Long Zhang

Dr Long Zhang is a Senior Lecturer in the Department of Electrical and Electronic Engineering at The University of Manchester. His research focuses on data-driven intelligence and control, including machine and statistical learning, neural networks, system identification, and their applications in smart renewable energy, robotics, and transportation. He is particularly interested in wind turbine condition monitoring and fault diagnosis. He is the founding director of the first industrial-scale wind turbine pitch bearing and blade laboratory at the University of Manchester and the director of the MSc course in Advanced Control and System Engineering. His research has been supported by EPSRC, Innovate UK, and industrial partners, with over £2.5m in funding. He supervises a range of undergraduate, master's, and PhD students.

Long Zhang is a researcher at the University of Manchester with expertise in Machine learning, System Identification, Advanced Control, Condition Monitoring, and Wind Energy. His work focuses on fault diagnosis and condition monitoring of wind turbine components, including bearings and blades, using advanced signal processing techniques such as empirical wavelet thresholding, Bayesian methods, and nonlinear filters. Zhang also explores machine learning applications for maintenance management and nonlinear system identification, emphasizing the integration of artificial intelligence in renewable energy systems. His research contributes to improving the reliability and efficiency of wind energy technologies through innovative diagnostic and predictive maintenance strategies.