机械装备与控制工程系
hantian@ustb.edu.cn
010-62334106,13146339921
机电楼811
本科生课程:《机电传动控制》
教育经历:
1996.09-2000.07 吉林大学 汽车工程学院 车辆工程专业,获学士学位
2000.09-2002.07 韩国釜庆大学 天游ty8检测中心官方登录 机械设计专业,获硕士学位
2002.09-2005.07 韩国釜庆大学 天游ty8检测中心官方登录 机械设计专业,获博士学位
工作经历:
2006.05-2011.06 天游ty8检测中心官方登录,讲师
2011.07-2022.07 天游ty8检测中心官方登录,副教授
2014.10-2015.10 澳大利亚 昆士兰科技大学,访问学者
2022.08-至今 a天游ty8检测中心官方登录,教授
2013年入选“北京市青年英才计划”,多次获得“北京科技大学优秀本科生导师”称号,指导多项“互联网+”、国家级创新创业项目。参加多项教学、教改项目。先后主持国家级项目,国家重点研发计划子课题承担和参与多项国家级科研项目,负责20余项校企合作项目,科研经验丰富。在学术领域,发表高水平论文40余篇,授权发明专利10余项,撰写外文著作一部。国际、国内EI及以上期刊审稿专家:Mechanical Systems and Signal Processing、Expert Systems with Applications、Journal of Manufacturing Systems、Knowledge-Based Systems、Applied Soft Computing、Reliability Engineering & System Safety、ISA Transactions、Structural Health Monitoring、Computers in Industry、Measurement、Chinese Journal of Mechanical Engineering、机械工程学报、航空学报、华中科技大学学报(自然科学版)、振动与冲击等。
科研项目:
[1]2024年创建国家自主创新示范区项目,钢铁行业高炉泥炮自动化作业机器换人关键技术开发及应用,在研,负责
[2]基于智能模型的稀土冶炼自动化装备开发,在研,负责
[3]智能消防巡检机器人研发及应用,在研,负责
[4]高炉泥炮自动装炮泥机器人关键技术开发及应用,在研,负责
[5]样品释放装置与新型捕获机构关键部件研制,在研,负责
[6]炼铁制造部泥炮打泥量电子标尺项目,日照钢铁有限公司,在研,负责
[7]发电实验台主机转子稳定性故障诊断及解决,上海朝临动力科技有限公司,在研 负责
[8]机体杆端球轴承研制阶段实验数据分析处理,中国航空综合技术研究所,在研 负责
[9]伸缩式撑杆研制阶段实验数据分析处理,中国航空综合技术研究所,在研 负责
[10]国家重点研发计划重点专项,智能水下推土装备研制,2018.07-2021.06 结题,子课题负责
[11]国家重点研发计划重点专项,流体机械复杂系统的关联耦合机制,2018.05-2021.04 结题,子课题参与
[12]风机传动链低速级故障诊断能力提升,三一重能股份有限公司,结题,负责
[13]龙门吊自动装卸渣土软件研制,中铁电气化局集团有限公司铁路工程公司,在研,负责
[14]北京高校青年英才计划,2013-2015,结题,负责
[15]对接机构钢丝绳持久拉伸寿命试验设备开发,上海宇航系统工程研究所,2019.10,结题,负责
[16]基于CMS系统的风电机组状态分析和故障诊断算法研究服务,中国电力科学研究院,2017.07,结题,主要参与
[17]系绳收放装置研制,上海宇航系统工程研究所,2016.11,结题,主要参与
[18]对接机构部件寿命试验设备,上海宇航系统工程研究所,2014.05,结题,主要参与
[19]燕钢ACL80型轴流压缩机振动问题研究,成都成发科能动力工程有限公司,2014.06,结题,负责
[20]涟钢CSP热连轧机振动在线监测及抑振控制,湖南华菱涟钢薄板有限公司,2013.04,结题,参与
[21]大型电磁振动台关键部件可靠性研究,北京航天希尔测试技术有限责任公司,2009.04,结题,参与
代表性成果:
期刊论文:
[1]Shengrong Shen, Tian Han *, Jiachen Pang, Car drag coefficient prediction using long–short term memory neural network and LASSO[J]. Measurement, 2024, 225. (SCI 2区 top)
[2]Tian Han, Dandan Qi, Jia Ma, Chaoyang Sun, Generative design and mechanical properties of the lattice structures for tensile and compressive loading conditions fabricated by selective laser melting [J]. Mechanics of Materials 2024, 118. (SCI 3区)
[3]Ruiyi Ma, Tian Han∗, Wenxin Lei,Cross-domain meta-learning fault diagnosis by multi-scale dilated convolution and adaptive relation module with one-shot new fault labeled data[J]. Knowledge-Based Systems, 2023, 261.(SCI 1区 top)
[4] Tian Han, lingjie Ding, Dandan Qi, Chao Li, Zhi Fu, Weidong Chen, Compound faults diagnosis method for wind turbine mainshaft bearing with Teager and second-order stochastic resonance[J]. Measurement, 2022, 202.(SCI 2区 top)
