Condition monitoring by acoustic emission and electrostatic technologies

Abstract

The increasing demands made on operational availability and reliability of machinery requires the adoption of innovative methods to assess the machine’s current condition and predict its condition in future. Rapid advances in the design and working condition of mechanical systems in industrial, aerospace and military equipment over the years have resulted in the ever-increasing complexity of problems encountered in the management of their maintenance. The ability to monitor the performance of machinery components in terms of wear and durability is extremely invaluable. Thus, it is essential to monitor wear occurrences and severity so prediction of any forthcoming failure can be made and hence accurate maintenance schedules can be planned. Acoustic emission (AE) is widely used in industry for detecting: cracking in a bridge structures; cavitation in pumps, piping and turbines; leak detection; welded joint defect; creep cracking; fatigue cracking; stress corrosion cracking; hydrogen embrittlement cracking; fracture and crack propagation; corrosion detection, etc. Electrostatic (ES) monitoring was originally developed for condition monitoring of the gas path of jet engines and turbines but has recently been adopted for studying lubricated systems at the University of Southampton. Both AE and ES are relatively new condition monitoring techniques that provide real-time outputs. The purpose of this project is to combine these two technologies together to examine whether they are sensitive to different aspects of the physics of contact degradation and elucidated the potential of the systems to detect precursors to severe wear. The project involved two experimental series: the first examined dry sliding and the second investigated lubricated sliding. Both employed steel-on-steel, ball-on-flat configurations using a pin-on-disc tribometer. During dry sliding test, the two condition monitoring techniques indicated three periods of activity identified by differences in magnitude and signal characteristics. Post-test analysis by SEM and EDX identification these three regions/wear regimes as running-in, delamination and delamination/oxidation. Experimental data showed that the AE RMS signal was very sensitive to the variation of the friction and good correlation was seen throughout testing. AE energy, counts and amplitude distribution are shown to be particularly sensitive to different wear mechanisms under dry sliding test conditions. The physical mechanisms behind the wear mechanisms were deeply investigated and the results showed that the intensity of AE signal was related to the scale of the de-bonding of material during severe adhesive, material transfer and severe delamination. Cracking and plastic deformation of the material, which occur during ratchetting, mild delamination and oxidation, generate lower level AE signal compared with the de-bonding of material. The bandwidth of the power spectrum of AE signals can be used to distinguish different wear mechanisms. Lubricated tests indicated again that AE and ES where sensitive to wear mechanisms in both loading and steady-state periods: plastic deformation, filmy wear, mild wear and scuffing (identified by post-test analysis). Transitions from mild to severe wear modes, detected by AE and ES sensors, were linked to intermittent white layer (phased transformed) regions and/or to incomplete oxide layers formed in the wear track. Overall the research project has shown that AE and ES exhibited the potential to become a powerful suite in condition monitoring.

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Identifiers

ORCID for Robert J.K. Wood: orcid.org/0000-0003-0681-9239

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