A new qualitative acoustic emission parameter based on Shannon’s entropy for damage monitoring

Chai, Mengyu; Zhang, Zaoxiao; Duan, Qing

doi:10.1016/j.ymssp.2017.08.007

Cited by 108 publications

(53 citation statements)

References 32 publications

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“…A relative measure of entropy based on the Kullback‐Leibler formulation was also investigated in few recent studies showing promising results. This approach was also used for damage monitoring purposes; however, more robust applications should still be defined …”

Section: Introductionmentioning

confidence: 99%

“…This approach was also used for damage monitoring purposes; however, more robust applications should still be defined. 24,27,38,39 This paper attempts to enhance the understanding of the damaging micromechanisms occurring in (pearlitic) DCIs, providing insights into the damage assessment by means of AE testing. A small part of the preliminary results of the study was presented in a report.…”

Section: Introductionmentioning

confidence: 99%

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Characterisation of the damaging micromechanisms in a pearlitic ductile cast iron and damage assessment by acoustic emission testing

D’Angela

Ercolino

Bellini

et al. 2020

Fatigue Fract Eng Mat Struct

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The damaging micromechanisms in a pearlitic (EN‐GJS700‐2) ductile cast iron (DCI) are investigated by means of scanning electron microscope (SEM) analysis and acoustic emission (AE) testing. Monotonic uniaxial tensile tests are performed on microtensile specimens under strain control. SEM analysis is applied under in situ conditions by means of a tensile holder. The multiple damaging micromechanisms are identified, and their evolution along with the mechanical response is characterised. The traditional AE features are found to be qualitatively correlated to the onset of the fracture damage over the elastic behaviour. The information entropy of the AEs evaluated according to both Shannon and Kullback‐Leibler formulations is proven to be well correlated to the ongoing damage and the incipient failure. Tentative failure criteria are finally proposed. The assessment approach is found to be promising for structural health monitoring purposes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characterisation of the damaging micromechanisms in a pearlitic ductile cast iron and damage assessment by acoustic emission testing

D’Angela

Ercolino

Bellini

et al. 2020

Fatigue Fract Eng Mat Struct

View full text Add to dashboard Cite

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“…This technique has been widely used in signal processing [34,35]. Discrete probability distribution in the research performed in [36,37] was based on the frequency of occurrence with a bin width. A comparison between these two techniques in Ref.…”

Section: Renyi's Entropymentioning

confidence: 99%

Identification of fatigue damage evaluation using entropy of acoustic emission waveform

et al. 2019

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Acoustic emission (AE) is a passive nondestructive testing (NDT) technique which is employed to identify critical damage in structures before failure can occur. Currently, AE monitoring is carried out by calculating the features of the signal received by the AE sensor. User-defined acquisition settings (i.e., timing and threshold) significantly affect many traditional AE features such as count, energy, centroid frequency, rise time and duration. In AE monitoring, AE features are strongly related to the damage sources. Therefore, AE features that are calculated due to inaccurate user-defined acquisition settings can result in inaccurately classified damage sources. This work presents a new feature of the signal based on the measure of randomness calculated using second-order Renyi's entropy. The new feature is computed from its discrete amplitude distribution making it independent of acquisition settings. This can reduce the need for human judgement in measuring the feature of the signal. To investigate the effectiveness of the presented feature, fatigue testing is conducted on an un-notched steel sample with simultaneous AE monitoring. Digital image correlation (DIC) is measured alongside AE monitoring to correlate both monitoring methods with material damage. The results suggest that the new feature is sensitive in identifying critical damages in the material.

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“…AE parameter-based approach offers real-time monitoring, whereas AE signal-based approach usually offers analysis in a postprocessing environment. So, it is vital for AE to select an analysis type [30].…”

Section: Introductionmentioning

confidence: 99%

Study on Acoustic Emission Localization of Concrete Using Modified Velocity

Qin

2019

Advances in Civil Engineering

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To improve the accuracy of the acoustic emission (AE) source localization, a new 3D AE source localization method was investigated which used a combination of the modified velocity and the 3D localization algorithm based on the exhaustive method. The wave speed has a significant effect on the AE location results. With the increase of distance, the AE signal seriously attenuated due to the anisotropy of concrete, and the measured velocity changed for various distances. The velocity-distance curves were obtained when employing different water-cement ratios (W/C) and aggregate sizes. However, the current AE location system adopted constant wave velocity. As a result, the error was tremendous. The accuracy of the localization before and after the modified velocity was compared. The 3D localization results showed that compared with the constant wave velocity, the position deviation of the modified velocity was smaller and the localization results with the modified velocity were more accurate.

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A new qualitative acoustic emission parameter based on Shannon’s entropy for damage monitoring

Cited by 108 publications

References 32 publications

Characterisation of the damaging micromechanisms in a pearlitic ductile cast iron and damage assessment by acoustic emission testing

Characterisation of the damaging micromechanisms in a pearlitic ductile cast iron and damage assessment by acoustic emission testing

Identification of fatigue damage evaluation using entropy of acoustic emission waveform

Study on Acoustic Emission Localization of Concrete Using Modified Velocity

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