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The 1st International Electronic Conference on Machines and Applications
Part of the International Electronic Conference on Machines and Applications series
15–30 Sep 2022
Manufacturing, Mechatronics, Machines, Automation and Control
- Go to the Sessions
- Event Details
IECMA 2022 is closed. Thank you for your participation.
The recordings of IECMA 2022 live sessions are available at:
https://iecma2022.sciforum.net/#recordings
The accepted proceedings papers will probably be published as one dedicated volume in MDPI Engineering Proceedings (ISSN:2673-4591) after the conference.
All participants of IECMA 2022 are welcome to submit an extended full paper to the Special Issue "Selected Papers from the 1st International Electronic Conference on Machines and Applications (IECMA 2022)" of the journal Machines, with a 20% discount on the Article Processing Charges.The IECMA 2022 award winners have been announced at https://iecma2022.sciforum.net/#awards
Live Sessions Information
Live Session Program
Live Session 1
16 Sep 2022
Time: 9:30 am CEST
Session Chair: Dr. Hai Wang
Speaker |
Presentation Topic |
Time (CEST) |
Dr. Hai Wang |
Introduction |
9:30am-9:40am |
Dr. Efstathios Velenis |
Expert Vehicle Control at The Limits of Handling |
9:40am–10:10am |
Dr. Hai Wang |
Modelling and robust control for steer-by-wire vehicles via sliding mode methodologies |
10:10am-10:40am |
Prof. Dr. Ming Yu |
Fault diagnosis and prognosis of steer-by-wire system based on finite state machine and extreme learning machine |
10:40am-11:10am |
Live Session 2
21 Sep 2022
Time: 3:00 pm CEST
Session Chair: Antonio J. Marques Cardoso
Speaker |
Presentation Topic |
Time (CEST) |
Prof. Dr. Antonio J. Marques Cardoso |
Introduction |
3:00pm-3:10pm |
Dr. Konstantinos Gyftakis |
An overview of electrical machines condition monitoring and fault diagnosis |
3:10pm-3:40pm |
Prof. Dr. Jose A Antonino Daviu |
Transient-based fault diagnosis of electric motors based on the analysis of electrical signals |
3:40pm-4:10pm |
Dr. Alejandro Gómez Yepes |
Fault Tolerance in Multiphase Electric Machine Drives |
4:10pm-4:40pm |
Live Session 3
27 Sep 2022
Time: 3:00 pm CEST
Session Chair: Prof. Dr. Dan Zhang
Speaker |
Presentation Topic |
Time (CEST) |
Prof. Dr. Dan Zhang |
Introduction |
3:00pm-3:10pm |
Prof. Makoto Iwasaki |
GA-Based Practical System Identification and Auto-Tuning for Multi-Axis Industrial Robots |
3:10pm-3:40pm |
Prof. Pierre Larochelle |
Synthesis of RR and CC Dyads for Pick and Place Tasks with Guiding Locations |
3:40pm-4:10pm |
Live Session Recordings
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List of accepted submissions (27)
Id | Title | Authors | Presentation Video | Poster PDF | |||||||||||||||||||||||||||||||||||||
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sciforum-061901 | The influence of the layer thickness change on the accuracy of the zygomatic bone geometry manufactured using the FDM technology | N/A | N/A |
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Designing and manufacturing a model of the anatomical structure while performing a surgical procedure is not a simple task. It is especially true of the craniofacial area, which consists of bone tissues with very complex geometry. Appropriate knowledge and skills in medicine and technical sciences are needed, which will allow the full use of currently available tools in the processes related to the reconstruction of the craniofacial areas. It is especially true of the central craniofacial region, which is most frequently damaged. Due to the unique geometry of the models of anatomical structures, manufacturing them using subtractive methods is very difficult or often impossible. This situation makes the additive methods an ideal alternative for manufacturing this model type. Many factors during 3D printing affect the accuracy of the model geometry. The most important are the type of technology used and the finishing treatment, the material used, the print layer's selected thickness, and the object's orientation in the 3D printer space. The manuscript determined the impact of changing the layer thickness on the zygomatic bone geometry accuracy. The reference model was obtained from the DICOM data obtained from the measurement carried out on a multi-detector tomograph. The printing process was carried out on a Fortus 360 - mc printer. Physical models of the zygomatic bone were made of ABS-M30 material using four-layer thicknesses: 0.127 mm, 0.178 mm, 0.254 mm, and 0.330 mm. To assess the accuracy of the model geometry printout, the MCA-II measuring arm with an MMDx100 laser head system was used. The adjustment of the nominal model obtained at the RE / CAD design stage and the reference model created at the measurement stage using the optical system was carried out using the best fit method with an accuracy of 0.001 mm. The accuracy analysis was presented by presenting statistical parameters and histograms. Based on the obtained results, a gradual deterioration in the accuracy of the model geometry representation with the increase of the print layer thickness was observed. However, all the models manufactured are within the accuracy of +/- 0.25 mm geometry, acceptable to surgeons. |
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sciforum-061931 | On-Line Diagnostics of Inter-Turn Short-Circuit Faults in Synchronous Reluctance Machines, Based on Voltage Symmetrical Components | , , | N/A | N/A |
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Fault diagnosis in electrical drives can be very difficult, especially when the input data comes from an operating electrical machine. The occurrence of Inter-Turns Short-Circuit (ITSC) fault is one of the most dangerous electrical machine failures, and if these are not detected at an early stage of development, they can result in serious consequences, both in terms of repair cost and safety. In this context, an effective on-line approach for diagnosisng ITSC fault is proposed, which is based on the computation and monitoring of a specific severity factor, defined as the ratio of positive and zero symmetrical components. This approach is implemented in a LabVIEW environment and employs the Short Time Least Square Prony's (STLSP) method. This does not require the determination of motor parameters and just involves the use of voltage sensors. Several tests were performed on a Synchronous Reluctance Machine (SynRM), for various operating conditions (healthy and faulty). The obtained results confirm the effectiveness of the proposed technique for diagnosing ITSC faults, with high reliability, rapidity, and accuracy. |
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sciforum-061969 | Accuracy and repeatability of thread measurements using replication technique | N/A | N/A |
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One of the important problems in verifying the dimensional and geometrical accuracy of products is the measurement in hard-to-reach places. One of the non-destructive measurement methods is the indirect measurement, using the replication technique. When evaluating each measurement method in the context of its legitimacy, one should consider its accuracy and repeatability. This study aimed to determine whether the error values of measurements with the use of replicates are dependent on the thread parameter being checked. Two types of replica materials were used in the study - one in initial liquid consistency, and the other in paste form. Both materials are used on a semi-flexible impression to measure the cross-section on a profile projector or optical microscope. After the replicas were made, they were cut with a double blade cutter to obtain 1 mm slices. The profiles were measured on an iNEXIV VMA-2520 metrology system. As the measurement of the replicas did not provide information on the position of the thread axis, it was not possible to determine the diameter parameters. The thread parameters measured were: thread angle, thread height, pitch and root radius. To assess the accuracy of the replica measurements, the results obtained were compared with the values from the direct measurement of the thread. The repeatability of the replicas in the context of measuring a given parameter was examined using the analysis of the means method. Irrespective of the replica material used, the largest errors in comparison with direct measurement were recorded for the thread angle. Measurements of this parameter were also characterized by the lowest repeatability. For the other analyzed parameters, the relative error was usually less than 1%. |
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sciforum-062016 | A Critical View on the Partial Discharge Models for Various Electrical Machines’ Insulation Materials | , , , , | N/A |
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Synchronous Generators (SGs) play a vital role in energy production as well as for the Industry. The insulation system of them, of which epoxy resin and mica are the most used insulation materials, plays the most significant role in proper operation and in extending its lifetime. Epoxy resin and mica have characteristics, which make them very good materials for a reliable SG insulation. Partial Discharges (PDs) are one of the most serious problems, because they can cause problems on the SG insulation. PDs are both a symptom of insulation degradation and a means to identify possible insulation faults. So, it is very important to detect PDs with offline or/and online PD Tests. A comparison of different MATLAB/Simulink PD models are presented in this paper. Epoxy resin, mica and a combination of these two insulation materials are used for simulations in order to investigate factors, such as the applied voltage, the geometry of the void inside the insulation, and how these affect the condition of the materials, and how these are related to PDs and flashover voltages, which may appear also in electrical machines’ insulation. The aforementioned factors can be used in order to check which of the materials is affected the most and which one is the most proper for SGs’ insulation system. |
