Lei Guan | Machine Learning | Research Excellence Award

Mr. Lei Guan | Machine Learning | Research Excellence Award

Director | China Academy of Safety Science and Technology | China

Lei Guan is a Director and Professor at the Risk Monitoring and Early Warning Center, China Academy of Safety Science and Technology, with expertise in risk monitoring, early warning systems, artificial intelligence, and industrial safety engineering. He holds a Bachelor’s degree in Materials Science and Master’s and Doctoral degrees in Mechanical Engineering with specialization in precision instruments and safety-related systems. He has led major national and ministerial research programs, directed key laboratories and professional committees, supervised graduate researchers, and provided technical leadership for large-scale industrial and governmental safety initiatives. His research focuses on intelligent work safety systems, industrial internet applications, digital twins, data-driven risk modeling, and emergency management, with sustained contributions through peer-reviewed publications, patents, and standards development. His scholarly impact is reflected in 18 citations, an h-index of 3, and 13 published articles.

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Featured Publications

Numerical simulation of the double pits stress concentration in a curved casing inner surface
W. Yan, L. Guan, Y. Xu, J.G. Deng – Advances in Mechanical Engineering, 9(1) (3 citations)

Safety monitoring and management system for fluid catalytic cracking (FCC) process
L. Fang, Z. Wu, L. Wei, R. Kang, L. Guan – International Conference on Information and Automation (3 citations)

Study on SVM-based Flame Recognition and Fire Warning for Cotton and Linen Warehouses
X. Zhao, S. Hao, L. Guan, Y. Wang, Q. Zhao, D. Lv – IEEE Conference on Advances in Electrical Engineering (2 citations)

Industrial Internet of Things (IIoT) Identity Resolution Techniques: A Review
C. Dai, H. Li, L. Guan, M. Chi – IEEE BigDataSecurity (1 citation)

Qiaoning Yang | Signal & Image Processing | Best Researcher Award

Assoc. Prof. Dr. Qiaoning Yang | Signal & Image Processing | Best Researcher Award

Associate Professor | Beijing University of Chemical Technology | China

Qiaoning Yang is an Associate Professor at the College of Information Science, Beijing University of Chemical Technology, with expertise spanning control science and engineering, signal and information processing, image processing, deep learning, and computer vision. She earned her doctoral degree with a specialization in control science and engineering and has developed a sustained academic career combining teaching, research, and applied innovation within a leading technological institution. Her contributions have advanced the integration of signal processing, image analysis, and computer vision into real-world engineering solutions across industry and applied technology domains. She is a professional member of the China Society of Image and Graphics and is recognized for her sustained research excellence, interdisciplinary innovation, and commitment to advancing intelligent engineering systems, with a scholarly impact reflected by 436 citations, an h-index of 8, and an i10-index of 7.

Citation Metrics (Google Scholar)

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Featured Publications

Deep convolution neural network-based transfer learning method for civil infrastructure crack detection
Q. Yang, W. Shi, J. Chen, W. Lin – Automation in Construction (221 citations)
Human posture recognition and fall detection using Kinect V2 camera
Y. Xu, J. Chen, Q. Yang, Q. Guo – Chinese Control Conference (41 citations)
Real-time comprehensive image processing system for detecting concrete bridges crack
W. Lin, Y. Sun, Q. Yang, Y. Lin – Computers and Concrete (15 citations)

Dr. Angel Sapena Bano | Modelling Machines for Optimization | Research Excellence Award

Dr. Angel Sapena Bano | Modelling Machines for Optimization | Research Excellence Award

Associate Professor | Universitat Politecnica de Valencia | Spain

Ángel Sapena Bañó, Profesor Titular at the Universitat Politècnica de València, is a specialist in electrical engineering with expertise in electrical machines, diagnostic methods, numerical modelling, and condition monitoring. He holds degrees in Industrial Engineering, Energy Technology for Sustainable Development, and Secondary Education, complemented by a doctorate in Industrial Engineering focused on advanced diagnostic techniques for electrical machines. His professional trajectory includes roles as Lecturer, Researcher, and Technical Specialist, contributing to major academic initiatives, laboratory modernization, and collaborative research activities. He has participated in multiple competitive and industrial R&D projects, developed fault-diagnosis tools for induction machines and wind-energy systems, and strengthened international cooperation through research stays and Erasmus teaching engagements. His research spans analytical and hybrid modelling, finite-element methods, machine-learning-based diagnostics, and real-time simulation, reflected in numerous high-impact journal articles, conference contributions, book chapters, and patented inventions. He has led and co-led research outputs as first and corresponding author, supervised a wide range of graduate projects, and contributed to organizing scientific conferences and special issues. His distinctions include recognized research merits, invited reviewer roles in indexed journals, participation in prominent research groups, and involvement in impactful national and international scientific initiatives. His scholarly record includes 1,035 citations, 60 documents, and an h-index of 17.

