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International Workshop on Health Monitoring of Offshore Wind Farms Sept. 26

th, 2014, Nanjing, China

COVER



CONTENT

INTRODUCTION ..................................................................................................................... 1

WELCOME WORDS FROM THE STATE KEY LAB ........................................................................ 4

SCHEDULE .............................................................................................................................. 5

PARTICIPANTS ....................................................................................................................... 7

PRESENTATION ABSTRACTS .................................................................................................. 15

Model-based Fatigue-Life Monitoring of Structures B. F. Spencer, Jr. and Hongki Jo ................................. 15

Integral Utilization of Multi-types of Structural Vibration Signals for Damage Identification Based on

the “Weak” Formulation of Pseudo-Excitation (PE) Technique: Virtual Vibration Deflection (VVD) Li

Cheng, Zhongqing Su and Hao Xu .................................................................................................................. 16

Planetary Gearbox Diagnosis Based on an Improved Fast Kurtogram Method Jing Lin, Xiaoqiang Xu

and Ming Zhao ............................................................................................................................................ 17

Particle Filter Based Structural Crack Propagation Prognosis Shenfang Yuan, Weibo Yang, Jian Chen, Lei

Qiu, Hanfei Mei ............................................................................................................................................ 18

Fault Diagnostics of the Planetary Gear System of Wind Turbine Fulei Chu, Yong Gui and Qinkai Han ..... 19

Health Monitoring of Wind Turbine Rotor Blades U. Gabbert and S. Duczek ............................................. 20

Numerical Simulation and Applications of Lamb Waves in On-line Monitoring and Off-line Evaluation

Techniques Ning Hu and Yaolu Liu ............................................................................................................. 21

Wind Turbine Gearbox Fault Diagnosis Using Single Channel Stationary Subspace Analysis Ruqiang Yan

and Yuning Qian .......................................................................................................................................... 22

Smart Sensing in the Light of Non-Destructive Testing and Structural Health Monitoring Gerd Dobmann

and Christian Boller ..................................................................................................................................... 23

Monitoring of Wind Farms and Case Studies Guiyun Tian ....................................................................... 24

Damage Identification Using Guided Waves: from Linear to Nonlinear, from Macroscopic to

Mesoscopic, from Distributed to Dispersed Sensing Zhongqing Su ......................................................... 25

Challenges for Condition Monitoring of Transmission Systems Jishan Zhang, Brian Shaw and Robert

Lambert ...................................................................................................................................................... 26

A New Physical Concept of Multiscale Shear-Strain Gradient for Identifying Delamination in

Composite Structures in Noisy Conditions Maosen Cao, W. Ostachowicz, M. Radzienski and Wei Xu ........... 27

Loading Independent Wind Turbine Condition Monitoring: A Baseline Model Approach Ziqiang Lang 28

Wind Turbine Blade Monitoring Using Noncontact Sensing Techniques Hoon Sohn, Byeong Jin Park and

Peipei Liu .................................................................................................................................................... 29

Key Mechanical Issues of Large Scale Wind Turbines - A Project Funded by the National Basic

Research Program Tongguang Wang ......................................................................................................... 30

Condition Monitoring for Reliable and Predicable Operation of Wind Turbines Xiandong Ma .............. 31

Mode-Adaptive Decentralized Control for Renewable DC Microgrid with Enhanced Reliability and

Flexibility Wuhua Li, Yunjie Gu and Xiangning He ........................................................................................ 32

MAP AND CONTACT INFORMATION ..................................................................................... 33



1

INTRODUCTION

Offshore wind farm health monitoring and maintenance are major challenges for

renewable energy generation due to large scale, high cost and extreme environments. The

development of faults in the tower or blades can cause serious secondary damage to the

whole wind turbine system if prompt repair action is not taken and can lead to

catastrophic failure. Consequently there is a real and urgent need to bring together

researchers in this field to develop a more “joined up” approach to these problems. The

FP7 International Research Staff Exchange Project of Health Monitoring of Offshore

Wind Farms (HEMOW) is endorsed by 5 institutions, 2 EU partners and research groups

in China and India to develop a joint networking and advanced research program based

on emerging technologies that will strengthen the research partnership between the

partners in the area of non-destructive evaluation, structural health monitoring,

systematic approach for condition monitoring and condition based maintenance in the

field of renewable energy, which is of growing importance worldwide.

International Workshop on Health Monitoring of Offshore Wind Farms is held as a

part of the exchange activities supported by HEMOW which is the second one following

the one held in 2011 in Newcastle University. The workshop is jointly organized by

Nanjing University of Aeronautics and Astronautics in China and Newcastle University

in UK which aims at providing a high level forum for the exchange of ideas across

disciplines and the encouragement of multidisciplinary research collaboration in the

growing domain of health monitoring of mechanical systems including but not limited to

offshore wind farms. All the participants who have been invited to this workshop are

world-wide famous experts from China Mainland, China Hong Kong, UK, Germany,

USA and Korea. This workshop is also sponsored by National Nature Science

Foundation of China and the State Key Laboratory of Mechanics and Control of

Mechanical Structures in Nanjing University of Aeronautics and Astronautics.



2

Organizers

Nanjing University of Aeronautics and Astronautics, China (NUAA)

Newcastle University, UK (UNEW)

Chairperson

Prof. Shenfang Yuan, Nanjing University of Aeronautics and Astronautics, China

Prof. Shenfang Yuan, Changjiang Chair professor of the State Key

Laboratory of Mechanics and Control of Mechanical Structures,

Nanjing University of Aeronautics and Astronautics(NUAA). She

received her Ph.D. from NUAA in 1996. Prof. Yuan’s main research

interests include structural health monitoring, smart structures, sensor

and measurement technology, wireless sensor network, signal

processing methods and experimental mechanics. She has authored 2

books and over 200 journal papers. She holds 35 Chinese invention

patents. She is the PI of a number of import projects, including China National Funds for

Distinguished Young Scientists, Key Project from National Science Foundation of China,

Key Program of National Basic Research Program of China and National High

Technology research program. She is the winner of the Special Support Program for

National High Level Leading Talents of China (2013), China National Funds for

Distinguished Young Scientists from NSFC (2012), Distinguished Young Scientist Award

from China Aviation Society (2011).

