Geopolymer-based modification of blasting sealing materials and optimization of blasting block size in coal seams of open pit mines

This research proposes the utilization of a geopolymer-based blasting sealing material to improve the profitability of coal sales and reduce the rate of coal fragmentation during blasting in open pit mines.The study first focused on optimizing the strength of the sealant material and reducing curing time.This was achieved by regulating the slag doping and sodium silicate solution modulus.The findings demonstrated that increasing slag content and improving the material resulted in an early rise in strength while increasing the modulus of the sodium silicate solution extended the curing time.The slag doping level was fixed at 80 g,and the sodium silicate solution modulus was set at 1.5.To achieve a strength of 3.12 MPa,the water/gel ratio was set at 0.5.The initial setting time was determined to be 33 min,meeting the required field test duration.Secondly,the strength requirements for field implementation were assessed by simulating the action time and force destruction process of the sealing material during blasting using ANSYS/LS-DYNA software.The results indicated that the modified material meets these requirements.Finally,the Shengli Open Pit Coal Mine served as the site for the field test.It was observed that the hole-sealing material’s hydration reaction created a laminated and flocculated gel inside it.This enhanced the density of the modified material.Additionally,the pregelatinized starch,functioning as an organic binder,filled the gaps between the gels,enhancing the cohesion and bonding coefficient of the material.Upon analyzing the post-blasting shooting effect diagram using the Split-Desktop software,it was determined that the utilization of the modified blast hole plugging material resulted in a decrease in the rate of coal fragmentation from 33.2%to 21.1%.This reduction exhibited a minimal error of 1.63%when compared to the field measurement,thereby providing further confirmation of the exceptional plugging capabilities of the modified material.This study significantly contributes to establishing a solid theoretical basis for enhancing the blasting efficiency of open pit mines and,in turn,enhancing their economic advantages.

Monitoring and Assessing Method for Blasting Vibration on Open-pit Slope in Hainan Iron Mine

A type of velocity sensor CD 1, an auto recording instrument on blasting vibration YBJ 1 and a random signal and vibration analysis system (CRAS) were used to monitor the particle vibration induced by blasting at open pit slope in Hainan Iron Mine. The attenuating rules of blasting ground vibration on slope were developed. By means of the analysis and calculation of the blasting vibration data at open pit slope and the vertical particle vibration velocity assessment method based on the concept of vibration strength, the empirical attenuating equations which can be used for predicting and estimating the damage of slope were derived.

Comparison of vibrations induced by excavation of deep-buried cavern and open pit with method of bench blasting

The measured data of vibrations induced by excavation of deep-buried cavern and open pit with method of bench blasting were analyzed by Fourier Transform and Wavelet Transform,and the characteristics of vibrations induced under these two circumstances were studied.It is concluded that with the similar rock condition and drilling-blasting parameters,vibration induced by bench blasting in deep-buried cavern has a higher main frequency and more scattered energy distribution than that in open pit.The vibration induced by bench blasting in open pit is mainly originated from the blast load,while the vibration induced by bench blasting in deep-buried cavern is the superposition of vibrations induced by blast load and transient release of in-situ stress.The vibration induced by transient release of in-situ stress increases with the stress level.

Analysis of the blasting effect on the electric shove loading efficiency of the open pit

The connection between blasting cost and comprehensive cost is the main concern.Some blasting effect factors (such as unit explosive consumption,uniformity of blockness,shape and porosity of blasting heap),which had an influence on electric shove loading efficiency,were analyzed.In the end a project to properly increase in blasting cost to decrease the comprehensive cost was put forward.At the same time,the hole-by-hole blasting is effective technology to improve blasting effect.

基于PEMD-MPE算法的露天矿爆破振动信号降噪方法

为了去除露天矿山爆破振动信号中混入的噪声成分,提出了一种基于PEMD-MPE算法的降噪方法。该算法通过自适应性正交经验模态分解(PEMD)得到完全正交的本征模态函数(IMF)分量,然后对各个IMF分量进行多尺度排列熵(MPE)的随机性检测,成功确定其中的噪声分量并将其去除。采用该算法对实测的露天矿山爆破振动信号进行降噪处理。结果表明:相比EMD-MPE和EEMD-MPE算法,PEMD-MPE算法的信噪比分别提高了3.520 dB和1.107 dB,且重构标准差和均方根误差最小,说明该算法不仅能够有效去除爆破振动信号中的噪声成分,还能有效保留真实信号。

Sizing of rock fragmentation modeling due to bench blasting using adaptive neuro-fuzzy inference system(ANFIS)