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sciforum-062053 | Effect of printing speed and layer height on geometrical accuracy of FDM-printed resolution holes of PETG artifacts | , , | N/A | N/A |
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Poly Ethylene Terephthalate Glycol (PETG) is a thermoplastic polyester with excellent formability, durability and chemical resistivity. Thus, it is an ideal choice for a wide range of applications, such as food and drink containers (cooking oil containers, bottles, FDA-compliant food storage containers), cosmetics packaging and medical and pharmaceutical applications (implants, packaging of pharmaceutical and medical devices). Furthermore, PETG-filament prints easily and gives excellent layer adhesion, thus it is widely used in Fused Deposition Modeling (FDM). However, in order to achieve high levels of process repeatability, it is essential to correlate process parameters with the mechanical properties and the geometrical accuracy of the final PETG product. In literature, there is a wide variety of studies that examine the mechanical properties of 3D-printed parts. On the other hand, studies of geometrical accuracy of FDM-processed parts are limited, according to authors’ best knowledge. In the current study, 5-hole PETG features are created by a low-budget FDM printer, according to the ISO ASTM 52902-2021 standard. The holes are of diameters of 4mm, 3mm, 2mm, 1mm and 0.5mm. The artifacts are built with three different printing speeds (20mm/s, 50mm/s and 80mm/s) and with three different layer heights (0.1mm, 0.2mm, 0.3mm). The measurements on these artifacts are the diameters of the holes, which are obtained with a microscope. The results are then analyzed statistically and commented. |
Welcome from the Chairs
Welcome from the Conference Chairs of the 1st International Electronic Conference on Machines and Applications (IECMA)
It is our pleasure to invite you to join the 1st International Electronic Conference on Machines and Applications (IECMA).
Machinery and engineering areas play a key role in an ever-increasingly technological society. Transportation, renewable energies, and more efficient buildings are just some of the domains where the intensive application of these systems has been most noticed. In all these applications, efficiency and reliability, automation and control, and advanced manufacturing, are of major concern.
The scope of this online conference is to get together worldwide well-known experts who are currently working on machinery and engineering and to provide an online forum for presenting and discussing new results.
Throughout this event, we aim to cover, among others, the following topics:
- Machines Testing and Maintenance
- Automation Systems
- Mechatronic and Intelligent Machines
- Turbomachinery
- Electrical Machines and Drives
- Advanced Manufacturing
There will be two special sessions:
- Vehicle Dynamics and Control (Special Session S1)
- Friction and Tribology (Special Session S2)
and also a Poster session. Posters can be presented without an accompanying proceedings paper and will be available online on the conference website during and after the e-conference. However, they will not be added to the proceedings of the conference.
Participants will have the opportunity to examine, explore and critically engage with issues and advances in these areas. We hope to facilitate discussions and exchanges within the community.
This event will solely be an online proceeding which allows participation from all over the world with no concerns of travel and related expenditures. The participation as well as the “attendance” of this online conference is free of charge.
The 1st International Electronic Conference on Machines and Applications (IECMA) will be held at https://iecma2022.sciforum.net/, on a platform developed by MDPI to organize electronic conferences.
The 1st International Electronic Conference on Machines and Applications (IECMA) is sponsored by MDPI and the scientific journal Machines, an Open Access publication journal of MDPI on machinery and engineering. Accepted papers will be published in the proceedings of this e-conference, and extended and expanded versions of conference proceedings papers can be submitted to Special Issue "Selected Papers from the 1st International Electronic Conference on Machines and Applications (IECMA 2022)" in journal Machines after the conference, with a 20% discount on the Article Processing Charges.
We hope you will join us and present your work at IECMA to be part of this stimulating online experience.
Event Chairs
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University of Beira Interior, Department of Electromechanical Engineering, Portugal
Antonio J. Marques Cardoso received the Dipl. Eng., Dr. Eng., and Habilitation degrees from the University of Coimbra, Coimbra, Portugal, in 1985, 1995 and 2008, respectively, all in Electrical Engineering. From 1985 until 2011 he was with the University of Coimbra, Coimbra, Portugal, where he was Director of the Electrical Machines Laboratory. Since 2011 he has been with the University of Beira Interior (UBI), Covilhã, Portugal, where he is Full Professor at the Department of Electromechanical Engineering and Director of CISE - Electromechatronic Systems Research Centre (http://cise.ubi.pt). He was Vice-Rector of UBI (2013-2014). His current research interests are in fault diagnosis and fault tolerance in electrical machines, power electronics and drives. He is the author of a book entitled Fault Diagnosis in Three-Phase Induction Motors (Coimbra, Portugal: Coimbra Editora, 1991), (in Portuguese), editor of a book entitled Diagnosis and Fault Tolerance of Electrical Machines, Power Electronics and Drives (IET/SciTech, UK, 2018) and also author of around 500 papers published in technical journals and conference proceedings. Prof. Marques Cardoso currently serves as Editor-in-Chief of the MDPI journal Machines, and Associate Editor of the IEEE Transactions on Industry Applications, IEEE Transactions on Industrial Electronics, IEEE Transactions on Power Electronics, IEEE Journal of Emerging and Selected Topics in Power Electronics, IEEE Open Journal of the Industrial Electronics Society, as well of the Springer International Journal of Systems Assurance Engineering and Management.
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Department of Mechanical Engineering, Lassonde School of Engineering, York University, Canada
Dr. Dan Zhang is a Professor and Tier 1 York Research Chair in Advanced Robotics and Mechatronics in the Department of Mechanical Engineering of the Lassonde School of Engineering at York University. From July 1, 2004, to December 31, 2015, Dr. Zhang was a Professor and Canada Research Chair in Advanced Robotics and Automation, was a founding Chair of the Department of Automotive, Mechanical and Manufacturing Engineering with the Faculty of Engineering & Applied Science at University of Ontario Institute of Technology. He received his PhD in Mechanical Engineering from Laval University in June, 2000. Dr. Zhang’s contributions to and leadership within the field of robotic and automation have been recognized with several prestigious awards, within his own university (Research Excellence Award both from university level in 2009 and faculty level in 2008), the Province of Ontario (Early Researcher Award in 2010), the professional societies (election to Fellow of the CAE in 2017, the ASME in 2016, the EIC in 2012 and the CSME in 2010) and federal funding agencies (Canada Research Chair in January 2009 and renewed in January 2014). As well, he was awarded the Inaugural Teaching Excellence by the Faculty of Engineering and Applied Science of UOIT in 2006 and the Best Professor Award by UOIT Engineering Students’ Society in 2012. Dr. Zhang is the editor-in-chief for International Journal of Mechanisms and Robotic Systems, the editor-in-chief for International Journal of Robotics Applications and Technologies, Associate editor for the International Journal of Robotics and Automation (ACTA publisher) and guest editors for other four international journals. Dr. Zhang served as a member of Natural Sciences and Engineering Research Council of Canada (NSERC) Grant Selection Committee. Dr. Zhang was director of Board of Directors at Durham Region Manufacturing Association and director of Board of Directors of Professional Engineers Ontario, Lake Ontario Chapter. Dr. Zhang is a registered Professional Engineer of Canada, a Fellow of the Canadian Academy of Engineering (CAE
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Department of Mechanical, Energy and Management Engineering, University of Calabria, Italy
Giuseppe Carbone is Associate Professor at DIMEG, University of Calabria and Chair of the IFToMM TC on Robotics and Mechatronics. He has got the Master and Ph.D. degree at University of Cassino (Italy) where he has been a Key Member of LARM (Laboratory of Robotics and Mechatronics) for about 20 years. He has carried out several periods of study and research abroad in Germany, Japan, China, South Corea, Brazil, Spain, UK, France, also delivering regular teaching courses in Spain and UK. His research interests cover aspects of Engineering Design, Mechanics of Robots, Mechanics of Manipulation and Grasp, Mechanics of Machinery with over 300 research paper outputs, 20 patents, and 16 Phd completions. He has been also member of 20 PhD evaluation Commissions and viva in Italy, Spain, Finland, UK, Romania, Mexico. He is currently coordinating the EU project AGEWELL and a Russian Federation funded project. He has been principal Investigator (PI) or co-PI of more than 20 projects including 7th European Framework and H2020 funds.