Prof. Guiyun Tian, Newcastle University, UK

Prof. Guiyun Tian, Chair Professor in Sensor Technologies,

Newcastle University, UK. Currently, he is also with School of

Automation Engineering, University of Electronic Science and

Technology of China. He received his Ph.D. degree from the

University of Derby, Derby, UK, in 1998. His current research

interests include non-destructive testing and evaluation, structural

health monitoring, sensors and wireless sensor network. More than

200 papers have been published in international journals such as Applied Physics Letters,

IEEE Transactions on Magnetics, IEEE Transactions on Sensors, and cited by

counterparts for more than 2000 times. He has hosted more than 10 projects funded by

the UK Engineering and Physical Sciences Research Council, The Royal Society and The

Royal Academy of Engineering, and performed long-term cooperation with world

famous companies and institutions such as Airbus, Rolls-Royce, Kohler Group, Fuji

Xerox and TIWI.



3

Organization committee

Prof. Shenfang Yuan, Nanjing University of Aeronautics and Astronautics, China

Prof. Guiyun Tian, Newcastle University, UK

Prof. Ke Xiong, Nanjing University of Aeronautics and Astronautics, China

Prof. Haitao Wang, Nanjing University of Aeronautics and Astronautics, China

Dr. Qiang Wang, Nanjing University of Posts and Telecommunications, China

Dr. Lei Qiu, Nanjing University of Aeronautics and Astronautics, China

Dr. Ruipeng Guo, Nanjing University of Aeronautics and Astronautics, China



4

WELCOME WORDS FROM THE STATE KEY LAB

The State Key Laboratory of Mechanics and Control of Mechanical Structures

(SKLMCMS) in NUAA was found in 2011 which was approved by Ministry of Science

and Technology of China.

SKLMCMS carries out the pioneer research on structural dynamics and control,

smart materials and structures, PZT based precision driving, Nano mechanics and

structure strength analysis. The State Key Lab represents the highest research level in

these areas in China and is one of the most important bases for knowledge and technique

innovation, personnel training and international academic exchange.

Totally, there are 52 full time faculty members in SKLMCMS, including 38 full

professors, 15 associate and assistant professors. Among them, there are 2 Academicians

of Chinese Academy of Science and 1 Academician of Academy of Science for the

Developing World. 1 Professor enters the “Recruitment Program of Global Experts”. 4

hold the Changjiang Chair Professor positions. 4 have won the National Science Fund for

Distinguished Young Scholars. 4 research teams have been awarded as national or

provincial innovation research teams.

In recent 5 years, SKLMCMS has totally received research funds of more than 210

million RMB, won 3 National Technology Invention Awards, published 15 monographs

and books and over 900 international peer-reviewed papers. Many important applications

in aerospace engineering have also been achieved.

In education aspects, nearly 300 Ph.D. students and undergraduate students study

annually in the State Key Lab. Till now, 4 Ph.D. dissertations have been awarded the

National Excellent Doctoral Degree Dissertations and additional 4 wins the Nominated

Award of the National Excellent Doctoral Degree Dissertations.

The State Key Lab also encourages international exchange. Every year, numerous of

faculties and students in the Lab are sponsored to visit abroad, and international scholars

and students are invited to visit the Lab. 2 foreign experts who are closely collaborated

with the Lab have won the National Friend Awards in China.

The Stake Key Lab is glad to sponsor this high level international workshop and

hopes this will be a good beginning of much new significant international cooperation.

Wish a successful Workshop!



5

SCHEDULE

8:40 – 11:55, Sept. 26th

, 2014

Room 506, A9 Building

Nanjing University of Aeronautics and Astronautics

Chair: Prof. Shenfang Yuan 8:40 – 9:00 Opening Ceremony

Welcome Speech

Prof. Ke Xiong (Nanjing University of Aeronautics and Astronautics, China)

HEMOW Background Introduction

Prof. Guiyun Tian (Newcastle University, UK)

Chair: Prof. Gerd Dobmann and Prof. Fulei Chu

9:00 – 9:20 Model-based Fatigue-Life Monitoring of Structures

B. F. Spencer (University of Illinois at Urbana-Champaign, USA)

9:20 – 9:40 Integral Utilization of Multi-types of Structural Vibration Signals for Damage

Identification Based on the “Weak” Formulation of Pseudo-Excitation (PE)

Technique: Virtual Vibration Deflection (VVD)

Li Cheng (The Hong Kong Polytechnic University, Hong Kong, China)

9:40 – 10:00 Planetary Gearbox Diagnosis Based on an Improved Fast Kurtogram Method

Jing Lin (Xi’an Jiaotong University, China)

10:00 – 10:20 Particle Filter Based Structural Crack Propagation Prognosis

Shenfang Yuan (Nanjing University of Aeronautics and Astronautics, China)

10:20 – 10:35 Coffee/Tea Break

Chair: Prof. Li Cheng and Prof. Jing Lin

10:35 - 10:55 Fault Diagnostics of the Planetary Gear System of Wind Turbine

Fulei Chu (Tsinghua University, China)

10:55 – 11:15 Health Monitoring of Wind Turbine Rotor Blades

Ulrich Gabbert (University of Magdeburg, Germany)

11:15 – 11:35 Numerical Simulation and Applications of Lamb Waves in On-line Monitoring

and Off-line Evaluation Techniques

Ning Hu (Chongqing University, China)

11:35 – 11:55 Wind Turbine Gearbox Fault Diagnosis Using Single Channel Stationary

Subspace Analysis

Ruqiang Yan (Southeast University, China)

12:00 - 13:30 Lunch



6

13:30 – 17:30, Sept. 26th

, 2014


Nanjing University of Aeronautics and Astronautics

Chair: Prof. Ziqiang Lang and Prof. Ning Hu

13:30 – 13:50 Smart Sensing in the Light of Non-Destructive Testing and Structural Health

Monitoring

Gerd Dobmann (Saar-University, Germany)

13:50 – 14:10 Monitoring of Wind Farms And Case Studies

Guiyun Tian (Newcastle University, UK)

14:10 – 14:30 Damage Identification Using Guided Waves: from Linear to Nonlinear, from

Macroscopic to Mesoscopic, from Distributed to Dispersed Sensing

Zhongqing Su (The Hong Kong Polytechnic University, Hong Kong, China)

14:30 – 14:50 Challenges for Condition Monitoring of Transmission Systems

Jishan Zhang (Newcastle University, UK)

14:50 – 15:10 A New Physical Concept of Multiscale Shear-Strain Gradient for Identifying

Delamination in Composite Structures in Noisy Conditions

Maosen Cao (Hohai university, China)