One of the most important characters of blasting,a basic step of surface mining,is rock fragmentation because it directly effects on the costs of drilling and economics of the subsequent operations of loading,hauling and crushing in mines.Adaptive neuro-fuzzy inference system(ANFIS)and radial basis function(RBF)show potentials for modeling the behavior of complex nonlinear processes such as those involved in fragmentation due to blasting of rocks.We developed ANFIS and RBF methods for modeling of sizing of rock fragmentation due to bench blasting by estimation of 80%passing size(K_(80))of Golgohar iron mine of Sirjan.Iran.Comparing the results of ANFIS and RBF models shows that although the statistical parameters RBF model is acceptable but ANFIS proposed model is superior and also simpler because ANFIS model is constructed using only two input parameters while seven input parameters used for construction of RBF model.

基于MD-PCA-BP模型的露天矿山爆破振动速度预测

为解决露天矿山爆破复杂场地地质条件的爆破振动预测问题,提出了一种基于马氏距离判别(MD)和主成分分析(PCA)的改进BP神经网络预测模型,即MD-PCA-BP模型。结合内蒙古长滩露天矿爆破振动监测数结果,利用马氏距离判别法剔除监测数据的离群值,并采用主成分分析法对爆破振动影响因素进行降维处理得到3个主成分因子,计算各主成分因子的得分,最终通过BP神经网络构建爆破振动与主成分得分的非线性关系,建立了基于MD-PCA-BP的爆破振动预测模型。结果表明:基于MD-PCA-BP模型建立的爆破振动速度预测模型预测结果与实测值的拟合度达到0.94,预测模型具有较高的预测精度;将预测结果与萨道夫斯基经验公式、2个改进的高程经验公式、MD-BP模型、PCA-BP模型以及BP模型进行比较,MD-PCA-BP模型的预测误差大部分在10%以内,相较于经验公式和未改进的BP预测模型具有更高的可靠度和准确度。基于MD-PCA-BP的爆破振动预测模型在复杂地形的爆破振动速度预测方面表现出了良好的预测效果,对复杂地形的爆破振动预测具有一定的参考作用。

Circle geometric constraint model for open-pit mine ore-matching and its applications

The circle geometric constraint model(CGCM) was put forward for resolving the open-pit mine ore-matching problems(OMOMP).By adopting the approaches of graph theory,block model of blasted piles was abstracted into a set of nodes and directed edges,which were connected together with other nodes in the range of circle constraints,to describe the mining sequence.Also,the constructing method of CGCM was introduced in detail.The algorithm of CGCM has been realized in the DIMINE system,and applied to a short-term(5d) program calculation for ore-matching of a cement limestone mine in Hebei Province,China.The applications show that CGCM can well describe the mining sequence of ore blocks and its mining geometric constraints in the process of mining blasted piles.This model,which is applicable for resolving OMOMP under complicated geometric constraints with accurate results,provides effective ways to solve the problems of open-pit ore-matching.

基于PCA-RVM的矿山岩石爆破粒径预测模型

为解决露天矿山爆破开采过程中岩石爆破粒径大小难以获取的问题,提出一种基于主成分分析法(PCA)及相关向量机(RVM)相结合的矿山岩石爆破粒径预测模型.该模型利用PCA对样本数据进行降维处理,选取出4个相互独立的主成分变量,并借助RVM构建主成分与爆破粒径之间的非线性映射关系,从而建立预测模型.将该模型应用于工程实例,并与BP神经网络和LM双隐含层模型进行对比.结果表明,在相同学习样本下,PCA-RVM模型预测结果与实际值更加接近,在平均相对误差和均方差上远小于另两种模型.

Analysis and Optimization of Blasting Practices at the Sangaredi Mine

Generally, the Mos hardness of bauxite is 2.5 to 3.5. According to the specific conditions of the Sangaredi bauxite deposit, that is, the rock hardness coefficient is between 3 and 6, and there is a clayey zone in the bauxite mining area, it is necessary to carry out blasting work before mining. This article mainly analyzes and optimizes the blasting practice of the Sangaredi open pit bauxite mine. The subject was finally extended to the reduction of nuisances due to blasting, that is to say essentially due to vibrations: this presupposed a study around the vibration data available, and the proposal of methods to limit these vibrations. The bottom conditions of the Sangaredi bauxite ore zone are studied. Bauxite reserves are very rich and the market is huge. The analysis of mine blasting practices, mainly the types of explosives, the selection and analysis of explosives and blasting equipment and choosing the mode of longitudinal blasting, the link of the blasting site of the mining area, further study the optimization of mining blasting practice, the choice of drilling and process to determine reasonable blasting parameters, which improving the drilling method. The experimental results show that this optimization scheme improves efficiency blasting of the bauxite mine but also promotes an increase in production.

