Special Paper Session #1: Prognostics and Health Management for Power Devices and Power Conversion Systems

Power conversion system (PCS), such as electric drive and power supply, is the “Heart” of intelligent and electric equipment, such as aircraft, high-speed train and automobile and so on. And the power device is the most widely used and has the highest failure rate in power electronics devices. There are some defects about the traditional reliability assurance methods based on pre-life prediction and post-failure analysis, such as high cost, low efficiency and poor accuracy. Prognostics and health management (PHM) technology is based on failure physics, which is used to predict and evaluate the reliability of a product in a real environment, and major accidents may be avoided.

This special session is interested in articles on the latest research progress and achievements of failure mechanism/physical models and data-driven methods for power conversion systems and devices. Potential topics include but are not limited to the following:

 

• Health assessment/life prediction based on failure mechanism/physical model
• Fault diagnosis/prediction of power conversion system based on data-driven methods
• PHM for Power devices（IGBT, MOSFET, etc）/Capacitors (electrolytic capacitors, film capacitors et.al)
• PHM for Power conversion systems (DC-DC, DC-AC, AC-DC, etc)
• PHM for Power electronics based on digital twins

 

Organizers:

Yiqiang Chen, China Electronic Product Reliability and Environmental Testing Research Institute, National Key Laboratory of Science and Technology on Reliability Physics and Application of Electronic Component. Email: yiqiang-chen@hotmail.com

 

Linghui Meng, China Electronic Product Reliability and Environmental Testing Research Institute, National Key Laboratory of Science and Technology on Reliability Physics and Application of Electronic Component. Email: menglinghui@ceprei.com

 

Special Paper Session #2: Nonlinear Dynamic Analysis and Control for Rotor Systems

 

Rotor systems are kernel components of rotating machinery in most industrial fields, such as aero-engines, gas turbines, steam turbines, generators, electric motors, and mechanical manufacturing. With the performance improvements of the rotating machinery, the complication of structural design is ever increasing. As a result, the rotor systems exhibit complicated nonlinear behaviors, which have become a serious threat to the security and stability of the whole system. Dynamic analysis and control theory plays an essential role in the structural design and operating maintenance of nonlinear rotor systems by providing a deep insight into underlying characteristics, function mechanisms, and the general relationship between parameters and the degree of nonlinearity of the system. More efficient and effective theoretical, numerical, and experimental methods need to be developed to understand the inside dynamic mechanism and characteristics of nonlinear rotor systems. Moreover, active, semi-active, and passive control techniques are expected to be applied to control unwanted vibrations from nonlinear rotor systems.

 

This special session is interested in articles on the latest research progress and achievements of dynamic analysis, structural optimization, and vibration control of nonlinear rotors. Potential topics include but are not limited to the following:

 

• Dynamic modeling of nonlinear rotor systems
• Nonlinear dynamic analysis in practical rotor systems
• Bifurcation and chaos in nonlinear rotor systems
• Nonlinear vibration response characteristics of rotor systems with faults
• Vibration and stability control of nonlinear rotor systems
• Active, semi-active, and passive control techniques applied in rotor systems
• Applications of intelligent controls, adaptive controls, nonlinear controls, and linear controls in rotor systems

 

 

Organizers:

 

Qinkai Han, The State Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China Email: hanqinkai@mail.tsinghua.edu.cn.

 

 

 

Special Paper Session #3: Quantitative Evaluation and Intelligent Diagnosis for Rotor and Bearing Faults in High-end Machinery

 

The rotor and support system are key components of such as aero engines, gas turbines, and generators. At the same time, these systems also frequently have faults, and existing diagnosis technologies still have many shortcomings: it is difficult to identify faults with similar features, sudden faults such as blade damage are difficult to analyze in advance, and bearing faults are challenging to diagnose quantitatively, and so on. The based on vibration analysis are effective means to solve the above problems and are also hot topics in theoretical research.

 

This special session is interested in papers on the latest research progress and achievements of quantitative evaluation and intelligent diagnosis for rotor and bearing faults in high-end machinery. Potential topics include but are not limited to the following:

 

• Fault mechanism of rotating machinery
• Fault simulation of high-end machinery
• Fault feature extraction method
• Intelligent diagnostic methods for faults in rotors, bearings, blades, etc
• Quantitative diagnosis and prediction of bearing faults
• Digital twin and other fault diagnosis techniques

 

Organizers:

 

Gang Tang, Beijing University of Chemical Technology, State Key Laboratory of High-end Compressor and System Technology. Email: tanggang@mail.buct.edu.cn

 