Session Chairs
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Caishan Liu
State Key Laboratory of Turbulence and Complex System, College of Engineering, Peking University, China
Professor Caishan Liu received his PhD degree in mechanical engineering from Tianjin University, Tianjin, China, in 1997. He is now a full professor and the head of the Department of Aerospace Engineering, Peking University, Beijing, China. His current research interests are generally related to Multibody System Dynamics, Contact/impact and Friction, Stability of Nonlinear Dynamics, Granular Physics, Bicycle dynamics, as well as the dynamics and control problems in various aerospace engineering applications, including vibration suppression of flexible structure, Aircraft landing dynamics and control, Separation mechanism dynamics, etc. Dr Liu has published over 100 peer reviewed papers. He currently serves as the Associate Editors of Multibody System Dynamics (MBS), and Int. J. Mechanical System Dynamics (IJMSD), the editor board of Int. J. Mechanical Science. He also served as editor member of Theoretical and Applied Mechanics Letters (TAML) during 2016-2020. Dr Liu has been serving as the Plenary Speaker, Keynote Speaker, General Chair of International Conferences, the technical program chair, and the symposium chair for various international conferences. He has presided over a number of National Natural Science Foundation of China (NSFC) and enterprise research projects.
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Matthias Meinke
Institute of Aerodynamics, RWTH Aachen University, Germany
Dr. Matthias Meinke received his M.Sc. (Dipl.-Ing.) and Ph.D. (Dr.-Ing.) degrees in mechanical engineering with honors from RWTH Aachen University in 1986 and 1993, respectively. After obtaining his Ph.D. degree, he became the head of the CFD group of the Institute of Aerodynamics of RWTH Aachen University. Since 1993, he has been teaching a Bachelor and Master course in computational fluid dynamics at RWTH Aachen University and has given lectures in various international universities, in Japan, Thailand, Kazakhstan, and Korea, to name a few. He is a reviewer for many international conferences and journals. Under his supervision, the CFD group is actively developing multiphysics simulation software, which will be published as an open-source project in 2022. He is the author of more than 150 journal articles, and at present, his Google Scholar h-index is 37.
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Hai Wang
College of Science, Health, Engineering and Education, Murdoch University, Australia
Hai Wang (M’13–SM’19) received his PhD degree from Swinburne University of Technology (SUT), Australia, in 2013, in electrical and electronic engineering. From 2014 to 2015, he was the Postdoc Research Fellow in the Faculty of Sciences, Engineering and Technology, at SUT, Australia. From 2015 to 2019, he was with the School of Electrical and Automation Engineering at Hefei University of Technology, China, where he served as the Full Professor (Huangshan Young Scholar) and the Deputy Discipline Head of Automation. Hai is currently the Senior Lecturer of Electrical Engineering, Academic Chair of Intelligent Industrial Control & Autonomous Systems Engineering (IICASE), and Director of Advanced Mechatronics, Robotics, and Controls Laboratory, in Discipline of Engineering and Energy, at Murdoch University, Perth, Australia. His research interests are in sliding mode control and observer, adaptive control, robotics and mechatronics, neural networks, nonlinear systems, and vehicle dynamics & control. Dr. Wang was the Chair of IEEE Industrial Electronics Society Western Australia Chapter in 2020. He currently serves as the Section EiC of Actuators, Associate Editor of Computers and Electrical Engineering, ASME-Journal of Autonomous Vehicles and Systems, Leading Guest Editors of Neural Computing and Applications, Computers and Electrical Engineering, Actuators, etc.
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Ibrahim Tansel
Department of Mechanical and Material Engineering, Florida International University, USA
Dr. I. Tansel received his Ph.D. degree from University of Wisconsin-Madison in 1986. He joined Florida international University (FIU) in 1990 after working for Tufts University for 4 years. He established the Mechatronics Laboratory and has been directing it for over 30 years. Dr. Tansel works on automation of manufacturing, structural health monitoring (SHM), development of computational tools for various engineering applications and manufacturing smart structures with additive manufacturing. He has used artificial neural networks, wavelet transformations, genetic algorithms, and analytic models extensively in his research work. His group developed a sensorless SHM system and received a patent. He has taught many courses including Manufacturing, Mechatronics, and System Identification. Dr. Tansel received the Outstanding Young Manufacturing Engineer Award in 1992 from Society of Manufacturing Engineers and received two research and one teaching awards from the Florida International University. He worked for various federal research labs of Air Force, NAVY and NASA for 13 summers as fellow of NRC and ASEE. He chaired the Mechanical and Materials Engineering Department of FIU between 2014 and 2017.
Event Committee
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Section of Manufacturing Technology, School of Mechanical Engineering, National Technical University of Athens, Greece
Dr. Angelos P. Markopoulos is an Associate Professor the School of Mechanical Engineering, National Technical University of Athens, Greece. His research includes topics such as precision and ultraprecision machining processes with special interest in high-speed hard machining, grinding and micromachining. Among the research topics he is interested, surface integrity, materials and machinability, tool wear and measurements technology in machining are included. Furthermore, he is an expert in manufacturing technology modeling and simulation, including the Finite Elements Method, Artificial Intelligence and Molecular Dynamics. He is the author of more than 150 papers in journals, conferences and book chapters on the above-mentioned areas and member of the editorial board of international journals.
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Davide Astolfi received the B.S., M.S. and Ph.D. degree in Physics and in Industrial and Information Engineering at the University of Perugia. He is currently a post-doctoral research fellow at the Department of Engineering of the University of Perugia. He has a decade of experience in the analysis and optimization of operating wind farms, in collaboration with international industrial partners. At present, he has coauthored around 100 publications in scientific journals and international conference proceedings. His research interests include renewable energy, wind energy, wind turbines, applied data analysis, fault diagnosis and condition monitoring of electrical machines, performance analysis and lifecycle optimization of energy systems, electrical systems for energy.
