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Intelligent condition monitoring of rotating machinery through electrostatic sensing and signal analysis

Wang, Lijuan, Yan, Yong, Hu, Yonghui, Qian, Xiangchen (2013) Intelligent condition monitoring of rotating machinery through electrostatic sensing and signal analysis. In: 2013 IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA),, 25-27 November 2013, Kuala Lumpur, Malaysia. (doi:10.1109/ICSIMA.2013.6717951) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/ICSIMA.2013.6717951

Abstract

Condition monitoring is a key step to identify the health status of working machinery and establish a necessary maintenance strategy. This paper proposes a novel intelligent system for the online monitoring of the operating conditions of rotating machinery using electrostatic sensors and signal processing techniques. This system is capable of providing simultaneous measurements of rotational speed, angular acceleration, vibration direction and frequency as well as an indication of mechanical wear. These parameters usually contain abundant fault-related information about the rotating machinery, which is to be extracted by detecting the electrostatic charge on the surface of the moving part. The general principle and system design considerations are presented. Preliminary experimental results obtained from laboratory tests demonstrate the effectiveness of the monitoring system.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/ICSIMA.2013.6717951
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Tina Thompson
Date Deposited: 12 Jun 2014 09:01 UTC
Last Modified: 29 May 2019 12:40 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/41396 (The current URI for this page, for reference purposes)
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