Special Track on Intelligent Maintenance with AI


Description


Intelligent maintenance (IM) is a strategy (action or methodology) that uses signal processing, data analysis, and decision support tools to predict and prevent potential failures with the knowledge of the principle of machines or systems. The recent advancements in computer science and technology, information theory, and electronics have facilitated the design and implementation of such IM systems. With the rapid development of artificial intelligence (AI) technology, intelligent maintenance has entered a new stage. In this special track, we would like to share our work on this topic, discuss the role of AI in IM, and promote the integration of AI and IM.

Track Chair


Xiaohang Jin's avatar
Xiaohang Jin

Zhejiang University of Technology, China

Invited Speakers (Alphabetical Order)


Zhilin Dong's avatar
Zhilin Dong

Zhejiang Normal University, China

Wei Fan's avatar
Wei Fan

Jiangsu University, China

Guanqi Fang's avatar
Guanqi Fang

Zhejiang Gongshang University, China

Wenpo Huang's avatar
Wenpo Huang

Hangzhou Dianzi University, China

Ziqian Kong's avatar
Ziqian Kong

Hangzhou Dianzi University, China

Xiuli Wang's avatar
Xiuli Wang

Zhejiang University of Technology, China

Name Title
Xiaohang Jin Prior Knowledge Embedded Networks for Condition Monitoring of Wind Turbine
Zhilin Dong Intelligent Bearing Fault Diagnosis Framework Based on EWT and 1D-ISACNN
Wei Fan Noise Resistant Correlation Method for Bearing Health Management
Guanqi Fang Exploring Initiation-Growth Correlation in Accelerated Degradation Testing Data
Wenpo Huang Statistical Test-based Adversarial Client Detection in Federated Learning under Poisoning Attacks
Ziqian Kong Remaining Useful Life Prediction Based on Spatio-temporal Graph Neural Network
Xiuli Wang Optimized Test Selection for Efficient Fault Detection in Complex Systems