Prediction of ground vibrations resulting from the blasting operations in an open-pit mine by adaptive neuro-fuzzy inference system

The aim of this study is to predict the peak particle velocity (PPV) values from both presently constructed simple regression model and fuzzy-based model. For this purpose, vibrations induced by bench blasting operations were measured in an open-pit mine operated by the most important magnesite producing company (MAS) in Turkey. After gathering the ordered pairs of distance and PPV values, the site-specific parameters were determined using traditional regression method. Also, an attempt has been made to investigate the applicability of a relatively new soft computing method called as the adaptive neuro-fuzzy inference system (ANFIS) to predict PPV. To achieve this objective, data obtained from the blasting measurements were evaluated by constructing an ANFIS-based prediction model. The distance from the blasting site to the monitoring stations and the charge weight per delay were selected as the input parameters of the constructed model, the output parameter being the PPV. Valid for the site, the PPV prediction capability of the constructed ANFIS-based model has proved to be successful in terms of statistical performance indices such as variance account for (VAF), root mean square error (RMSE), standard error of estimation, and correlation between predicted and measured PPV values. Also, using these statistical performance indices, a prediction performance comparison has been made between the presently constructed ANFIS-based model and the classical regression-based prediction method, which has been widely used in the literature. Although the prediction performance of the regression-based model was high, the comparison has indicated that the proposed ANFIS-based model exhibited better prediction performance than the classical regression-based model.     

Controlled blasting in an open-pit mine for improved slope stability

Summary A case study is presented where a controlled blasting programme (presplitting) was adopted in an open-pit copper mine in order to improve the stability of the resulting cut slopes. The aim was to reduce over break and minimize damage to the final pit walls from production blasts. The use of presplitting allowed considerably higher benches to be adopted with much steeper overall slope angles. The extra cost of presplitting was fully justified by the improved face stability and the resulting reduction in overburden quantity.     

模糊神经网络在矿震预测中的应用

矿震同天然地震一样会给矿山生产及人身安全等带来重大灾难。也是目前尚不能准确预测的矿山灾害现象之一。根据现有的研究成果可知，矿震是一个多输入、多干扰、单输出的复杂系统。由于干扰项的存在，使利用建模、神经网络等手段对系统进行预测时会导致很大误差。模糊神经网络系统在建立对象输入、输出关系时与传统数学方法不同。即可以建立在无模型基础上，并利用其较强的学习训练特性，自动获取对象的输入、输出关系表达；可以将专家的评价语言作为系统的干扰项引入。这在一定程度上缓解了人为因素对预测结果的影响，且平滑了观测数据的随机性。文章利用改进的模糊神经网络及抚顺老虎台矿的矿震资料，对矿震最大震级的预测方法进行了探索。‘初步探讨了改进的模糊神经网络在矿震预测中的应用。得出在运用模糊神经网络进行预测时，为减小预测误差，应综合多种因素并提高专家评判语言的精确度的结论。指出在建立矿震系统预测模型时，利用干扰项将人为因素引入系统是必需的。通过实际应用证明其可行性。     

基于DEA算法的矿山修复生态效益评估模型

为准确展现矿山修复生态效益成果,设计基于DEA算法的矿山修复生态效益评估模型。依据矿山地理区域特征和其修复生态效益目的,利用层次分析法,建立矿山修复生态效益评估指标体系;根据获取的一级、二级和三级评估指标,利用DEA算法建立DEA评估模型,通过求解DEA评估模型内的C2R线性规划模型,对决策单元进行判定,当判定为无效时...     

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Environmental Earth Sciences -     

改进的灰色系统理论预测矿井涌水量

基于我国东部许多大水矿区煤炭资源日渐枯竭,衰老矿井涌水量变化巨大的现状,以灰色系统理论为基础,提出了一种新的矿井涌水量预测组合模型——GM (1,1)–Markov–新陈代谢组合模型以及用于预测结果综合评价的指数Z。模型验证结果表明,该组合模型的预测结果优于其他模型,减小了序列数据波动性大、新旧信息更替差异所造成的误差,能够较好地解决时间跨度下采空区残留涌水、意外突水等不确定因素对衰老矿井涌水量预测精度和可靠性的影响。将该组合模型及其他模型应用于开滦集团荆各庄衰老矿井涌水量的预测,结果显示：GM (1,1)–Markov–新陈代谢组合模型的综合评价指数最高,达到0.475;荆各庄矿2011—2015年的矿井涌水量将分别为13.055 m³/min、12.730 m³/min、12.579 m³/min、12.493 m³/min和12.503 m³/min。     

