Microstructural, mechanical and acoustic emission-assisted wear characterization of equal channel angular pressed (ECAP) low stacking fault energy brass

Филиппов, А. В.; Tarasov, S. Yu.; Фортуна, С. В.; Podgornykh, O. A.; Shamarin, N. N.; Рубцов, В. Е.

doi:10.1016/j.triboint.2018.03.023

Cited by 32 publications

(12 citation statements)

References 36 publications

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“…The MDF is the frequency which divides AE power spectrum into two regions with equal energy. Both of these AE signal characteristics have been suggested to correlate with tribological behavior [1,26,27]. Fig.…”

Section: Fig 1 Experimental Setup 22 Ae Signal Acquisition and Datmentioning

confidence: 94%

“…The integrated AE RMS can be related to frictional work and wear under different sliding speeds [18] and loads [21] and can detect the sliding speed threshold for accelerated wear [18]. The integrated AE RMS [22,23] may also have a direct correlation with the wear volume and wear rate [24].In the frequency domain, AE parameters such as energy and median frequency (MDF) can be used, with the former being correlated to CoF [25,26] and wear volume [27] and the latter being correlated to CoF [26,28] and frictional work [29]. The amplitude of individual AE frequency components can also be excited by specific wear mechanisms, which can be determined based on power spectral density (PSD) and auto-covariance techniques [30].…”

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confidence: 99%

“…In the frequency domain, AE parameters such as energy and median frequency (MDF) can be used, with the former being correlated to CoF [25,26] and wear volume [27] and the latter being correlated to CoF [26,28] and frictional work [29]. The amplitude of individual AE frequency components can also be excited by specific wear mechanisms, which can be determined based on power spectral density (PSD) and auto-covariance techniques [30].…”

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confidence: 99%

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Using acoustic emission to characterize friction and wear in dry sliding steel contacts

Geng

Puhan

Reddyhoff

2019

Tribology International

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Acoustic emission (AE) was recorded during tribological tests on 52100 steel specimens under different loads. AE signals were transformed to the frequency domain using a Fast Fourier Transform and parameters such as power, RMS amplitude, mean frequency, and energy were analyzed and compared with friction coefficient and wear volume measurements. Results show that certain acoustic frequencies reflect friction while others reflect wear. If frequencies are chosen optimally, AE and friction signals are highly correlated (Pearson coefficients >0.8). SEM and Raman analysis reveal how plastic deformation and oxide formation affect friction, wear and AE simultaneously. AE recordings contains more information than conventional friction and wear volume measurements and are more sensitive to changes in wear mechanism. This all demonstrates AE's potential as a tool to monitor tribological behavior.waveform can correlate with the quantity of wear particles, as does the AE energy [14]. Moreover, the amplitude and length of a train of AE waves can be associated with individual slip events during the stick-slip [15]. In addition to this, the AE event location can determin mode I crack propagation in fretting fatigue [16]. The instantaneous RMS amplitude has been found to correlate with CoF [17][18][19], distinguish between different stages in CoF evolution [20] and even predict CoF based on a power law relation [18]. AE RMS can also be sensitive to applied load, velocity and mechanical properties of sliding components [20]. The integrated AE RMS can be related to frictional work and wear under different sliding speeds [18] and loads [21] and can detect the sliding speed threshold for accelerated wear [18]. The integrated AE RMS [22,23] may also have a direct correlation with the wear volume and wear rate [24].In the frequency domain, AE parameters such as energy and median frequency (MDF) can be used, with the former being correlated to CoF [25,26] and wear volume [27] and the latter being correlated to CoF [26,28] and frictional work [29]. The amplitude of individual AE frequency components can also be excited by specific wear mechanisms, which can be determined based on power spectral density (PSD) and auto-covariance techniques [30]. In addition to this, it has been found that low and high frequencies are associated with different lubricant conditions [28]. Peak frequencies can vary depending on wear mechanism, with adhesive wear emission suggested to occur around 1.1 MHz and abrasive wear between 0.25-1 MHz [31,32], while stick slip results in dominant AE frequencies around 10 kHz [20].Time-frequency analysis can also be applied to AE signals, with evolving PSD spectra indicating different stages wear [19] and wavelet analysis detecting the onset of scuffing [33,34] and other wear states [35] [36].Reviewing this literature it is apparent that the instantaneous RMS value of the acquired AE signal has been the most widely used parameter to correlate with friction and wear [17-19, 22, 23, 37, 38]. However, recently questions h...

