Modelling acoustic emissions generated by tribological behaviour of mechanical seals for condition monitoring and fault detection

Towsyfyan, Hossein; Gu, Fengshou; Ball, Andrew; Liang, Bo

doi:10.1016/j.triboint.2018.04.021

Cited by 33 publications

(28 citation statements)

References 35 publications

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“…In Ref. [248], acoustic emission (AE) signals were used for condition monitoring of mechanical seals. A comprehensive model of AE energy discharge under different lubrication regimes was developed, and the RMS of AE signals was correlated with sliding speed.…”

Section: Wear Monitoring and Debris Analysismentioning

confidence: 99%

A review of recent advances in tribology

et al. 2020

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The reach of tribology has expanded in diverse fields and tribology related research activities have seen immense growth during the last decade. This review takes stock of the recent advances in research pertaining to different aspects of tribology within the last 2 to 3 years. Different aspects of tribology that have been reviewed including lubrication, wear and surface engineering, biotribology, high temperature tribology, and computational tribology. This review attempts to highlight recent research and also presents future outlook pertaining to these aspects. It may however be noted that there are limitations of this review. One of the most important of these is that tribology being a highly multidisciplinary field, the research results are widely spread across various disciplines and there can be omissions because of this. Secondly, the topics dealt with in the field of tribology include only some of the salient topics (such as lubrication, wear, surface engineering, biotribology, high temperature tribology, and computational tribology) but there are many more aspects of tribology that have not been covered in this review. Despite these limitations it is hoped that such a review will bring the most recent salient research in focus and will be beneficial for the growing community of tribology researchers.

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Section: Wear Monitoring and Debris Analysismentioning

confidence: 99%

A review of recent advances in tribology

et al. 2020

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“…Moreover, the technique is effective only for transparent fluids as reported in (Al Thobiani, 2011). In acoustic emission testing, another NDT method, high frequency AE waves are affected by transmission path and wave distortion which are technically considered as a major problem in AE condition monitoring of rotating machines (Towsyfyan et al, 2018). Moreover, in most cases, distinguishing the AE signals from the background noise imposes several challenges.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Study on Vibration Signatures for Detecting Incipient Cavitation in Centrifugal Pumps Based on Envelope Spectrum Analysis

Al‐Obaidi

Towsyfyan

2019

JAFM

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Vibration signatures have been studied for monitoring the condition of centrifugal pumps by many researchers, however, there is limited published information on the application of vibration analysis to incipient pump cavitation. The paper will review the state of the art in the field and develops an effective signal processing approach based on envelope spectral analysis to close this gap. A purpose-built test rig was employed for recording vibration signals from a centrifugal pump at a wide range of operating conditions. The collected data was then processed using time domain and frequency domain analysis methods. The study has shown that the vibration energy concentrated mainly in the frequency range between 8-15 kHz. At the flow rates less than 300(l/min), i.e. in design flow rate range, the vibration amplitudes remain constant and does not show a notable change by the flow rate increase. However, a notable increase in the vibration level is evident when the flow rate exceeds 300 (l/min). Analysis the result of filtered vibration signatures has revealed that vibration signal parameters: peak value, root mean squared (RMS), crest factor along with vibration spectrum allow development of cavitation (for the flow rates higher than 300 (l/min)) to be diagnosed reliably. However, conventional signal processing methods may not produce a clear separation of the incipient cavitation from the healthy baseline. Therefore, envelope spectrum analysis has been carried out on recorded vibration signatures to detect the onset of cavitation from the baseline and satisfactory results have been perceived.

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“…Edward et al [26]. H. Towsyfyan et al [31] developed a dynamic model based on the multiple interaction of the AE source mechanisms in different tribological regimes to predict the RMS value of an AE signal as summarised in Table 1. This model that has been validated experimentally in Ref.…”

Section: Introductionmentioning

confidence: 99%

“…This model that has been validated experimentally in Ref. [31] will be used in the remainder of present work to explain the effect of operating conditions (e.g. contact load and rotational speed) on the tribological AEs and thus for interpreting the results of seal monitoring.…”

Section: Introductionmentioning

confidence: 99%

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

Towsyfyan

Ball

et al. 2018

Friction

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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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Modelling acoustic emissions generated by tribological behaviour of mechanical seals for condition monitoring and fault detection

Cited by 33 publications

References 35 publications

A review of recent advances in tribology

A review of recent advances in tribology

An Experimental Study on Vibration Signatures for Detecting Incipient Cavitation in Centrifugal Pumps Based on Envelope Spectrum Analysis

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

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