Profiles: Scopus | ORCID

Featured Publications

Ángel Sapena Bañó*, Model-based diagnostic techniques for induction machines under transient operational conditions. Int. J. Electr. Power Energy Syst., Accepted.

Ángel Sapena Bañó*, Hybrid FEM–analytical modelling framework for efficient fault detection in eccentric induction motors. Sensors, 2025, 25, 1–28.

Ángel Sapena Bañó, Deep learning–enhanced condition monitoring strategies for electrical machines operating in variable regimes. Mathematics and Computers in Simulation, 2025, 1–28.

Prof. Yu-Ling He | Electric Machine | Best Researcher Award

Prof. Yu-Ling He | Electric Machine | Best Researcher Award

North China Electric Power University | China

Yu-Ling He is a distinguished professor and accomplished researcher in mechanical and electrical engineering at North China Electric Power University. Serving as Vice Dean of the Department of Mechanical Engineering and Vice Dean of the Hebei Engineering Research Center for Advanced Manufacturing & Intelligent Operation and Maintenance of Electric Power Machinery, he has established himself as a leading authority in electromechanical systems, intelligent maintenance, and vibration engineering. As an IEEE Senior Member and recognized provincial talent, he has earned multiple prestigious awards and continues to advance power machinery research globally.

Professional Profile

Scopus Profile | ORCID

Education

Professor Yu-Ling He pursued dual bachelor’s degrees in Mechanical and Electrical Engineering at North China Electric Power University, Baoding, graduating. He then earned a master’s degree in Mechatronics Engineering, where his outstanding academic performance led to early graduation. Continuing at the same institution, he completed his Ph.D. in Power Machinery and Engineering, with his doctoral thesis recognized as an excellent dissertation by the university. His academic training laid a strong foundation for his expertise in advanced electromechanical systems and energy-related technologies.

Experience

Yu-Ling He began his academic career as a lecturer and advanced to associate professor. After years of impactful teaching, research, and service, he was promoted to full professor. He also gained international experience as an academic visitor in the Department of Electrical and Electronics Engineering at the University of Nottingham, Beyond his academic roles, he serves as Vice President and Secretary General of the Hebei Society for Vibration Engineering and contributes actively to several national and provincial research centers. His leadership has significantly shaped advanced research in electric power machinery and intelligent systems.

Research Focus

The central focus of Professor He’s research lies in advanced design, manufacturing, and intelligent maintenance of power equipment. His expertise includes mathematical modeling, digital twin technologies, and signal processing for electromechanical systems. He has contributed to the development of intelligent mechatronics equipment and integrated energy systems, addressing challenges in system reliability, performance monitoring, and predictive maintenance. By exploring the interaction of magnetic, thermal, and mechanical multi-physics fields, he has provided groundbreaking insights into generator performance under fault conditions. His research directly supports the safe, efficient, and sustainable operation of power systems worldwide.

Awards & Honors

Throughout his career, Yu-Ling He has received an impressive array of honors at national and international levels. Among these are the Best Research Award at the International Research Awards on Fiber-Reinforced Polymer, a Gold Medal at the International Exhibition of Inventions of Geneva, and first and special prizes at the National Equipment Management and Technology Innovation Awards. He has also been recognized as an Excellent Expert of Baoding City, Top Youth Talent of Hebei Province, and Young Star Pacesetter of Hebei. These accolades, combined with multiple provincial science and technology progress awards, reflect his sustained contributions to advancing engineering and innovation.

Publication Top Notes

Title: Electromechanical Characteristics under Single and Combined Faults in Synchronous Generators
Author(s): Yu-Ling He, Gui-Ji Tang, Shu-Ting Wan
Journal/Publisher: China Electric Power Press (Monograph)

Title: A New Hybrid Model for Electromechanical Characteristic Analysis Under SISC in Synchronous Generators
Author(s): Yu-Ling He*, Yu-Yang Zhang, Ming-Xing Xu, Xiao-Long Wang, Jing Xiong
Journal: IEEE Transactions on Industrial Electronics

Title: A New External Search Coil Based Method to Detect Detailed Static Air-Gap Eccentricity Position in Non-Salient Pole Synchronous Generators
Author(s): Yu-Ling He*, Zhi-Jie Zhang, Wen-Qiang Tao, Xiao-Long Wang, David Gerada, Chris Gerada, Peng Gao
Journal: IEEE Transactions on Industrial Electronics

Title: Impact of Stator Interturn Short Circuit Position on End Winding Vibration in Synchronous Generators
Author(s): Yu-Ling He, Ming-Xing Xu, Wen Zhang, Xiao-Long Wang*, Peng Lu, Chris Gerada, David Gerada
Journal: IEEE Transactions on Energy Conversion

Title: A Novel Universal Model Considering SAGE for MFD-based Faulty Property Analysis under RISC in Synchronous Generators
Author(s): Yu-Ling He*, Yang Wang, Hong-Chun Jiang, Peng Gao, Xing-Hua Yuan, David Gerada, Xiang-Yu Liu
Journal: IEEE Transactions on Industrial Electronics

