基本信息

刘承宝  男  博士、副研究员  中国科学院自动化研究所
电子邮件: liuchengbao2016@ia.ac.cn
通信地址: 北京市海淀区中关村东路95号
邮政编码:100190

个人简介

刘承宝,博士,中国科学院自动化研究所副研究员,中国科学院人工智能创新研究院2035创新任务团队子任务负责人,长期从事智能制造、知识自动化、人工智能与大数据等方面的研究工作。担任中国自动化学会制造技术专业委员会委员、中国机械工程学会机械工业自动化分会委员、全国机器人标准化技术委员会人形机器人标准化工作组(SAC/TC591/WG2)委员,《工业工程》、《制造业自动化》、《数据采集与处理》等期刊青年编委。近年来,主持承担了国家自然科学基金青年基金1项、国家重点研发计划课题1项及子课题2项、工信部工业互联网创新发展工程项目3项、企业委托项目3项。发表SCI/EI论文30余篇,授权美国发明专利2项、国家发明专利10余项,登记软件著作权4项,参与制定发布国家标准3项,参与编写发布《工业智能白皮书(2022)》,获得中国自动化学会科技进步奖一等奖(排名2/15)、中国商业联合会科技进步奖一等(排名2/15)广东省科技进步一等奖(排名6/15)、北京市科技进步奖二等奖(排名3/10)中国机械工业科技进步奖二等奖(排名3/10)等奖项。相关成果已在新能源汽车动力电池、集成电路、航空航天核电钢铁、有色等行业应用推广。

招生信息

本课题组每年接收计算机自动化软件工程等相关方向的博士、硕士研究生,同时常年招聘工业智能智能优化决策大数据分析软件开发等岗位实习生访学生联培生,有意者可邮件联系。

教育背景

2016-09--2019-06   中国科学院大学   工学博士学位
2013-09--2016-06   冶金自动化研究设计院   工学硕士学位
2008-09--2012-06   西安建筑科技大学   工学学士学位
学位

中国科学院自动化研究所,控制理论与控制工程,工学博士

工作经历

   
工作简历
2022-04~现在, 中国科学院自动化研究所, 副研究员
2019-07~2022-03,中国科学院自动化研究所, 助理研究员
社会兼职
2024-01-01-今,《工业工程》, 青年编委
2023-12-14-今,中国指挥与控制学会, 高级会员
2023-11-01-今,《数据采集与处理》, 青年编委
2023-08-10-今,全国机器人标准化技术委员会人形机器人标准化工作组(SAC/TC591/WG2), 委员
2022-03-01-今,《冶金自动化》期刊, 青年编委
2022-01-01-今,《制造业自动化》期刊, 青年编委
2021-01-01-今,中国自动化学会制造技术专业委员会, 委员
2021-01-01-今,中国机械工程学会工业自动化分会委员会, 委员
2020-10-17-今,中国自动化学会, 高级会员
2020-01-01-今,中国机械工程学会, 高级会员

奖励荣誉与知识产权

   
奖励信息
(1) 中国机械工业科学技术奖, 二等奖, 部委级, 2022
(2) 中国自动化学会科技进步奖, 一等奖, 其他, 2022
(3) 中国商业联合会科学技术奖, 一等奖, 部委级, 2022
(4) 广东省科学技术奖, 一等奖, 省级, 2022
(5) 北京市科学技术奖, 二等奖, 省级, 2021
专利信息

  1. Chengbao Liu, Jie Tan. Optimization decision-making method of industrial process fusing domain knowledge and multi-source data, 2022-08-09, US11,409,270B1.

  2. Jie Tan, Chengbao Liu. Acquisition method for domain rule knowledge of industrial process, 2022-09-27, US11,455,548B2

  3. 刘承宝,谭杰,赵宏博,李永杰,葛小亮. 多源异构数据融合的高炉煤气流分布状态识别方法及系统,2022-05-09,授权号:ZL202210496119.7.

  4. 谭杰,李媛,刘承宝. 一种基于主动学习的分布式检测系统,2021-10-28,申请号:CN202111262486.2.

