Acoustic emission in steel failure

Volodin, T. V.; Хасанов, О. Л.; Konovalov, S. V.; Volodin, V. L.; Зуев, Л. Б.

doi:10.3103/s0967091210120053

Cited by 1 publication

(1 citation statement)

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“…Some methods have been proposed to extract the signals related to relevant sources of AE based on: (i) time domain features, 5,6) (ii) frequency domain features 6,7) or (iii) localization of the origin of the AE signal and relating this position with a possible real source of damage. 8,9) In all cases, the filtering process uses characteristics of the waveform ( Fig.…”

Section: Introductionmentioning

confidence: 99%

Filtering of Acoustic Emission Signals for the Accurate Identification of Fracture Mechanisms in Bending Tests

Martínez-González¹,

Picas²,

Garbí³

et al. 2013

Mater. Trans.

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In this manuscript, acoustic emission (AE) analysis is used to identify the fracture mechanisms that take place during a three-point bending test of steel specimens. However, an important source of AE was detected and related to the deformation of the supports and the surface of the steel specimen in contact. This source creates AE signals that are very high in number and amplitude, and prevent determining accurately the onset stress for fracture mechanisms in specimens. A signal filtering is proposed based on the properties of the initial part of the recorded AE waveform, combined with a linear localization. The filtering successfully allows the AE signals to be classified according to their source as background noise, damage due to contact of the specimen surface to the supports and fracture mechanisms occurring in the specimen microstructure as a result of the bending test. The aforementioned filter has been successfully applied in case of a cold work tool steel DIN 1.2379 to determine accurately the stress level at which the first damaging mechanisms start to occur in the microstructure in situ during the three-point bending test. Filtered AE signal results indicating damage in the microstructure have been corroborated by inspection of the specimen's surface in a Confocal Microscope. In default of using the proposed filter, unfiltered signals have been estimated to lead to an overestimation of critical stresses of about 20%, what is undesirable for most applications.

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