Title: Impact of Static Air-Gap Eccentricity on Thermal Responses of Stator Winding Insulation in Synchronous Generators
Author(s): Yu-Ling He, Kai Sun, Yu Wu, Hai-Sen Zhao, Xiao-Long Wang*, Chris Gerada, David Gerada
Journal: IEEE Transactions on Industrial Electronics

Title: Comprehensive Analysis on Rotor Vibration Characteristics Based on a Novel Dynamic Stator Interturn Short Circuit Model of Synchronous Generator
Author(s): Yu-Ling He, Meng-Ya Jiang, Kai Sun, Ming-Hao Qiu, Ming-Xing Xu, Na Zhang, Ming He, Tie-Jun Ci, David Gerada
Journal: IEEE Transactions on Energy Conversion

Title: Impact of 3D air gap eccentricity on winding insulation temperature characteristic in PMSG
Author(s): Yu-Ling He, Yi-Fan Bai, Wen Zhang, Yong Li, Ming-Xing Xu, Xiao-Long Wang, David Gerada
Journal: Alexandria Engineering Journal

Title: Rotor loss and temperature variation under single and combined faults composed of static air-gap eccentricity and rotor inter-turn short circuit in synchronous generators
Author(s): Yu-Ling He, Wen Zhang, Ming-Xing Xu, Wen-Qiang Tao, Hui-Lan Liu*, Long-Jiang Dou, Shu-Ting Wan, Jun-Qing Li, David Gerada
Journal: IET Electric Power Applications

Title: Rotor UMP characteristics and vibration properties in synchronous generator due to 3D static air-gap eccentricity faults
Author(s): Yu-Ling He, Yue-Xin Sun, Ming-Xing Xu, Xiao-Long Wang*, Yu-Cai Wu, Gaurang Vakil, David Gerada, Chris Gerada
Journal: IET Electric Power Applications

Title: Impact of stator interturn short circuit fault on shaft voltage in a synchronous generator
Author(s): Yu-Ling He, Pei-Jie Yang, Kai Sun, Zhen-Li Xu, Hai-Peng Wang*, Xian-Long He, David Gerada
Journal: IET Electric Power Applications

Title: Stator current identification in generator among single and composite faults composed by static air-gap eccentricity and rotor inter-turn short circuit
Author(s): Yu-Ling He, Ming-Hao Qiu, Meng-Ya Jiang, Fu-Cheng Zhou*, David Gerada, Xiao-Chen Zhang, Xiao-Dong Du
Journal: IET Electric Power Applications

Title: Effect of static/dynamic air-gap eccentricity on stator and rotor vibration characteristics in doubly-fed induction generator
Author(s): Yu-Ling He, De-Rui Dai, Ming-Xing Xu, Wen Zhang, Gui-Ji Tang*, Shu-Ting Wan, Xiao-Ling Sheng, David Gerada
Journal: IET Electric Power Applications

Title: Experimental Simulation and Electromechanical Characterization of Dynamic Air Gap Eccentricity Faults in PMSG
Author(s): Yu-Ling He*, De-Rui Dai, Ming-Xing Xu, Wen Zhang, Xiang-Ao Liu, Yong Li, Yun Xing, Wen-Jie Zheng, David Gerada
Journal: IEEJ Transactions on Electrical and Electronic Engineering

Title: Impact of 3D Air Gap Eccentricity on Winding insulation Temperature Characteristic in PMSG
Author(s): Yu-Ling He, Yi-Fan Bai, Wen Zhang, Li Yong, Ming-Xing Xu*, Xiao-Long Wang, David Gerada
Journal: Alexandria Engineering Journal

Title: A comprehensive study on stator vibrations in synchronous generators considering both single and combined SAGE cases
Author(s): Wen Zhang, Yu-Ling He*, Ming-Xing Xu, Wen-Jie Zheng, Kai Sun, Hai-Peng Wang
Journal: International Journal of Electrical Power & Energy Systems

Title: A novel hybrid approach for damage identification of wind turbine bearing under variable speed condition
Author(s): Xiaolong Wang, Yuling He*, Haipeng Wang, Aijun Hu, Xiong Zhang
Journal: Mechanism and Machine Theory

Conclusion

Yu-Ling He exemplifies the qualities of an outstanding researcher, educator, and innovator. His career reflects a remarkable combination of academic excellence, practical innovation, and leadership in advancing electromechanical engineering. By bridging theory with application, he has contributed to safer, more efficient, and more sustainable power systems. His achievements in securing competitive research grants, publishing influential works, and earning international recognition demonstrate his global impact in the field. As a dedicated mentor, editor, and collaborator, he continues to shape the next generation of engineering researchers. His profile makes him a highly deserving candidate for recognition in any award honoring excellence in research.