宋万清
发布时间: 2021-01-08 浏览次数: 3707

姓名

宋万清

性别

职称

教授

研究方向

状态监测与故障诊断,电力系统可靠性分析,人工智能算法应用,高级统计学

地址

上海松江区龙腾路333号现代交通中心7931

邮政编码

201620

联系电话

13916842386

电子邮箱

swqls@126.com

个人简介

北京科技大学自动控制理论与应用专业硕士学位,东华大学机械制造及其自动化专业博士学位,2013.1-2014.3在美国弗吉尼亚理工大学高级研究学者,2019.11-2020.10意大利米兰理工大学高级研究学者。硕士毕业后在中石化仪征化纤集团公司工作,从事大型项目电、仪控制的外商谈判、设计、安装、调试和ISO9000惯标文件编写,获电气、仪表高级工程师。200111月调入bob电竞体育平台登录,主讲25门本科课程,2门研究生课。2007-2009年,三次应邀赴意大利罗马大学、佩鲁贾大学、萨兰诺大学做小波、混沌、分形的讲学。2010年,作为特聘专家赴约旦进行一项矿山开采控制系统项目的招标与谈判。20185月,应邀到俄罗斯乌法国立石油大学和BRISK大学做学术报告。近年发表性论文80多篇,其中5篇高被引,出版教材一本。担任多个国际SCI期刊审稿人;2017年主持完成上海市自然基金一项;兼任教育部评审专家、上海市科委评审专家、上海市教委评审专家。


主要成果

6年主要成果:

一、主持代表性课题和获批发明专利:

1.主持“压缩传感与长相关随机模型的机械设备运行状态监测与预测研究”,上海市自然科学基金(14ZR1418500),2014.7-2017.6

2.基于FBM的长相关模型的轴承内圈故障剩余寿命预测方法,专利号ZL201910683262.5,授权时间:2021.5.11

3.一种电力负荷短期预测方法,专利号ZL201810542186.1,授权时间2020.7.10

4.一种轴承振动信号稀疏重构的方法,专利号ZL201611154387.1,授权时间2019.2

5.一种基于长相关FARIMA模型的短期电力负荷预测方法,专利号CN104318334B,授权时间2017.7

6.一种冷冻站中央监控系统专利号ZL200710172720,授权时间2011.4

二、出版教材

宋万清等编著,数据挖掘, 铁道科学出版社,2019.1     

三、近年第一作者和通讯作者代表性论文:

[1]Duan S,Song, W Q*, Zio E, Cattani C,Li MProduct technical life prediction based on multi-modes and fractional Lévy stable motionMechanical Systems and Signal Processing2021,161(12):107974SCI:1区) 

[2]He Liu,Wanqing Song*,EnricoZio, Metabolism and difference iterative forecasting model based on long-range dependent and grey for gearbox reliability, ISA transactions, 2021, https://www.sciencedirect.com/science/article/pii/S0019057821002573?dgcid=author, SCI: 2区)

[3]Liu H, Song W Q*, Zhang Y J, et al. Generalized Cauchy Degradation Model with Long-range Dependence and Maximum Lyapunov Exponent for Remaining Useful Life[J]. IEEE Transactions on Instrumentation & Measurement2021DOI10.1109/TIM.2021.3063749 SCI: 2区)

[4]Liu H, SongW Q*, Zio E. Generalized Cauchy Difference Iterative Forecasting Model for Wind Speed Based on Fractal Time Series[J]. Nonlinear Dynamics, 2021, 103(1):1-15SCI: 2区)

[5] Liu H,SongW Q*, Niu Y H,et al.A Generalized Cauchy Method for Remaining Useful Life Prediction of Wind Turbine Gearboxes[J]. Mechanical Systems and Signal Processing2021, 153(15):107471SCI:1区)

[6]Ren, LijiaDeng, JuequanSong, Wanqing, A Fractional Brownian Motion Model for Forecasting Lost Load and Time Interval Between Power Outages[J]. IEEE ACCESS, 2021, 9:6623-6632SCI2区)

[7]Deng Juequan, Song wanqing*, A Discrete Increment Model for Electricity Price Forecasting Based on Fractional Brownian Motion, IEEE access, DOI: 10.1109/ACCESS.2020.3008797 (SCI:2)

