In situ coal gasification poses a potential environmental risk to groundwater pollution although it depends mainly on local hydrogeological conditions. In our investigation,the possible processes of groundwater pollution origi-nating from underground coal gasification （UCG） were analyzed. Typical pollutants were identified and pollution con-trol measures are proposed. Groundwater pollution is caused by the diffusion and penetration of contaminants generated by underground gasification processes towards surrounding strata and the possible leaching of underground residue by natural groundwater flow after gasification. Typical organic pollutants include phenols,benzene,minor components such as PAHs and heterocyclics. Inorganic pollutants involve cations and anions. The natural groundwater flow after gasification through the seam is attributable to the migration of contaminants,which can be predicted by mathematical modeling. The extent and concentration of the groundwater pollution plume depend primarily on groundwater flow ve-locity,the degree of dispersion and the adsorption and reactions of the various contaminants. The adsorption function of coal and surrounding strata make a big contribution to the decrease of the contaminants over time and with the distance from the burn cavity. Possible pollution control measures regarding UCG include identifying a permanently,unsuitable zone,setting a hydraulic barrier and pumping contaminated water out for surface disposal. Mitigation measures during gasification processes and groundwater remediation after gasification are also proposed.
The back propagation （BP）-based artificial neural nets （ANN） can identify complicated relationships among dissolved gas contents in transformer oil and corresponding fault types, using the highly nonlinear mapping nature of the neural nets. An efficient BP-ALM （BP with Adaptive Learning Rate and Momentum coefficient） algorithm is proposed to reduce the training time and avoid being trapped into local minima, where the learning rate and the momentum coefficient are altered at iterations. We developed a system of transformer fault diagnosis based on Dissolved Gases Analysis （DGA） with a BP-ALM algorithm. Training patterns were selected from the results of a Refined Three-Ratio method （RTR）. Test results show that the system has a better ability of quick learning and global convergence than other methods and a superior performance in fault diagnosis compared to convectional BP-based neural networks and RTR.
Wireless sensor networks （WSNs） are very important for monitoring underground mine safety. Sensor node deployment affects the performances of WSNs. In our study, a chain-type wireless underground mine sensor network （CWUMSN） is first presented. A CWUMSN can monitor the environment and locate miners in underground mines. The lowest density deployment strategies of cluster head nodes are discussed theoretically. We prove that the lifetime of CWUMSN with a non-uniform deployment strategy is longer than with a uniform deployment strategy. Secondly, we present the algorithm of non-uniform lowest density deployment of cluster head nodes. Next, we propose a dynamic choice algorithm of cluster head nodes for CWUMSN which can improve the adaptability of networks. Our experiments of CWUMSN with both non-uniform lowest density and uniform lowest density deployments are simulated. The results show that the lifetime of CWUMSN with non-uniform lowest density deployment is almost 2.5 times as long as that of the uniform lowest density deployment. This work provides a new deployment strategy for wireless underground mine sensor networks and then effectively promotes the application of wireless sensor networks to underground mines.
When an extremely thick rock bed exists above a protected coal seam in the bending zone given the condition of a mining protective seam, this extremely thick rock bed controls the movement of the entire overlying stratum. This extremely thick rock bed, called a ＂main key stratum＂, will not subside nor break for a long time, causing lower fractures and bed separations not to close and gas can migrate to the bed separation areas along the fractures. These bed separations become gas enrichment areas. By analyzing the rule of fracture evolution and gas migration under the main key stratum after the deep protective coal seam has been mined, we propose a new gas drainage method which uses bore holes, drilled through rock and coal seams at great depths for draining pressure relief gas. In this method, the bores are located at a high level suction roadway （we can also drill them in the drilling field located high in an air gateway）. Given the practice in the Haizi mine, the gas drainage rate can reach 73% in the middie coal group, with a gas drainage radius over 100 m.
To improve the precision and reliability in predicting methane hazard in working face of coal mine, we have proposed a forecasting and forewarning model for methane hazard based on the least square support vector （LS-SVM） multi-classifier and regression machine. For the forecasting model, the methane concentration can be considered as a nonlinear time series and the time series analysis method is adopted to predict the change in methane concentration using LS-SVM regression. For the forewarning model, which is based on the forecasting results, by the multi-classification method of LS-SVM, the methane hazard was identified to four grades： normal, attention, warning and danger. According to the forewarning results, corresponding measures are taken. The model was used to forecast and forewarn the K9 working face. The results obtained by LS-SVM regression show that the forecasting have a high precision and forewarning results based on a LS-SVM multi-classifier are credible. Therefore, it is an effective model building method for continuous prediction of methane Concentration and hazard forewarning in working face.
