Entropy Applications in Condition Monitoring and Fault Diagnosis
This special issue belongs to the section "Signal and Data Analysis".
Special Issue Information
Dear Colleagues,
With the increasing automation of industrial production, the complexity of the system has increased significantly. The study of complex system condition monitoring and fault diagnosis technology is of great importance to improve both the level of technology and productivity. The long-term development of information theory makes it possible to use information-theoretic methods for signal feature extraction analysis of complex systems. Entropy, as a characteristic indicator to measure the uncertainty of signal state distribution and signal complexity, can quantitatively describe the information contained inside the signal. The study of how to use entropy to reflect the operation state and characteristic information of complex systems has become one of the current research hotspots in the field of condition monitoring and fault diagnosis.
Dr. Liansheng Liu
Dr. Yuqing Li
Guest Editors
Manuscript Submission Information
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Keywords
- information theory
- condition monitoring
- signal processing
- complexity measure
- fault diagnosis
- anomaly detection
- remaining useful life prediction
- machine learning
- intelligent maintenance.
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Published Papers
Entropy - ISSN 1099-4300