  5. 谭杰,李经纬,刘承宝. 碳化硅表面原子台阶宽度测量方法及系统,2021-07-19,授权号:ZL202110815513.8.

  6. 刘承宝, 谭杰. 融合领域知识与多源数据的工业过程优化决策方法, 2021-2-18, 授权号: ZL202110186760.6.

  7. 刘承宝, 谭杰. 工业过程领域规则知识获取方法, 2021-2-18, 授权号: ZL202110186773.3.

  8. 刘承宝, 谭杰. 嵌入领域规则的工业过程优化决策知识推理方法, 2021-2-18, 授权号: ZL202110186775.2.

  9. 刘承宝, 谭杰. 基于知识蒸馏的工业过程优化决策模型迁移优化方法, 2021-2-18, 授权号: ZL202110186781.8.

  10. 王学雷,刘承宝,谭杰. 基于大数据分析的电池分选方法及系统,2018-11-21,授权号: ZL2018113935180.

  11. 王学雷, 满春涛, 王连旌, 白熹微, 刘承宝. 电池配组方法,2018-09-14,授权号: ZL201811075331.6.

  12. 谭杰, 刘承宝, 王学雷. 锂电池涂布生产的知识决策方法,2017-10-11,授权号: ZL201710940572.1.

  13. 谭杰, 白熹微, 黄学文, 刘承宝, 李亚宁. 物化视图选择和优化方法及装置,2017-09-07,授权号: ZL201710801784.1.

标准信息

  1. 国家标准,刘承宝(参与),通用制造工艺知识表示,GB/T 39475-2020,2020.11.19

  2. 国家标准,刘承宝(参与),通用制造工艺知识分类及编码方法,GB/T 39469-2020,2020.11.19

  3. 国家标准,刘承宝(参与),工业机器人云服务平台分类及参考体系结构,GB/T 40212-2021,2021.5.21

出版信息

   
学术论文

  1. Chengbao Liu, Jie Tan* and Xuelei Wang. A data-driven decision-making optimization approach for inconsistent lithium-ion cell screening. Journal of Intelligent Manufacturing, 2020, 31(4): 833-845.

  2. Chengbao Liu, Jie Tan*, Jingwei Li, Yuan Li, Huanjie Wang. Temporal Hypergraph Attention Network for Silicon Content Prediction in Blast Furnace, IEEE Transactions on Instrumentation and Measurement (TIM), 2022, 71:1-13.

  3. Jingwei Li, Yuan Li, Jie Tan and Chengbao Liu*. It takes two: Dual Branch Augmentation Module for domain generalization. Neural Networks, 2024, 172: 106094.

  4. Jingwei Li, Yuan Li, Jie Tan and Chengbao Liu*. Bridging the gap with grad: Integrating active learning into semi-supervised domain generalization. Neural Networks, 2024, 171: 186-199

  5. Tingkun Zhang, Chengbao Liu*, Zhenjie Liu, Jie Tan and Mutellip Ahmat*. Temporal Double Graph Convolutional Network for CO and CO2 Prediction in Blast Furnace Gas. IEEE Transactions on Instrumentation and Measurement (TIM), 2023, 73: 1-13.

  6. Yuan Li, Jingwei Li, Huanjie Wang, Chengbao Liu, Jie Tan*. Knowledge enhanced ensemble method for remaining useful life prediction under variable working conditions. Reliability Engineering & System Safety, 2024, 242: 109748.

  7. Jingwei Li, Yuan Li, Huanjie Wang, Chengbao Liu, Jie Tan*. Exploring Explicitly Disentangled features for Domain Generalization. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023, 33(11): 6360-6373.

  8. Huanjie Wang, Yuan Li, Xiwei Bai, Jingwei Li, Jie Tan*, Chengbao Liu. Label propagation-based unsupervised domain adaptation for intelligent fault diagnosis. Journal of Intelligent Manufacturing2023, DOI: 10.1007/s10845-023-02186-1.

  9. Baowen Xu, Xuelei Wang*, Chengbao Liu, Zhenjie Liu, Liwen Kang. Dual-channel spatio-temporal wavelet transform graph neural network for traffic forecasting. In Proceedings of 2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia, 18-23 June, 2023: 1-8.