A fully-mechanized coal mining （FMCM） technology capable of filling up the goaf with wastes （including solid wastes） is described. Industrial tests have proved that by using this technology not only can waste be re-used but also coal resources can be exploited with a higher recovery rate without removing buildings located over the working faces. Two special devices, a hydraulic support and a scraper conveyor, run side-by-side on the same working face to simultaneously realize mining and filling. These are described in detail. The tests allow analysis of rock pressure and ground subsidence when backfilling techniques are employed. These values are compared to those from mining without using backfilling techniques, under the same geological conditions. The concept of equivalent mining height is proposed based on theoretical analysis of rock pressure and ground subsidence. The upper limits of the rock pressure and ground subsidence can be estimated in backfilling mining using this concept along with traditional engineering formulae.
The dynamic characteristics of a belt conveyor are determined to a large extent by the properties of the belt. This paper describes experiments designed to establish the dynamic properties of belting material. The dynamic elastic modulus, viscous damping and rheologicat constants of the belt were measured. Several properties were studied as a function of the tensile loading on the belt. These included longitudinal vibration, the natural vibration frequency in the transverse direction and the response to an impulse excitation. Vibration response was observed under several different excitation frequencies. Most of these properties have not been tested previously under conditions appropriate for the ISO/DP9856 standard. Two types of belt were tested, a steel reinforced belt and a fabric reinforced belt. The test equipment was built to provide data appropriate for designing belt conveyors. It was observed that the stress wave propagation speed increased with tensile load and that tensile load was the main factor influencing longitudinal vibrations.
For the production of low ash content clean coal, separation at low density is required for some raw coals. Based on analyzing the fluidizing characteristics of magnetic pearls with a specific size distribution and formation mechanism of a microbubble fluidized bed, optimal technological and operating parameters suitable for low density coal separation were determined. The experimental results show that an air dense medium fluidized bed with low density can be formed using magnetic pearls as medium solids, which can efficiently beneficiate coal of 6–50 mm size with a probable error value of 0.05 at a separating density of 1.44 g/cm .
A new method based on principal component analysis (PCA) and support vector machines (SVMs) is proposed for fault diagnosis of mine hoists. PCA is used to extract the principal features associated with the gearbox. Then, with the irrelevant gearbox variables removed, the remaining gearbox, the hydraulic system and the wire rope parameters were used as input to a multi-class SVM. The SVM is first trained by using the one class-based multi-class optimization algorithm and it is then applied to fault identification. Comparison of various methods showed the PCA-SVM method successfully removed redundancy to solve the dimensionality curse. These results show that the algorithm using the RBF kernel function for the SVM had the best classification properties.
A new type of device,a dissolved-air flotation column,was developed for separation of oily wastewater. The unique design idea of the dissolved-air flotation column is the combined use of dissolved-air flotation and column flotation. The dissolved air release occurred within the column separation system. As a potential application the column was investigated for its performance in separating emulsified oil droplets in oily wastewater. A high separation efficiency was obtained in a series of tests. The aeration performance of the bubble generator used in the dissolved-air flotation column was also studied in particular.
Using ANSYS software, we developed a modeling program for several kinds of wire ropes with metal cores and built a geometric model for the 6×19 IWS wire rope. Through proper grid partitioning, a finite element model for calculating the deformation of wire rope was obtained. Completely constraining one end of the wire rope and applying an axial force to the other end, we established the boundary conditions for solving the model. In addition, we numerically simulated the stress and deformation of the wire, obtaining the deformation distribution of each wire within the wire rope under different laying directions. At the end, a tensile test of the 6×19 IWS wire rope was carried out and the results of simulation and experiment compared.
The relationships between mechanical characteristics of rock and microcosmic mechanism at high temperatures were investigated by MTS815, as well as the stress-strain behavior of granite under the action of temperatures ranging from room temperature to 1200 °C. Based on a micropore structure analyzer and SEM, the changes in rock porosity and micro structural morphology of sample fractures and brittle-plastic characteristics under high temperatures were analyzed. The results are as follows: 1) Mechanical characteristics do not show obvious variations before 800 °C; strength decreases suddenly after 800 °C and bearing capacity is almost lost at 1200 °C. 2) Rock porosity increases with rising temperatures; the threshold temperature is about 800 °C; at this temperature its effect is basically uniform with strength decreasing rapidly. 3) The failure type of granite is a brittle tensile fracture at temperatures below 800 °C which transforms into plasticity at temperatures higher than 800 °C and crystal formation takes place at this time. Chemical reactions take place at 1200 °C. Failure of granite under high temperature is a common result of thermal stress as indicated by an increase in the thermal expansion coefficient, transformation to crystal formation of minerals and structural chemical reactions.
In the paper results of passive tomography calculations have been presented to assess rockburst hazard and locate high seismic activity zones in the vicinity of longwall 306 in Zabrze Bielszowice coal mine. The area of study was 1000 m in X direction by 900 m in Y direction. The zones of high values of P-wave propagation velocity have been found to correlate with the distribution of large seismic tremors.
