1.      Lei Mao*, Kai He, Lisa Jackson, Qiang Wu. Application of artificial neural networks in polymer electrolyte membrane fuel cell system prognostics. Natural-inspired Computing Paradigms in Systems: Reliability, Availability, Maintainability, Safety and Cost (RAMS+C). 2021, ELSEVIER.

2.      Y.Y.A. Abuker, Z. Liu, L. Mao*. Fault classification of polymer electrolyte membrane fuel cell system based on empirical mode decomposition. Advances in Condition Monitoring and Structural Health Monitoring, 2020, Springer Nature.

3.      Z. Liu, W. Pan, Y.Y.A. Abuker, L. Mao* (2020). A novel method of PEM fuel cell fault diagnosis based on signal-to-image conversion. Advances in Condition Monitoring and Structural Health Monitoring, 2020, Springer Nature.

4.      Mao, L. *, Goodall, P., Jackson, L., West, A. (2018). Enhanced condition monitoring of the machining process using wavelet packet transform, 2018, Safety and Reliability – Safe Societies in a Changing World, 2018, 1477-1483, CRC Press, Taylor & Francis Group, London, ISBN 9780815386827.

5.      Vasilyev, A., Andrews, J., Mao, L., Jackson, L.M. (2018). The use of bond graph modelling in polymer electrolyte membrane fuel cell fault diagnosis, 2018, Safety and Reliability – Safe Societies in a Changing World, 2018, 1545-1551, CRC Press, Taylor & Francis Group, London, ISBN 9780815386827.