Wavelet threshold de-noising of rock acoustic emission signals subjected to dynamic loads

Liu, Xiling; Liu, Zhou; Li, Xibing; Rao, M. Venu Gopala; Dong, Longjun

doi:10.1088/1742-2140/aaacad

Cited by 22 publications

(16 citation statements)

References 26 publications

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“…Then, wavelet de-noising and two-layer lifting wavelet decomposition and reconstruction techniques can be used to process the screened waveforms with the largest centroid frequency collected by the AE sensors P2, P3, P7, and P10. It was found that Daubechies and Symlets wavelet series are more suitable for AE signal analysis in dynamic loading tests [38], and Sym5 wavelet was considered to be the most suitable candidate for soft threshold filtering [39]. Thus, the signals collected by AE sensors was decomposed into five layers using the Sym5 wavelet, and the threshold processing was adjusted according to the noise level of wavelet decomposition in each layer.…”

Section: Variation Of Ae and Strain In Various Working Casesmentioning

confidence: 99%

Investigation on Rupture Initiation and Propagation of Traffic Tunnel under Seismic Excitation Based on Acoustic Emission Technology

Liu

Zeng

Fan

et al. 2022

Sensors

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Traffic tunnels are important engineering structures in transportation, and their stability is critical to traffic safety. In particular, when these tunnels are in an earthquake-prone area, the rupture process under seismic excitation needs to be studied in depth for safer tunnel design. In this paper, based on a construction project on the Nairobi-Malaba railway in East Africa, a laboratory shaking table test with 24 working cases of seismic excitation on a mountain tunnel is designed, and the acoustic emission (AE) technique is employed to investigate the tunnel rupture process. The results show that the high frequency components between 20 and 30 kHz of AE signals are the tunnel rupturing signals under the seismic excitation under such conditions. The tunnel vault and the arch foot are prone to rupture during the seismic excitation, and the initial rupture in the arch foot and vault of the tunnel occur under the horizontal and vertical Kobe wave seismic excitation, respectively, with a maximum acceleration of 0.4 g. After the rupture initiation, the tunnel arch foot continues to rupture in the subsequent working cases regardless of whether the excitation direction is horizontal or vertical, while the tunnel vault does not rupture continuously with the implementation of the subsequent excitations. Moreover, the Kobe seismic wave has a higher degree of damage potential to underground structures than the El seismic wave.

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Section: Variation Of Ae and Strain In Various Working Casesmentioning

confidence: 99%

Investigation on Rupture Initiation and Propagation of Traffic Tunnel under Seismic Excitation Based on Acoustic Emission Technology

Liu

Zeng

Fan

et al. 2022

Sensors

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“…Different wavelet bases provide different results. Various wavelet bases have been applied to wavelet packet analysis, such as Symlets basis, Morlet basis, and Meyer basis [38][39][40][41][42]. In view of the complexity and diversity of AE signals, wavelet bases with symmetry and tight support should be selected [43,44].…”

Section: Wavelet Packet Frequency Band Decomposition Of the P-signalsmentioning

confidence: 99%

Time–Frequency Domain Characteristics of Acoustic Emission Signals and Critical Fracture Precursor Signals in the Deep Granite Deformation Process

Zhang

Liu

et al. 2021

Applied Sciences

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To study the crack evolution law and failure precursory characteristics of deep granite rocks in the process of deformation and failure under high confining pressure, granite samples obtained from a depth of 1150 m are tested using a TAW-2000 triaxial hydraulic servo testing machine and a PCI-II acoustic emission monitoring system. Based on the stress–strain curve and IET function, the loading process of the sample is divided into five stages: crack closure, linear elastic deformation, microcrack generation and development, macroscopic fracture generation and energy surge, and post-peak failure. The evolution trend and fracture evolution law of the acoustic emission signal event interval function in different stages are analyzed. In particular, the signals with an amplitude greater than 85 dB, a peak frequency greater than 350 kHz, and a frequency centroid greater than 275 kHz are defined as the failure precursor signals before the rock reaches the peak stress. The defined precursor signal conditions agree well with the experimental results. The time–frequency analysis and wavelet packet decomposition of the precursor signal are performed on the extracted characteristic signal of the failure precursor. The results show that the time-domain signal is in the form of a continuous waveform, and the frequency-domain waveform has multi-peak coexistence that is mainly concentrated in the high-frequency region. The energy distribution obtained by the wavelet packet decomposition of the characteristic signal is verified with the frequency-domain waveform. The energy distribution of the signal is mainly concentrated in the 343.75–375 kHz frequency band, followed by the 281.25–312.5 kHz frequency band. The energy proportion of the high-frequency signal increases with the confining pressure.

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“…By substituting formulas (8) and (10) into formula (5), we obtain the expression describing the improved statistical damage constitutive model:…”

Section: Advances In Civil Engineeringmentioning

confidence: 99%

“…Wang and Yang [9] studied the dynamic fracture toughness of coal rocks under the action of an impact load. Liu et al [10] assessed the acoustic emission wavelet denoising threshold of rocks under a dynamic load. Scherbakov and Chmel [11] investigated the impact fracture characteristics of granite at different temperatures.…”

Section: Introductionmentioning

confidence: 99%

An Improved Statistical Damage Constitutive Model for Granite under Impact Loading

Zhao

Yang

et al. 2019

Advances in Civil Engineering

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To study the impact properties of granite, the parameters (including the stress-strain curve, elasticity modulus, peak strength, and peak strain) of the test pieces in each group were determined via standard split-Hopkinson pressure bar tests. The results revealed that the prepeak stress-strain curves are approximately linear; the postpeak stress-strain curve declined sharply and exhibited the characteristics of brittle material failure after the stress exceeded the peak strength. In terms of the specimen form following failure, for increasing strain rate, the granite specimen became increasingly fragmented after failure. In addition, the single-parameter statistical damage constitutive model was improved, and a double-parameter statistical damage constitutive model for describing the total stress-strain curve of granite under the action of impact loading was proposed. The parameters of the statistical damage model, m and a, were obtained via fitting. The results revealed that the parameter m decreases with increasing elasticity modulus, whereas the parameter a increases. Similarly, the peak strength and the peak strain increased (in general) with increasing strain rate.

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Wavelet threshold de-noising of rock acoustic emission signals subjected to dynamic loads

Cited by 22 publications

References 26 publications

Investigation on Rupture Initiation and Propagation of Traffic Tunnel under Seismic Excitation Based on Acoustic Emission Technology

Investigation on Rupture Initiation and Propagation of Traffic Tunnel under Seismic Excitation Based on Acoustic Emission Technology

Time–Frequency Domain Characteristics of Acoustic Emission Signals and Critical Fracture Precursor Signals in the Deep Granite Deformation Process

An Improved Statistical Damage Constitutive Model for Granite under Impact Loading

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