  10. Yuan Li, Jingwei Li, Chengbao Liu, Jie Tan*. Time Series Forecasting Model Based on Domain Adaptation and Shared Attention. In Proceedings of International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2023), Cham: Springer Nature Switzerland, 2023: 215-225.

  11. Yuan Li, Huanjie Wang, Jingwei Li, Chengbao Liu and Jie Tan*. ACT: Adversarial Convolutional Transformer for Time Series Forecasting. In Proceedings of 2022 International Joint Conference on Neural Networks (IJCNN), Padua, Italy, Jul. 18-23, 2022: 1-8. 

  12. Huanjie Wang, Xiwei Bai, Sihan Wang, Jie Tan* and Chengbao Liu. Generalization on Unseen Domains via Model-Agnostic Learning for Intelligent Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement (TIM), 2022, 71:1-11.

  13. Jingwei Li, Huanjie Wang, Ke Wu, Chengbao Liu, Jie Tan*. Cross-attention-map-based regularization for adversarial domain adaptation. Neural Networks, 2022,145: 128-138.

  14. Yudong Wang, Xiwei Bai, Chengbao Liu, Jie Tan*. A multi-source data feature fusion and expert knowledge integration approach on lithium-ion battery anomaly detection. Journal of Electrochemical Energy Conversion and Storage, 2022, 19(2): 021003. 

  15. Yudong Wang, Xiwei Bai, Chengbao Liu, Jie Tan*. Lithium-Ion Power Battery Grouping: A Multisource Data Fusion-Based Clustering Approach and Distributed Deployment. Journal of Electrochemical Energy Conversion and Storage, 2022, 19(2): 021016.

  16. Ke Wu, Jie Tan*, and Chengbao Liu*. Cross-domain few-shot learning approach for lithium-ion battery surface defects classification using an improved siamese network. IEEE Sensors Journal, 2022, 22(15): 11847-11856. 

  17. Ke Wu, Jie Tan*, Hailun Xia, Chengbao Liu*. An exposure fusion-based structured light approach for the 3D measurement of a specular surface. IEEE Sensors Journal, 2021, 21(5): 6314 - 6324. 

  18. Ke Wu, Jie Tan*, Chengbao Liu*. A novel approach to obtain optimal exposure for 3D shape reconstruction of high dynamic range objects. Measurement Science and Technology, 2021, 32(9): 095206. 

  19. Ke Wu, Jie Tan*, Jingwei Wu, Chengbao Liu. Few-shot learning approach for 3D defect detection in lithium battery. In Proceedings of 2021 International Conference on Intelligent Manufacturing and Industrial Automation (CIMIA 2021) ,Mar. 26-28,2021, Guilin, China, V(1884).

  20. Xiwei Bai, Jie Tan*, Xuelei Wang, Lianjing Wang, Chengbao Liu, Liyong Shi, Wei Sun. Study on distributed lithium-ion power battery grouping scheme for efficiency and consistency improvement. Journal of Cleaner Production, 2019, 233:429-445.

  21. Chengbao Liu, Jie Tan*, Heyuan Shi and Xuelei Wang. Lithium-ion Cell Screening with Convolutional Neural Networks Based on Two-step Time-series Clustering and Hybrid Resampling for Imbalanced Data. IEEE Access, 2018, 6:59001-59014. 

  22. Chengbao Liu, Xuelei Wang*, Ke Wu, Jie Tan, Fulin Li, Wenfa Liu. Oversampling for Imbalanced Time Series Classification Based on Generative Adversarial Networks. In Proceedings of 2018 4th IEEE International Conference on Computer and Communications (ICCC), Chengdu, China, Dec. 7-10, 2018: 1104-1108. 

  23. Chengbao Liu, Xuelei Wang*, Jie Tan, Lianjing Wang, Wei Sun, Wenxiang He. Discharge Voltage Time Series Classification of Lithium-ion cells Based on Deep Neural Networks. In Proceedings of 2018 4th IEEE International Conference on Computer and Communications (ICCC), Chengdu, China, Dec. 7-10, 2018: 2128-2132. 