The use of air decks in production blasting in an open pit coal mine

The influence of air deck blasting on blast performance and blast economics and its feasibility has been studied in the production blasting of soft and medium strength sandstone overburden rocks in an open pit coal mine in India. The air deck blasting technique was very effective in soft and medium strength rocks. Its main effects resulted in reducing fines, in producing more uniform fragmentation and in improving blast economics. The fines were reduced by 60–70% in homogeneous sandstones. Oversize boulders were reduced by 80% and shovel loading efficiency was improved by 20–40% in blocky sandstones. The explosive cost was reduced by 10–35% dependent on the type of rock mass. Throw, backbreak and ground vibration were reduced by 10–35%, 50–80% and 30–94% respectively. For a particular rock mass and blast design environment, air deck length (ADL) significantly influenced the fragmentation. ADL as represented by air deck factor (ADF) in the range of 0.10–0.35 times the original charge length (OCL) produced optimum results. ADF beyond 0.35 resulted in poor fragmentation and in inadequate burden movement.     

矿山地质环境影响评价及修复研究——以汶川某废弃露天矿山为例

矿山正常的生产经营活动势必形成一定的矿山地质环境问题。为全面贯彻生态文明思想,牢固树立“绿水青山就是金山银山”的理念,按照恢复生态、兼顾景观总体要求,因地制宜、多措并举,扎实开展废弃露天矿山地质环境修复。依据矿山地质环境保护与恢复的相关规范与要求,以汶川某废弃露天矿山为例,从矿山环境角度介绍了矿山地质环境的影响因素,开展矿山斜坡整体稳定性、采场边坡稳定性、弃渣堆稳定性及地形地貌景观破坏等地质环境影响评价,划分治理重点、次重点和一般3个基本的矿山地质环境保护与恢复防治区。结果表明: 矿山斜坡及弃渣堆现状基本稳定、采场边坡稳定性较差、地形地貌景观影响和破坏程度中等; 研究区矿山地质环境保护与恢复治理可划分为一般防治区和较严重防治区,其中一般防治区面积约554 m2(矿区无因采矿活动诱发的地质灾害,影响区内无居民居住,无威胁对象,矿区及周围地表水体未漏失,矿业活动对水土环境影响程度为影响程度小,未影响到矿区及周围生活供水)、较严重防治区面积186 m2(矿区与影响区地质灾害发生可能性小,地形地貌景观影响和破坏程度较严重)。针对评价结果提出的“坡面浮石清理+清除建筑垃圾、块石+植被重建”等修复建议,为同类型矿山绿色开采及地质环境保护措施提供了的重要技术参考依据。     

露天矿高台阶爆破的数值分析

高台阶爆破可行性研究属于多因素影响、复杂的系统工程。针对高台阶爆破的研究现状,提出了从爆破机制角度证实高台阶爆破可行性的方法,基于数值模拟方法对台阶爆破过程进行分析。通过对比现行普通台阶爆破与高台阶爆破过程中台阶难爆部位（台阶底部与顶部）应力场变化趋势,发现采用高台阶爆破可以得到与普通台阶爆破相当或更好的爆破效果。从爆破机制角度证实,高台阶爆破技术在巴润铁矿具有可行性。数值分析结果表明,高台阶爆破时采用的最佳起爆方式为全药柱同时起爆方式,其次为中间起爆和两端起爆方式,不适宜采用孔底起爆方式。     

Controlled blasting in a limestone mine using electronic detonators: A case study