Minghui Hu, Beijing University of Chemical Technology, State Key Laboratory of High-end Compressor and System Technology. Email: humh2008@163.com

 

 

Special Paper Session #4: Prognostics and Health Management for Industrial Machinery

 

Organizers:

 

Diego Cabrera, Mechanical Engineering Department, Salesian Polytechnic University, Cuenca, Ecuador, email: diegoroman17_2@hotmail.com

 

Mauricio Villacis, Computer Sciences and Artificial Intelligence Department, Seville University, Seville, Spain, email: mvillacism@gmail.com

 

Jiapeng Wu, Computer Sciences and Artificial Intelligence Department, Seville University, Seville, Spain, email: jiawu@alum.us.es

 

 

 

Special Paper Session #5: Intelligent Diagnostics / Prognostics Methods under Insufficient Fault Information

 

Organizers:

 

Jianyu Long, Dongguan University of Technology, longjy@dgut.edu.cn

 

Yi Qin, Chongqing University, qy_808@aliyun.com

 

Jinglong Chen, Xi'an Jiaotong University, jlstrive2008@mail.xjtu.edu.cn

 

 

Special Paper Session #6: Prognostics and Health Management for Rotary Machinery Systems

 

Organizers:

 

Shuai Yang, Professor, National research base of intelligent manufacturing service Chongqing Technology and Business University，jerryyang@ctbu.edu.cn

 

Tianyang Wang, Associate professor, Department of mechanical engineering, Tsinghua University, wty19850925@mail.tsinghua.edu.cn

 

Juanjuan Shi, Professor, School of rail transportation, Soochow University, jshi091@suda.edu.cn

 

 

Special Paper Session #7: Prognostics and Health Management Technology in Rail Transit

 

Prognostic and Health Management (PHM) technology has emerged as a crucial tool in the field of rail transit, revolutionising the way maintenance and reliability are managed. With the increasing complexity and sophistication of rail systems, ensuring safe and efficient operation of trains has become paramount. Traditionally, reliability assurance methods relied on prelife prediction and post-failure analysis, which often proved to be inefficient, costly, and sometimes inaccurate. PHM technology addresses these limitations by using the principles of failure physics to assess the reliability of equipment under real-world operating conditions, enabling potential accidents to be mitigated or avoided.

 

This special session is interested in articles on the latest research progress and achievements in the application of PHM in rail transit. Potential topics include but are not limited to the following:

 

• Health monitoring and prediction of rail transportation equipment
• Signal processing and fault diagnosis
• RUL prediction and degradation analysis
• Health management and maintenance decision support
• Data-driven fault analysis and root cause analysis
• Safety management and risk assessment

 

Organizers:

 

Dechen Yao, Beijing University of Civil Engineering and Architecture

 

Zaigang Chen, Southwest Jiaotong University

 

Changqing Shen, Soochow University

 

Special Paper Session #8: Applications of Digital Twin Models in PHM

 

Organizers:

 

Wenliao Du, Zhengzhou University of Light Industry, E-mail: dwenliao@zzuli.edu.cn

 

Yixiang Huang, Shanghai Jiaotong University, E-mail: huang.yixiang@sjtu.edu.cn

 

 

Special Paper Session #9: The Sensing, Diagnosis and Control of Electromechanical Systems

 

The sensing, diagnostic, and control of electromechanical systems are the key techniques to guarantee the performance of electromechanical systems, which have witnessed a rapid development over the past years. Numerous applications have been found in industries, such as manufacturing, healthcare, agriculture, and transportation. The integration of the novel sensing techniques allows the advanced electromechanical systems to perceive the data for performance analysis and optimization. Fault diagnosis plays a vital role in the health management of electromechanical systems and improving maintenance schedules. The field has seen significant advancements in areas such as machine learning, computer vision, and decision-making algorithms, data-driven methods, all of which have contributed to the development and maintenance of electromechanical systems.

 

This special session is interested in articles on the latest research progress and achievements of the sensing, diagnosis and control techniques for the development and maintenance of advanced electromechanical systems. Potential topics include but are not limited to the following: transit. Potential topics include but are not limited to the following:

 

• Advanced sensing and data acquisition
• Modeling methodology of complex electromechanical systems
• Condition monitoring techniques for electromechanical machines
• Diagnostics and prognostics techniques and systems
• Signal processing and image processing methods
• Intelligent control algorithm and systems

 

Organizers:

 

Dong Zhen, Hebei University of Technology, School of Mechanical Engineering/Advanced Equipment Research Institute. Email: d.zhen@hebut.edu.cn

 

Guojin Feng, Hebei University of Technology, School of Mechanical Engineering. Email: G.Feng@hebut.edu.cn