, 2017, 240: 98-109.

²  雷亚国,陈吴,李乃鹏,林京. 自适应多核组合相关向量机预测方法及其在机械设备剩余寿命预测中的应用[J]. 机械工程学报, 2015, 52(1): 87-93.