15:10 - 15:30 Photo

15:30 – 15: 45 Coffee/Tea Break

Chair: Prof. B. F. Spencer and Prof. Maosen Cao

15:45 – 16:05 Loading Independent Wind Turbine Condition Monitoring: A Baseline Model

Approach

Ziqiang Lang (Sheffield University, UK)

16:05 – 16:25 Wind Turbine Blade Monitoring Using Noncontact Sensing Techniques

H. Sohn (Korea Advanced Institute of Science and Technology, Korea)

16:25 – 16:45 Key Mechanical Issues of Large Scale Wind Turbines - A Project Funded by the

National Basic Research Program

Tongguang Wang (Nanjing University of Aeronautics and Astronautics, China)

16:45 – 17:05 Condition Monitoring for Reliable and Predicable Operation of Wind Turbines

Xiandong Ma (Lancaster University, UK)

17:05 - 17:25 Mode-Adaptive Decentralized Control for Renewable DC Microgrid with

Enhanced Reliability and Flexibility

Wuhua Li (Zhejiang University, China)

17:25 – 17:30 Concluding Remarks

18:00 – 19:30 Banquet



7

PARTICIPANTS (List in order of speaking)

Prof. Ke Xiong is now the Assistant to President of Nanjing University of

Aeronautics and Astronautics and the Director of State Key Laboratory of

Mechanics and Control of Mechanical Systems. He received his Ph.D.

degrees from Nanjing University of Aeronautics and Astronautics, China, in

1997. He is a council member of Chinese Aviation Society and permanent

member of Indian Society for Advancement of Materials and Process

Engineering. His main research interest is smart materials and structural

systems, including development of actuator and adaptive structural

technologies, shape memory alloy, ionic polymer metal composites and devices, structural health

monitoring with Piezoelectric SMART Layer for aerospace applications and ground test of

aircraft structure strength applied electro-metric techniques and experimental stress-strain

analysis. He is the PI of a number of research projects funded by the National Natural Science

Foundation of China (NSFC). He has published one book and over 60 papers. He has also

received 5 important awards, including a National Invention Award and a National Teaching

Award.

Email: [email protected]

Prof. B. F. Spencer, Jr. is the Nathan M. and Anne M. Newmark Endowed

Chair of Civil Engineering at the University of Illinois at

Urbana-Champaign. He received his M.S. and Ph.D. degrees in Theoretical

and Applied Mechanics at Illinois in 1983 and 1985, respectively. He is the

author of more than 200 journal papers and has written two books. His

current research interests include structural health monitoring, smart sensors

and wireless sensor networks.


Prof. Li Cheng is a Chair Professor and the Director of Consortium for

Sound and Vibration Research (CSVR) at the Department of Mechanical

Engineering, The Hong Kong Polytechnic University. His research interests

include noise and vibration control, structural health monitoring, smart

material/structure and fluid-structure interaction. Dr. Cheng published

extensively in his research area, with over 350 publications including

book/book chapters and journal/conference papers. He was elected a fellow

of the Acoustical Society of America, a fellow of the Acoustical Society of

China, IMechE and the Hong Kong Institution of Engineers. Dr. Cheng currently serves as an

Associate Editor for the Journal of Acoustical Society of America, Associate Editor of Structural

Health Monitoring: an International Journal, as well as six other international journals.




8

Prof. Jing Lin received his Ph.D. degree in mechanical engineering from

Xi’an Jiaotong University in 1999. From January 2009 to present, he is a

professor with School of Mechanical Engineering of Xi’an Jiaotong

University. He obtained the National Distinguished Youth Foundations of

China in 2011 and was awarded the Natural Science Award of China in

2013. He is the author of more than 50 journal papers. His current research

interests include machinery dynamic analysis, fault diagnosis and structural

health monitoring.


Prof. Shenfang Yuan, Changjiang Chair professor of the State Key

Laboratory of Mechanics and Control of Mechanical Structures, Nanjing

University of Aeronautics and Astronautics(NUAA). She received her Ph.D.

from NUAA in 1996. Prof. Yuan’s main research interests include structural

health monitoring, smart structures, sensor and measurement technology,

wireless sensor network, signal processing methods and experimental

mechanics. She has authored 2 books and over 200 journal papers. She

holds 35 Chinese invention patents. She is the PI of a number of import

projects, including China National Funds for Distinguished Young

Scientists, Key Project from National Science Foundation of China, Key Program of National

Basic Research Program of China and National High Technology research program. She is the

winner of the Special Support Program for National High Level Leading Talents of China (2013),

China National Funds for Distinguished Young Scientists from NSFC (2012), Distinguished

Young Scientist Award from China Aviation Society (2011).


Prof. Fulei Chu is a professor in the Department of Mechanical

Engineering at Tsinghua University in Beijing. He received his first degree

in mechanical engineering from Jiangxi University of Science and

Technology, his M.S. is from Tianjin University and his Ph.D. in dynamics

and vibration from Southampton University in UK. He is the author of more

than 200 journal papers and has also authored 3 books and edited 2

conference proceedings. His current research interests include rotating

machinery dynamics, machine condition monitoring and fault detection,

nonlinear vibration and vibration control. He is the winner of China

National Funds for Distinguished Young Scientists.




9

Prof. U. Gabbert graduated at the University of Magdeburg as Mechanical

Engineer (Dipl.-Ing.). He received the first doctoral degree (Dr.-Ing.) in

mechanics. Then he was working as a design engineer in a pump and

compressor company. Since 1992 he is full University Professor and Head

of the Chair of Computational Mechanics. His research interests are finite

elements, smart structures, active vibration and noise control, structural

health monitoring and medical engineering.


Prof. Ning Hu is a Professor and Dean of College of Aerospace

Engineering, Chongqing University, China. His main research interests

focus on the following several fields: solids mechanics, computational

mechanics, numerical algorithms and simulations of various physical

problems, functional composite materials, structural composite materials,

composite structures, on-line and off-line structural monitoring and

evaluation techniques, etc. To date, he has generated over 170

peer-reviewed journal papers including 110 SCI ones, and around 80

international conference papers.