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LARM2: Laboratory of Robot Mechatronics, Department of Industrial Engineering, University of Rome Tor Vergata, Italy
Marco Ceccarelli (Rome, 26 May 1958) received his Ph.D. in Mechanical Engineering from La Sapienza University of Rome, Italy, in 1988. He is Professor of Mechanics of Machines at the University of Rome Tor Vergata, Italy, where he chairs LARM2: Laboratory of Robot Mechatronics. His research interests cover subjects of robot design, mechanism kinematics, experimental mechanics with special attention to parallel kinematics machines, service robotic devices, mechanism design, and history of machines and mechanisms whose expertise is documented by several published papers in the fields of Robotics and Mechanical Engineering. He has been visiting professor in several universities in the world. He is ASME fellow. Professor Ceccarelli serves in several Journal editorial boards and conference scientific committees. He is editor-in-chief of the MDPI journal Robotics and of the SAGE International Journal on Advanced Robotic Systems for the area on Service Robotics He is editor of the Springer book series on Mechanism and Machine Science (MMS) and History of MMS. He has been the President of IFToMM, the International Federation for the Promotion of MMS in 2008-11 and 2016-19. He has started several IFToMM sponsored conferences including (HMM) Symposium on History of Machines and Mechanisms, MEDER (Mechanism Design for Robotics) and MUSME (Multibody Systems and Mechatronics). More information at the web page: LARM2 webpage: http://larmlaboratory.net
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Xiang Li is an associate professor in school of mechanical engineering of Xi'an Jiaotong University, China. Before that, he was a postdoctoral fellow at University of Cincinnati, US and a visiting scholar at University of California at Merced, US. He received the B.S. degree and the Ph.D. degree both in mechanics from Tianjin University, China, in 2012 and 2017, respectively. His research interests include industrial artificial intelligence, industrial big data, intelligent fault diagnosis and prognosis, etc. He has published more than 70 research papers in the journals of IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, etc., including 13 ESI highly cited papers and 4 ESI hot papers. His citations are over 3000 in Google Scholar with an h-index of 25. He is the journal editorial board members of Machines, IEEE/CAA Journal of Automatica Sinica, Mathmatics etc.
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School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
Dr Ooi Kim Tiow is a Professor in the School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore. He obtained his BEng and PhD in Mechanical Engineering from the University of Strathclyde, Scotland, U.K. in 1986 and 1990, respectively. In his more than 30 years of career with the university, he has been bestowed thrice Teacher of the Year Award, and twice The Nanyang Award for Excellence in Teaching. Dr Ooi is a prolific inventor; he has numerous patents in his name and a few have been commercialized. His innovative works have won numerous local and international awards, including the World’s Best Technology Showcase, USA, in 2009; Institute of Mechanical Engineering, UK, Fluid Mechanics Group-Donald Julius Groen Prize, in 2017 and TECO Green Tech International Competition Bronze Medal in 2019. His latest invention, Coupled Vane Compressor (CVC) also won the Gold Award at the International Borneo Innovation Exhibition and Competition, Malaysia in 2021. In 2014, he was awarded the Nanyang Innovation and Entrepreneurship Award. He publishes more than 170 research papers in international journal and conferences and has been invited to be Editor in Chief, Associate Editor, Editorial Board Member, Guest Editor and Reviewers of International Journals. He sits in numerous international advisory boards for international conferences in UK, Europe, China and India. Dr Ooi is a co-author of a book and chapters of encyclopedias. He is widely consulted by engineering companies both locally and internationally. He is a member of American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHARE). Other information about Prof Ooi can be obtained in the following links: 1. MAE, NTU webpage: https://dr.ntu.edu.sg//cris/rp/rp00713 2. Google Scholar: https://scholar.google.com.sg/citations?user=RqkHITUAAAAJ&hl=en 3. Journal of Process Mechanical Engineers, Part-E https://journals.sagepub.com/editorial-board/pie
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Ignacio González-Prieto was born in Malaga, Spain, in 1987. He received the Industrial Engineer and M.Sc. degrees in Fluid Mechanics from the University of Malaga, Malaga, Spain, in 2012 and 2013, respectively, and the Ph.D. degree in electronic engineering from the University of Seville, Sevilla, Spain, in 2016.His research interests include multiphase machines, wind energy systems, and electrical vehicles.
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Department of Industrial Engineering, Manufacturing Technology Research Laboratory, Italy
Prof. Gianni Campatelli is an associate professor of manufacturing technologies at the University of Firenze (Italy). His main interests are the additive manufacturing technologies for metals and machining processes; he believes that the integration of such technologies could led to new manufacturing solutions, particularly interesting for repairing and implementing greener manufacturing strategies. He led many National and EC projects as local and global coordinator.
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Department of Civil and Industrial Engineering, University of Pisa, Italy
Paola Forte got her Master degree cum laude in Mechanical Engineering and PhD in Tribology at the University of Pisa. She has been associate professor of Machine Design at the University of Pisa until 2020 when she retired but continued to cooperate with her department as research associate. Her activity regarded lubrication and bearings, vibro-acoustic analysis of components, design of devices employing magnetorheological fluids, mechanical behavior of biological materials. She is author and co-author of almost 200 scientific papers, a chapter of a book on Structural Dynamics and a book on Machine Design.
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School of Automation Science and Electrical Engineering, Beihang University, China
Qing Gao received the B. Eng. and Ph.D. degrees in Mechanical and Electrical Engineering from the University of Science and Technology of China, Hefei, China, in 2008 and 2013, respectively. He also received the Ph.D. degree in Mechatronics Engineering from the City University of Hong Kong, Kowloon, Hong Kong in 2014. From 2014 to 2016, he was with the School of Engineering and Information Technology, University of New South Wales, Canberra at the Australian Defense Force Academy, as a postdoctoral research associate. Since 2018, he has joined the School of Automation Science and Electrical Engineering, Beihang University as a full professor. His research interests include intelligent control and quantum control. Dr. Gao received the Outstanding Research Thesis Award from City University of Hong Kong in 2013, and the Outstanding Doctoral Dissertation Award from the Chinese Academy of Sciences in 2015. He is the recipient of the Alexander von Humboldt Fellowship of Germany and the 21st Guan Zhao-Zhi Award.
intelligent control and quantum control
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Chen Lv is a Nanyang Assistant Professor at School of Mechanical and Aerospace Engineering, and the Cluster Director in Future Mobility Solutions, Nanyang Technological University, Singapore. He received his PhD degree at Department of Automotive Engineering, Tsinghua University, China in Jan 2016. He was a joint PhD researcher at UC Berkeley, USA during 2014-2015, and worked as a Research Fellow at Cranfield University, UK during 2016-2018. He joined NTU and founded the Automated Driving and Human-Machine System (AutoMan) Research Lab since June 2018. His research focuses on intelligent vehicles, automated driving, and human-machine systems, where he has contributed 2 books, over 100 papers, and obtained 12 granted patents. He serves as Associate Editor for IEEE T-ITS, IEEE TVT, and IEEE T-IV. He received many awards and honors, selectively including the Highly Commended Paper Award of IMechE UK in 2012, Japan NSK Outstanding Mechanical Engineering Paper Award in 2014, Tsinghua University Outstanding Doctoral Thesis Award in 2016, IEEE IV Best Workshop/Special Session Paper Award in 2018, Automotive Innovation Best Paper Award in 2020, the winner of Waymo Open Dataset Challenges at CVPR 2021, and Machines Young Investigator Award in 2022.
intelligent vehicles, automated driving, and human-machine systems
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Mechanical Engineering Department, MEtRICs Research Center, University of Minho, Portugal
Concluded Habilitation Title in February 2019 at University of Minho, Portugal. He received his PhD degree in Mechanical Engineering – Automation, from University of Minho, Portugal and, in simultaneous, from Ecole Normale Superieure de Cachan, France, in 2006. He is Deputy Director of MEtRICs Research Center and Assistant Professor, with Habilitation, at Mechanical Engineering department of University of Minho. He has authored, or co-authored, more than 220 refereed journal and conference proceedings papers. He coordinates and has coordinated - and participated as collaborator - in several Research and Technology Transfer Projects on Mechatronics and Automation domains. His main interests are related with Industry 4.0, more specifically, on the design and development of Cyber-Physical Systems; design and analysis of dependable controllers for obtaining dependable mechatronic systems; and mechatronic systems design with special focus on medical or biomedical applications, wellbeing and/or rehabilitation. He is member of IEEE and member of IFAC.
