Advanced Sensing Techniques and Fault Diagnosis in Electric Power Engineering
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".
Deadline for manuscript submissions: 20 March 2027 | Viewed by 137
Editor
Interests: measurements and metrology; technical diagnostics; high-voltage engineering; partial discharges
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The adequate technical condition assessment of key apparatus is a crucial assumption in the provision of reliable and continuous electric power delivery to customers. To meet this requirement, any fault in the power system must be detected and diagnosed as early as possible, with particular emphasis on the precision of the diagnostic process. Various on-line and off-line diagnostic methods are widely applied to the early detection of any system malfunctions. Furthermore, a number of different sensors may also be applied to capture selected physical quantities that may be used to indicate the type of potential faults. A specific fault diagnostic process is typically performed by experts in the field; however, artificial intelligence (AI)-based systems are increasingly being proposed to support the decision-making process related to this task.
With this in mind, we are launching a Special Issue, titled “Advanced Sensing Techniques and Fault Diagnosis in Electric Power Engineering”. We invite researchers to contribute high-quality original research or technical papers, reviews, and case studies to this Special Issue. Practical papers in which either examples of good present practice are described and disseminated or new proposals of improvements and applications of innovative solutions regarding sensor design, evaluation, and applications; signal processing and measurements, prediction; or modelling and classification regarding fault diagnostics in electric power engineering are particularly sought. Theoretical papers of high technical merit relying on mathematical arguments and computation are also welcome, but authors are asked to highlight and justify their potential applications in electric power engineering.
Dr. Michał Kunicki
Guest Editor
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Keywords
- fault diagnostics
- condition-based maintenance
- predictive maintenance
- decision support system
- high voltage
- cable
- transformer
- overhead line
- generator
- converters
- insulation
- dielectrics
- substation
- transmission
- distribution
- generation
- reliability
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