Bayesian discriminant analysis for prediction of coal and gas outbursts and application

Based on the principle of Bayesian discriminant analysis, we established a model of Bayesian discriminant analysis for predicting coal and gas outbursts. We selected five major indices which affect outbursts, i.e., initial speed of methane diffusion, a consistent coal coefficient, gas pressure, destructive style of coal and mining depth, as discriminating factors of the model. In our model, we divided the type of coal and gas outbursts into four grades regarded as four normal populations. We then obtained the corresponding discriminant functions through training a set of data from engineering examples as learning samples and evaluated their criteria by a back substitution method to verify the optimal properties of the model. Finally, we applied the model to the prediction of coal and gas outbursts in the Yunnan Enhong Mine. Our results coincided completely with the actual situation. These results show that a model of Bayesian discriminant analysis has excellent recognition performance, high prediction accuracy and a low error rate and is an effective method to predict coal and gas outbursts.

Pattern recognition prediction of coal and gas outburst hazard in the sixth mine of Hebi

Based on the systematical analysis influence factors of coal and gas outburst, the main factors and their magnitude was determined by the corresponding methods.With the research region divided into finite predicting units,the internal relation between the factors and the hazard of coal and gas outburst,that was combination model of influence factors,was ascertained through multi-factor pattern recognition method.On the basis of contrastive analysis the pattern of coal and gas outburst between prediction region and mined region,the hazard of every predication unit was determined.The mining area was then divided into coal and gas outburst dangerous area,threaten area and safe area re- spectively according to the hazard of every predication unit.Accordingly the hazard of mining area is assessed.

Development of regional prediction information system of coal and gas outburst

Coal and gas outburst information system is based on-Geographic Information System(GIS), with which the relation among mine geological structure, coal features, stress field and coal and gas outburst were researched, and also the relation between gas distributed condition and dangerous degrees. Various prediction method, index and technique were applied to realize the data visualization; the accuracy of region prediction was increased. The system has successfully applied in Huainan minging area and Pingdingshan minging area.

Application of dynamic set-pair analysis in coal and gas outburst prediction

Analyzed the factors which affected the coal and gas outburst,then established the corresponding indicator system.Built a dynamic set-pair analysis prediction model which combined of Markov model and set-pair analysis model,and then it applied to coal and gas outburst prediction.Finally,compared the prediction results with the actual results As provided a reference to the coalmine in safety decision-making.The research results indicate that there are four districts in high dangerous level,two districts in middle level and one district in low level,which consistent with the actual situation;the dynamic set-pair analysis model has a good effect in predicting coal and gas outburst.Especially in the continuous time intervals,according to the data of mined exploration and the connec- tion degree analysis,we can deduce the dangerous levels of unexplored districts from the historical data.In different districts,the relevant indicators can be adjusted accordingly,so as to enhance the accuracy of the prediction.

Prediction method for risks of coal and gas outbursts based on spatial chaos theory using gas desorption index of drill cuttings

Based on the evolution of geological dynamics and spatial chaos theory, we proposed the advanced prediction an advanced prediction method of a gas desorption index of drill cuttings to predict coal and gas outbursts. We investigated and verified the prediction method by a spatial series data of a gas desorption index of drill cuttings obtained from the 113112 coal roadway at the Shitai Mine. Our experimental results show that the spatial distribution of the gas desorption index of drill cuttings has some chaotic charac- teristics, which implies that the risk of coal and gas outbursts can be predicted by spatial chaos theory. We also found that a proper amount of sample data needs to be chosen in order to ensure the accuracy and practical maneuverability of prediction. The relative prediction error is small when the prediction pace is chosen carefully. In our experiments, it turned out that the optimum number of sample points is 80 and the optimum prediction pace 30. The corresponding advanced prediction pace basically meets the requirements of engineering applications.

Hazard prediction of coal and gas outburst based on the Hamming distance artificial intelligence algorithm (HDAIA)

Currently,coal mining faces the uncertainty of the risk of coal and gas outbursts and inaccurate prediction results.Owing to this,an artificial immune algorithm(AIA)was developed for coal and gas outburst prediction based on the Hamming distance(HD)calculation method of antibody and antigen affinity called the Hamming distance artificial intelligence algorithm(HDAIA).The correlation matrix of coal and gas outburst indicators was constructed using the interpolation function in the algorithm.The HD algorithm was used to obtain the affinity between the antibody and antigen,and the minimum HD was screened to obtain the prediction result.The collected dynamic data of the drilling cuttings gas desorption index Ki and the drilling cuttings weight S during the excavation process of the 11,192-working face of a coal mine in Guizhou Province,China,were used as prediction indices.The results indicate that the prediction result of the HDAIA for the risk of coal and gas outbursts is consistent with the actual risk of outbursts,and it has a good prediction of the risk of coal and gas outbursts.The HDAIA can be used as a novel method for predicting the risk of coal and gas outbursts.

