Early Identification of Abnormal Regions in Rock-Mass Using Traveltime Tomography

Dong, Longjun; Pei, Zhongwei; Xie, Xin; Zhang, Yihan; Yan, Xianhang

doi:10.1016/j.eng.2022.05.016

Cited by 41 publications

(13 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The LFVS method can be combined with other methods to achieve better water inrush prevention effect. Combined with tomography method, the fault location accuracy can be further improved (Dong et al, 2022). As a typical water and gas channel (Chen et al, 2021;Tian et al, 2022), the fault can be further monitored by acoustic emission method after positioning by LFVS method (Rui et al, 2022a;Rui et al, 2022b).…”

Section: Discussionmentioning

confidence: 99%

A fault location method based on polarization analysis for coal mine

Zeng

Wang²,

Xin³

et al. 2023

Front. Earth Sci.

View full text Add to dashboard Cite

A fault is a main cause for water inrush in coal mines. The detection of faults plays an important role in the prevention and governance of water inrush in coal mines. It is hard to determine the direction of seismic wave propagation under the condition of full space of mines, leading to difficulty in accurate fault detection. This paper compares and analyzes the polarization information extraction capability of time-domain polarization analysis, frequency-domain polarization analysis, and time-frequency (TF)-domain polarization analysis, and proposes a TF-domain polarization analysis-based method for locating faults in coal mines. Firstly, the polarization analysis of signals mixed in the time domain was carried out. The results of three kinds of polarization analysis show that the TF-domain polarization analysis can accurately determine the polarization direction of multi-type signals in the case of aliasing. Secondly, a time-space-domain high-order three-dimensional three-component numerical simulation experiment was conducted. The TF-domain polarization analysis was adopted to extract the polarization information of each geophone and locate the fault. The error of the predicted fault strike was 0.16°, and the distance deviation was about 2.03%. Finally, in-situ three-component seismic signals of coal mine were used to predict the location and strike of fault. The data from on-site actual drilling verified the effectiveness of the mine fault location method based on the TF-domain polarization analysis. The predicted fault strike is consistent with the drilling data, and the distance deviation is about 5.5%.

show abstract

Section: Discussionmentioning

confidence: 99%

A fault location method based on polarization analysis for coal mine

Zeng

Wang²,

Xin³

et al. 2023

Front. Earth Sci.

View full text Add to dashboard Cite

show abstract

“…Hyperspectral remote sensing is uniquely positioned to acquire abundant spectral information beyond normal optical image sensors and has been recognized as an important avenue to address challenges for many applications [ 1 ], such as environmental monitoring [ 2 ], mine exploration [ 3 ], precision agriculture [ 4 ], seed viability study [ 5 ], biotechnology [ 6 ], psychophysical studies [ 7 ], pharmaceuticals [ 8 ], and exploration of oil and gas [ 9 ]. In comparison to other techniques, for example, acoustic emission tomography [ 10 , 11 , 12 ] is an important monitoring method in the minefield utilizing a combination of active and passive sources. The hyperspectral camera does not require direct contact with the object’s surface; therefore, it can be applied to the broader field.…”

Section: Introductionmentioning

confidence: 99%

Active and Low-Cost Hyperspectral Imaging for the Spectral Analysis of a Low-Light Environment

Tang

Song

Gui

et al. 2023

Sensors

View full text Add to dashboard Cite

Hyperspectral imaging is capable of capturing information beyond conventional RGB cameras; therefore, several applications of this have been found, such as material identification and spectral analysis. However, similar to many camera systems, most of the existing hyperspectral cameras are still passive imaging systems. Such systems require an external light source to illuminate the objects, to capture the spectral intensity. As a result, the collected images highly depend on the environment lighting and the imaging system cannot function in a dark or low-light environment. This work develops a prototype system for active hyperspectral imaging, which actively emits diverse single-wavelength light rays at a specific frequency when imaging. This concept has several advantages: first, using the controlled lighting, the magnitude of the individual bands is more standardized to extract reflectance information; second, the system is capable of focusing on the desired spectral range by adjusting the number and type of LEDs; third, an active system could be mechanically easier to manufacture, since it does not require complex band filters as used in passive systems. Three lab experiments show that such a design is feasible and could yield informative hyperspectral images in low light or dark environments: (1) spectral analysis: this system’s hyperspectral images improve food ripening and stone type discernibility over RGB images; (2) interpretability: this system’s hyperspectral images improve machine learning accuracy. Therefore, it can potentially benefit the academic and industry segments, such as geochemistry, earth science, subsurface energy, and mining.

show abstract

“…This method is applicable to microseismic sources localization under complex abnormal arrivals in the rock mass structure of dynamic underground mining. However, with the continuous development and optimization of travel time tomography identification technology, a new method proposed by Dong et al can also be applied to define the potentially risky area [ 11 ]. The development of the real-time monitoring has conversely made the detection of abnormal regions in complex structures a challenging target.…”

Section: Introductionmentioning

confidence: 99%

Risk Field of Rock Instability using Microseismic Monitoringdata in Deep Mining

Dong

Zhu

Yan

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

With the gradual depletion of surface resources, rock instability caused by deep high stressand mining disturbance seriously affects safe mining. To create effective risk management, a rockinstability risk field model using microseismic monitoring data is proposed in this study. Rockinstability risk was presented visually in 3D visualization. The in-situ microseismic monitoringdata was collected and analyzed to make calculation of peak ground velocity (PGV), peak groundacceleration (PGA), energy flux, energy and seismic moment. Indicator weights of PGV, PGA, energyflux are confirmed by using the analytic hierarchy process (AHP) to calculate risk severity. The Copulafunction is then used to solve the joint probability distribution function of energy and seismic moment.Then the spatial distribution characteristics of risk can be obtained by data fitting. Subsequently, thethree-dimensional (3D) risk field model was established. Meanwhile, the established risk field isverified by comparing monitoring data without disturbance and the blasting data with disturbance.It is suggested that the proposed risk field method could evaluate the regional risk of rock instabilityreasonably and accurately, which lays a theoretical foundation for the risk prediction and managementof rock instability in deep mining.

show abstract

Early Identification of Abnormal Regions in Rock-Mass Using Traveltime Tomography

Cited by 41 publications

References 45 publications

A fault location method based on polarization analysis for coal mine

A fault location method based on polarization analysis for coal mine

Active and Low-Cost Hyperspectral Imaging for the Spectral Analysis of a Low-Light Environment

Risk Field of Rock Instability using Microseismic Monitoringdata in Deep Mining

Contact Info

Product

Resources

About