Tribological behaviour diagnostic and fault detection of mechanical seals based on acoustic emission measurements

Hossein TOWSYFYAN; Fengshou GU; Andrew D BALL; Bo LIANG

doi:10.1007/s40544-018-0244-4

Friction 2019, 7(6): 572-586 https://doi.org/10.1007/s40544-018-0244-4

Research Article |

Open Access | Issue | Published: 06 November 2018

Tribological behaviour diagnostic and fault detection of mechanical seals based on acoustic emission measurements

Show Author's Information Hide Author's Information Hossein TOWSYFYAN^¹(

), Fengshou GU^², Andrew D BALL^², Bo LIANG^²

1Institute of Sound and Vibration Research (ISVR), Digital Signal Processing and Control Group, University of Southampton, Southampton SO17 1BJ, UK

2School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK

Keywords:

tribology, acoustic emission, condition monitoring

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TOWSYFYAN H, GU F, BALL AD, et al. Tribological behaviour diagnostic and fault detection of mechanical seals based on acoustic emission measurements. Friction, 2019, 7(6): 572-586. https://doi.org/10.1007/s40544-018-0244-4

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Abstract

Acoustic emission (AE) has been studied for monitoring the condition of mechanical seals by many researchers, however to the best knowledge of the authors, typical fault cases and their effects on tribological behaviour of mechanical seals have not yet been successfully investigated. In this paper, AE signatures from common faults of mechanical seals are studied in association with tribological behaviour of sealing gap to develop more reliable condition monitoring approaches. A purpose-built test rig was employed for recording AE signals from the mechanical seals under healthy and faulty conditions. The collected data was then processed using time domain and frequency domain analysis methods. The study has shown that AE signal parameters: root mean squared (RMS) along with AE spectrum, allows fault conditions including dry running, spring out and defective seal faces to be diagnosed under a wide range of operating conditions. However, when mechanical seals operate around their transition point, conventional signal processing methods may not allow a clear separation of the fault conditions from the healthy baseline. Therefore an auto-regressive (AR) model has been developed on recorded AE signals to classify different fault conditions of mechanical seals and satisfactory results have been perceived.

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Tribological behaviour diagnostic and fault detection of mechanical seals based on acoustic emission measurements

Show Author's information Hide Author's Information Hossein TOWSYFYAN^¹(

), Fengshou GU^², Andrew D BALL^², Bo LIANG^²

1Institute of Sound and Vibration Research (ISVR), Digital Signal Processing and Control Group, University of Southampton, Southampton SO17 1BJ, UK

2School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK

Abstract

Keywords: tribology, acoustic emission, condition monitoring

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Received: 28 June 2018

Revised: 03 August 2018

Accepted: 27 August 2018

Published: 06 November 2018

Issue date: December 2019

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This article is published with open access at Springerlink.com

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