Matter-elements model and application for prediction of ccoal and gas outburst

The theory and method of extenics were applied to establish classical field matterelements and segment field matter elements for coal and gas outburst.A matter-element model for prediction was established based on five matter-elements,which includedgas pressure,types of coal damage,coal rigidity,initial speed of methane diffusionand in-situ stress.Each index weight was given fairly and quickly through the improvedanalytic hierarchy process,which need not carry on consistency checks,so accuracy ofassessment can be improved.

Prediction Model for Gas Outburst Intensity of Coal Mining Face Based on Improved PSO and LSSVM

For the problems of nonlinearity,uncertainty and low prediction accuracy in the gas outburst prediction of coal mining face,the least squares support vector machine(LSSVM)is proposed to establish the prediction model.Firstly,considering the inertia coefficients as global parameters lacks the ability to improve the solution for the traditional particle swarm optimization(PSO),an improved PSO(IPSO)algorithm is introduced to adjust different inertia weights in updating the particle swarm and solve the fitness to stagnate.Secondly,the penalty factor and kernel function parameter of LSSVM are searched automatically,and the regression accuracy and generalization performance is enhanced by applying IPSO.Finally,to verify the proposed prediction model,the model is applied for gas outburst prediction of Jiuli Hill coal mine in Jiaozuo City,and the results are compared with that of PSO-SVM model,IGA-LSSVM model and BP model.The results show that the relative errors of the proposed model are not greater than 2.7%,and the prediction accuracy is higher than other three prediction models.The IPSO-LSSVM model can be used to predict the intensity of gas outburst of coal mining face effectively.

Application of computational intelligence platform in coal and gas outburst prediction

The present situation of lacking fast and effective coal and gas outburst prediction techniques will lead to long out- burst prevention cycles and poor accurate prediction effects and slows down coal roadway drive speed seriously. Also, due to historical and economic reasons, some coal mines in China are equipped with poor safety equipment, and the staff professional capability is low. What＇s worse, artificial and mine geological conditions have great influences on the traditional technologies of coal and gas outburst prediction. Therefore, seeking a new fast and efficient coal and gas outburst prediction method is nec- essary. By using system engineering theory, combined with the current mine production conditions and based on the coal and gas outburst composite hypothesis, a coal and gas outburst spatiotemporal forecasting system was established. This system can guide forecasting work schedule, optimize prediction technologies, carry out step-by-step prediction and eliminate hazard hier- archically. From the point of view of application, the proposed system improves the prediction efficiency and accuracy. On this basis, computational intelligence methods to construct disaster information analysis platform were used. Feed-back results pro- vide decision support to mine safety supervisors.

Application of the catastrophe progression method in predicting coal and gas outburst

Based on catastrophe theory,we used the catastrophe progression method to predict the risk of coal and gas outbursts in coal mines.According to the major factors affecting coal and gas outbursts,we built a comprehensive evaluation index system and a coal and gas outburst prediction model.In addition,we performed a standard transformation for each index system;based on the degree the various indices affect the risk of an outburst,to make the data dimensionless.Based on the outburst data from eight mines,we determined catastrophe progression values and verified these values.The results show that:1) converting multi-dimensional problems into one-dimensional problems using this catastrophe progression method can simplify the steps of predicting coal and gas outbursts;2) when pre-determined catastrophe progression values are used to predict coal and gas outbursts,the predicting accuracy rate can be as high as 87.5%;3) the various coal mines have different factors inducing outbursts with varying importance of these factors and 4) the catastrophe progression values,calculated based on these factors,can be used effectively to predict the risk of outbursts in coal mines.

Failure modes of coal containing gas and mechanism of gas outbursts

In order to explain the mechanism for gas outburst, the process of evolving fractures in coal seams is described using system dynamics with variable boundaries. We discuss the failure modes of coal containing gas and then established the flow rules after failure. The condition under which states of deformation convert is presented and the manner in which these convert is proposed. In the end, the process of gas outbursts is explained in detail. It shows that a gas outburst is a process in which the boundaries of coal seams are variable because of coal failure. If the fractures are not connected or even closed owing to coal/rock stress, fractured zones will retain a certain level of carrying capacity because of the self-sealing gas pressure. When the accumulation of gas energy reaches its limit, coal seams will become unstable and gas outbursts take place.

