报告人：Prof. Dr. CHU Ning
报告时间：2024年11月8日下午15:30-16:30
报告地点：机械楼D526
报告摘要：
The complex problem of localizing sound sources with different motion patterns is addressed in this study, especially on the identification and separation of rotating and static sound sources. An innovative method is proposed that integrates Modal Combined Beamforming (MCB) with the equivalent source approach, leveraging the unique spatio-temporal properties of rotating and static sound sources. And a complete propagation matrix is constructed, then the Rotating-Static Sources Power Propagation (R-S2P) model is introduced to the intricate interactions between the sound sources and their environment. This R-S2P model is effectively solved by using the Least Absolute Shrinkage and Selection Operator (LASSO) within an Alternating Direction Method of Multipliers (ADMM) algorithm. The effectiveness of this method is rigorously tested through extensive simulations and real-world experiments.
个人简介：
Dr. Chu Ning, professorate engineer, IEEE senior member, and vice-chairman of the Zhejiang Acoustic Society; Chief researcher with Zhejiang Shangfeng Special Blower Company Ltd., China. He received B.S. degree in information engineering from the National University of Defense Technology, Changsha, China in 2006, and the M.S. and Ph.D. in automatic, signal image processing from the Paris-Saclay University, France in 2010 and 2014, respectively, and the postdoc at EPFL Switzerland.
His research interests are acoustic source imaging, infrared detection and Bayesian inference in machine fault prognosis. He has invented “Industrial Lung System” for green ventilation equipment, reported by CCTV2 in 2022, selected into the list of Zhejiang industrial Internet platform, and best cases of China intelligent manufacturing. In recent 5 years, he published more than 24 top journal papers and own 31 China invention patents, presided 3 national and provincial research projects.
