Intelligent Maintenance and Fault Diagnosis of Mobility Equipment

Dear Colleagues,

In recent years, mobility equipment has seen rapid technological advancements, making maintenance and fault diagnosis increasingly complex. Integrating intelligent systems and sensing technologies has brought significant improvements in mobility equipment maintenance and fault diagnosis.

This Special Issue invites original research that addresses key challenges in developing autonomous maintenance frameworks to enhance mobility equipment's reliability, safety, and performance. The aim is to explore the latest techniques in data-driven maintenance frameworks, predictive diagnostics, real-time fault detection, and fault response strategies using advanced sensors, cyber-physical systems, and machine learning models.

Topics of interest include, but are not limited to:

• Next-generation sensor technologies;
• Vibration and acoustic analysis;
• Signal processing techniques;
• Real-time fault detection;
• Model-based diagnosis;
• Fault-tolerant control strategies;
• Intelligent control algorithms for vibration and noise;
• Predictive maintenance;
• Multimodal data and information fusion and transfer;
• Other topics related to mobility equipment for fault diagnosis.

Prof. Dr. Hongtao Xue
Prof. Dr. Peng Chen
Dr. Zhiqiang Liao
Guest Editors

Manuscript Submission Information

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