Except for very deep-seated deposits, open cast mining method has been recognized as the safest and most productive mode for mining minerals. Ever growing demand in minerals and coal has compelled the mine operators to increase the size of mine, which has resulted in an increasing trend towards large capacity open cast projects. Explosives and blasting techniques play a significant role in efficient opencast mining operations. There have been constant technological developments towards safer, faster, economical and more efficient blasting systems. Further, globally increased competitiveness has necessitated to carryout blasts in such a way that the desired degree of fragmentation is achieved in the primary blast, with minimum undesired side effects such as ground vibration, air blast/noise, flyrock, generation of oversize boulders, formation of toe, and over break or back break. Hence, the ultimate objective of the blasting engineer is to ensure that the blasts are carried out in an eco-friendly manner. This paper presents a case study of limestone mine where a controlled blasting was conducted near a green structure of wagon tippler (at 2 m) being constructed for foundation work of belt conveyor as the mine management wants to double the existing production. This paper deals with controlled blast design and its implementation using electronic detonators with signature hole technique.     

A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.     

煤矿下山巷道爆破掘进技术试验研究

为解决煤矿下山巷道爆破掘进中普遍存在的循环进尺小、炮眼利用率低、爆后矸石堆积迎头、留底严重等问题,基于“裂槽、抛碴”思想,有机结合直眼和斜眼掏槽的各自优点,设计了含抛碴眼的楔形掏槽方式这一新型掏槽结构。在华恒矿-1 000水平副暗斜井,通过改变掏槽眼的布置位置和起爆顺序、设置抛碴辅助眼等措施,结合弧形和直线形组成的混合型辅助眼布置方式,制定出3种下山巷道爆破掘进技术方案并进行现场试验。通过掘进进尺、残眼深度、巷道成型、抛碴距离、矸石块度、矸石高度等指标,评价设计方案,最终优选出一种综合指标最好的爆破方案。该矿采用此技术,月进尺提高了40%以上,验证了该技术在下山巷道爆破掘进中的有效性。     

台阶压碴爆破效果遗传神经网络预测

应用遗传神经网络模型对台阶压碴爆破效果进行了预测,增强了预测结果的可靠性。遗传神经网络是人脑的模型,从爆破实例中获取经验知识,并应用专家知识对爆破效果进行预测,取得了符合实际的预测结果,从而,为选择爆破控制参数和取得良好的爆破效果提供了依据。     

Prediction of flyrock and backbreak in open pit blasting operation: a neuro-genetic approach

An ideally performed blasting operation enormously influences the mining overall cost. This aim can be achieved by proper prediction and attenuation of flyrock and backbreak. Poor performance of the empirical models has urged the application of new approaches. In this paper, an attempt has been made to develop a new neuro-genetic model for predicting flyrock and backbreak in Sungun copper mine, Iran. Recognition of the optimum model with this method as compared with the classic neural networks is faster and convenient. Genetic algorithm was utilized to optimize neural network parameters. Parameters such as number of neurons in hidden layer, learning rate, and momentum were considered in the model construction. The performance of the model was examined by statistical method in which absolutely higher efficiency of neuro-genetic modeling was proved. Sensitivity analysis showed that the most influential parameters on flyrock are stemming and powder factor, whereas for backbreak, stemming and charge per delay are the most effective parameters.     

Nanoscale study of As biomineralization in an acid mine drainage system

Spatial and seasonal variations of the oxidation of Fe(II) and As(III) have been previously documented in the Carnoulès (Gard, France) Acid Mine Drainage (AMD) by bulk analyses. These variations may be correlated with the variations in the activity of indigenous As(III)- and Fe(II)-oxidizing bacteria living in the As-rich Carnoulès water. The activity of these bacteria indeed plays an important role in the nature and composition of the solid phases that sequester arsenic at this site. In order to better understand the interactions of microbes with Fe and As in the Carnoulès AMD, we combined Transmission Electron Microscopy (TEM) and Scanning Transmission X-ray Microscopy (STXM) to collect near-edge X-ray absorption fine structure (NEXAFS) spectra at high spatial and energy resolution and to perform high spatial resolution imaging at the 30-50 nm scale. Spectromicroscopy was performed at the C K-edge, Fe L_2,3-edge, and As L_2,3-edge, which allowed us to locate living and/or mineralized bacterial cells and to characterize Fe and As oxidation states in the vicinity of those cells. TEM was used to image the same areas, providing higher resolution images and complementary crystallographic and compositional information through electron diffraction and EDXS analysis. This approach provides unique information on heterogeneous geochemical processes that occur in a complex microbial community in an AMD environment at the micrometer and submicrometer-scale. Bacterial cells in the Carnoulès AMD were frequently associated with mineral precipitates, and a variety of biomineralization patterns were observed. While many mineral precipitates were not associated with bacterial cells, they were associated with pervasive organic carbon. Finally, abundant biomineralized organic vesicles were observed in the Carnoulès AMD. Such vesicles may have been overlooked in highly mineralized extreme environments in the past and may represent an important component in a common biomineralization process in such environments.     

