Energy spectral density characterization of microseismic events in potash mines

Errington, Angus F. C.; Daku, B.L.F.; Prugger, Arnfinn; Dodds, D.E.

doi:10.1016/j.measurement.2008.06.007

Cited by 4 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In previous studies, the mathematical analysis method was extensively applied in to analyze the distribution of the main frequency of MS signals. Ge [32] and Errington et al [33] analyzed the energy spectral density characterization of MS events in two potash mines and found that peak frequency of MS signals is approximately 38 Hz or 54 Hz. Lu et al [34] studied the spectrum characteristics of MS signals monitored in situ, such as coal and gas outburst, rock burst, pressure release blasting, etc., and found that before a coal and gas outburst occurred, the low-frequency component of 0-10 Hz changed significantly, and the relatively high-frequency component of 90-240 Hz increased correspondingly.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation on Time-Frequency Characteristics of Microseismic Signals in the Damage Evolution Process of Coal and Rock

Yang

Rui

et al. 2020

Energies

View full text Add to dashboard Cite

The deformation and failure of coal and rock materials is the primary cause of many engineering disasters. How to accurately and effectively monitor and forecast the damage evolution process of coal and rock mass, and form a set of prediction methods and prediction indicators is an urgent engineering problems to be solved in the field of rock mechanics and engineering. As a form of energy dissipation in the deformation process of coal and rock, microseismic (MS) can indirectly reflect the damage of coal and rock. In order to analyze the relationship between the damage degree of coal and rock and time-frequency characteristics of MS, the deformation and fracture process of coal and rock materials under different loading modes was tested. The time-frequency characteristics and generation mechanism of MS were analyzed under different loading stages. Meanwhile, the influences of properties of coal and rock materials on MS signals were studied. Results show that there is an evident mode cutoff point between high-frequency and low-frequency MS signals. The properties of coal and rock, such as the development degree of the original fracture, particle size and dense degree have a decisive influence on the amplitude, frequency, energy and other characteristic parameters of MS signals. The change of MS parameters is closely related to material damage, but has no strong relation with the loading rate. The richness of MS signals before the main fracture depends on the homogeneity of materials. With the increase of damage, the energy release rate increases, which can lead to the widening of MS signals spectrum. The stiffness and natural frequency of specimens decreases correspondingly. Meanwhile, the main reason that the dominant frequency of MS detected by sensors installed on the surface of coal and rock materials is mainly low-frequency is friction loss and the resonance effect. In addition, the spectrum and energy evolution of MS can be used as a characterization method of the damage degree of coal and rock materials. Furthermore, the results can provide important reference for prediction and early warning of some rock engineering disasters.

show abstract

Section: Introductionmentioning

confidence: 99%

Experimental Investigation on Time-Frequency Characteristics of Microseismic Signals in the Damage Evolution Process of Coal and Rock

Yang

Rui

et al. 2020

Energies

View full text Add to dashboard Cite

show abstract

“…However, it is commonly found that microseismic focus energy obtained from the energy density method is relatively defective and is not reliable enough [20,21]. As obtained from the idealized theoretical model, focus energy computation is easily influenced by geological difference, manual operation, and firmware performance [22,23]. Relative dispersion of individual focus energy obtained from different channels is great with the high dependency on the physical properties of rock medium.…”

Section: Introductionmentioning

confidence: 99%

Focus Energy Determination of Mining Microseisms Using Residual Seismic Wave Attenuation in Deep Coal Mining

Zhang

Liu

Chen

et al. 2018

Shock and Vibration

View full text Add to dashboard Cite

Based on the energy attenuation characteristics of residual wave in deep rock, a method was developed to determine the microseismic focus energy. Differential energy loss in infinitesimal spreading distance is logically deduced, upon which energy attenuation equation was established. With a logarithmic transformation, a linear relation of the residual seismic energy with distance is formulated. Its intercept was used to determine the microseismic focus energy. The result is compared with that determined by the energy density method. The reliability of the determined focus energy and the impact of the built-in velocity threshold on the residual wave energy computation are discussed. Meanwhile, the energy absorption coefficient used for representing the absorption characteristics of the rock medium in the mining region under study is also clarified. Key findings show that the microseismic focus energy confirmed by the residual wave attenuation is reliable. The result’s accuracy is quite high, especially for the events in deep rock with great homogeneity. The developed focus energy computation method is closely dependent on the integrity of waveform, accuracy of repositioning, and reliability of effective components extraction. The new method has been shown to be effective and practical.

show abstract

An Subarea Localization Algorithm based on Combination Features using Representative Audio Fingerprint

Wang

Luo

et al. 2019

2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

View full text Add to dashboard Cite

Energy spectral density characterization of microseismic events in potash mines

Cited by 4 publications

References 3 publications

Experimental Investigation on Time-Frequency Characteristics of Microseismic Signals in the Damage Evolution Process of Coal and Rock

Experimental Investigation on Time-Frequency Characteristics of Microseismic Signals in the Damage Evolution Process of Coal and Rock

Focus Energy Determination of Mining Microseisms Using Residual Seismic Wave Attenuation in Deep Coal Mining

An Subarea Localization Algorithm based on Combination Features using Representative Audio Fingerprint

Contact Info

Product

Resources

About