刘欢 (副教授)

副教授 硕士生导师

性别:男

出生年月:1989-02-20

毕业院校:中国地质大学(武汉)

学历:博士研究生

学位:工学博士学位

在职信息:在职

所在单位:自动化学院

入职时间:2018-07-01

学科:测控技术与仪器 自动化

办公地点:物探楼 103

联系方式:027-67883091

Email:

个人简历

刘欢,男,1989年生,黑龙江大庆人,博士,特任副教授,硕士生导师,IEEE会员,中国地质大学(武汉)地大学者-青年优秀人才计划入选者


主要研究方向为高精度地球物理勘探仪器、微弱信号检测、无损检测(基于机器学习和数据挖掘,包括复合材料损伤程度智能预测,地下输油管道腐蚀特征匹配技术)。仪器主要包括:磁力仪(普通质子磁力仪、Overhauser磁力仪、光泵磁力仪、三分量磁力仪);电法仪(新型智能电法仪、高密度电法仪);地热地温测量仪等。

主持中国地质科学院物化勘查研究所专项资金项目1项(15万),中央高校杰出人才培育基金1项(20万);以骨干成员参与国家自然科学基金面上项目、国家重大科学仪器设备开发专项、总装备预先研究项目、NRC加拿大国家研究委员会专项资金项目、NASA美国国家航空航天局开放课题等项目。先后主持或参与研制的仪器有:分布式页岩气开采水力压裂电位监测仪、动态质子磁梯度航弹探测器、地面地磁监测仪。

近年来,发表SCI/EI论文20余篇,引用70余次(Google Scholar)。担任多个外文期刊及国际会议审稿人,包括:IEEE Transactions on Industrial ElectronicsIEEE Transactions on Instrumentation and MeasurementIEEE Transactions on ReliabilityMeasurementIEEE International Conference on Industrial Technology (ICIT)

英文个人主页请访问:https://huanliu5186.wixsite.com/huanliu


教育经历

2012.09 - 2018.06,中国地质大学(武汉),地球探测与信息技术专业,博士(硕博连读)

2016.09 - 2017.09,加拿大英属不列颠哥伦比亚大学(UBC),电气工程与计算机科学专业,联合培养(国家留学基金委资助)

2008.09 - 2012.06,中国地质大学(武汉),测控技术与仪器专业,学士

 

工作经历

2018.07 - 至今,中国地质大学(武汉),自动化学院,特任副教授


科研项目

1.   中央高校杰出人才培育基金:多源磁测数据融合机理研究(主持,在研)

2.   中国地质科学院物化勘查研究所专项资金项目:页岩气开采水力压裂电位监测仪研究 (主持,结题) 

3.   国家自然科学基金面上项目:基于优化动态核极化的新型Overhauser磁力仪研究(骨干成员,在研)

4.   国家重大科学仪器设备开发专项:海洋地磁场矢量测量仪开发与应用(骨干成员,在研)

5.   解放军总装备部装备预先研究项目:动态激发质子磁法XXX技术研究(骨干成员,结题)

6.   NRC加拿大国家研究委员会研究项目:地下输油管道无损探伤技术研究(骨干成员,结题) 

7.   NASA美国国家航空航天局开放课题:复合材料损伤程度智能预测研究(骨干成员,结题


学术成果


期刊论文


[1]   Huan Liu, Zheng Liu, Brandon Taylor, et al. Matching pipeline In-line inspection data for corrosion characterization, NDT & E International, 101: 44-52, 2019. 

[2]   Huan Liu, Haobin Dong, Jian Ge, et al. Apparatus and method for efficient sampling of critical parameters demonstrated by monitoring an Overhauser geomagnetic sensor, Review of Scientific Instruments, 89(12): 125109, 2018. 

[3]   Huan Liu, Haobin Dong, Zheng Liu, et al. A comprehensive study on the weak magnetic sensor character of different geometries for proton precession magnetometer, Journal of Instrumentation, 13(9): T09003, 2018. 

[4]   Huan Liu, Zheng Liu, Shuo Liu, et al. A nonlinear regression application via machine learning techniques for geomagnetic data reconstruction processing, IEEE Transactions on Geoscience and Remote Sensing, PP(99): 1-13, 2018. 

[5]   Huan Liu, Haobin Dong, Zheng Liu, et al. Application of Hilbert-Huang decomposition to reduce noise and characterize for NMR FID signal of proton precession magnetometer, Instruments and Experimental Techniques, 61(1):55-64, 2018. 

[6]   Huan Liu, Haobin Dong, Zheng Liu, et al. Noise characterization for the FID signal from proton precession magnetometer, Journal of Instrumentation, 12(7): P07019, 2017. 

[7]   Huan Liu, Haobin Dong, Zheng Liu, et al. Construction of an Overhauser magnetic gradiometer and the applications in geomagnetic observation and ferromagnetic target localization, Journal of Instrumentation. 12(10): T10008, 2017. 

[8]   Huan Liu, Haobin Dong, Jian Ge, et al. An improved tuning control algorithm based on SVD for FID signal, Journal of Advanced Computational Intelligence and Intelligent Informatics, 21(1): 133-138, 2017.

