Effects of micro-structure on fatigue crack propagation and acoustic emission behaviors in a micro-alloyed steel

Han, Zhiyuan; Luo, Hongyun; Zhang, Yubo; Cao, Jingwei

doi:10.1016/j.msea.2012.08.138

Cited by 56 publications

(31 citation statements)

References 26 publications

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“…In the past, researchers have correlated AE signals to large fatigue crack propagation in metals. A popular method for doing so has been to correlate the number times the AE voltage signal crosses a certain amplitude threshold, referred to as counts, and the crack growth rate using a power law relationship [4][5][6][7][8][9][10][11][12][13]. In addition, other AE features have been studied as fatigue cracks grow, such as amplitude [11,12,14,15], energy [14,15], rise time [11,[15][16][17], and average frequency [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…While methods for estimating stable crack growth rate based on AE signals are well established, estimating crack damage at the smallest possible scale is most desirable. This idea has motivated researchers to better understand wave dynamics of AE signals within single crystals [18][19][20][21] and polycrystalline materials [11,12,15,[22][23][24][25][26][27][28][29][30] (see [31] for further discussion on past AE literature). From these studies, researchers concluded that AE activity is present during initial damage due to dislocation motion and microcracks, and various AE features can be correlated to damage.…”

Section: Introductionmentioning

confidence: 99%

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Damage Assessment Using Information Entropy of Individual Acoustic Emission Waveforms during Cyclic Fatigue Loading

et al. 2017

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Featured Application: The work presented in this paper outlines three methods to analyze individual acoustic emission waves emitted within a cyclically-loaded metallic structure. Upon further development, one potential application of the proposed analysis methods would be to aid in estimating the remaining useful life of aircraft structures.Abstract: Information entropy measured from acoustic emission (AE) waveforms is shown to be an indicator of fatigue damage in a high-strength aluminum alloy. Three methods of measuring the AE information entropy, regarded as a direct measure of microstructural disorder, are proposed and compared with traditional damage-related AE features. Several tension-tension fatigue experiments were performed with dogbone samples of aluminum 7075-T6, a commonly used material in aerospace structures. Unlike previous studies in which fatigue damage is measured based on visible crack growth, this work investigated fatigue damage both prior to and after crack initiation through the use of instantaneous elastic modulus degradation. Results show that one of the three entropy measurement methods appears to better assess the damage than the traditional AE features, whereas the other two entropies have unique trends that can differentiate between small and large cracks.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Damage Assessment Using Information Entropy of Individual Acoustic Emission Waveforms during Cyclic Fatigue Loading

et al. 2017

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“…To achieve the signal acquistion, the acoustic emission sensor converts the material damage signal generated by the crack propagation into an electrical signal. Several works in literature have shown that acoustic emission techniques can be used to detect and evaluate crack initiation and to show the dynamic characteristics in time [7,8].In the early studies of various scholars, the initial crack size of V-shaped groove varied from 0.05 mm to 0.5 mm [9]. In this paper, the initial crack size of the V-shaped groove was set to 0.3mm, and the acoustic emission technique was used to accurately determine the cracking time of the metal bar with V-shaped groove.…”

Section: Acoustic Emission Test Process For the Crack Initiation Of Vmentioning

confidence: 99%

Study on the Cracking Time in Low-stress Precision Cropping Based on Acoustic Emission Technology

Zhang¹,

Li²,

Du³

et al. 2018

dteees

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Abstract. The high-speed centrifuge and low-stress precision cropping is the technology which makes use of the stress concentration effect of the prefabricated V-shaped groove on the surface of the metal bar and relies on the expansion of the crack to achieve precision cropping. This paper applies the acoustic emission testing technology to monitor the entire process of low-stress precision cropping in order to solve the problem that the cracking time of V-shaped groove tip cannot be precisely determined during the low-stress cropping. It is concluded that the acoustic emission signal can be used to describe the crack damage process of V-shaped groove tip, providing better cross-section quality. Based on this, the cracking time of V-shaped groove tip is further determined, which better meets the requirements of low-stress precision cropping.

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“…The crack initiation has been shown to be accompanied by a significant increase in the peak amplitude, cumulative count and energy of the AE [5]. Han et al [6] [7], suggested AE features such as count rate, peak amplitude and risetime are sensitive to three different stages of fatigue; stage 1 fatigue crack initiation, stage 2 slow fatigue crack propagation and stage 3 rapid crack propagation. Han et al [7] [8] distinguished other cracking mechanisms based on peak amplitude and rise time observation such as twinning, crack extension, cleavage facture, plastic zone activity, ligament shearing between micro-voids and micro-cracks.…”

Section: Introductionmentioning

confidence: 99%

Identification of fatigue damage evolution in 316L stainless steel using acoustic emission and digital image correlation

et al. 2018

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Abstract.One of the main objectives of Acoustic Emission (AE) monitoring is to identify approaching critical stage of damage in the structure before it fails. State-of-the-art AE analysis is done on the features in both the time and frequency domains. Many features such as centroid frequency, duration, rise-time, count and energy are dependent on acquisition settings; threshold and timing parameters. Incorrect acquisition settings may result in inaccurate classification of the AE source. This work proposes a new feature in the time domain signal based on 2 nd order Renyi's entropy, which proves to be efficient in identifying different stages of damage. Renyi's entropy is a measure of uncertainty or randomness of the signals and is directly derived from the distribution of signal amplitude. Therefore, it is independent of threshold and timing parameters. The validity of the proposed parameter is investigated by performing AE monitoring during fatigue endurance test of 316L stainless steel. Digital Image Correlation (DIC) and global strain monitoring was carried out to relate material damage with AE activity. The result shows Renyi's entropy to be an effective measure to identify critical stages of damage in the material.

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Effects of micro-structure on fatigue crack propagation and acoustic emission behaviors in a micro-alloyed steel

Cited by 56 publications

References 26 publications

Damage Assessment Using Information Entropy of Individual Acoustic Emission Waveforms during Cyclic Fatigue Loading

Damage Assessment Using Information Entropy of Individual Acoustic Emission Waveforms during Cyclic Fatigue Loading

Study on the Cracking Time in Low-stress Precision Cropping Based on Acoustic Emission Technology

Identification of fatigue damage evolution in 316L stainless steel using acoustic emission and digital image correlation

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