Environmental impacts of bench blasting at Hisarcik Boron open pit mine in Turkey

This paper presents the results of ground vibration measurements carried out in Hisarcik Boron open pit mine located on the west side of central Anatolia near Kütahya province in Turkey. Within the scope of this study to predict peak particle velocity (PPV) level for this site, ground vibration components were measured for 304 shots during bench blasting. In blasting operations, ANFO (blasting agent), gelatin dynamite (priming), and delay electric detonators (firing) were used as explosives. Parameters of scaled distance (charge quantity per delay and the distance between the source and the station) were recorded carefully and the ground vibration components were measured for all blast events using two different types of vibration monitors (one White Mini-Seis and one Instantel Minimate Plus Model). The absolute distances between shot points and monitor stations were determined using GPS. The equation of square root scaled distance extensively used in the literature was taken into consideration for the prediction of PPV. Then, the data pairs of scaled distance and particle velocity obtained from the 565 event records were analyzed statistically. At the end of statistical evaluation of the data pairs, an empirical relation which gives 50% prediction line with a reasonable correlation coefficient was established between PPV and scaled distance.     

基于PSO-DSRVM的边坡变形预测

为了建立高精度的边坡位移预测模型,文章采用基于粒子群优化(PSO)的双稀疏相关向量机(DSRVM)建立边坡稳定性和影响因素之间的非线性关系。双稀疏相关向量机是在变分和相关向量机(RVM)框架下提出的一种多核组合优化的方法,相比于RVM和其他多核学习方法,DSRVM不仅有更少的训练时间,并且能够得到更高的预测精度。由于DSRVM的核参数对预测效果的影响较大,文章采用粒子群算法实现多个核参数的优化选取并应用于边坡位移预测。最后将本文提出的基于粒子群优化的双稀疏相关向量机(PSO-DSRVM)预测结果与极限学习机(ELM)和小波神经网络(WNN)预测结果进行对比,通过均方根误差(RMSE)、复相关系数(R²)和平均相对预测误差(ARPE)进行评价,验证了PSO-DSRVM模型在边坡变形预测上的可行性。     

基于T-S模糊故障树的煤矿坑道钻机液压动力系统故障诊断研究

针对煤矿坑道钻机液压动力系统复杂化带来系统中各元件间逻辑关系模糊、失效形式多态性及故障概率获取困难等问题,克服传统故障树在复杂机电液装备故障诊断分析中的局限性,实现及时准确获取设备故障信息,发现故障原因并采取措施,提出一种基于T-S模糊故障树煤矿坑道钻机液压动力系统的故障诊断方法。以ZDY25000LK型钻机液压动力系统为研究对象,对系统的层次结构进行分析,以T-S模糊故障树描述系统的性能变量,进行分析建树。根据质心距离相似度的度量法对专家评估的底事件模糊概率进行修正,求解顶事件在不同故障程度时发生概率的梯形模糊数。通过T-S概率重要度分析,确定各底事件的重要度排序,指出在不同故障程度时液压动力系统的薄弱环节。结果表明：部件级到系统级事件发生严重故障的概率呈递增趋势,系统中多个部件发生轻微故障时,系统发生严重故障的可能性较大。各事件的故障程度对上级事件发生的贡献度不同,根据重要度排序锁定故障位置并判断故障原因。当液压动力系统出现严重故障时,根据重要度分析结果,应优先排查安全阀工作情况、油泵内部磨损情况及内部串油情况。该方法实现在不同故障程度时系统中薄弱环节的快速定位,在鄂尔多斯淮河能源...