Gravitational Search Algorithm for Microseismic Source Location in Tunneling: Performance Analysis and Engineering Case Study

Ma, Chunchi; Jiang, Yupeng; Li, Tianbin

doi:10.1007/s00603-019-01809-5

Cited by 18 publications

(11 citation statements)

References 18 publications

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“…While the stiffness and natural frequency of specimens decreased correspondingly, and friction loss and resonance effect caused that the dominant frequency of MS detected by sensors installed on the surface of coal and rock materials was mainly of low frequency. (4) The relationship between the change of MS parameters, such as the amplitude, energy and cumulative energy and loading rate had no obvious regularity. The amplitude of the MS signals generated by the raw coal specimens was approximately equal to that of the cement specimens, both of which were higher than the shaped coal specimens.…”

Section: Discussionmentioning

confidence: 99%

“…As a form of energy dissipation in the process of coal and rock damage, MS accompany the whole process of deformation and fracture of coal and rock and can reflect the internal damage evolution process of coal and rock in real time. MS monitoring technology has been widely applied to source location [3,4], safety design [5], prediction and early warning of disasters [6,7], etc. in mine, tunnel cavern, diversion tunnel of hydropower station, underground storage cavern, slope excavation, etc.…”

Section: Introductionmentioning

confidence: 99%

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

Yang

Rui

et al. 2020

Energies

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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.

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Section: Discussionmentioning

confidence: 99%

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

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“…This algorithm is widely used to solve various problems. For example, the GSA was applied to optimize parameters in a geothermal power generation system in the study of Özkaraca and Keçebaş [35], to determine the location of a microseismic source in order to warn about explosions in tunnels in [36]. Mahanipour and Nezamabadi-pour described the use of GSA for the automatic creation of computer programs in [37] and the feature construction in [38].…”

Section: Training a Classifier With The Gravitational Search Algorithmmentioning

confidence: 99%

Application of the Gravitational Search Algorithm for Constructing Fuzzy Classifiers of Imbalanced Data

et al. 2019

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The presence of imbalance in data significantly complicates the classification task, including fuzzy systems. Due to a large number of instances of bigger classes, instances of smaller classes are not recognized correctly. Therefore, additional tools for improving the quality of classification are required. The most common methods for handling imbalanced data have several disadvantages. For example, methods for generating additional instances of minority classes can worsen classification if there is a strong overlap of instances from different classes. Methods that directly modify the fuzzy classification algorithm lead to a decline in the interpretability of the model. In this paper, we study the efficiency of the gravitational search algorithm in the tasks of selecting the features and tuning the term parameters for fuzzy classifiers of imbalanced data. We consider only data with two classes and apply the algorithm based on extreme values of classes to construct models with a minimum number of rules. In addition, we propose a new quality metric based on the sum of the overall accuracy and the geometric mean with the presence of a priority coefficient between them.

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“…e microseisms determine the failure characteristics and mechanism of rockburst [19][20][21][22][23][24]. To date, the interactive mechanism between microseismic activity and supporting structure remains less investigated, and the microseismic activity is rarely used to guide support strategy.…”

Section: Introductionmentioning

confidence: 99%

Effect of the Initial Support of the Tunnel on the Characteristics of Rockburst: Case Study and Mechanism Analysis

Fan²,

et al. 2022

Advances in Civil Engineering

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Rockburst is still a stubborn disease in the field of engineering geology. The present research pays more attention to the influence of geological conditions on rockburst and less to the influence of type and stiffness of engineering support on rockburst. We explore the influence of support stiffness from weak to strong on rockburst and reveal the characteristics of fracture and microseismicity during rockburst through microseismic monitoring and numerical simulation. The main results and conclusions can be drawn: (1) Strong stiffness support makes the surrounding rock accumulates higher energy before rockburst. The evolution of microseismicity and its indexes can be used as precursors of potentially strong rockburst. (2) Strong stiffness support is easy to concentrate high stress under the action of surrounding rock pressure, and it is easy to fail under the disturbance of external load. This will produce a “sudden unloading effect” on the surrounding rock mass and may lead to a more serious rockburst. Numerical simulation verifies the existence of that effect and are consistent with the actual signs of failure. Our research is helpful to clarify the rockburst problem in the field of engineering geology, specifically to reveal the mechanism of rockburst and the early warning criteria of rockburst hazard under the action of supporting structure, which can provide practical data and theoretical support for scientific and reasonable prevention and control of rockburst risk in tunnel and underground engineering.

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Gravitational Search Algorithm for Microseismic Source Location in Tunneling: Performance Analysis and Engineering Case Study

Cited by 18 publications

References 18 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

Application of the Gravitational Search Algorithm for Constructing Fuzzy Classifiers of Imbalanced Data

Effect of the Initial Support of the Tunnel on the Characteristics of Rockburst: Case Study and Mechanism Analysis

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