Dr Fang Duan

Dr Fang Duan, LSBU

Lecturer; Director of Intelligent Condition Monitoring and Asset Management Research Centre

  • Email:
  • Telephone:
    020 7815 7578
  • School/Division:
    Engineering / Electrical and Electronic Engineering
 

Dr Fang Duan is a Lecturer in School of Engineering as well as the Director of Intelligent Condition Monitoring and Asset Management Research Centre at London South Bank University.

Fang Duan received a Bachelor’s degree in telecommunication engineering from Southwest Jiaotong University, Chengdu, China in 2005 and a Masters and PhD degree in electrical engineering from the University of Adelaide, Australia in 2008 and 2015 respectively. She is currently a Lecturer in the School of Engineering as well as the Director of Intelligent Condition Monitoring and Asset Management Research Centre at London South Bank University. Her research interests include condition monitoring, fault diagnosis and prognosis, parameter estimation, global optimisation and asset management.

Fang’s experience in university teaching started in 2012 when she worked as a Teaching Assistant at University of Adelaide. Her role was to lead the tutorial classes, experiment and workshops.

At London South Bank University, Fang has taught six undergraduate courses since 2016. She had valuable chances to learn from experienced lecturers and different ways to keep the attention and motivation of students in different sized classes. In many of these classes, the knowledge levels and cultural background of students varied, which is an important aspect considered when course
materials are prepared and discussed.

Fang’s experience in university teaching started in 2012 when she worked as a Teaching Assistant at University of Adelaide. Her role was to lead the tutorial classes, experiment and workshops.

At London South Bank University, Fang has taught six undergraduate courses since 2016. She had valuable chances to learn from experienced lecturers and different ways to keep the attention and motivation of students in different sized classes. In many of these classes, the knowledge levels and cultural background of students varied, which is an important aspect considered when course
materials are prepared and discussed.

  • Condition monitoring and asset management of electrical and mechanical systems
  • Advanced algorithms for signal processing and data analytics for diagnosis and prognosis
  • Collaborative design and technical integration in industry-university projects
  • Multi-disciplinary expertise in electrical engineering, asset management, reliability engineering, and telecommunication engineering
  • Project management for multi-national projects, systems engineering concepts

Most recent publications

Loukopoulos, P and Zolkiewski, G and Bennet, I and Sampath, S and Pilidis, P and Duan, F and Sattar, TP and Mba, D Reciprocating compressor prognostics of an instantaneous failure mode utilising temperature only measurements. Applied Acoustics, DOI 10.1016/j.apacoust.2017.12.003

Duan, F and Xiaochuan, L and Tariq, S and Ian, B and David, M Canonical Variable Analysis for Fault Detection, System Identification and Performance Estimation. Lecture Notes in Mechanical Engineering, 3. 247-257.

Xiaochuan, L and Duan, F and Bennett, I and Mba, D Combining Canonical Variate Analysis, Probability Approach and Support Vector Regression for Failure Time Prediction. In: 2017 International Conference on Sensing, Diagnostics, Prognostics and Control, 16th - 18th August 2017, Shangai, China.

Duan, F and Corsar, M and Zhou, L and Mba, D Using independent component analysis scheme for helicopter main gearbox bearing defect identification. In: 2017 IEEE International Conference on Prognostics and Health Management (ICPHM), 19th - 21st June 2017, Texas, USA.

Zhou, L and Duan, F and Mba, D and Faris, E A comparative study of helicopter planetary bearing diagnosis with vibration and acoustic emission data. In: 2017 IEEE International Conference on Prognostics and Health Management (ICPHM), 19-21 June 2017, Dallas, TX, USA.

Loukopoulos, P and Sampath, S and Plidis, P and Zolkiewski, G and Bennett, I and Duan, F and Sattar, TP and Mba, D Reciprocating compressor prognostics. In: CMSM 2017 7th International Congress Design and Modelling of Mechanical Systems, 27 - 29 March 2017, Hammamet, Tunisia.

Li, X and Duan, F and Mba, D and Bennett, I Multidimensional prognostics for rotating machinery: A review. Advances in Mechanical Engineering, 9. DOI 10.1177/1687814016685004

Zhou, L and Duan, F and Mba, D Wireless Acoustic Emission Transmission System Designed for Fault Detection of Rotating Machine. Lecture Notes in Networks and Systems, 4. 201-207. DOI 10.1007/978-3-319-48725-0_19

Loukopoulos, P and Sampath, S and Pilidis, P and Zolkiewski, G and Bennett, I and Duan, F and Mba, D Dealing with missing data for prognostic purposes. In: Prognostics and System Health Management Conference, 19th October - 21 October 2016, Chengdu, China.

Zhou, L and Duan, F and Mba, D and Corsar, M and Greaves, M and Sampath, S and Elasha, F Helicopter gearbox bearing fault detection using separation techniques and envelope analysis. In: Prognostics and System Health Management Conference (PHM-Chengdu), 2016, 19th - 21st October 2016, Chengdu, China.

More publications at LSBU Research Open
  • IEEE Member
  • Reviewer of IEEE Transactions on Industrial Electronics
  • Reviewer of IEEE Transactions on Energy Conversion
 
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