Rock burst in a circular tunnel under high in-situ stress conditions was investigated with a numerical method coupled the rock failure process theory （RFPA） and discontinuous deformation theory （DDA）. Some numerical tests were carraied out to investigate the failuer patterns of circular tunnel under unloading conditions. Compared the results under loading conditions,the shapes of failure zones are more regular under the unloading conditions. The failure pat-terns in the same type of rock mass are clearly different because of non-homogeneity of the rock material. The extension of cracks shows some predictability with an increasing of in-situ stress. When the homogeneity index of rocks （m） is ei-ther relatively high or low and lateral pressure coefficients （λ） is high,the number of regular shear slide cracks decreases and the probability of a rock burst also becomes lower. Our numerical simulation results show that the stability of sur-face rock and the natural bedding stratification of rock material greatly affect rock bursts. Installing bolts with due dili-gence and suitably can effectively prevent rock bursts. However,it is not effective to control rock bursts by releasing the strain energy with normal pre-boreholes.
In order to study the rules of rock bursts caused by faults by means of mechanical analysis of a roof rock-mass balanced structure and numerical simulation about fault slip destabilization, the effect of coal mining operation on fault plane stresses and slip displacement were studied. The results indicate that the slip displacement sharply increases due to the decrease of normal stress and the increase of shear stress at the fault plane when the working face advances from the footwall to the fault itself, which may induce a fault rock burst. However, this slip displacement will be very small due to the increase of normal stress and the decrease of shear stress when the working face advances from the hanging wall to the fault itself, which results in a very small risk of a fault rock burst.
The uptake capacities, and the adsorption kinetics, of copper, Cu（Ⅱ）, nickel, Ni（Ⅱ）, and cadmium, Cd（Ⅱ）, on peat have been studied under static conditions. The results show that the adsorption rates are rapid： equilibrium is reached in twenty minutes. The adsorption of copper, nickel and cadmium is pH dependent over the pH range from 2 to 6. The adsorption kinetics can be excellently described by the Elovich kinetic equation. The adsorption isotherm fits a Langmuir model very well. The adsorption capacities follow the order Cu^2＋ 〉 Ni^2＋〉 Cd^2＋ in single-component systems and the competitive adsorption capacities fall in the decreasing order Cu^2＋ 〉 Ni^2＋〉 Cd^2＋ in multi-component systems. The adsorption capacities of these three heavy metal ions on peat are consistent with their observed competitive adsorption capacities.
In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by Chen Q S. In the model, firstly, the author establishes the attribute space matrix and determines the weight based on Shannon entropy theory; secondly, calculates attribute measure; thirdly, evaluates that with confidence criterion and score criterion; finally, an application example is given. The results show that the water quality of the groundwater sources for the city comes up to the grade II or III standard. There is no pollution that obviously exceeds the standard and the water can meet people＇s needs .The results from anevaluation of this model are in basic agreement with the observed situation and with a set pair analysis （SPA） model.
Ti-bearing blast furnace slag is a valuable secondary resource containing about 24 percent of TiO2. In this paper a process of leaching Ti-bearing blast furnace slag with sulfuric acid to recover TiO2, and the kinetics of that reaction, are described. Under laboratory conditions the rate is controlled by a chemical reaction. The leaching reaction is in accord with a shrinking unreacted-core model. The apparent reaction order of the leaching reaction was 1.222 and the apparent activation energy was 87.01 kJ/mol. The model fits the observed data well until 90% of the TiO2 has be leached from the particles. The model disagrees with observations during later periods of the reaction because the solution becomes supersaturated with Ti ions, which precipitate as H2TiO4. The assumptions of constant reactant concentration and that there is no effect from the product layer on diffusion, also cause the model to deviate from the actual values.
Using GIS, GPS and GPRS, an intelligent monitoring and dispatch system of trucks and shovels in an open pit has been designed and developed. The system can monitor and dispatch open-pit trucks and shovels and play back their historical paths. An intelligent data algorithm is proposed in a practical application. The algorithm can count the times of deliveries of trucks and loadings of shovels. Experiments on real scenes show that the performance of this system is stable and can satisfy production standards in open pits.
Classification and recognition of hyperspectral remote sensing images is not the same as that of conventional multi-spectral remote sensing images. We propose,a novel feature selection and classification method for hyperspectral images by combining the global optimization ability of particle swarm optimization （PSO） algorithm and the superior classification performance of a support vector machine （SVM）. Global optimal search performance of PSO is improved by using a chaotic optimization search technique. Granularity based grid search strategy is used to optimize the SVM model parameters. Parameter optimization and classification of the SVM are addressed using the training date corre-sponding to the feature subset. A false classification rate is adopted as a fitness function. Tests of feature selection and classification are carried out on a hyperspectral data set. Classification performances are also compared among different feature extraction methods commonly used today. Results indicate that this hybrid method has a higher classification accuracy and can effectively extract optimal bands. A feasible approach is provided for feature selection and classifica-tion of hyperspectral image data.