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Pavlo Maruschak got his PhD degree in 'Fracture Mechanics' in 2005 at the Ternopil State Technical University. Since 2005 he has been assistant professor at the Ternopil Ivan Puluj National Technical University, Department of Industrial Automation (Ukraine). Since 2013 he has been professor of Industrial Automation at the TNTU. He is author of more than 300 technical papers, mainly oriented to the failure of different materials, creep-fatigue cracks growth, the application of the technical diagnostics method to the structural analysis, the mechanical behaviour of metallic materials, the impact toughness of notched components as well as the reliability of welded joints. Since 2013, he has been working on different aspects of the Deep Residual Neural Network direction, by mainly focusing attention on problems related to the classification of steel surface defects and damage assessment of engineering materials and components. In particular, he has attempted to renovation of functional surfaces methods suitable for metallurgical equipment. Prof. Maruschak’s areas of expertise can be summarised as follows: -fracture mechanics; -industry applications diagnostic methods; - reliability analysis; - wear; - machining process; - metallurgy.
Fracture mechanics; industry applications diagnostic methods; reliability analysis; wear; machining process; metallurgy
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Department of Industrial and Systems Engineering, The Hong Kong Polytechnical University
Chao Huang is a Research Assistant Professor at the Department of Industrial and System Engineering, The Hong Kong Polytechnical University. Her research interests are human-machine collaboration, fault-tolerant control, mobile robot (EV, UAV), and path planning and control. Prior to Polyu, she was a research fellow at Nanyang Technological University (NTU) and the National Institutes of Informatics (NII). She is a co-author of "Wireless Communication Networks Supported by Autonomous UAVs and Mobile Ground Robots". She has served on program committees and/or helped to organize special issues on sensors, Machines, and Aerospace. She has served as review editor of Frontiers in Mechanical Engineering.
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Department of Industrial Engineering of the Polytechnic School and of the Basic Sciences of the University of Naples Federico II, Italy
Vincenzo Niola is full professor of “Complements of Mechanics” and of “Tribology and Diagnostics of Mechanical Systems” at the Department of Industrial Engineering of the Polytechnic School and of the Basic Sciences of the University of Naples Federico II. PATENTS https://patents.justia.com/inventor/vincenzo-di-nicola SPIN OFF Constitution of the "VICEMA" Spin Off approved by the Board of Directors of the University of Naples on 29.07.2016, letter of protocol n. 0074301 AWARDS Best Papers (Evaluated by 6 international experts, different for each discipline) NOVEMBER 2011, Catania, Sicily, Italy, November 3-5, 2011: • Best Paper for the 4th WSEAS International Conference on Sensors and Signals (SENSIG '11) V. Niola, V. Avagliano, G. Quaremba - "The Problem of GWN", pp. 363-370
• Analysis of the tribological behavior of porous bearings • Determination of the motion of the lubricating film using pattern recognition techniques • Relief, determination and classification of defects on metallic materials • Location and classificat
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Sami Shamoon College of Engineering, Department of Electrical and Electronic Engineering, Beer-Sheva, Israel
Dmitry Baimel received M.Sc and Ph.D. degrees in electrical engineering from the Ben-Gurion University of the Negev, Israel, in 2008 and 2013, respectively. He is currently a Head of the Department of Electrical and Electronics Engineering at the Shamoon College of Engineering. He is also the head of “Electric Drives Research Center”.
power systems; renewable energy; smart grids
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Poznan University of Technology, Faculty of Control, Robotics and Electrical Engineering, Institute of Robotics and Machine Intelligence, Division of Control and Optimization, Poland
Member, IEEE, received the M.Sc. degree from Poznan University of Technology, in 2002, and the Ph.D. degree in 2005, and D.Sc. degree in 2013 from the same University, respectively. Since 2020 he is an associate professor of PUT. He was a Visiting Scholar with the University of Madrid, FCT Nova in Lisbon, UNINA in Naples, and Czech Technical University in Prague. He is the (co)author of 60+ publications in peer-reviewed conferences, 20+ publications in impacted journals and 40+ papers in the other journals. He focuses on using control or optimization techniques, optimal, adaptive or robust control methods, developing linear matrix inequality conditions for anti-windup compensation, and tuning problems. He was a member of UPM-UPO-PUT team in the MBZIRC 2020 robotic competitions (Abu Dhabi) where they scored the third place in the Grand Challenge.
Keynote Speakers
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Prof. Dr. Jose A Antonino-Daviu Department of Electrical Engineering, Universitat Politècnica de València, Spain |
Short Bio
Jose Antonino-Daviu received the M.Sc. and Ph.D. degrees in electrical engineering, both from the Universitat Politècnica de València, Valencia, Spain, in 2000 and 2006, respectively. He has worked for IBM, involved in several international projects. He is currently a Full Professor in the Department of Electrical Engineering, Universitat Politècnica de València. He was an Invited Professor at Helsinki University of Technology, Finland, in 2005 and 2007, Michigan State University, USA, in 2010, Korea University, South Korea, in 2014, Université Claude Bernard Lyon 1, France, and Coventry University, U.K., in 2016. He is a coauthor of more than 200 papers published in technical journals and conference proceedings. He is also the coauthor of one international patent.
Dr. Antonino-Daviu is an Associate Editor of the IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, IEEE INDUSTRIAL ELECTRONICS MAGAZINE and IEEE Journal of Emerging and Selected Topics in Industrial Electronics. He received the IEEE Second Prize Paper Award of the Electric Machines Committee of the IEEE Industry Applications Society (2013). He also received the Best Paper Award in the conferences IEEE ICEM 2012, IEEE SDEMPED 2011 and IEEE SDEMPED 2019 and the “Highly Commended Recognition” of the IET Innovation Awards in 2014 and in 2016. He was the General Co-Chair of SDEMPED 2013 and is a member of the Steering Committee of IEEE SDEMPED. He is also General Co-Chair of ICEM’2022 and Member of the ICEM Administrative Committee. In 2016, he received the Medal of the Spanish Royal Academy of Engineering (Madrid, Spain) for his contributions in new techniques for predictive maintenance of electric motors. In 2018, he has been awarded with the prestigious ‘Nagamori Award’ from the Nagamori Foundation (Kyoto, Japan). In 2019, he received the SDEMPED diagnostic achievement Award (Toulouse, France) for his contributions to electric motors advanced diagnosis.
Proposed presentation title: Transient-based fault diagnosis of electric motors based on the analysis of electrical signals
Abstract of the speech
Over recent years, traditional methods for condition monitoring of electric motors that rely on the analysis of electric signals (currents or fluxes) under steady-state have been complemented, and in some cases replaced, by modern methodologies relying on the analysis of these signals under steady-state operation of the machine. This talk explains the foundations of these techniques and the main advantages that they can provide (avoidance of false indications, higher reliability…). The main options for the application of transient-based diagnosis methods are exposed and several application examples will be commented.
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Prof. Makoto Iwasaki IEEE Fellow |
Short Bio
Makoto Iwasaki received the B.S., M.S., and Dr. Eng. degrees in electrical and computer engineering from Nagoya Institute of Technology, Nagoya, Japan, in 1986, 1988, and 1991, respectively. Since 1991, he has been with the Department of Computer Science and Engineering, Nagoya Institute of Technology, where he is currently a Professor at the Department of Electrical and Mechanical Engineering.