[5]Zhiqiang Chao, Tian Han*, Fault diagnosis of rolling bearings using a cascade midpoint residual convolutional neural network with multiscale[J]. Neurocomputing, 2022, 506.(SCI 2区 top)
[6]Tian Han, Jiachen Pang, Andy C. C, Remaining useful life prediction of bearing based on stacked autoencoder and recurrent neural network[J]. Journal of Manufacturing System, 2021, 61.(SCI 2区 top)
[7] Tian Han, Zhiqiang Chao, Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021, 43(9).(SCI 4 区)
[8] Tian Han*, Ruiyi Ma, JiguiZheng. Combination bidirectional long short-term memory and capsule network for rotating machinery fault diagnosis[J]. Measurement, 2021, 176.(SCI 2区 top)
[9] Tian Han*, Longwen Zhang, Zhongjun Yin. Rolling bearing fault diagnosis with combined convolutional neural networks and support vector machine[J]. Measurement, 2021(1):109022. (SCI 2区 top)
[10] Tian Han*, Zhixin Tian, Zhongjun Yin, Andy C.C. Tan. Bearing fault identification based on convolutional neural network by different input modes[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2020, 42(9). (SCI 4区)
[11] Li Zhang, Han Tian*, Zhongjun Yin, Kaichun Zhao. Lane detection in dense fog using a polarimetric dehazing method. Applied Optics, 2020, 59.(SCI 3区)
[12]韩天, 张雨霖, 缪存孝, 刘建丰, 薛帅, VCSEL激光器抗干扰温度控制, 红外与激光工程, 2020, (6)(EI已收录)
[13]Tian Han*, Qiannan Liu, LiZhang, Andy C.C. Tan. Fault feature extraction of low speed roller bearing based on Teager energy operator and CEEMD[J]. Measurement, 2019, 138.(SCI 2区 top)
[14] Wang, Ruiming, Han, Tian*, Wang, Wenrui, et al. Fracture analysis and improvement of the main shaft of wind turbine based on finite element method[J]. Advances in Mechanical Engineering, 2018, 10(4):168781401876900. (SCI4区)
[15] Tian Han*, Xueliang Liu, Andy C.C. Tan. Fault diagnosis of rolling element bearings based on Multiscale Dynamic Time Warping, Measurement, 2017(95):355-366.(SCI 2区 top)
[16] Shuang Pan, Tian Han*, Andy C. C. Tan and Tian Ran Lin. Fault Diagnosis System of Induction Motors Based on Multiscale Entropy and Support Vector Machine with Mutual Information Algorithm, Shock and Vibration. 2016:1-12.(SCI 4区)
[17] Yin, Zhongjun, Zhang, Hang, Han, Tian*. Simulation of particle flow on an elliptical vibrating screen using the discrete element method[J]. Powder Technology, 2016:S0032591016305538.(SCI 2区)
[18]潘双, 韩天*, 史琳, 轴流压缩机转子动力学特性研究, 机械设计与制造, 2015(11):8-12.(中文核心)
[19]Han, Tian*, Chenxi Huang, Andy C.C. Tan. Experimental and finite element analysis to identify the source of vibration of a coach. Engineering Failure Analysis. 2014(44): 100–109. (SCI 3区).
