Health Monitoring of Electrical Actuators and their supplies

  E-mail   Print

Guest Editors
Prof. Guy Clerc
University of Lyon – University of Claude Bernard Lyon1

Prof. Abdenour Soualhi
University of ST Etienne

Manuscript Topics
Faults diagnosis and prognosis of electrical systems play a key role in the reliability and safety of industrial systems especially in key sectors (military, aviation, aerospace and nuclear, etc.). Topics of “Health monitoring of electrical actuators” aim to introduce new methods for faults diagnosis and prognosis of electrical systems like induction or synchronous machines, mechanical systems like gearbox driven by these actuators. Electrical actuators play an increasing role in industrial applications. They bring flexibility, reduce the environmental impact and improve the ration power/weight. However, they become more and more complex. In order to provide a safe operation, diagnosis and prognosis methods must be implemented. These methods, also called data driven methods, use measured data collected from sensors placed on the system in order to construct relevant features. These features will be implemented in a diagnostic and/or prognostic model to estimate the state of the system. As an example, artificial intelligence offers significant improvements to diagnosis and is structural member of prognosis. It can be used to classify the different faults, to predict their occurrence or to give the remaining useful life.

Papers submitted to this Issue are expected to provide an original contribution, proposing new solutions, improvements to existing solutions, and new applications in emerging sectors. The paper can address the solution of specific problems in the sector of interest using algorithms, experimental tests, and numerical analysis. All contributions should be applied to electrical and mechanical systems such as actuators, static converters, electrical network, bearings, gearbox... .

The following topics are within the scope of “Health monitoring of electrical Systems”, but are not limited to:

• Fault detection and diagnosis
• Real-time monitoring
• Health monitoring
• Signal processing
• Classification
• Prognosis
• Predictive maintenance
• Machine learning
• Remaining useful life estimation

Paper submission 
All manuscripts will be peer-reviewed before their acceptance for publication.
The deadline for manuscript submission is 31 December 2019

Instructions for authors
Please submit your manuscript to online submission system

Muhammad Hussain, Mahmoud Dhimish, Violeta Holmes, Peter Mather
+ Abstract     + HTML     + PDF(1557 KB)
Qichun Zhang
+ Abstract     + HTML     + PDF(1001 KB)
Ryan Michaud, Romain Breuneval, Emmanuel Boutleux, Julien Huillery, Guy Clerc, Badr Mansouri
+ Abstract     + HTML     + PDF(3095 KB)
Open Access Journals
Open Access Journals