As professional contributions of the IEEE, he has been an AdCom member of IEEE Industrial Electronics Society (IES) in term of 2010 to 2024, a Technical Editor for IEEE/ASME TMech from 2010 to 2014, an Associate Editor for IEEE TIE since 2014, a Management Committee member of IEEE/ASME TMech (Secretary in 2016 and Treasurer in 2017), a Co-Editors-in-Chief for IEEE TIE since 2016, a Vice President for Planning and Development in term of 2018 to 2021, respectively. He is IEEE fellow class 2015 for "contributions to fast and precise positioning in motion controller design".
He has received the Best Paper Award of Trans of IEE Japan in 2013, the Best Paper Award of Fanuc FA Robot Foundation in 2011, the Technical Development Award of IEE Japan in 2017, the Nagamori Awards in 2017, the Ichimura Prize in Industry for Excellent Achievement of Ichimura Foundation for New Technology in 2018, the Technology Award of the Japan Society for Precision Engineering in 2018, and the Commendation for Science and Technology by the Japanese Minister of Education in 2019, respectively. He is also a fellow of IEE Japan, and a member of Science Council of Japan.
His current research interests are the applications of control theories to linear/nonlinear modeling and precision positioning, through various collaborative research activities with industries.
Proposed presentation title: GA-Based Practical System Identification and Auto-Tuning for Multi-Axis Industrial Robots
Abstract of the speech
Fast-response and high-precision motion control is one of indispensable techniques in a wide variety of high performance mechatronic systems including micro and/or nano scale motion, such as data storage devices, machine tools, manufacturing tools for electronics components, and industrial robots, from the standpoints of high productivity, high quality of products, and total cost reduction. In those applications, the required specifications in the motion performance, e.g. response/settling time, trajectory/settling accuracy, etc., should be sufficiently achieved. In addition, the robustness against disturbances and/or uncertainties, the mechanical vibration suppression, and the adaptation capability against variations in mechanisms should be essential properties to be provided in the performance.
The keynote speech presents a practical auto-tuning technique based on a genetic algorithm (GA) for servo controllers of multi-axis industrial robots. Compared to conventional manual tuning techniques, the auto-tuning technique can save the time and cost of controller tuning by skilled engineers, reduce performance deviation among products, and achieve higher control performance. The technique consists of two main processes: one is an autonomous system identification process, involving the use of actual motion profiles of a typical robot. The other is an autonomous control gain tuning process in the frequency and time domains, involving the use of GA, which satisfies the required tuning control specifications, e.g., control performance, execution time, stability, and practical applicability in industries. The proposed technique has been practically evaluated through experiments performed with an actual six-axis industrial robot.
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Prof. Pierre Larochelle Department Head |
Short Bio
Pierre Larochelle serves as Department Head and Professor of Mechanical Engineering at the South Dakota School of Mines & Technology. Previously he served as an Associate Dean and Professor of Mechanical Engineering at the Florida Institute of Technology. His research focuses on the design of complex robotic mechanical systems and enabling creativity and innovation in design. He is the founding director of the RObotics and Computational Kinematics INnovation (ROCKIN) Laboratory, has over 100 publications, holds three US patents, and serves as a consultant on robotics, automation, machine design, creativity & innovation, and computer-aided design. In 2012 at NASA’s request he created a 3-day short course on Creativity & Innovation. This course has been very well received and he has taught it exclusively more than 30 times at NASA’s various centers and laboratories across the nation to more than 600 of NASA scientists and engineers. He currently serves as the Chair of the U.S. Committee on the Theory of Mechanisms & Machine Science and represents the U.S. in the International Federation for the Promotion of Mechanism & Machine Science (IFToMM) (2016-22). He serves as a founding Associate Editor for the ASME Journal of Autonomous Vehicles and Systems (2020-23). Moreover, he serves on the Executive Committee of ABET’s Engineering Accreditation Commission (EAC) and as an ABET Accreditation Visit Team Chair. He has served as Chair of the ASME Design Engineering Division (2018-2019), the ASME Mechanisms & Robotics Committee (2010-2014), and as an Associate Editor for the ASME Journal of Mechanisms & Robotics (2013-19), the ASME Journal of Mechanical Design (2005-11), and for Mechanics Based Design of Structures & Machines (2006-13). He is a Fellow of the American Society of Mechanical Engineers (ASME), a Senior Member of IEEE, and a member of Tau Beta Pi, Pi Tau Sigma, ASEE, and the Order of the Engineer.
Proposed presentation title: Synthesis of RR and CC Dyads for Pick and Place Tasks with Guiding Locations
Abstract of the speech
A novel dimensional synthesis technique for solving the mixed exact and approximate motion synthesis problem for planar, spherical, and spatial dyads is presented. The methodology uses an analytic representation of the dyad's rigid body constraint equation in combination with an algebraic geometry formulation of the exact synthesis for three prescribed positions to yield designs that exactly reach the prescribed pick & place positions while approximating an arbitrary number of guiding positions. The result is a dimensional synthesis technique for mixed exact and approximate motion generation for planar RR, spherical RR, and spatial CC dyads. A solution dyad may be directly implemented as an open chain or two solution dyads may be combined to form a 4R or 4C closed chain; e.g. a planar four-bar mechanism. The synthesis algorithm only utilizes algebraic geometry and does not require the use of a numerical optimization algorithm or a metric on the elements of SE(2), SO(3), or SE(4); the groups of planar, spherical, and spatial displacements. Two implementations of the synthesis algorithm are presented; computational and graphical construction. Examples of the synthesis of planar four-bar, spherical four-bar, and spatial 4C mechanisms for pick and place tasks are included. Finally, applications and future works are discussed.
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Dr. Konstantinos Gyftakis Technical University of Crete, Greece |
Short Bio
K. N. Gyftakis received the Diploma in Electrical and Computer Engineering from the University of Patras, Patras, Greece in 2010. He pursued a Ph.D. in the same institution in the area of electrical machines condition monitoring and fault diagnosis (2010-2014). Furthermore, he worked as a Post-Doctoral Research Assistant in the Dept. of Engineering Science, University of Oxford, UK (2014-2015). Then he worked as Lecturer (2015-2018) and Senior Lecturer (2018-2019) in Coventry University, UK. Between 2015-2022 he worked as a Lecturer in Electrical Machines, University of Edinburgh.
He is currently an Associate Professor with the Technical University of Crete, Greece.
His research interests focus in the fault diagnosis, condition monitoring and degradation of electrical machines. He has authored more than 110 papers in international scientific journals and conferences and chapter for the book: “Diagnosis and Fault Tolerance of Electrical Machines, Power Electronics and Drives”, IET, 2018. Finally, he serves as an Editor for the IEEE Transactions on Energy Conversion.
Proposed presentation title: An overview of electrical machines condition monitoring and fault diagnosis
Abstract of the speech
Electrical machines are key devices for the electric power generation, industrial production and every day life of mankind. Although generally robust, electrical machines may experience faults which if undetected may lead to catastrophic breakdowns with significant negative outcomes. This reality demands the development of reliable condition monitoring. This seminar will cover most major faults in induction motors such as stator inter-turn faults, broken bars and mechanical faults, as well as rotor faults in direct drive permanent magnet generators. The goal of the seminar is to instruct and introduce researchers and engineers in the field of diagnostics covering significant ground and discussing several aspects.
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Dr. Alejandro Gómez Yepes Applied Power Electronics Technology Research Group, University of Vigo, Spain |
Short Bio
Alejandro Gómez Yepes was born in A Coruña, Spain, in November 1985. He received the M.Sc. and Ph.D degrees in electrical engineering from the University of Vigo, Spain, in January 2009 and December 2011, respectively.
