Signal Processing and Artificial Intelligence Technology for High-End Equipment Fault Diagnosis

Dear Colleagues,

With the enrichment of functions and the integration of intelligence, the safety of high-end equipment in various industrial fields, such as high-speed trains, wind turbines, engines, gas turbines, compressors and machine tools, is receiving unprecedented attention from academia and industry. Fault diagnosis is an effective means to ensure the safe operation of machines, and it can significantly minimize operation and maintenance costs and enhance the economic benefits. Scholars, researchers and engineers are seeking advanced and efficient fault diagnosis technologies to ensure the performance and efficiency of machines, especially high-end equipment. With the advancement of monitoring and sensing technology, machine status data are continuously accumulated, providing effective support for the development of fault diagnosis technology based on signal processing and artificial intelligence. Therefore, this Special Issue aims to publish research work on condition monitoring and fault diagnosis of high-end equipment through advanced signal processing and artificial intelligence technologies.

This Special Issue welcomes original and high-quality research articles and review articles that address a wide range of topics related to the fault diagnosis of high-end equipment. The articles are expected to provide novel and newly developed ideas, algorithms, methods, and technologies that contribute to a better understanding of condition monitoring and fault diagnosis in high-end equipment. The scope of this Special Issue includes, but is not limited to, the following:

• Vibration, acoustic, and current-based machine fault diagnosis;
• Novel sensing technology for machine fault diagnosis;
• Novel signal processing and artificial intelligence algorithms for machine fault diagnosis or condition monitoring;
• Fault diagnosis or condition monitoring of high-speed trains, wind turbines, engines, gas turbines, compressors and machine tools;
• Fault diagnosis or condition monitoring of bearings, gears and rotors.

We look forward to receiving your contributions.

Dr. Bingyan Chen
Dr. Yao Cheng
Guest Editors

Manuscript Submission Information

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• signal processing
• artificial intelligence
• machine learning
• machine condition monitoring
• machine fault diagnosis
• high-end equipment