Prof. Ruqiang Yan is a professor at Southeast University. He received his

Ph.D. degree from the University of Massachusetts Amherst in 2007, and

his M.S. and B.S. degrees from the University of Science and Technology

of China (USTC) in 2002 and 1997, respectively. He is co-author of the

book “Wavelets: Theory and Applications for Manufacturing” and has

published over 100 refereed journal and conference papers. His research

interests include nonlinear time-series analysis, multi-domain signal

processing, and energy-efficient sensing and sensor networks for the condition monitoring and

health diagnosis of large-scale, complex, dynamical systems. Dr. Yan is an associate editor of the

IEEE Transactions on Instrumentation and Measurement. He is a Co-Chair of the Technical

Committee on Signals and Systems in Measurement of the IEEE Instrumentation and

Measurement Society.




10

Prof. Dr. Gerd Dobmann is Senior Scientific Consultant and works

together with the Chair of Non-destructive Testing (NDT) and Quality

Assurance of the Saar-University in Saarbrücken, Germany. He received

the Diploma in applied physics in 1974 and the Ph.D. in NDT in 1979,

respectively. He has published more than 300 scientific papers and is

subject editor of the Journal NDT&E International of the Elsevier

Publishing House. His current research interests are in online-monitoring

of materials degradation phenomena.


Prof. Guiyun Tian, Chair Professor in Sensor Technologies, Newcastle

University, UK. Currently, he is also with School of Automation

Engineering, University of Electronic Science and Technology of China.

He received his Ph.D. degree from the University of Derby, Derby, UK,

in 1998. His current research interests include non-destructive testing and

evaluation, structural health monitoring, sensors and wireless sensor

network. More than 200 papers have been published in international

journals such as Applied Physics Letters, IEEE Transactions on

Magnetics, IEEE Transactions on Sensors, and cited by counterparts for

more than 2000 times. He has hosted more than 10 projects funded by the UK Engineering and

Physical Sciences Research Council, The Royal Society and The Royal Academy of Engineering,

and performed long-term cooperation with world famous companies and institutions such as

Airbus, Rolls-Royce, Kohler Group, Fuji Xerox and TIWI.


Dr. Zhongqing Su is an associate professor in the Department of

Mechanical Engineering at The Hong Kong Polytechnic University, with a

research focus particularly on structural health monitoring (SHM). He

earned his Ph.D. from The University of Sydney, Australia, with a

prestigious Australian government scholarship IPRS. Dr. Su is the

author/co-author of 2 research monographs, 4 edited books and international

conference proceedings, 4 book chapters, and over 160 refereed papers

including approaching 100 SCI journal papers. Dr. Su received the

‘Structural Health Monitoring - Person of the Year (SHM-POY) Award 2012’, one of the highest

accolade and most well-recognized award in this field.




11

Dr. Jishan Zhang is a mechanical engineer and researcher with over 20

years of experience in the field of geared transmissions. Dr. Zhang started at

Design Unit of Newcastle University, UK, firstly as a Ph.D. candidate

studying gear fatigue in 2000 and obtained his degree 5 years later. He has

since then been working at Design Unit as a research associate. Dr. Zhang’s

main research areas include gear material, heat treatment, surface

engineering, micropitting, macropitting, scuffing, gear lubrication and

condition monitoring of geared transmissions. He has been involved in many

projects funded by British Gear Association, UK Ministry of Defense (Navy) and consultancy

projects from European industries. Dr. Zhang has been instrumental in developing links for Design

Unit with chinese industry and academia and has recently engaged in setting up gear testing

facilities as well as providing associated training to Chinese engineers.


Prof. Maosen Cao is a professor at Hohai University. He received his Ph.D.

degree in hydraulic structural engineering from Hohai University in 2005

and obtained a Top-100 Excellent Doctoral Dissertation Award in 2008. He

has six years’ experience of conducting research in Hong Kong, the United

States, and Poland, and is the author of more than 50 journal papers.

Current research interests include structural health monitoring, wavelet

analysis, and multiscale dynamic modeling and simulation.


Prof. Ziqiang Lang holds the position of Chair Professor in Complex

Systems Analysis and Design in the Department of Automatic Control and

Systems Engineering at the University of Sheffield, UK. His main research

interests cover the development of theories and methods in system

modeling, analysis, signal processing, and control and the application of

these in a wide range of engineering areas including condition monitoring

and fault diagnosis for wind turbines. He has published more than one

hundred research papers and, as a principal investigator, completed many

research projects including projects supported by UK EPSRC, TSB, Royal Society and

collaborative projects with industrial partners.




12

Prof. Hoon Sohn received his B.S. (1992) and M.S. (1994) degrees from

Seoul National University, Seoul, Korea and Ph.D. (1999) from Stanford

University, California, USA, all in Civil Engineering. He is now Professor

at KAIST (Korea Advanced Institute of Science and Technology) in Korea.

Over last twenty years, his research interests include guided waves,

noncontact laser ultrasonics, structural health monitoring, nondestructive

testing, smart materials and sensing, and statistical pattern recognition to

name a few. He has published over 100 refereed journal articles, over 250

conference proceedings, and 10 book & book chapters. He was selected as one of 100 most

promising individuals in Korea in 2012 by Donga Daily Newspaper, which is one of the three

major newspapers in Korea. He was also the recipient of SHM Person-of-Year Award at 2011

International workshop on SHM and 2008 Young Scientists Award in Korea.


Prof. Tongguang Wang is a professor at Nanjing University of

Aeronautics and Astronautics (NUAA), and the Director of Jiangsu Key

Laboratory for Wind Turbines. He was the Chief Scientist, designated by

the Ministry of Science and Technology, for the project “Fundamental

Study of Large Size Wind Turbine Aerodynamics” funded by a Chinese

government strategic basic research program – the National Basic Research

Program of China (known as 973 Program in China). As the Chief Scientist

again, he is now leading a Chinese team of 30 doing the 973 project “Key

Mechanical Issues and Design of Large Scale Wind Turbines”.


