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.
Highlights
A review of sealing technology [1] reiterated the important role of mechanical seals in rotating machines
This paper demonstrates the effectiveness of Acoustic emission (AE) measurements to detect operating faults of mechanical seals at initial stages
Based on the experimental study presented in this work, the frequency range of 270 ± 35 kHz can present the tribological behaviour of mechanical seals
Summary
A review of sealing technology [1] reiterated the important role of mechanical seals in rotating machines. Based on the operating conditions, three main mechanisms may contribute to AE generation in sliding of mating surfaces, i.e. viscous friction due to shearing of lubricant layers [22, 24, 25], flow induced asperity deformations due to the interaction between surface asperities and fluid flows (that leads to the development of a vibratory behaviour in the surface asperities under HL regime due to dynamic bending and reclamation of surface asperities ) [22] and direct asperity contacts [22, 25−27] which are well documented in the literature. To introduce a robust AE based approach for accurate seal monitoring, a novel time series analysis will be carried out (as detailed in Section 4) to distinguish different fault condition of mechanical seals operating around their transition point, where conventional signal processing methods may face some challenges as detailed in Section 3.2 to Section 3.4
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