Tianran Lin, PHD, Professor

Qingdao University of Technology

Title: Monitoring and Fault Detection of Rotating Machinery under Complex Operating Conditions

Abstract: Key power transmission machinery, such as those employed in rail transportation, aerospace, and mining, are subjected to prolonged operation under complex load and/or variable speed conditions. The critical mechanical components in the power transmission train, including gears and bearings, are particularly vulnerable due to mechanical fatigue under such operating condition which can lead to progressive damage accumulation or sudden mechanical failures. Several advanced condition monitoring and signal processing techniques have been developed in order to effectively capture the instantaneous health condition change of these components in real time to prevent a dire consequence. Signal separation and de-noising techniques, time-frequency analysis techniques are the most frequently employed tools for an early fault detection under complicate mechanical operating conditions. This talk summarizes the recent advancements in signal processing-based fault diagnosis techniques for rotating machinery operating under varying load/speed condition and noisy environment. Practical cases are also presented in this talk to highlight the essence of these techniques in ensuring the reliability and safety operation of critical rotating machinery as well as the potential in future industrial applications. 

Biography:Tianran Lin, Taishan Scholar, Professor of Qingdao University of Science and Technology, Ph.D. He graduated from the University of Western Australia in 2006 with a Ph.D. degree in Philosophy. He then worked at the Queensland University of Technology (QUT) until 2015 when he joined Qingdao University of Technology (QUT) full-time through the Shandong Taishan Scholar Talent Introduction Program. His research interests include: vibration and noise analysis and control (including theoretical analysis and experimental techniques), finite element and boundary element numerical simulation analysis of rotating machinery monitoring and fault diagnosis techniques. He has proposed a number of new signal processing methods, including sampling frequency reduction, linearization of acoustic emission signals, half-blind signal separation method, etc., and solved some of the problems often encountered in machinery monitoring. He has published a series of papers in international authoritative core SCI journals mainly as the first and corresponding author.