From June 2008 he is working with the Applied Power Electronics Technology Research Group (APET) of the University of Vigo, Spain. From April 2011 to July 2011, he joined the Department of Electronics and Electrical Engineering of Liverpool John Moores University, UK. From August 2016 to June 2018, he joined the Advanced Electric Machines and Power Electronics (EMPE) lab of Texas A&M University, USA. In addition, from September 2018 to October 2018, he joined the Electromechatronic Systems Research Centre (CISE) of the University of Beira Interior, Portugal. He is a Ramon y Cajal research fellow at the University of Vigo, Spain, since January 2020.
His research interests mainly include digital control of power electronics converters, with special focus, currently, on multiphase ac motor drives. He has co-authored more than 100 scientific publications (mostly in journals) in the field of power electronics, with over 5000 citations. He is a recipient of the 2018 First Prize Paper Award and Second Prize Paper Award from the IEEE Industry Applications Society. He currently serves as an Associate Editor of the IEEE Transactions on Industrial Electronics and the IET Electric Power Applications, and as an Editorial Board member of Machines. He has also participated in 7 and 5 R&D projects funded by public and private entities, respectively.
Presentation title: Fault Tolerance in Multiphase Electric Machine Drives
Abstract of the speech
Multiphase drives offer enhanced fault-tolerant capabilities compared with conventional three-phase ones. Their phase redundancy makes them able to continue running in the event of faults in certain phases, such as open- or short-circuit ones. Moreover, their greater number of degrees of freedom permits improving the performance not only under faults affecting individual phases, but also under those affecting the machine/drive as a whole. That is the case of failures in the dc link, resolver/encoder, control unit, cooling system, etc. Accordingly, multiphase drives are becoming remarkable contenders for applications where high reliability is required, such as electric vehicles and standalone/off-shore generation. Actually, the literature on the subject has grown exponentially in recent years. This keynote speech presents an overview about the state-of-the-art regarding fault tolerance in multiphase drives. The most important recent advances, emerging trends and open challenges are highlighted.
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Dr. Efstathios Velenis Reader in Vehicle Dynamics and Control |
Short Bio
Dr Velenis is a Reader at the Advanced Vehicle Engineering Centre at Cranfield University. His research interests include vehicle dynamics and control, optimal, nonlinear, model predictive control, active chassis control, control of autonomous vehicles, vehicle limit handling, modelling of expert driving techniques. Dr Velenis received his MSc and PhD degrees from the School of Aerospace Engineering at Georgia Institute of Technology in 2000 and 2006 respectively and his Mechanical Engineering Diploma from the National Technical University of Athens in 1999. In 2006 he was awarded the Luther Long award for the best PhD dissertation in Engineering Mechanics at GeorgiaTech. Following his PhD, Efstathios held a Post-doctoral researcher position at GeorgiaTech and was a visiting researcher at Ford Motor Company in MI, USA. Prior to joining Cranfield he was a lecturer in Mechanical Engineering at Brunel University London. He has co-authored over 80 research papers in peer-reviewed journals and conferences and is an associate editor of the IEEE Transactions on Vehicular Technology.
Presentation title: Expert Vehicle Control at The Limits of Handling
Abstract of the speech
Active chassis-control/safety systems have had an enormous impact in the global society and economy by achieving significant reduction of road traffic accidents, injuries and deaths. Several of these systems aim at delivering a stable, predictable and intuitive response of the vehicle for the average human driver. At the same time, expert human drivers in the field of motorsport, routinely operate their vehicles outside the envelope enforced by such active safety systems, to fully exploit the performance of the vehicle. In this presentation we discuss research work which aims to shed light into the optimality properties and performance benefits of driving techniques used by race drivers including extreme operating conditions which require expert skills. We also present a framework for the development of control algorithms able to stabilise the vehicle dynamics in such extreme conditions. Inspired by expert driving techniques a driver assist system concept for evasive manoeuvring is presented. Finally, in the context of driverless vehicles, the requirement for predictable and intuitive response of the vehicle for the average human driver becomes irrelevant. We envision that autonomous vehicle controllers will use expert skills to control the vehicle dynamics and operate outside the envelope enforced by current active safety systems if necessary. We present recent results in the development of autonomous vehicle controllers able to operate the vehicle at the limits of handling including their implementation on a prototype vehicle platform.
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Dr. Hai Wang College of Science, Health, Engineering and Education, Murdoch University, Australia |
Short Bio
Hai Wang (M’13–SM’19) received his PhD degree from Swinburne University of Technology (SUT), Australia, in 2013, in electrical and electronic engineering. From 2014 to 2015, he was the Postdoc Research Fellow in the Faculty of Sciences, Engineering and Technology, at SUT, Australia. From 2015 to 2019, he was with the School of Electrical and Automation Engineering at Hefei University of Technology, China, where he served as the Full Professor (Huangshan Young Scholar) and the Deputy Discipline Head of Automation. Hai is currently the Senior Lecturer of Electrical Engineering, Academic Chair of Intelligent Industrial Control & Autonomous Systems Engineering (IICASE), and Director of Advanced Mechatronics, Robotics, and Controls Laboratory, in Discipline of Engineering and Energy, at Murdoch University, Perth, Australia. His research interests are in sliding mode control and observer, adaptive control, robotics and mechatronics, neural networks, nonlinear systems, and vehicle dynamics & control. Dr. Wang was the Chair of IEEE Industrial Electronics Society Western Australia Chapter in 2020. He currently serves as the Section EiC of Actuators, Associate Editor of Computers and Electrical Engineering, ASME-Journal of Autonomous Vehicles and Systems, Leading Guest Editors of Neural Computing and Applications, Computers and Electrical Engineering, Actuators, etc.
Presentation title: Modelling and robust control for steer-by-wire vehicles via sliding mode methodologies
Abstract of the speech
For automotive steer-by-wire (SbW) systems, system parametric uncertainties, nonlinearities (frictions, etc) and external disturbances (tyre self-aligning torque from road surfaces) exist and greatly make the control design to be quite challenging and difficult. In this talk, the mathematical modelling of the SbW system will be further explored and presented by an equivalent second-order dynamical system. Next, based on the derived simplified model of SbW system, a series of robust control schemes via sliding mode control (SMC) methodologies will be introduced, such that the robustness, good convergence property of steering tracking, and excellent disturbance rejection ability of the closed-loop SbW control system can be well obtained. Further, novel SMC-based yaw stability control schemes including upper and lower controllers are developed for SbW vehicles to improve the vehicle manoeuvrability and yaw stability performance. Hardware-in-the-loop and vehicle platforms are established, where fruitful real-time experiments are presented in support of the remarkable performance and effectiveness of the proposed schemes. Practical concerns surrounding the gaps between academia and industry on this topic are also reported.
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Prof. Dr. Ming Yu School of Electrical Engineering and Automation, Hefei University of Technology, China |
Short Bio
Ming Yu (M’12) received the B.E. and M.E. degrees in automobile engineering from Hefei University of Technology, Anhui, China, in 2001 and 2004, respectively, and the Ph.D. degree in electrical and electronic engineering from Nanyang Technological University, Singapore, in 2012. From 2013 to 2014, he was a Research Fellow in the Rolls-Royce@NTU Corporate Lab, Nanyang Technological University. Since 2014, he has been with the School of Electrical and Automation Engineering, Hefei University of Technology, Hefei, China, as a Professor. His research interests include fault diagnosis and prognosis of mechatronic systems, hybrid system modeling, and evolutionary algorithms, computational optimal control.He has more than 80 refereed journal and conference proceedings papers in related areas. He was a guest editor of Actuators.