[8]Fei WuCarlo CattaniWanqing Song*EnricoZioFractional ARIMA with an improved cuckoo search optimization for the efficient Short-term power load forecastingAlexandria Engineering JournalAvailable online 7 July 2020https://authors.elsevier.com/sd/article/ S1110-0168(20)30313-6

[9]Shouwu Duan, Wanqing Song, Carlo Cattani*, Yakufu Yasen and He LiuFractional Levy Stable and Maximum  Lyapunov Exponent for Wind Speed Predictionsymmetry2020, 12, 605; DOI:10.3390/sym12040605

[10] Haiyang Wang, Wanqing Song*, Enrico Zio, Aleksey Kudreyko, Yujin Zhang, Remaining Useful Life Prediction for Lithium-ion Batteries Using Fractional Brownian Motion and Fruit-fly Optimization Algorithm, measurement, Measurement, 2020, 161(9):107904(SCI: 2区,ESI)

[11]He Liu, Wanqing Song*, Ming Li, Aleksey Kudreyko, Enrico Zio, Fractional Lévy stable motion: Finite difference iterative forecasting model, Chaos, Solitons and Fractals,2020, 133(4):109632SCI:2, ESI

[12]Wanqing Song*, Xiaoxian Chen, Carlo Cattani and Enrico Zio, Multi-Fractional Brownian Motion and Quantum-Behaved Partial Swarm Optimization for Bearing Degradation Forecastingcomplexity2020(1):8543131  ( ESI)

[13]Song WQ*, Cattani, C., Chi, C.-H,       Multifractional Brownian motion and quantum-behaved particle swarm optimization for short term power load forecasting: An integrated approach, Energy, 2020, 194(3):116847SCI一区)  ( SCI: 1区,ESI)

[14]Wanqing SongAleksey A. KudreykoNail G. MigranovSurface effects in the model of polymer-stabilized ferroelectric liquid crystal cellsIndian Journal of Physics2019,12:1-7

[15]Song, WQ*., Li, M., Li, Y., Cattani, C., Chi, C.-H, Fractional Brownian motion: Difference iterative forecasting models, Chaos, Solitons and Fractals,123(2019): 347-355SCI2

[16]Yujin Zhang,Wanqing Song*, Tire Vibration Trend Forecasting via FARIMA and Finite-Element Modal, IEEE Access, 2018SCI2

[17]李宇飞,宋万清*, 无量纲参数滚动轴承长相关故障趋势预测,噪声与振动控制,2018, 3(6):141-156

[18]Yangde Gao, SongWanqing*, Spare optimistic based on improved ADMM and the minimum entropy deconvolution for the early weak fault diagnosis of bearings in marine systems, ISA Transactions, 201810.1SCI2

[19]Wanqing Song*, Nazarova Maria N., Ting Zhang, Yujin Zhang, Ming Li. Sparse Reconstruction Based on the ADMM and Lasso-LSQR for Bearings Vibration Signals, IEEE Access, 2017, 5: 20083-20088SCI2

[20]Yangde Gao, Wanqing Song*, Multi-Scale Permutation Entropy Based on Improved LMD and HMM for Rolling Bearing Diagnosis, Entropy, 2017,19(4) ( ESI 2021.3)

[21]Wanqing Song*, Sparse Optimization of Vibration Signal by ADMM, Journal of Applied Mathematics, 2017(2017):1-5

[22]Wanqing Song*, Ming Li, Jiankai Liang, Prediction of Bearing Fault Using Fractional Brownian Motion and Minimum Entropy Deconvolution, Entropy, 2016, 18(11):418~433

[23]Zongli Shi, Wanqing Song*, Saied Taheri, Improved LMD, Permutation Entropy and Optimized K-Means to Fault Diagnosis for Roller Bearings, Entropy, 2016, 18(3):1~11

[24]Jiankai Liang, Carlo Cattani, Wanqing Song*, Power Load Prediction Based on Fractal Theory, Advances in Mathematical Physics, 2015. 3

[25]李庆,宋万清*LMD与非凸罚最小化Lq正则子压缩传感的轴承振动信号重建中南大学学报, 2015, 46(10):3697-3702 EI

[26]Wingqing Song*, Qing Li, Tool Wear Detection Using Lipschitz Exponent and HarmonicMathematical Problems in Engineering(中国机械工程学报)2011624):1068-1073

  

欢迎立志报考博士的同学申报我的硕士研究生!



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