Dr. Xiandong Ma is a Senior Lecturer in the Engineering Department at

Lancaster University, UK. He received his Ph.D. in high-voltage power

plant condition monitoring from Glasgow Caledonian University, UK in

2003. His employment experience included Nanjing Automation Research

Institute as a Senior Research Engineer, Lancaster University and then The

University of Manchester as a Postdoctoral Research Associate, and

ALSTOM Power Ltd. UK as a Generator Condition Monitoring Engineer

before returning to Lancaster in 2008. His current research interests include

intelligent condition monitoring and fault diagnosis of distributed generation systems with wind

turbines, advanced signal processing and data mining, and electromagnetic NDT testing and

imaging. Dr. Ma has published over 80 refereed journal and international conference papers.


mailto:[email protected]



13

Prof. Wuhua Li received the B.Sc. and Ph.D. degree in Applied Power

Electronics and Electrical Engineering from Zhejiang University,

Hangzhou, China, in 2002 and 2008, respectively. From 2004 to 2005, he

was a Research Intern, and from 2007 to 2008, a Research Assistant in GE

GRC. In 2010, he was promoted as an Associate Professor. Since 2013, he

has been a Full Professor in the College of Electrical Engineering, Zhejiang

University. From 2010 to 2011, he was a Ryerson University Postdoctoral

Fellow at Ryerson University, Canada. His research interests include

advanced power electronics and renewable energy interfaces. Dr. Li has published more than 100

peer-reviewed technical papers and holds over 30 issued/pending patents.


Prof. Xiangning He received the B.Sc. and M.Sc. degrees from Nanjing

University of Aeronautics and Astronautics (NUAA), Nanjing, China, in

1982 and 1985, respectively, and the Ph.D. degree from Zhejiang University,

Hangzhou, China, in 1989. Since 1996, he has been a Full Professor in the

College of Electrical Engineering, Zhejiang University. He is currently the

Vice Dean of the College of Electrical Engineering, Zhejiang University.

His research interests are power electronics and their industrial applications.

He is the author or co-author of more than 200 papers and one book

“Theory and Applications of Multi-level Converters”. He holds 12 patents. He is a Fellow of the

Institution of Engineering and Technology (formerly IEE), UK.


Prof. Zhanqun Shi is a professor at Hebei University of Technology. He

received his B.S. and M.S. degrees in Mechanical Engineering from

Hebei University of Technology in 1984 and 1987, respectively, and his

Ph.D. degree in Diagnostic Engineering from Manchester University in

2004. He is the author of more than 80 academic publications. His current

research interests include turbocharger health monitoring, wind turbine

condition and model-based condition monitoring for mechatronic control

systems. He is the dean of Institute of Science and Technology at

Hebei University of Technology.





14

Prof. Haitao Wang is a professor of Nanjing University of Aeronautics and

Astronautics. He received his B.S. and M.S. degrees in Biomedical

Engineering and Instrument from Xi'an Jiaotong University in 1991 and

1994, respectively, and his PhD degree in Astronomical Physics from

Chinese Academy of Science in 2002. He is the author of more than 80

journal papers. His current research interests include photoelectric detection,

NDT new technologies.


Dr. Qiang Wang is an associate professor of Nanjing University of Posts

and Telecommunications. He received his B.S. from Yanshan University, in

2002, and M.S. and Ph.D. degrees from Nanjing University of Aeronautics

and Astronautics(NUAA), in 2005 and 2009, respectively. From 2011 to

2012, he was a Research Fellow with the Department of Mechanical

Engineering, The Hong Kong Polytechnic University. He has published

over 30 refereed journal papers including over 10 SCI journal papers. His

research interests include Lamb wave based structural health monitoring,

smart materials and structures, advanced sensor technology and signal processing.


Dr. Lei Qiu is an associate professor at Nanjing University of Aeronautics

and Astronautics (NUAA). He received his B.S. degree in Flight Vehicle

Design and Engineering from NUAA in 2006, and his Ph.D. degree in Test

and Measurement Technology from NUAA in 2012. He has published more

than 70 peer-reviewed journal papers and 13 international conference

papers. He has also been authorized 20 Chinese patents and 7 software

copyrights. His current research interests include structural prognosis and

health management, structural health monitoring, signal processing, smart

sensor and system integration.


Dr. Ruipeng Guo is a lecturer in College of Automation Engineering at

Nanjing University of Aeronautics and Astronautics(NUAA). She received

her Ph.D. degree in Instrumentation Science and Technology from Shanghai

Jiaotong University in 2011. From Nov. 2013 to Feb. 2014, she was a

visiting researcher in the School of Electrical and Electronic Engineering at

Newcastle University, UK. She is the author of more than 20 journal papers.

Her current research interests include in process measurement theory and

technology, photoelectric detection, and non-destructive testing.




15

PRESENTATION ABSTRACTS

(List in order of speaking)

Model-based Fatigue-Life Monitoring of Structures

B. F. Spencer, Jr.1, a and Hongki Jo2, b

1Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign,

Urbana, USA

2Department of Civil Engineering and Engineering Mechanics, University of Arizona, Tucson, USA

[email protected], [email protected]

Abstract: The inspection and maintenance of structures of all types is critical to the

safety of the public and often critical to the economy of a region. Fatigue is among one

of the most critical damage mechanisms in steel structures. Fatigue is not readily

observable, particularly during the period of crack initiation, which typically

corresponds to up to 90% of the fatigue life. Fatigue is considered in the design stage

using modern provisions and, if the critical locations are known a priori, can be

monitored by direct strain measurement and visual inspection. However, for today’s

complex civil infrastructure, including wind turbines, the critical locations are numerous

and often difficult to identify. This paper presents an innovative framework for fatigue

assessment at arbitrary locations on the structure combining computational models and

limited physical sensor information. The use of multi-metric measurements is

advocated to improve the accuracy of the approach. A numerical example is provided to

illustrate the proposed fatigue assessment framework.



16

Integral Utilization of Multi-types of Structural Vibration Signals for

Damage Identification Based on the “Weak” Formulation of

Pseudo-Excitation (PE) Technique: Virtual Vibration Deflection (VVD)

Li Cheng1, 2, a, Zhongqing Su1, 2, b and Hao Xu1, c

1The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China

2The Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong

[email protected], [email protected], [email protected]

Abstract: A damage identification method relying on the integral utilization of multiple

types of structural vibration signals was developed in this study. The principle of the

method was established based on a “weak” formulation of the recently developed

Pseudo-Excitation (PE) technique. The “weak” formulation is capable of integrating

derivatives of structural vibration deflections, of different orders, in its various

expanded expressions, and these derivatives are directly linked with different types of

vibration signals which can be measured experimentally, such as vibration

displacements, angles of rotations and dynamic strains, etc. As a representative

application, densely measured vibration displacements and sparsely measured dynamic

strains were integrated through the method defined as virtual vibration defection

(VVD), aimed at detecting small damage in beam-like structure. Numerical study was

firstly conducted and an experiment was carried out subsequently to identify

multi-cracks in an aluminum beam-like structure. It was shown that at the cost of

additional measurements of dynamic strains at several points along the inspected

structure, prominently enhanced noise immunity and detection accuracy have been

gained by VVD, compared with the detection results constructed based on the original

formulation of PE technique using purely of vibration displacement measurement.

