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2023年7月27日学术报告

发布时间 :2023-07-26 来源:   万海英 已浏览:

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.

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