[9]   Huan Liu, Haobin Dong, Jian Ge, et al. Research and develop of the test apparatus for measuring the excitation frequency of Overhauser magnetometer probe, Acta Electronica Sinica, 45(2): 1272-1280, 2017. 

[10]  Haobin Dong, Huan Liu (共同第一作者,通讯作者), Jian Ge, et al. A high-precision frequency measurement algorithm for FID signal of proton magnetometer, IEEE Transactions on Instrumentation and Measurement, 65(4): 898-904, 2016. 

[11]  Huan Liu, Haobin Dong, Jian Ge, et al. Research on a secondary tuning algorithm based on SVD & STFT for FID signal, Measurement Science and Technology, 27(10): 105006, 2016. 

[12]  Huan Liu, Haobin Dong, Jian Ge, et al. Magnetic field gradient detector based on the nuclear Overhauser effect, Chinese Journal of Scientific Instrument, 36(3): 592-600, 2015. 

[13]  Bingjie Bai, Huan Liu, Jian Ge, et al. Research on an improved resonant cavity for Overhauser geomagnetic sensor, IEEE Sensors Journal, 18(7): 2713-2721, 2018. 

[14]  Jian Ge, Haobin Dong, Huan Liu, et al. Overhauser geomagnetic sensor based on the dynamic nuclear polarization effect for magnetic prospecting, Sensors, 16(6): 806-822, 2016. 

[15]  Yuefei Huang, Jian Ge, Haobin Dong and Huan Liu (通讯作者). An automatic wide-band 90o phase shifter for optically pumped cesium magnetometers, IEEE Sensors Journal, 17(23):7928-7934, 2017. 

[16]  Haobin Dong, Shuting Hu, Jian Ge, Huan Liu, et al. A high-precision and fast-sampling frequency measurement method based on FPGA carry chain for airborne optically pumped cesium magnetometer. Review of Scientific Instruments, 89(7): 075001, 2018. 

[17]  Jian Ge, Chengda Lu, Haobin Dong, Huan Liu, et al. The detection technology of near-surface UXO based on magnetic gradient method and Overhauser sensor, Chinese Journal of Scientific Instrument, 36(5): 38-50, 2015. 

[18]  Jian Ge, Xiangyu Qiu, Haobin Dong, Wang Luo, Huan Liu, et al. Short-time and high-precision measurement method for Larmor frequency of marine Overhauser sensor. IEEE Sensors Journal, 18(4): 1442-1448, 2018. 


会议论文


[1]  Huan Liu, Yihao Liu, Shuo Liu, et al. What can machine learning do for geomagnetic data processing? A reconstruction application, IEEE International Conference on Instrumentation and Measurement Technology (I2MTC), 1-6, 2018.

[2]  Huan Liu, Shuo Liu, Zheng Liu, et al. Prognostics of damage growth in composite materials using machine learning techniques, IEEE International Conference on Industrial Technology (ICIT), 1042-1047, 2017.

[3]  Huan Liu, Haobin Dong, Jian Ge, et al. A high-precision proton magnetometer based on a multi-channel frequency measurement, IEEE International Conference on Instrumentation and Measurement Technology (I2MTC), 1-6, 2016.

[4]  Huan Liu, Haobin Dong. Research and developed of magnetic field gradient detector based on the nuclear Overhauser effect, IEEE International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC), 330-333, 2015.

[5]  Zheng Liu, Huan Liu. Experimenting capacitive sensing techniques for structural integrity assessment, IEEE International Conference on Industrial Technology (ICIT), 922-927, 2017.

[6]  Fang Shi, Xiang Peng, Huan Liu, et al. Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods, Smart Structures and NDE for Industry 4.0, 1060207, 2018. 

[7]  Bingjie Bai, Haobin Dong, Jian Ge, Huan Liu, et al. A resonant cavity based on birdcage coil for Overhauser geomagnetic sensor, IEEE International Conference on Instrumentation and Measurement Technology (I2MTC), 1-6, 2018.


学术报告


2018  IEEE I2MTC,张贴海报,休斯顿,美国

        • What Can Machine Learning Do for Geomagnetic Data Processing? A Reconstruction Application

        • A Resonant Cavity Based on Birdcage Coil for Overhauser Geomagnetic Sensor

2017  IEEE ICIT,作分会场报告,多伦多,加拿大

        • Prognostics of Damage Growth in Composite Materials Using Machine Learning Techniques

        • Experimenting Capacitive Sensing Techniques for Structural Integrity Assessment

2016  ITCA,作分会场报告,东京,日本

        • An Improved Tuning Control Algorithm Based on SVD for FID signal

2016  IEEE I2MTC,张贴海报,台北,中国台湾

        • A High Precision Proton Magnetometer Based on a Multi-Channel Frequency Measurement

2015  IEEE IMCCC,张贴海报,秦皇岛,中国

        • Research and Developed of Magnetic Field Gradient Detector Based on the Nuclear Overhauser Effect


发明专利


[1]   董浩斌, 刘欢等. 提高质子旋进类传感器调谐精度和信噪比的方法及系统, 公布日:2017.05.31.

[2]   葛健, 董浩斌, 邱香域, 刘欢等. 一种基于量化时延法提高FID信号测频精度的方法及电路, 公布日:2017.05.10.


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