Fault Diagnosis and Condition Monitoring for Induction Motors
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 15 March 2025 | Viewed by 86
Special Issue Editors
Interests: mechanical dynamics; fault diagnosis; artificial intelligence; intelligent operation and maintenance
Interests: fault diagnosis; signal processing; rotating machinery dynamics
Interests: intelligent operation and maintenance and health management for high-end electromechanical and hydraulic equipment; artificial intelligence and signal processing; digital twins and physical information systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Induction motors are pivotal in industrial applications due to their robustness, simplicity, and cost-effectiveness. Ensuring their reliable and efficient operation is crucial, as unexpected failures can lead to significant downtime and financial losses. Therefore, research on fault diagnosis and condition monitoring of induction motors is essential for predictive maintenance and operational efficiency.
Modern fault diagnosis and condition monitoring techniques combine sensors, signal processing, machine learning algorithms, and real-time data analytics to detect, diagnose, and predict potential faults. These advancements facilitate early anomaly detection, enabling timely maintenance and reducing the risk of catastrophic failures.
This Special Issue aims to showcase the latest research and developments in fault diagnosis and condition monitoring for induction motors. We invite scientists, engineers, and industrial practitioners to contribute their theoretical and technological advancements. Topics of interest include advanced sensor technologies, signal processing methods, machine learning approaches, real-time monitoring systems, and case studies demonstrating successful applications. We welcome original research papers, review articles, and case studies that address both theoretical and practical challenges in this critical field.
The topics of this Special Issue include, but are not limited to, the following areas:
- Methods and techniques for detecting and diagnosing faults in induction motors.
- Application of fault diagnosis in maintaining machinery health.
- Implementation strategies for predictive maintenance in industrial environments.
- Development and integration of real-time condition monitoring systems for induction motors.
- Advanced signal processing methods for the analysis of motor vibration, acoustic, and electrical signals.
- Utilization of machine learning algorithms for fault detection and diagnosis.
- Techniques for collecting and analyzing real-time data from induction motors.
- Development of robust algorithms for anomaly detection and classification.
- Advances in sensor technologies for fault detection and condition monitoring.
Dr. Feibin Zhang
Dr. Jinfeng Huang
Dr. Xiaoli Zhao
Guest Editors
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Keywords
- induction motor diagnostics
- predictive maintenance
- condition monitoring
- machine learning
- sensor technology
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