Analysis of experimentally generated friction related acoustic emission signals

Asamene, Kassahun; Sundaresan, M.

doi:10.1016/j.wear.2012.07.019

Cited by 32 publications

(22 citation statements)

References 32 publications

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“…The events from cracks are in some respect comparable with the events of pencil lead break (PLB) signatures. 20 The waveforms are often portrayed by a solid rise subsequently a relatively calm period and afterward the reflected signals are observed.…”

Section: Construction Of Reference Signalmentioning

confidence: 99%

Acoustic Emission Signal Analysis and Event Extraction through Tuned Wavelet Packet Transform and Continuous Wavelet Transform While Tensile Testing the AA 2219 Coupon

Bose¹,

Sasikumar²,

Jose³

et al. 2018

IJAV

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Aluminium Alloy AA 2219 is the principal metal for the production of propellant reservoir used in launch vehicles. The propellant tanks are often proof tested with acoustic emission technique (AET) to ensure its health. Acoustic Emission Testing during the structural health monitoring and proof testing is complex and unrealistic occasionally as it is performed in the noisy environment. Identification of signature corresponds to crack and its extraction from noise signatures is a major challenge in AET. Wavelet Packet Transform is an efficient mathematical tool for the analysis of AE signals. This paper recommends a novel combination of normalized cross correlation, Wavelet Packet Transform and Continuous wavelet transform to detect and extract the event related to failure. Experiments were carried out on AA 2219 tensile coupons at different threshold conditions. The recorded AE hits contain signals related to different events such as atmospheric noise, rubbing noise and other noise signals along with the signals from cracks. By applying the fine tuned wavelet packet transform technique in combination with CWT, the extraction of denoised single event related to crack was executed. Based on the frequency and the wavelet coefficient the crack related hits and the noisy hits are categorized.

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Section: Construction Of Reference Signalmentioning

confidence: 99%

Acoustic Emission Signal Analysis and Event Extraction through Tuned Wavelet Packet Transform and Continuous Wavelet Transform While Tensile Testing the AA 2219 Coupon

Bose¹,

Sasikumar²,

Jose³

et al. 2018

IJAV

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show abstract

“…A test fixture to simulate friction between a steel bar and pads is shown in Figure 1; this fixture is slightly modified from the fixture used in [5]. The mechanism of operation is such that as the bottom end is subjected to triangular type cyclic displacements, successive cycles of stick and slip are generated between the pads and the steel bar.…”

Section: Test Fixturementioning

confidence: 99%

“…James Li et al [4] used two normalized features obtained from experimentally generated acoustic emission signals and used these two features to classify different types of defects in bearings. Asamene et al [5] examined frequency features of AE signals obtained from friction tests to characterize features of AE signals in response to conditions prevailing at contact between surfaces. Baranov et al [6] developed a model for determining the parameters of AE accompanying contact friction of solids.…”

Section: Introductionmentioning

confidence: 99%

Monitoring friction related surface degradation using acoustic emission technique

et al. 2013

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Relative motion between surfaces of mechanical parts causes surface wear and damage. The degradation to the surfaces has been monitored using vibration characteristics as well as acoustic emissions generated during the relative surface movements. In particular, acoustic emission signals were found to be sensitive to some of the microscopic processes occurring at the frictional interface. In this study, friction between two surfaces was monitored experimentally under controlled conditions. Relative velocity, contact pressure, and surface roughness values were varied in the experiments. Friction related acoustic emission signals were recorded and analyzed to understand the relationship between the signals generated and the physical processes giving rise to these signals. Information related to the stick-slip movements during cyclic motion, in the experiments, was observed from the signals. Features of the waveforms were found to reveal the conditions existing at the friction interface. In particular, the changes in the surface roughness and contact pressure were readily observed from the acoustic emission signals.

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“…Hase et al [11] built an interesting correlation map of AE frequency spectra and several phenomena associated with deformation and fracture. The correlation between AE frequency and tribological phenomena, such as rolling and collisions of surface asperities [12][13][14], detachment and transfer of material consecutive to an adhesive interaction and plastic deformations and cutting, ploughing or fragmentation by relatively sharp asperities [15], were also investigated. In addition, the relationship between AE amplitude and wear production, on one side, and internal plastic flow of the tribological circuit, on the other side, were explored [16].…”

Section: Introductionmentioning

confidence: 99%

Tribolumen: A Tribometer for A Correlation Between AE Signals and Observation of Tribological Process in Real-Time—Application to A Dry Steel/Glass Reciprocating Sliding Contact

et al. 2020

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This paper deals with the development of an original apparatus called TRIBOLUMEN designed specifically for friction experiments on transparent materials. The friction measurement is synchronized with an acoustic emission (AE) sensor and the device is also equipped with a high-speed camera offering a direct view at the interface to gain a deeper understanding of tribological mechanisms. The TRIBOLUMEN device is in ball-on-flat contact configuration with a range of strokes from 5 to 500 µm and an oscillation frequency from 5 to 600 Hz. The experiments showed that this device has an adequate rigidity and can detect subtle friction modifications of the oscillating contacts. The observation of a steel-on-glass contact in real-time highlighted the initiation of Hertzian cracks followed by the formation of debris in the contact. Using the synchronous measurement, these mechanisms were clearly associated with different stages in the friction measurement and in the AE signals, which permitted to identify the AE signature of Hertzian cracks.

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Analysis of experimentally generated friction related acoustic emission signals

Cited by 32 publications

References 32 publications

Acoustic Emission Signal Analysis and Event Extraction through Tuned Wavelet Packet Transform and Continuous Wavelet Transform While Tensile Testing the AA 2219 Coupon

Acoustic Emission Signal Analysis and Event Extraction through Tuned Wavelet Packet Transform and Continuous Wavelet Transform While Tensile Testing the AA 2219 Coupon

Monitoring friction related surface degradation using acoustic emission technique

Tribolumen: A Tribometer for A Correlation Between AE Signals and Observation of Tribological Process in Real-Time—Application to A Dry Steel/Glass Reciprocating Sliding Contact

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