  24. Lianjing Wang, Jie Tan, Chuntao Man, Xiwei Bai, Xuelei Wang, Chengbao Liu. Battery Grouping Based on Dynamic Gaussian Mixture Model. In Proceedings of 2018 4th IEEE International Conference on Computer and Communications (ICCC), Chengdu, China, Dec. 7-10, 2018: 2635-2640.

  25. Lianjing Wang, Jie Tan, Chuntao Man, Xiwei Bai, Xuelei Wang, Chengbao Liu. Application of Modified K-Means Clustering Algorithm in Battery Grouping. In Proceedings of 2018 4th IEEE International Conference on Computer and Communications (ICCC), Chengdu, China, Dec. 7-10, 2018: 2007-2011.

  26. Chengbao Liu, Jie Tan*, Hongsheng Zhao, Yaning Li, Xiwei Bai. Path Planning and Intelligent Scheduling of Multi-AGV Systems in Workshop. In Proceedings of the 36th Chinese Control Conference (CCC), Dalian, China, July 26-28, 2017: 2735 – 2739. 

  27. Yaning Li, Xuelei Wang, Jie Tan, Chengbao Liu, Xiwei Bai. Intelligent integrated coking flue gas indices prediction. In Proceedings of 2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Kanazawa, Japan, 26-28 June, 2017: 39-45.

  28. Yaning Li, Xuelei Wang, Xiwei Bai, Jie Tan, Chengbao Liu. Optimal setting for coking flue gas denitriation process indices based on PCR-multi-case fusion. In Proceedings of  2017 3rd IEEE International Conference on Cybernetics (CYBCONF), Exeter, UK, 21-23 June, 2017: 1-7.

  29. Heyuan Shi, Kun Tang*, Chengbao Liu, Xiaoyu Song, Chao Hu and Jiaguang Sun. Memetic-based schedule synthesis for communication on time-triggered embedded systems. International Journal of Distributed Sensor Networks, 2017, 13(10):1-7. 

  30. 李亚宁, 王学雷, 谭杰, 刘承宝, 白熹微. 焦化换向过程烟气脱硝扰动建模与前馈控制, 化工学报, 2017, 68(8): 3168-3176.

  31. 刘承宝, 刘新忠, 苗宇. 基于混合核PSO-LSSVM的轧制力预测[J]. 冶金自动化, 2016, 40(02): 15-19+24.

科研项目

  1. 国家自然科学基金-青年科学基金项目,62003344,多源信息融合的工业过程知识获取方法研究,2021/01-2023/12,主持;

  2. 国家自然科学基金-广东联合基金重点项目,U1801263,离散制造过程人工智能驱动的优化与控制,2019/01-2022/12,参与;

  3. 国家自然科学基金-广东联合基金重点项目,U1701262,工业过程数据实时获取与知识自动化,2018/01-2021/12,参与;

  4. 国家重点研发计划项目,2022YFB3304602,数据和知识驱动的云边协同信息处理技术,2022/11-2025/10,主持(课题负责人);

  5. 国家重点研发计划项目,2020YFB1711101,全流程物质流与能量流网络化双驱动精确建模与动态仿真,2020/11-2023/10,主持(子课题);

  6. 国家重点研发计划项目,2019YFB1704702,有色金属行业数据互联/服务共享/流程管理的跨域集成技术,2019/12-2022/11,主持(子课题);

  7. 工信部工业互联网创新发展工程专项,面向XXXX行业基于信息物理系统(CPS)的XXX系统,2020/05-2022/04,主持;

  8. 工信部工业互联网创新发展工程专项,基于“工业互联网平台+区块链”的XXX系统,2020/09-2022/09,主持;

  9. 工信部工业互联网创新发展工程专项,面向XXX行业工业机理模型库,2019/07-2021/12,主持;

  10. 工信部智能制造综合标准化与新模式应用项目,新能源汽车动力电池生产智能化工厂,2016/05-2018/12,参与;

  11. 企业委托,高炉炼铁过程知识自动化技术开发,2021.9-2023.6,主持;

  12. 企业委托,冶金工业模型开发,2021.7-2022.12,主持;

  13. 企业委托,碳化硅工业模型开发,2021.6-2022.6,主持.