[20]Zhanqi Zhang, Zhongjun Yin, Tian Han*, Andy C.C. Tan. Fracture analysis of Wind Turbine main shaft. Engineering Failure Analysis. 2013(34): 129–139. (SCI3区)
[21]韩天, 史琳, 赵爱国. 基于Adams的风力发电机齿轮故障分析, 计算机辅助工程, 2013.22(1).256-260.(中文核心)
[22]韩天, 史琳, 张庆海.基于有限元的轴承参数变化对离心式压缩机转子固有特性的影响研究, 机械传动, 2013.37(11).14-17.(中文核心)
[23] 韩天, 尹忠俊, 杨邵伟, 电机转子断条故障诊断方法探讨, 电力系统及其自动化学报,2009, 93-98.(EI: 10848859)
[24]韩天, 孙欣, 尹忠俊, 基于多代理决策融合的电机状态识别, 北京科技大学学报, 2007, 29(2): 182-186.(EI: 20080811110876)
[25] Tian Han, Bo-Suk Yang and Zhong-Jun Yin, Feature-based fault diagnosis system of induction motors using vibration signal, Journal of Quality in Maintenance, 2007,13(2):163-5175.(EI: 9557442)
[26]Tian Han and Bo-Suk Yang, Development of an e-maintenance system integrating advanced techniques, Computers in Industry, 2006,57(6):569-580.(SCI 2区)
[27]Tian Han, Bo-Suk Yang, Won-Ho Choi, and Jae-Sik Kim, Fault diagnosis system of induction motors based on neural network and genetic algorithm using stator current signals, International Journal of Rotating Machine,2006,1-13. (EI)
著作
Tian Han, Intelligent Fault Diagnostics System of Induction motor, LAMBERT Academic Publishing, 248页, 2014
专利
第一发明人申请发明专利14项,授权8项:
[1]韩天, 申圣容, 庞佳晨, 轿车车体侧面轮廓风阻系数的预测方法:CN202311131377.6
[2]韩天, 王威中, 吴迪平, 高炉炉前智能操作系统及方法:CN202410577344.2
[3]韩天, 祁丹丹, 用于拉压载荷条件下点阵结构建模方法及其衍生点阵结构:CN202211254831.2
[4]韩天, 雷文鑫, 陈哲涵, 基于深度学习的已有火焰环境中异常烟火识别监测方法:CN113192038A
[5]韩天, 马瑞艺, 基于改进CNN与关系模块的旋转部件故障诊断方法及其装置:CN113111820B
[6]韩天, 张超, 张升, 基于创成式优化及导向式重构的大中型件轻量化设计方法:CN112800655B
[7]韩天,黄陈熙,尹忠俊, 一种基于时间序列模型的轴类零件裂纹判别方法:CN104251815A
[8]韩天,胡纯,缪存孝,赵航,一种旋转调制径向球面永磁偏置磁轴承:CN105156475A
[9]韩天,缪存孝,赵航,魏振博, 一种旋转调制双线圈轴向球面纯电磁磁轴承:CN106949145A
[10]韩天,王泽,基于CNN模型和迁移学习的滚动轴承故障诊断方法:CN110220709A
[11]韩天,刘倩男,尹忠俊,缪存孝,导引绳侧边进线式放线滑车:CN109193459A
[12]韩天,王泽,尹忠俊,缪存孝,用于无人机架线系统的放线滑车:CN109217180A
[13]韩天,刘倩男,尹忠俊,缪存孝,无人机架线系统及架线方法:CN109473910A
[14]韩天, 祁丹丹, 用于拉压载荷条件下点阵结构建模方法及其衍生点阵结构:CN115563789A
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