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Section: Fig 1 Experimental Setup 22 Ae Signal Acquisition and Datmentioning

confidence: 94%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Using acoustic emission to characterize friction and wear in dry sliding steel contacts

Geng

Puhan

Reddyhoff

2019

Tribology International

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“…Skåre et al [14] used AE RMS to monitor progressive behaviour of the stamping tool and Shanbhag et al [15] used AE mean-frequency to investigate wear initiation on the stamping tool at the microscopic level. Filippov et al [16][17][18] studied the correlation between the AE frequency characteristics and the wear in the metal cutting process. The AE median frequency feature was observed to be sensitive to the chatter mode vibrations and discontinuous chip formation in the metal cutting process as well as the wear rate during tribological sliding tests.…”

Section: Introductionmentioning

confidence: 99%

“…The AE median frequency feature was observed to be sensitive to the chatter mode vibrations and discontinuous chip formation in the metal cutting process as well as the wear rate during tribological sliding tests. In the tribology study on the equal channel angular pressing process, a direct correlation was observed between the wear and AE Lubricants 2020, 8,25 3 of 23 signal median frequency feature as the number of forming operations increased [18]. Most of these studies are focussed on defining frequency features of the AE signal obtained from either machining processes, a tribology setup, or from the semi-industrial stamping setup.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Galling Wear Using Acoustic Emission Frequency Characteristics

2020

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In the sheet metal stamping process, during sliding contact between the tool and sheet, it is expected that severe events such as tool wear or fracture on the sheet generate acoustic emission (AE) burst waveforms. Attempts have been made in the literature to correlate the AE burst waveform with the wear mechanisms. However, there is a need for additional studies to understand the frequency characteristics of the AE burst waveform due to the severity and progression of the galling wear. This paper will determine the AE frequency characteristics that can be used to monitor galling wear, independent of the experimental process examined. The AE burst waveforms generated during the stamping and scratch tests are analysed in this paper to understand the change in the AE frequency characteristics with the galling severity. These AE burst waveforms were investigated using the Hilbert Huang Transform (HHT) time-frequency technique, band power, and mean-frequency. Subsequently, these AE frequency features are correlated with the wear behaviour observed via high-resolution profilometer images of the stamped parts and scratch surfaces. Initially, the HHT technique is applied to the AE burst waveform to understand the influence of wear severity in the power distribution over the wide AE frequency range. Later, the AE bandpower feature is used to quantitatively analyse the power in each frequency interval during the unworn and worn tool conditions. Finally, the mean-frequency of AE signal is identified to be able to determine the onset of galling wear. The new knowledge defined in this paper is the AE frequency features and wear measurement feature that can be used to indicate the onset of galling wear, irrespective of the processes examined. Highlights •AE burst waveform can be used to investigate galling. • AE mean-frequency can indicate galling wear initiation at industrial and tribological condition. • Profile depth wear feature can be used quantitatively to correlate with AE frequency features. • Frequency-magnitude and bandpower increased with increase in galling severity.

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Acoustic emission characterization of sliding wear under condition of direct and inverse transformations in low-temperature degradation aged Y-TZP and Y-TZP-AL2O3

et al. 2018

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In this research, results of the investigation of the sliding friction and wear of yttria-stabilized tetragonal zirconia polycrystalline (Y-TZP) and Y-TZP-Al 2 O 3 samples preliminarily subjected to low-temperature degradation are reported. The investigation was carried out using a pin-on-disk tribometer with simultaneous recording of acoustic emission (AE) and vibration acceleration. The sliding wear process was found to be determined by dynamic direct and inverse Y-TZP transformations detected by monoclinic and tetragonal X-ray diffraction peak ratios. The AE signals generated under direct and inverse transformations can be used to characterize wear and friction mechanisms as well as direct and inversed sliding-induced phase transformations. The AE signal energy grows with the friction coefficient and the inverse transformation degree. Reduction of the AE signal energy indicates establishing the mild wear stage caused by effective stress-induced direct martensitic transformation. The AE signal median frequency increases in the case of lower friction. Numerical studies of wear subsurface fracture under conditions of stress-induced martensitic transformation were used to elucidate the role played by the phase transformation in Y-TZP and Y-TZP-Al 2 O 3. Martensitic transformation in Y-TZP was described with use of the non-associated dilatant plasticity model. Simulation results particularly show that increase in the value of dilatancy coefficient from 0 to 0.2 is accompanied by 25%−30% reduce in characteristic length and penetration depth of sliding-induced subsurface cracks. As shown the AE may be an effective tool for in-situ monitoring the subsurface wear of materials experiencing both direct and inverse transformations.

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Microstructural, mechanical and acoustic emission-assisted wear characterization of equal channel angular pressed (ECAP) low stacking fault energy brass

Cited by 32 publications

References 36 publications

Using acoustic emission to characterize friction and wear in dry sliding steel contacts

Using acoustic emission to characterize friction and wear in dry sliding steel contacts

Investigation of Galling Wear Using Acoustic Emission Frequency Characteristics

Acoustic emission characterization of sliding wear under condition of direct and inverse transformations in low-temperature degradation aged Y-TZP and Y-TZP-AL2O3

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