A fuzzy comprehensive evaluation methodology for rock burst forecasting using microseismic monitoring

Cai, Wu; Li, Dou; Zhang, Min; Cao, Wenzhuo; Shi, Ji‐Quan; Feng, Longfei

doi:10.1016/j.tust.2018.06.029

Cited by 191 publications

(73 citation statements)

References 49 publications

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“…[40][41][42] In this section, AE parameters were selected to characterize the damage characteristics of coal samples under cyclic loading. [40][41][42] In this section, AE parameters were selected to characterize the damage characteristics of coal samples under cyclic loading.…”

Section: Ae Characteristics Of Coal Samples Under Cyclic Loadingmentioning

confidence: 99%

“…Previous study has shown that the damage process of coal and rock can be effectively reflected by AE parameters. [40][41][42] In this section, AE parameters were selected to characterize the damage characteristics of coal samples under cyclic loading. Figure 7 clearly illustrates the variation of AE ringing counts of coal samples under cyclic loading with different stress levels.…”

Section: Ae Characteristics Of Coal Samples Under Cyclic Loadingmentioning

confidence: 99%

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Mechanical response characteristics and permeability evolution of coal samples under cyclic loading

Yang

Cao

Cheng

et al. 2019

Energy Science & Engineering

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Understanding the stress‐cracks‐permeability evolution law inside coal body under cyclic loading is significant to optimize the gas extraction technology and gas disasters prevention technology. In order to explore the influence of mining cyclic stress on the mechanical behavior and permeability variation of gas‐bearing seams, the experiments on permeability evolution, deformation law, and acoustic emission (AE) characteristics of coal samples under cyclic loading with different loading stress level and different loading frequency were carried out. These results indicate that the higher loading stress level, the shorter the fatigue life of coal sample. With the increase of the loading stress level, the change rate of permeability became higher and the relation curves between permeability and loading cycles developed from “U” to “V,” which can be defined and divided into three stages, for example, decrease stage, stable stage, and increase stage. And the permeability in the decrease stage can be modeled as a power function of the loading cycles, while the permeability in the increase stage can be modeled as an exponential function of the loading cycles. Besides, the loading stress level has a significant on the permeability, while the loading frequency has little impact on the permeability evolution. In the process of coal deformation under cyclic loading, the strain development of strain coal samples was in the shape of inverted “S,” while the variation of the peak values of corresponding AE ring counts presented “U” type. In addition, there was a good correlation between the permeability and the AE parameters of coal samples, which provide a new sight into the dynamic variation process of the stress‐cracks‐permeability evolution inside coal body under cyclic loading.

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Section: Ae Characteristics Of Coal Samples Under Cyclic Loadingmentioning

confidence: 99%

Section: Ae Characteristics Of Coal Samples Under Cyclic Loadingmentioning

confidence: 99%

Mechanical response characteristics and permeability evolution of coal samples under cyclic loading

Yang

Cao

Cheng

et al. 2019

Energy Science & Engineering

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“…Research findings reveal that the higher the strain energy that can be stored in coal-rock masses, the higher its tendency to burst [4,15]. It has been observed in many coal mines that rockbursts start at a depth of 600-800 m [17][18][19]. As shown in Figure 1, Table 1, and Figure 2, rockbursts frequently occurred both in coal seams 11 and 17 of Xing'an Coal Mine when the mining depths approached 600 m in the two coal seams, while there were no rockbursts before this depth.…”

Section: Static Stressmentioning

confidence: 96%

A Novel Experimental Technique to Simulate Shock Behaviour and Bursting Failure of Roadways

Wang

Gong

et al. 2019

Shock and Vibration

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Rockburst is a sudden and dynamic failure of rock that can cause serious injury to miners and damage to the underground excavations. Stress path, dynamic disturbance, and support system play important and different roles in the generation processes of rockbursts, resulting rockbursts with variety of reasons and failure modes. A test facility that was capable of simulating such factors was developed to study shock behaviour and bursting failure of roadways. e results demonstrate that the modeled roadway was in good condition and retained a shock resistance capacity after three drop loads. Until the acceleration amplitude increased to a certain level at the time of the fourth dynamic loading, sudden bursting failure of modeled roadway occurred. Many large fragments ejected from the upper and middle regions of the roadway, accompanied with loud noise. A deep pit was observed after the bursting failure. e axial of the fan-shaped pit had an angle above the vertical. In addition, shock behaviour of the modeled roadway had been changed by the anchor-net support. Significant differences appeared between the acceleration signals measured in two roadway sections with and without the anchor-net support. e acceleration magnitude of the supported roadway section was strongly reduced by the presence of the anchor-net support. Even when the unsupported roadway section underwent a sudden injection failure, the roadway with anchor-net support was in good condition. is study may eventually lead to a methodology for studying the rockbursting resistance capacity of underground roadways.

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“…The proposed model has been evaluated using the Molchan statistical procedure by comparing complicated reasoning procedure of the forecasting model with knowledge simulation provided by human experts using the datasets of Iran. A rock burst forecasting model has been presented in [13] by studying the seismic features of coal mining in China. In this study, Gaussian shaped membership function has been combined with the exponential distribution function using reliability theory.…”

Section: Fuzzy Expert System (Fes)mentioning

confidence: 99%

“…The literature survey reveals that different approaches of expert systems including fuzzy, rule-based, neuro-fuzzyand machine/deep learning methods have been used to forecast future earthquake from historic and instrumental data. In practice, ES have also been efficiently used for risk analysis and assessment in multiple areas such as, information technology (IT) [10], engineering [11], economics, healthcare [12], and civil engineering [13][14][15]. The motivation behind applying expert system technique for earthquake prediction lies in its noticeable effectiveness and reliability [16] of such approaches in other disciplines.…”

Section: Introductionmentioning

confidence: 99%

Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

2020

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Earthquake is one of the most hazardous natural calamity. Many algorithms have been proposed for earthquake prediction using expert systems (ES). We aim to identify and compare methods, models, frameworks, and tools used to forecast earthquakes using different parameters. We have conducted a systematic mapping study based upon 70 systematically selected high quality peer reviewed research articles involving ES for earthquake prediction, published between January 2010 and January 2020.To the best of our knowledge, there is no recent study that provides a comprehensive survey of this research area. The analysis shows that most of the proposed models have attempted long term predictions about time, intensity, and location of future earthquakes. The article discusses different variants of rule-based, fuzzy, and machine learning based expert systems for earthquake prediction. Moreover, the discussion covers regional and global seismic data sets used, tools employed, to predict earth quake for different geographical regions. Bibliometric and meta-information based analysis has been performed by classifying the articles according to research type, empirical type, approach, target area, and system specific parameters. Lastly, it also presents a taxonomy of earthquake prediction approaches, and research evolution during the last decade.

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A fuzzy comprehensive evaluation methodology for rock burst forecasting using microseismic monitoring

Cited by 191 publications

References 49 publications

Mechanical response characteristics and permeability evolution of coal samples under cyclic loading

Mechanical response characteristics and permeability evolution of coal samples under cyclic loading

A Novel Experimental Technique to Simulate Shock Behaviour and Bursting Failure of Roadways

Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

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