A coupled DEM and LBM model for simulation of outbursts of coal and gas

An outburst of coal and gas is a major hazard in underground coal mining. It is generally accepted that an outburst occurs when certain conditions of stress, coal gassiness and physical-mechanical properties of coal are met. Outbursting is recognized as a two-step process, i.e., initiation and development. In this paper, we present a fully-coupled solid and fluid code to model the entire process of an outburst. The deformation, failure and fracture of solid （coal） are modeled with the discrete element method, and the flow of fluid （gas and water） such as free flow and Darcy flow are modeled with the lattice Boltzmann method. These two methods are coupled in a two-way process, i.e., the solid part provides a moving boundary condition and transfers momentum to the fluid, while the fluid exerts a dragging force upon the solid. Gas desorption from coal occurs at the solid-fluid boundary, and gas diffusion is implemented in the solid code where particles are assumed to be porous. A simple 2D example to simulate the process of an outburst with the model is also presented in this paper to demonstrate the capability of the coupled model.

Coal and gas outburst mechanism of the “Three Soft” coal seam in western Henan

Based on the particularities of gas outbursts,i.e.,low gas bearing capacity and low gas pressure in the "Three Soft" coal seam in western Henan,we applied the theories of plate tectonics and regional structural evolution to investigate the mechanism of this seam and its impact on the coal seam gas formation.Our investigation revealed that coal and gas outbursts are distributed in a strip in a NW direction,with a number of high-penetration mines scattered towards the south side and low-gas mines largely located on the north side.We analyzed the statistics of 38 gas explosions and the rock-coal sturdiness number coefficient f of 167 sampling sites in the region and found the gas outburst mechanism that features a "low indicator outburst phenomenon".The mechanism is characterized by structural coal as its core,a low gas bearing capacity,low gas pressure and sturdiness coefficient f mostly less than 0.3.Our research results provide a theoretical foundation for effective control of gas disasters.

Catastrophic mechanism of coal and gas outbursts and their prevention and control

Based on the engineering observations of coal and gas outbursts during mining processes and the experimental results,we built a thin plate mechanical model for layered and spalled coal bodies.We studied the mechanical mechanism of outbursts,due to instability,of thin plates of coal rocks under the action of in-plane load and normal load,by using the catastrophe theory.The total potential function is derived for the layered rock system,the cusp catastrophe model for the system is established,the bifurcation set that makes the system unstable is given,the process in which gradual change of action forces leads to catastrophic change of state is analyzed,and the effect of movement path of point(P,q) in the control space on the stability of rock plate is analyzed.The study results show that during the process of coal mining,the stability of the layered coal bodies depends not only on its physical properties and dimensions but also on the magnitudes and changing paths of the in-plane load and the normal load.When the gas in the coal bodies ahead of the mining face is pre-drained,the gas pressure can be reduced and the normal load q can be lowered.Consequently,disasters such as coal and gas outbursts can be effectively prevented.

Response characteristics of gas pressure under simultaneous static and dynamic load:Implication for coal and gas outburst mechanism

Coal and gas outbursts are dynamic disasters in which a large mass of gas and coal suddenly emerges in a mining space within a split second.The interaction between the gas pressure and stress environment is one of the key factors that induce coal and gas outbursts.In this study,first,the coupling relationship between the gas pressure in the coal body ahead of the working face and the dynamic load was investigated using experimental observations,numerical simulations,and mine-site investigations.It was observed that the impact rate of the dynamic load on the gas-bearing coal can significantly change the gas pressure.The faster the impact rate,the speedier the increase in gas pressure.Moreover,the gas pressure rise was faster closer to the impact interface.Subsequently,based on engineering background,we proposed three models of stress and gas pressure distribution in the coal body ahead of the working face:static load,stress disturbance,and dynamic load conditions.Finally,the gas pressure distribution and outburst mechanism were investigated.The high concentration of gas pressure appearing at the coal body ahead of the working face was caused by the dynamic load.The gas pressure first increased gradually to a peak value and then decreased with increasing distance from the working face.The increase in gas pressure plays a major role in outburst initiation by resulting in the ability to more easily reach the critical points needed for outburst initiation.Moreover,the stronger the dynamic load,the greater the outburst initiation risk.The results of this study provide practical guidance for the early warning and prevention of coal and gas outbursts.

