 Debris Recognition Methods in the Lubrication System with Electrostatic SensorsHuijie Mao, Hongfu Zuo, Han Wang, Yibing Yin and Xin Li Mathematical Problems in Engineering, 2018, vol. 2018, 1-15 Abstract: The oil-line electrostatic sensor (OLS) is a developing debris monitoring sensor. Previous work has shown that electrostatic charge signals can indicate the debris by calculating the Root Mean Square (RMS) value or the correlation-based indicator, but the precision of these methods is not high. This paper further developed the more accurate methods to obtain detailed debris information. Firstly, to interpret the monitoring principle of OLS and provide the guidance for developing the debris recognition methods, this paper analyzed the possible charge sources in the lubrication system and obtained the characteristics of the OLS by establishing its mathematical model. Further, a new OLS test rig was designed and verified the correctness of the sensor’s characteristics and its mathematical model. Based on the characteristics of the sensor, two new debris recognition methods were proposed. Finally, the effects of the new debris recognition methods were verified by the practical industrial gearbox bench test. Results showed that, compared to the traditional methods, the new methods could recognize the debris effectively and provide more detailed information of the debris. Date: 2018 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8043526 DOI: 10.1155/2018/8043526 Access Statistics for this article More articles in Mathematical Problems in Engineering from Hindawi |
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