(Supported by National Natural Science Foundation of China for a research grant, Grant

No.: 11272272)



17

Planetary Gearbox Diagnosis Based on an Improved Fast Kurtogram

Method

Jing Lin1, a, Xiaoqiang Xu2, b and Ming Zhao2, c

1State Key Laboratory for Manufacturing System Engineering, Xi’an Jiaotong University, Xi’an,

China

2School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China


Abstract: Planetary gearbox is a key part in a wind turbine. Vibration and acoustic

measurement are widely used for condition monitoring and fault diagnosis for planetary

gearboxes. However, diagnosis for planetary still remains difficult due to the complex

modulation of gear mesh, planetary gear orbital rotation and transmission path

function. Moreover, signals are easily contaminated by extraneous impacts in practice.

Fast kurtogram method based on spectral kurtosis (SK) has been proved an efficient tool

for extracting fault impulses in the diagnosis of rolling element bearings (REB) and

gearboxes. Although the optimal narrowband indicated by fast kurtogram is accurate

and effective for the simulated or experimental signals, one serious drawback of fast

kurtogram is that it is very sensitive to large random impacts which are frequently

encountered in industrial applications. It is shown in this paper that the narrowband

with maximum kurtosis is always associated with large interferential impacts, rather

than the real fault. An improved fast kurtogram method is proposed to avoid this

limitation, which takes the periodicity of envelope of filtered signals into consideration

and sets harmonic to noise ratio (HNR) as the parameter to estimate periodicity of

signal. The novel method computes the HNR of envelope of filtered signals before

computing their kurtosis. By integrating HNR into fast kurtogram, the interference

coming from aperiodic components can be avoided effectively. In the experiment, a

planetary gear with chip fault is used to test the effectiveness of the novel method. The

result shows that the novel method for fault detection is robust to the interference

from random impulses and is especially suitable for the signal processing of acoustic

signal which is inevitably affected by environmental noise in industrial applications.

mailto:xuxiaoqiang@



18

Particle Filter Based Structural Crack Propagation Prognosis

Shenfang Yuan1, a, Weibo Yang1, Jian Chen1, Lei Qiu1, b, Hanfei Mei1

1The State Key Lab of Mechanics and Control of Mechanical Structures, Nanjing University of

Aeronautics and Astronautics, Nanjing, China.


Abstract: Crack propagation prognosis is one of the key technologies in the area of

engineering structural failure prognosis and health management. This presentation

proposes a particle filter method combined with the Lamb wave based structural health

monitoring method for fatigue crack propagation prognosis. Paris rule is adopted as the

damage evolution state model. The measurement model is obtained using damage

index extracted from active Lamb wave approach. The crack length is predicted

efficiently using particle filter technique. Experiments are performed to verify the

effective of the proposed method. The experimental results show that the error of crack

length predicted after 20000 load cycles is less than 2%. Further researches on this

method are also discussed in this presentation.



19

Fault Diagnostics of the Planetary Gear System of Wind Turbine

Fulei Chu1, a, Yong Gui1, b and Qinkai Han1, c

1Department of Mechanical Engineering, Tsinghua University, Beijing, China


Abstract: The planetary gearbox is a fault-prone component of the drivetrains in large

wind turbines. Gear faults could lead to severe accidents to the whole wind turbine

system if detected not promptly. Thus, in this presentation, a dynamic model is built to

obtain the vibration responses of a planetary gear system with tooth faults and

with/without time-varying speeds. These signals are analyzed by different methods and

the fault characteristics of the system are obtained. The simulation results are verified

by the dynamic experiments of a planetary gear-box test rig.



20

Health Monitoring of Wind Turbine Rotor Blades

U. Gabbert1, a, S. Duczek1,b

1Otto von Guericke University Magdeburg, Magdeburg, Germany


Abstract: At first an overview of monitoring technologies for wind turbines in Germany

is presented, where a special focus is on rotor blade inspections. In the second part

ultrasonic wave based methods are discussed from an experimental as well as a

computational point of view. The measurements are performed with help of a laser

scanning vibrometer. For the numerical analysis special higher order finite elements as

well as finite cell methods are presented and applied. These new methods, recently

developed by the authors, have great advantageous for ultrasonic wave based damage

detection and design purposes.



21

Numerical Simulation and Applications of Lamb Waves in On-line

Monitoring and Off-line Evaluation Techniques

Ning Hu1, a and Yaolu Liu2, b

1College of Aerospace Engineering, Chongqing University, China

2Department of Mechanical Engineering, Chiba University, Japan


Abstract: In this work, first, we describe some new numerical methods to effectively

simulate the Lamb wave propagation in plate or shell like structures. The interaction of

Lamb waves with various damages in structures has been studied in detail, and the

provided data are very helpful for the application of Lamb waves in on-line structural

health monitoring and off-line non-destructive evaluation. Second, we report our

several works on the on-line structural health monitoring using PZT sensor/actuator

network. These techniques which can monitor the damage position and size will be

explained in detail. Some of them employ the knowledge obtained from the previous

numerical studies about the interaction between Lamb waves and various damages.

Third, we describe two off-line techniques for non-destructive evaluation of materials

and structural components. One is a visualization technique of wave propagation, which

can remarkably enhance the reliability of non-destructive evaluations. Furthermore, a

concept of “wave energy flow” is proposed to be integrated into the wave propagation

visualization technique to evaluate the damage shape and damage size. The second

technique is a Lamb wave based scanning method, which can evaluate various damages

quickly with very small amount of scanning data.



22

Wind Turbine Gearbox Fault Diagnosis Using Single Channel Stationary

Subspace Analysis

Ruqiang Yan1, a and Yuning Qian1, b

1School of Instrument Science and Engineering, Southeast University, Nanjing, China


Abstract: This paper presents a new signal decomposition approach, based on

continuous wavelet transform (CWT) and stationary subspace analysis (SSA), for wind

turbine gearbox fault diagnosis. The SSA is a blind source separation technique that can

extract stationary and non-stationary source components from multi-dimensional

signals without the need for independency and prior information of the source signals.

