A Time-Frequency Based Approach for Acoustic Emission Assessment of Sliding Wear

Abstract

The acoustic emission method is one of few contemporary non-destructive testing techniques enabling continuous on-line health monitoring and control of tribological systems. However, the existence of multiple “pseudo”-acoustic emission (AE) and noise sources during friction, and their random occurrence poses serious challenges for researchers and practitioners when extracting “useful” information from the upcoming AE signal. These challenges and numerous uncertainties in signal classification prevent the unequivocal interpretation of results and hinder wider uptake of the AE technique despite its apparent advantages. Currently, the signal recording and processing technologies are booming, and new applications are born on this support. Specific tribology applications, therefore, call for developing new and tuning existing approaches to the online AE monitoring and analysis. In the present work, we critically analyze, compare and summarize the results of the application of several filtering techniques and AE signal classifiers in model tribological sliding friction systems allowing for the simulation of predominant wear mechanisms. Several effective schemes of AE data processing were identified through extensive comparative studies. Guidelines were provided for practical application, including the online monitoring and control of the systems with friction, characterizing the severity and timing of damage, on-line evaluation of wear as sliding contact tests and instrumented acceleration of tribological testing and cost reduction.

A review of advances in tribology in 2020–2021

“…Advanced sensing technologies, particularly in-situ measurements, are useful for characterizations of friction, wear, and lubrication in testing or practical operation. A time-frequency based approach for analysis of acoustic emission [368], in-situ-determination of tribologically induced hydrogen permeation by using electrochemistric methods [369], and a Tribo-Raman-spacer layer imaging method (SLIM) which is able to detect tribofilm formation process and tribofilm thickness on the sliding surface have been developed [370]. Besides of the evaluations of wear resistance of materials by using laboratory standard tribometers, system level or assembly level bench tests, such as full-size journal bearings, ball bearings, gears, are not replaceable in industry.…”

Early Detection of Subsurface Fatigue Cracks in Rolling Element Bearings by the Knowledge-Based Analysis of Acoustic Emission

“…The failure starts to evolve unpredictably after some variable time of service, as embryonic subsurface cracks are extremely challenging to reveal during service. When it reaches a critical size at the surface of the component, the fault is detectable by a wealth of vibration and acoustic emission (AE) techniques [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ], or a combination of both. These techniques are powered by contemporary signal processing algorithms [ 21 , 22 ] and/or other non-destructive testing methods, such as the ultrasound technique [ 23 ], Barkhausen noise analysis [ 24 ], shock-pulse methods [ 25 ], infrared thermography [ 26 , 27 , 28 ], oil monitoring [ 29 ], etc., or a combination of these methods [ 30 , 31 ].…”

The Comparison of the Main Time-Frequency Transformations of Spectral Analysis of Acoustic Emission Signals

“…1). В методе акустической эмиссии (АЭ) периодограммы используются при: вычислении энергии (мощности) сигналов [1], полосовой частотной фильтрации или широкополосном шумопонижении [2][3][4], кластеризации данных и распознавании источников АЭ [5][6][7], оценке передаточных характеристик акустического тракта и затухания в нем [8], гармоническом анализе работы узлов циклического действия [9] и т. д. Однако периодограмма не позволяет обнаружить, в какой момент времени возникают те или иные отличия в частотной области, т. е. не отображает динамику частотных изменений в сигнале (рис. 1).…”