A review of electrostatic monitoring technology: The state of the art and future research directions

Wen, Zhenhua and Hou, Junxing and Atkin, Jason (2017) A review of electrostatic monitoring technology: The state of the art and future research directions. Progress in Aerospace Sciences, 94 . pp. 1-11. ISSN 0376-0421

PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution Non-commercial No Derivatives.
Download (185kB) | Preview


Electrostatic monitoring technology is a useful tool for monitoring and detecting component faults and degradation, which is necessary for system health management. It encompasses three key research areas: sensor technology; signal detection, processing and feature extraction; and verification experimentation. It has received considerable recent attention for condition monitoring due to its ability to provide warning information and non-obstructive measurements on-line. A number of papers in recent years have covered specific aspects of the technology, including sensor design optimization, sensor characteristic analysis, signal de-noising and practical applications of the technology. This paper provides a review of the recent research and of the development of electrostatic monitoring technology, with a primary emphasis on its application for the aero-engine gas path. The paper also presents a summary of some of the current applications of electrostatic monitoring technology in other industries, before concluding with a brief discussion of the current research situation and possible future challenges and research gaps in this field. The aim of this paper is to promote further research into this promising technology by increasing awareness of both the potential benefits of the technology and the current research gaps.

Item Type: Article
Keywords: Electrostatic monitoring technology; Prognostics and Health Management; Aero-engine; Condition monitoring; Electrostatic sensor; Electrostatic signal
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1016/j.paerosci.2017.07.003
Depositing User: Eprints, Support
Date Deposited: 01 Nov 2017 10:43
Last Modified: 01 Sep 2018 04:30
URI: http://eprints.nottingham.ac.uk/id/eprint/47736

Actions (Archive Staff Only)

Edit View Edit View