Multi-scale analysis ability inherent in CWT allows for decomposing one dimensional

signal into multi-dimensional signals, which can be naturally used as inputs to SSA to

obtain the stationary parts and non-stationary parts of the original signal. Subsequently,

the selected non-stationary component is analyzed by the envelope spectrum to

identify potential fault-related characteristic frequency. Experimental studies from a

real wind turbine gearbox test have verified the effectiveness of the presented method.



23

Smart Sensing in the Light of Non-Destructive Testing and Structural

Health Monitoring

Gerd Dobmann1, a, Christian Boller1, b

1Chair of NDT and Quality Assurance, Saar-University, Saarbrücken, Germany

[email protected]

Abstract: Non-destructive testing (NDT) is around as a discipline for more than half of a

century now. It has become a means to qualify materials and structures as well as to

assess those structures along their operational life through application of physical

principles and realized through specific sensors and sensor signal processing algorithms

which lead to visualization of a material’s and structure’s condition in a way that this

may be seen at even microscopic scale and 3D. Different of those physical principles are

applied where acoustics and electromagnetics play a very significant role. NDT is

specifically performed at damage critical locations and at defined intervals in time

mainly through a hand held but possibly also an automated inspection process.

However those locations to be inspected are quite hidden or generally difficult to access

and may therefore lead to a time and hence cost consuming process. A means to

alleviate those disadvantages has emerged with advanced sensor and materials

technologies which allow sensors, or better sensor systems, to be adapted or generally

integrated onto or into a structural component allowing NDT to become an integral part

of the component. This is what is considered today to be structural health monitoring

(SHM). Many of the SHM systems can therefore be seen as derivatives of NDT

technology developed in a classical way.

The presentation will make reference to a variety of vibrations and elastic waves based

principles used such as classical modal analysis, acoustic emission, phased array

ultrasonics and guided waves as well as electromagnetic principles considering

electromagnetic impedance, permeability, Barkhausen noise and higher harmonics

analysis including advanced sensor signal processing. Applications will include metallic

as well as composite structures. A major emphasis will be placed on damage tolerance

principles and what rewards those could provide in terms of life cycle management

when implementing an SHM system.



24

Monitoring of Wind Farms and Case Studies

Guiyun Tian1, a

1 School of Electronic Science and Technology, Newcastle University, UK

[email protected]

Abstract: This talk reviews condition and structural health monitoring of wind farms,

offshore in particular. Research challenges and opportunities are identified. Based on

previous work of non-destructive testing and evaluation (NDT & E), structural health

monitoring (SHM), recent research progress on inspection and monitoring of turbine

blades, gear fatigues, generators and corrosion are reported and discussed. Through the

investigation of case studies, merits of proposed research have been evaluated. Future

work of electromagnetic sensing and imaging for life cycle assessment and precursors

for wind farms is derived and discussed. Potential follow-up activities of HEMOW are

also outlined.



25

Damage Identification Using Guided Waves: from Linear to Nonlinear,

from Macroscopic to Mesoscopic, from Distributed to Dispersed Sensing

Zhongqing Su1, a

1The Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong

SAR, China

[email protected]

Abstract: Current structural health monitoring (SHM) techniques making use of guided

waves are confronted by a few of inherent bottlenecks including particularly the

restricted information that conventional linear signal features can convey, the

inefficiency in detecting small-scale damage (e.g., fatigue cracks), and the dilemma in

striking a compromise between “sensing cost” and “sensing effectiveness”. All these

have created a vast barrier towards the real-world applications of SHM techniques

developed in laboratories. Motivated by such recognition, this talk summarizes the

efforts dedicated by the research team led by the author over the years, with a hope to

circumvent these bottlenecks, partially if not completely.



26

Challenges for Condition Monitoring of Transmission Systems

Jishan Zhang1, a, Brian Shaw1, b and Robert Lambert1, c

1Design Unit, School of Mechanical and Systems Engineering, Newcastle University, UK


Abstract: An overview of condition monitoring research and development work that

Design Unit has been undertaking over recent few years will be presented. The research

is driven by a need to assure the integrity of running transmission systems and to give

early warning of developing issues that could lead to catastrophic failure thus allowing

early intervention limiting ultimate damage and associated cost and downtime (e.g. for

off-shore wind turbine applications). The experimental results presented are mainly

from gear testing performed under controlled conditions where failure modes were

able to be closely monitored with conventional inspection methods and correlated with

applied condition monitoring approaches. The main techniques investigated include the

monitoring of vibration, acoustic emission, oil debris sensing, gear micropitting, gear

macropitting, gear scuffing, and efficiency of the gear transmission. Challenges

associated with above-mentioned techniques will be highlighted. A brief description will

also be given of a newly developed wind turbine planet bearing test rig that is now

being used to investigate how condition monitoring can be applied to this application.



27

A New Physical Concept of Multiscale Shear-Strain Gradient for

Identifying Delamination in Composite Structures in Noisy Conditions

Maosen Cao1, a, W. Ostachowicz2, b, M. Radzienski2, c and Wei Xu1, d

1Department of Engineering Mechanics, Hohai University, Nanjing, China

2Institute of Fluid Flow Machinery, Polish Academy of Sciences, Gdansk, Poland

[email protected], [email protected],[email protected] [email protected]

Abstract: Delamination is a typical failure mode in composite laminates. To detect

delamination, a new physical concept of a multiscale shear-strain gradient (MSG) is

formulated from a vibrational modeshape of a Kirchhoff plate. The features of the MSG

can be described as follows: (1) It characterizes delamination with an explicit physical

implication and strong robustness to noise, superior to most existing methods that rely

solely on signal processing; (2) It is related only to the shear strain and not to the elastic

and geometrical parameters or a physical model of the laminate being inspected, and is

therefore well suited to the identification of delamination in any thin-plate structure;

and (3) It defies the traditional understanding that vibrational features are not effective

for locating delamination in composite structures. Experimental results for the diagnosis

of delaminations induced by thermal effect show the high accuracy and reliability of the

MSG in localizing slight delamination.



