IWACCE-MLFDPIS’24

Machine Learning Based Fault Diagnosis and Prognosis Methods for Industrial Systems

The aim of this special section is to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of fault diagnosis and prognosis technology and understand how machine learning strategy can influence it. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.

IWACCE-MLFDPIS’24 Session Chair

Dr. Zhaohua Liu, Professor at Hunan University of Science and Technology, China.

Research Interests: Intelligent monitoring and control of new energy equipment, wind power artificial intelligence, artificial intelligence and machine learning, intelligent fault diagnosis