Projects per year
Personal profile
Research interests
My primary focus in research has revolved around several key areas. These include the condition monitoring of electric motors, as well as the diagnosis and prognosis of faults in rotational machines such as helicopter gearboxes and compressors. Another significant aspect of my research has been in the field of asset management. Additionally, I have explored the application of artificial intelligence (AI) specifically in the realm of power electronics, encompassing applications in both electrical and mechanical systems.
Education/Academic qualification
Electrical Motor Condition Monitoring, Doctor of Engineering, Induction motor parameters estimation and faults diagnosis using optimisation algorithms, University of Adelaide
23 Aug 2010 → 12 Dec 2014
Award Date: 12 Dec 2014
Electrical Engineering, Master of Science, Induction motor fault diagnostics using global optimization algorithm
1 Feb 2009 → 20 Aug 2010
Award Date: 20 Aug 2010
Electrical Engineering, Master of Engineering, Estimation of DC offset parameters using global optimization technique
1 Feb 2007 → 19 Dec 2008
Award Date: 18 Jan 2008
External positions
Visiting Researcher, University of Huddersfield
1 Jan 2024 → …
Visiting Researcher, University of Central Florida
25 Mar 2018 → 24 Mar 2019
Keywords
- Induction Machine
- Condition Monitoring
- Parameters Estimation
- Fault diagnosis and prognosis
- global optimisation algorithms
- Artificial Intelligence
- Power Electronics
- Helicopter Main Gearbox
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
-
SDG 4 Quality Education -
SDG 7 Affordable and Clean Energy -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities -
SDG 13 Climate Action
Fingerprint
Dive into the research topics where Fang Duan is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
AI-Power: Artificial Intelligence for Next Generation Power Electronics
Duan, F. (CoPI)
1/09/21 → 31/08/27
Project: Research council
-
Physics-Informed Data-Driven Methods for Condition Monitoring of Wind Turbine Generators
Duan, F. (PI)
1/09/21 → 31/08/23
Project: UK charity
Research output
-
Application of Digital Twin Technology in Asset Management: A Comprehensive Literature Review
Huang, C., Duan, F., Graja, O., Wang, H., Yang, W. & Cattley, R., 2 Jan 2026, (E-pub ahead of print) Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences, UNIfied 2025 - Volume 1. Wei, K., Yang, W., Dai, J. & Chen, B. (eds.). Cham, Switzerland: Springer, p. 471-481 11 p. (Mechanisms and Machine Science; vol. 188).Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding
-
Balancing performance and complexity: A review of structural control for wind turbine blades and towers
Fakhry, P., Duan, F., Salem, S. & Tokhi, M. O., 19 Mar 2026, (E-pub ahead of print) In: Journal of Low Frequency Noise Vibration and Active Control.Research output: Contribution to journal › Article › peer-review
Open Access1 Link opens in a new tab Citation (SciVal) -
Machine Learning-Enabled Virtual Sensors for Wind Turbines: Technologies, Challenges, and Pathways to Digitization
Bibi, A., Graja, O., Duan, F. & Yang, W., 2 Jan 2026, Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences, UNIfied 2025 - Volume 1. Wei, K., Yang, W., Chen, B. & Dai, J. (eds.). Cham, Switzerland: Springer, p. 1151-1162 12 p. (Mechanisms and Machine Science; vol. 188).Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding
-
XGBoost-Guided Spectrogram Pruning with SE-Augmented Residual CNN for Wind Turbine Gearbox Fault Diagnosis Under Unsteady Conditions
Huang, C., Bibi, A., Yang, W., Duan, F., Miao, H. & Mishra, R., 2 Jul 2026, In: Energies. 19, 13, 29 p., 3153.Research output: Contribution to journal › Article › peer-review
Open Access -
Fault Diagnosis of Wind Turbine Drivetrains Using XGBoost-Assisted Discriminative Frequency Band Identification and a CNN–Transformer Network
Huang, C., Yang, W., Graja, O., Duan, F., Wei, Z. & Zhang, L., 1 Dec 2025, In: Applied Sciences. 15, 23, 12726.Research output: Contribution to journal › Article › peer-review
Open Access1 Link opens in a new tab Citation (SciVal)