Fault Identification and Prognosis for Electromechanical Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 5824
Special Issue Editors
Interests: digital signal processing; structural health monitoring; condition monitoring; artificial intelligence; vibration analysis; motor current signature analysis; adaptation of diagnosis systems
Special Issues, Collections and Topics in MDPI journals
Interests: Optics & Terahertz; Diagnosis; Structural Health Monitoring; NDT&E
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Fault identification and failure prognosis for electromechanical systems have become very important for most industrial sectors and for academic research. Fault identification includes fault detection, fault isolation, estimation of failure modes of faults, and fault severity estimation.
This Special Issue’s scope is on novel research and developments, related to:
- Fault detection;
- Fault isolation;
- Estimation of failure modes of faults;
- Fault severity estimation;
- Failure prognosis.
The main challenges for these areas are as follows:
- Multiclass weak fault detection and fault isolation;
- Effect of variable system operating conditions on fault identification and failure prognosis;
- Increase of accuracy of fault severity estimation and estimation of the remaining useful life before failure;
- Effects of physics of fault/failure on fault identification and failure prognosis;
- Automation of on-line fault identification and failure prognosis.
Addressing these challenges requires novel research and developments, related to data analysis in frequency and multifrequency domains, fault detection, machine learning and pattern recognition, fault severity estimation, failure mode analysis, and analysis of physics of fault/failure mechanisms in materials and rotating equipment and stress analysis.
The following main topics, applied for electromechanical systems, describe this SI:
- Fault identification;
- Fault detection;
- Fault isolation and fault severity estimation;
- Failure modes of faults;
- Failure prognosis and estimation of the remaining useful life before failure;
- Data analysis in frequency and multifrequency domains;
- Pattern recognition and machine learning;
- Physics of fault/failure.
This Special Issue will not cover non-novel “case study” papers and papers, related to software fault prediction. Potential authors need to make clear statements of paper novelties, which should be based on comprehensive state-of-the art reviews.
Prof. Dr. Len Gelman
Prof. Dr. Shuncong Zhong
Guest Editors
Manuscript Submission Information
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Keywords
- fault identification
- fault detection
- fault isolation and fault severity estimation
- failure modes of faults
- failure prognosis and estimation of the remaining useful life before failure
- data analysis in frequency and multifrequency domains
- pattern recognition and machine learning
- physics of fault/failure