Research on electromagnetic radiation (EMR) waveform characteristics of coal failure process using Hilbert-Huang transform (HHT)

Yin, Shiping; Song, Dazhao; Li, Jie; He, Xueqiu; Qiu, Liming; Lou, Quan; Wei, Menghan; Liu, Yang

doi:10.1016/j.measurement.2021.110195

Cited by 23 publications

(7 citation statements)

References 38 publications

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“…The frequency information of the AE signal can be obtained by transforming the time–amplitude signal with the Fourier transform method. 42 The peak frequency (also called dominant frequency) and frequency centroid (the gravity of the frequency spectrum) illustrated in Figure 4 B are two important parameters reflecting the frequency information of the AE signal, which were used to distinguish the different rocks. 43 In this study, the distributions of the peak frequency and frequency centroid during the intact and deformed coal failure are investigated and displayed in Figure 6 .…”

Section: Resultsmentioning

confidence: 99%

Time–Frequency Characteristics and Evolution Law of Acoustic Emission Signals during the Deformation and Failure of Deformed Coal

et al. 2023

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The research on the time−frequency characteristics and evolution law of acoustic emission (AE) signals during deformed coal failure is more conducive to understand the damage mechanism of coal. In this study, the experiments of AE monitoring during the intact and deformed coal failure were first conducted under loading axial stress and unloading confining stress conditions. Based on the evolution characteristics of volume strain and AE event rate, the damage process of coal was divided into three stages: nonfracture development stage, stable development stage of fracture, and unstable development stage of fracture. The distribution and evolution of AE waveform time−frequency properties under different damage processes were then analyzed and discussed. Besides, the evolution of the average value of different time−frequency parameters per 200 s for the intact coal and per 25 s for the deformed coal was discussed. The results show that the amplitude of most AE events stabilizes in 40−50 dB during the intact and deformed coal failure. The average amplitude of the deformed coal has an approximate positive correlation with the loading stress. The percentage of AE events with longer duration and rise time increases suddenly before the peak stress for the intact coal and after the peak stress for the deformed coal, which corresponds to the abrupt increase property of the average duration and rise time. For the frequency properties, the peak frequency and frequency centroid of the intact coal are distributed within 50−125 and 75−150 kHz, with those of the deformed coal located within 20−120 and 80−130 kHz, respectively. The average peak frequency and frequency centroid of the intact coal show an upward trend except for the initial fracture closure stage, while the average peak frequency and average frequency centroid of the deformed coal present a downward trend before the peak stress and have a smaller growth after the peak stress. According to the above-mentioned analysis, the sudden increase of the average duration and rise time, the lower average peak frequency, and the lower frequency centroid can be regarded as the precursor for the instability and failure of deformed coal. This research can provide a new idea and theoretical guidance for the early warning of outbursts.

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Section: Resultsmentioning

confidence: 99%

Time–Frequency Characteristics and Evolution Law of Acoustic Emission Signals during the Deformation and Failure of Deformed Coal

et al. 2023

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“…The generation mechanism of EMR is complex. For the generation mechanism of EMR, previous researchers have proposed various hypotheses, such as the crack propagation effect, 45,46 piezoelectric effect, 47 friction effect and 48 electromotive effect. 49 The stress drop is mainly related to the nucleation and propagation of cracks.…”

Section: Mechanism Analysis Of the Acoustic-electrical Energy Release...mentioning

confidence: 99%

Structural health monitoring of building rock based on stress drop and acoustic‐electric energy release

Yin

Song

et al. 2021

Structural Contr & Hlth

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“…Arslan and Karhan 33 classified the healthy and diseased phonocardiogram (PCG) signals based on the HHT method and machine learning algorithms. Yin et al 34 used the HHT method to analyze the electromagnetic radiation (EMR) waveform characteristics of the coal failure process.…”

Section: Introductionmentioning

confidence: 99%

Research on improved modal parameter identification method using Hilbert-Huang transform

Zhang

Chen

Yan

et al. 2023

Measurement and Control

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In the wind tunnel test, the full-bridge aeroelastic model needs to simulate both the shape and dynamic characteristics of the real bridge, and modal parameters are key dynamic parameters. Therefore, it is essential to identify the modal parameters of the model accurately. To get accurate modal parameters of the long-span bridge model in the wind tunnel test, the applications of the Hilbert-Huang transform for modal parameter identification were analyzed in this paper. Then a band-pass filter is designed to filter the original signal so that the intrinsic mode function obtained by empirical mode decomposition can satisfy the single-component signal requirement and eliminate the mode mixing effect effectively. Meanwhile, the endpoint data extension method based on SVM (Support Vector Machine) was presented to restrain the end effects of empirical mode decomposition. Finally, taking the Oujiang Bridge as the engineering background, the improved algorithm was applied to modal parameter identification of the bridge under ambient excitation. The modal parameters such as modal frequency and damping ratio were obtained. The reliability of the improved method was verified by comparing the identified modal parameters with the results of the finite element method, and it turns out that the improved method can reduce the frequency identification error of vertical bend, lateral bend, and torsion to 1.01%, 4.07%, and 1.68%. The results indicated that the improved method based on the Hilbert-Huang transform can accurately identify the main modal parameters of the structure and can be better applied to identify the modal parameters of long-span bridge structures.

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Research on electromagnetic radiation (EMR) waveform characteristics of coal failure process using Hilbert-Huang transform (HHT)

Cited by 23 publications

References 38 publications

Time–Frequency Characteristics and Evolution Law of Acoustic Emission Signals during the Deformation and Failure of Deformed Coal

Time–Frequency Characteristics and Evolution Law of Acoustic Emission Signals during the Deformation and Failure of Deformed Coal

Structural health monitoring of building rock based on stress drop and acoustic‐electric energy release

Research on improved modal parameter identification method using Hilbert-Huang transform

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