28

Loading Independent Wind Turbine Condition Monitoring: A Baseline

Model Approach

Ziqiang Lang1, a

1 Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield,

UK

[email protected]

Abstract: Traditionally, wind turbine condition monitoring (CM) is conducted via fitting

sensors inside wind turbines and analyzing features of sensor signals using appropriate

signal processing techniques to examine wind turbines’ operating conditions and health

status. However, the signal only based CM often cannot distinguish the changes in

sensor signals due to different loading conditions such as, e.g., different wind speeds

and turbine power outputs etc, from the changes induced by faults or damage in wind

turbine components or systems. In order to resolve this problem, a baseline model

approach is developed in the present study. The basic idea is to build a baseline model

representing the relationship between the features of sensor signals and wind speed

and turbine power output etc turbine loading condition dependent parameters. Then, a

tolerance range of the signal feature's deviation from what is evaluated by the baseline

model is determined. Moreover, the CM of wind turbine is implemented by examining

whether the deviation of the observed signal feature from what is predicted by the

baseline model is within this tolerance range or not, so as to determine the turbine

system or component’s working conditions with the effects of some significant loading

conditions being taken into account. The application of this approach to the analysis of

field data collected over three different months from an operating wind turbine has

been studied. The results verify the effectiveness and demonstrate the potential

significance of the new technique in practical engineering applications.



29

Wind Turbine Blade Monitoring Using Noncontact Sensing Techniques

Hoon Sohn1, a, Byeong Jin Park1, b, Peipei Liu1, c

1Civil and Environmental Engineering Department, KAIST, Daejeon, South Korea


Abstract: Wind energy is emerging as one of clean energy sources for 21st century, and

there are a large number of wind turbine systems already in operation or under

construction. Current research on wind turbine systems focus on design and fabrication,

but it is expected that monitoring and maintenance will soon become an important

issue. In response to these expected demands for monitoring, there are a large number

of ongoing researches for developing monitoring systems for wind turbine systems.

When it comes to wind blades, the majority of the current researches propose

installation of discrete sensors such as accelerometers or fiber optic sensors inside the

blades. However, because of the rotation nature of the blades, it becomes a daunting

task to install and wire all these sensors through the blades and get signals out. In this

study, we take a rather different approach. We intend to detect incipient micro cracks

and millimeter range delamination using noncontact sensing techniques such as laser

ultrasonics and laser lock-in thermography. Preliminary test results performed on actual

10kW wind turbine blades will be presented.



30

Key Mechanical Issues of Large Scale Wind Turbines - A Project Funded by

the National Basic Research Program

Tongguang Wang1, a

1Nanjing University of Aeronautics and Astronautics, Nanjing, China

[email protected]

Abstract: A very brief introduction is given in this report to the project “Key Mechanical

Issues of Large Scale Wind Turbines” funded by the National Basic Research Program. To

meet the national strategic requirements in wind energy, this project focuses on the

following three key issues in large scale wind turbine mechanics: (1) wind turbine 3D

rotational aerodynamics in complicated circumstances, (2) wind turbine aeroelasticity

and hydrodynamics and their coupling effects in complicated circumstances, and (3)

wind turbine support and foundation structural dynamics in complicated offshore

circumstances. Six workpackages are included in this project: (1) Study of Unsteady

Aerodynamic Mechanism and High-Accuracy Numerical Simulation for Wind Turbine; (2)

Study of the Aeroelastic Mechanism and Structural Dynamics of Nonlinear Large

Deformation of Wind Turbine; (3) Study of Offshore Floating Wind Turbine Dynamics

under Wind, Ocean Wave, and Ocean Current; (4) Study of Dynamics and Safety for

Bottom-Fixed Offshore Wind Turbine Foundation; (5) Experimental Study of Wind

Turbine Flow Structure and Aerodynamics-Hydrodynamics-Structure Coupling; (6) Study

of Comprehensive Mechanical Analysis and Integrated Optimization of

High-Performance Wind Turbine.




31

Condition Monitoring for Reliable and Predicable Operation of Wind

Turbines

Xiandong Ma1, a

1Engineering Department, Lancaster University, Lancaster LA1 4YR, UK

[email protected]

Abstract: Condition monitoring in this context is taken to mean the use of advanced

technologies in order to determine the condition of wind turbines, and to analyse,

diagnose and predict potential failures. Monitoring and diagnostics of wind turbines and

their subsystems will play an increasing role in their competitive operation.

Consolidated knowledge about their past and current conditions can be used to

improve performance, efficiency, reliability and availability, thus enabling the optimal

scheduling of maintenance activities and minimizing the risk of costly unexpected

failure of the turbines during their service life. However, measurement signals are often

non-stationary, stochastic and even more complex in a harsh environment like offshore

wind farms. In real terms, the measured signals when a fault is developing are usually

small in magnitude but may indicate the start of a significant failure. Furthermore, there

are large volumes of data that need to be processed and transmitted for further

analysis, especially for continuous online monitoring. Minimising the number of sensors

whilst still maintaining a sufficient number to assess the system’s conditions is a critical

concern for condition monitoring. This talk will describe the journey in the development

of smart condition monitoring techniques and the associated instruments to address

the above challenges at Lancaster University, UK.



32

Mode-Adaptive Decentralized Control for Renewable DC Microgrid with

Enhanced Reliability and Flexibility

Wuhua Li1, a, Yunjie Gu1 and Xiangning He1, b

1College of Electrical Engineering, Zhejiang University, Hangzhou, China

[email protected] and [email protected]

Abstract: The microgrid provides a new paradigm for the power generation and delivery,

and is taken as a promising building block for the future smart power system. The

dc-based power systems driven by power electronic converters are envisaged as an

enabling technology for the microgrid concept. A mode-adaptive decentralized control

strategy is proposed for the power management of a dc microgrid with multiple

renewable distributed generators and energy storage systems. In the presented solution,

the dc bus voltage signal is used not only to enable power sharing among different

sources, but also to designate microgrid operation modes and facilitate seamless mode

transitions. With this mode-adaptive operation mechanism, a greater control freedom

can be achieved than the conventional dc voltage droop control scheme. More

importantly, this approach features fully self-disciplined regulation of distributed

converters without an extra control center or communication link. Therefore, both

reliability and flexibility can be enhanced. Finally, the effectiveness of the proposed

technique is verified experimentally based on a composite dc microgrid test system.



33

MAP AND CONTACT INFORMATION

Contact

Qiang Wang

Telephone: +86 189 5204 6906, Email: [email protected]

Ruipeng Guo

Telephone: +86 139 5168 9056, Email: [email protected]

Shenfang Yuan

Telephone: +86 25 84893460, Email: [email protected]

Seminar venue

Room 506, A9 Building, Nanjing University of Aeronautics and Astronautics

Nanjing, China

NUAA Campus

Grand Metropark Hotel Nanjing

Zhongshan East Road

Yudao Street

A18 Building


West Gate

North Gate




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