报告题目:Deep Fault Diagnosis and Explainability for Rotary Machines
报告人:Hamid Reza Karimi 教授(米兰理工大学)
报告时间:2023年7月27日下午3:00
报告地点:物联网工程学院C317
摘要:The objective of this speech is to address some challenges and recent results on fault diagnosis of mechanical systems, with a focus on advanced artificial intelligence algorithms developments. Specifically, different deep learning models such as deep supervised, unsupervised and reinforcement learning algorithms are examined to establish a trustworthy intelligence fault diagnosis model. The talk will be concluded with some results on the development of explainable intelligence fault diagnosis framework based on post-hoc visualization methods.