Coal damage mechanism in the developing process of coal and gas outburst

Based on the damage analysis of elliptical aperture,the mechanism of coal damagein the developing process of coal and gas outburst was researched.The results show thatthe damage to coal by gas is mainly caused by the concentrated tensile stress appearing nearthe endpoint of the pores.Fractures in coal,gas pressure,ground stress and the tensilestrength of the coal matrix are the major controlling factors of this kind of damage.When theground stress releases abruptly and the gas pressure is high,tensile failure will occur aroundthe endpoint of the small pores due to gas pressure,and the coal may be broken up like powder;this is called pulverization.Otherwise,when the gas pressure is low,the tensile stress canonly occur around the endpoint of the large pores and fractures due to gas pressure,the fracturesin coal extend and link together,the fracture extension direction is statistically perpendicularto the direction of the minor principal stress.This kind of damage is shown as the stratifiedspall around the outburst hole.

Pore characterization of different types of coal from coal and gas outburst disaster sites using low temperature nitrogen adsorption approach

To characterize the pore features of outburst coal samples and investigate whether outburst coal has some unique features or not, one of the authors, working as the member of the State Coal Mine Safety Committee of China, sampled nine outburst coal samples(coal powder and block) from outburst disaster sites in underground coal mines in China, and then analyzed the pore and surface features of these samples using low temperature nitrogen adsorption tests. Test data show that outburst powder and block coal samples have similar properties in both pore size distribution and surface area. With increasing coal rank, the proportion of micropores increases, which results in a higher surface area. The Jiulishan samples are rich in micropores, and other tested samples contain mainly mesopores, macropores and fewer micropores. Both the unclosed hysteresis loop and force closed desorption phenomena are observed in all tested samples. The former can be attributed to the instability of the meniscus condensation in pores,interconnected pore features of coal and the potential existence of ink-bottle pores, and the latter can be attributed to the non-rigid structure of coal and the gas affinity of coal.

Effectiveness analysis of methane-drainage by deep-hole controlled pre-splitting blasting for preventing coal and gas outburst

In the study of the application effectiveness of deep-hole controlled pre-splittingblasting technology,it was found through laboratory micro test and field study on a mine insouth China that under the technology,coal masses produce many irreversible cracks.Afterblasting,the nearer the distance from blasting hole,the larger the BET surface areaand volume ratio of the infiltration pore are;they increased by 11.47%and 5.73%,respectively.The coefficient of air permeability is increased 4 times.After 3 months,the gasdrainage rate was increased by 66%.In the first 15 days,the cumulative pumped gas was1.93 times of blasting before.The average absolute gas emission decreased by 63.46%.Experimental results show that deep-hole controlled pre-splitting blasting not only preventscoal and gas outburst,but also gives good economic results.

Pattern Recognition and Forecast of Coal and Gas Outburst

Coal and gas outburst is a complicated dynamic phenomenon in coal mines, Multi-factor Pattern Recognition is based on the relevant data obtained from research achievements of Geo-dynamic Division, With the help of spatial data management, the Neuron Network and Cluster algorithm are applied to predict the danger probability of coal and gas outburst in each cell of coal mining district. So a coal-mining district can be divided into three areas： dangerous area, minatory area, and safe area. This achievement has been successfully applied for regional prediction of coal and gas outburst in Hualnan mining area in China.

Determination of indices and critical values of gas parameters of the first gas outburst in a coal seam of the Xieqiao Mine

Based on the important role in mine safety played by parameters of the first gas outburst, we propose a method of combining historic data, theoretical analysis and experimental research for the purpose of crit- ical values of gas parameters of the first gas outburst in a coal seam of the Xieqiao Mine. According to a characteristic analysis and a summary of the rules of coal and gas outbursts in the No.8 coal seam of a Hua- inan mine, we have investigated their effect on coal and gas outbursts in terms such as ground stress, gas, and coal structure. We have selected gas parameters and determined the critical values of each of the fol- lowing indices： gas content as 7.7 m^3/t, tectonic coal as 0.8 m thick, the absolute gas emission as 2 m3/min, the rate of change as 0.7 m3/min, the gas desorption index of a drilling chip KI as 0.26 mL/（g min^1/2） and the values of desorption indexes Ah2 as 200 Pa. From a verification of the production, the results indicate that application of each index and their critical values significantly improve the level of safety in the pro- duction process, relieve the burden upon the mine, save much labor and bring clear economic benefits.