Presentation title: Fault diagnosis and prognosis of steer-by-wire system based on finite state machine and extreme learning machine
Abstract of the speech
In this work, an integrated condition monitoring method combining model-based fault diagnosis and data-driven prognosis is proposed for steer-by-wire (SBW) system. First, the SBW system is modeled by bond graph (BG) technique and a twodegree-of-freedom (2-DOF) state-space model of the vehicle is built. Based on the 2-DOF model, the estimated selfaligning torque is used for the control of feedback motor. The fault detection is carried out by evaluating the analytical redundancy relations derived from the BG model. Since the fault isolation performance is essential to subsequent fault estimation process, a new fault isolation method based on finite state machine is developed to improve the isolation ability by combining the dependent and independent analytical redundancy relations, where the number of potential faults could be decreased. In order to refine the possible fault set to determine the true fault, a cuckoo search (CS)–particle filter is developed for fault estimation. Based on the estimated true fault, prognosis can be implemented which is important to achieve failure prevention and prolong system lifespan. To this end, an optimized extreme learning machine (OELM) is proposed where the input weights and hidden layer biases are optimized by CS. Based on data representing fault values obtained from the fault identification, the OELM model is trained for remaining useful life prediction of failing component. Finally, the proposed methodologies are validated by simulations.
Instructions for Authors
Submissions should be made by authors online by registering with www.sciforum.net, and using the "New Submission" function once logged into the system.
Note: Institutional email address is requested especially for the corresponding author. Please submit the abstract with the institutional email address, the submissions with the email addresses like gmail.com, 163.com, hotmail.com, qq.com etc. will not be reviewed.
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Scholars interested in participating in the conference can submit their abstract (about 200–300 words) online on this website until 18th May 2022 17 June 2022.
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The Conference Committee will notify the acceptance of the abstract by 15th June 2022 30 June 2022.
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In case of acceptance, authors will be asked to submit their manuscript (short proceedings paper, 3-6 pages) before 28th July 2022 11 August 2021. Optionally, authors of accepted abstracts will be able to submit a poster, a slides presentation (in PDF) and/or a short video presentation (max. 3-5minutes) as supporting material of the paper. Authors will receive a notification about the acceptance of their papers by 25 August 2022.
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The manuscripts and presentations will be available on sciforum.net for discussion and rating during the time of the conference, from 15-30 September 2022.
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The accepted proceedings papers will probably be published as one dedicated volume in MDPI Engineering Proceedings journal (ISSN 2673-4591). Publication of proceedings paper is free of charge.
Note: Before publication, Engineering Proceedings journal will review accepted papers using the powerful text comparison tool: iThenticate. This procedure aims to prevent scholarly and professional plagiarism.Articles with a high repetition rate and lack of novelty will not be published in the conference proceedings.
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The Open Access Journal Machines will publish a Special Issue of the conference after the conference.
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The submission to the Machines is independent of the conference proceedings and will follow the usual process of the journal, including peer-review, APC, etc. All participants of IECMA2022 are welcome to submit an extended full paper to the Special Issue "Selected Papers from the 1st International Electronic Conference on Machines and Applications (IECMA 2022)" of the journal Machines, with a 20% discount on the Article Processing Charges.
Proceedings papers must be prepared in MS Word using the Engineering Proceedings template (see below) and should be converted to PDF format before submission. The manuscript should count at least 3 pages (incl. figures, tables and references) and should not exceed 6 pages. Carefully read the rules outlined in the 'Instructions for Authors' on the journal website and ensure that your manuscript submission adheres to these guidelines.
Manuscripts for the proceedings issue must have the following organization:
- Title
- Full author names
- Affiliations (including full postal address) and authors' e-mail addresses
- Abstract
- Keywords
- Introduction
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- Results and Discussion
- Conclusions
- (Acknowledgements)
- References
Authors are encouraged to prepare a presentation in PowerPoint or similar software, to be displayed online along with the manuscript. Slides can be prepared the same way as for any traditional conference. They should be converted to PDF format before submission.
Authors are requested to submit video presentations accompany with extended submissions. Video should be no longer than 3-5 minutes and prepared with one of the following formats: .mp4 / .webm / .ogg (max size: 250Mb). It should be submitted with the full manuscript before 11 August 2022 (full submission deadline).
Posters will be available on this conference website during and after the event. Like papers presented on the conference, participants will be able to ask questions and make comments about the posters. Posters can be presented without an accompanying proceedings paper. However, they will not be added to the proceedings of the conference.
After acceptance, please upload a copy of the proceedings/abstract as a PDF and word, in the corresponding fields, and upload the Poster PDF in the field "Presentation PDF (optional)".
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For detailed instructions on how to submit a poster, please contact us at iecma@mdpi.com.
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Event Awards
To acknowledge the support of the conference's esteemed authors and recognize their outstanding scientific accomplishments, we are pleased to launch the following awards:
Winner Announcement
On behalf of the chairs of IECMA 2022, we are pleased to announce the winner of the Best Paper Award:
- sciforum-061174, "New transfer learning approach based on CNN network for fault diagnosis"
Alasmer Ibrahim, Fatih Anayi and Michael Packianather
The Award consists of 500 CHF and an opportunity to publish a featured paper in Machines for free.
On behalf of the chairs of IECMA 2022, we are pleased to announce the winner of the Best Poster Award:
- sciforum-062165, "Defining the Technical Availability of a Production System with Respect to its Complexity"
Lennard Sielaff, Dominik Lucke and Alexander Sauer
The Award consists of 300 CHF and an opportunity to publish a featured paper in Machines for free.
The Awards
Number of Awards Available: 1
The Best Paper Award is given to the paper judged to make the most significant contribution to the conference. There will be one winner selected for this award, the winner will receive a certificate and 500 CHF and the winner will be offered an opportunity to publish a featured paper in Machines for free.Number of Awards Available: 1
The Best Poster Award is given to the submission judged to make the most significant and interesting poster for the conference. There will be one winner selected for this award, the winner will receive a certificate and 300 CHF and the winner will be offered an opportunity to publish a featured paper in Machines for free.Terms and Conditions:
1. Full paper/poster must be submitted to IECMA2022.
2. The quality of the paper/poster.
3. The scientific content of the paper/poster.
Evaluation
1. Each Evaluation Committee member will give an assessment for each paper/poster in terms of the criteria outlined above.
2. The score for each paper/poster will be ranked, from highest to lowest.
3. If two or more papers/posters get the same score, further evaluation will be carried out.
4. All decisions made by the Evaluation Committee are final.
Conference Secretariat
Ms. Nora Zhang
Mr. Jonathan Liu
Ms. Stefanie Tian
MDPI Branch Office, Beijing
E-Mail: iecma@mdpi.com
Sponsoring Opportunities
For information regarding sponsoring opportunities, please contact the conference secretariat.
Sponsors and Partners
For information regarding sponsorship and exhibition opportunities, please click here.
Organizers
Media Partners
A. Machines Testing and Maintenance
Session Chair
Prof. Dr. Antonio J. Marques Cardoso, University of Beira Interior, Department of Electromechanical Engineering, Calçada Fonte do Lameiro, Portugal
B. Automation Systems
Session Chair
Prof. Dr. Dan Zhang, Department of Mechanical Engineering, Lassonde School of Engineering, York University, Toronto, Canada
C. Mechatronic and Intelligent Machines
Session Chair
Prof. Dr. Giuseppe Carbone, Department of Mechanical, Energy and Management Engineering, University of Calabria, Italy
E. Electrical Machines and Drives
Session Chair
Prof. Dr. Antonio J. Marques Cardoso, University of Beira Interior, Department of Electromechanical Engineering, Calçada Fonte do Lameiro, Portugal
F. Advanced Manufacturing
Session Chair
Professor Ibrahim Tansel, Department of Mechanical and Material Engineering, Florida International University, USA
S1. Vehicle Dynamics and Control
Session Chair
Dr. Hai Wang, Murdoch University, Perth, Australia