基于HHO-LSSVM的露天煤矿抛掷爆破效果预测研究

为提高露天矿抛掷爆破效果预测精度,进而反馈优化爆破参数设计。建立HHO-LSSVM(哈里斯鹰算法优化最小二乘支持向量机)模型,预测抛掷爆破效果;将该模型所得预测精度及效率与未经优化的LSSVM(最小二乘支持向量机)、ELM(极限学习机)、GA-BP(遗传算法优化BP神经网络)、PSO-LSSVM(粒子群算法优化最小二乘支持向量机)模型进行对比。研究结果表明:采用HHO-LSSVM模型相较于未经优化的LSSVM和ELM模型所得到的有效抛掷率、松散系数、最远抛掷距离的预测精度均具有更高的决定系数值,更小的均方根误差值;HHO-LSSVM模型预测的有效抛掷率、松散系数、最远抛掷距离与实测数据之间的平均误差分别为2.7015%,2.9834%,2.8345%,均在5%以内,说明HHO-LSSVM模型对抛掷爆破效果具有较好的预测精度。研究结果可为通过准确预测爆破效果进而反馈抛掷爆破的优化设计提供一定参考。

基于CiteSpace的露天矿爆破技术知识演化和趋势分析

为了研究露天矿爆破技术的发展轨迹和热点变化规律,在中国学术期刊出版总库(CNKI)中选取“露天矿”并含“爆破”检索条件,获得1116篇有效期刊文献作为样本。通过利用CNKI的文献可视化分析报告和CiteSpace这一可视化知识图谱工具,对我国露天矿爆破研究领域的发展现状、分布特征、研究热点和前沿趋势进行了全面而深入的研究和分析。研究表明:露天矿爆破研究主要分为:(1)露天矿爆破理论的确立和发展阶段(2010年前)、(2)现代技术运用和创新阶段(2010—2015年)、(3)绿色智能精细化发展阶段(2015年至今)3个阶段;学科分布主要是矿业工程和工业通用技术与设备;发文期刊主要是《爆破》、《工程爆破》以及其他矿业工程领域的期刊;研究作者及机构主要是矿业相关高等学校教师以及企业、研究院研究人员;研究主题主要包括爆破工艺过程中的爆破设计软件开发与应用,孔网参数、炸药单耗、装药结构等爆破参数优化,深孔爆破、台阶爆破、抛掷爆破、预裂爆破等爆破方式,爆破振动的控制与监测,数值模拟、人工智能算法的应用,爆破质量原因分析及爆破效果评价。未来的露天矿爆破将继续朝着自动化、智能化、精确化和环境友好化的方向发展,通过技术创新和多学科融合,为矿山行业提供更高效、安全、可持续的爆破解决方案。

露天矿山大孔径预裂爆破参数研究与应用

预裂爆破是控制边坡成形、降低爆破动载影响的重要手段。为研究炮孔直径203 mm预裂爆破最佳不耦合系数和炮孔间距,运用LS-DYNA数值软件建立以不耦合系数、炮孔间距为变量的数值模型,分析不同工况下炮孔周围的裂纹扩展和峰值应力强度。结果表明:在空气不耦合系数分别为2.53、2.90、3.38、4.06、5.07、6.77的6种工况中,不耦合系数为4.06时,爆炸能量的利用率最高、裂纹扩展良好,与理论公式推导相符;进一步建立空气不耦合系数为4.06,炮孔间距为1.5、2.0、2.5、3.0、3.5 m的5组模型,得到炮孔间距为2.5 m时满足孔间裂纹贯穿条件,符合现场工况要求;现场应用效果较好,为类似工程提供借鉴。

露天采矿爆破振动对民房破坏的LS-SVM预测模型

利用支持向量机学习原理,研究露天采矿爆破振动对民房破坏的预测问题。选取爆破振动幅值、主频率、主频率持续时间、灰缝强度、砖墙面积率、房屋高度、屋盖形式、圈梁构造柱、施工质量和场地条件作为露天采矿爆破振动对民房破坏的影响因素,以工程实际检测数据为训练样本,建立露天采矿爆破振动对民房破坏的LS-SVM预测模型。利用32组爆破实验数据作为学习样本对支持向量机进行训练,建立相应的预测模型并通过回代估计方法进行回检,误判率为0,用另外12组现场实验数据作为检验样本进行测试,测试结果良好。结果表明,LS-SVM预测方法的误判率低,判别精度高,为露天采矿爆破振动对民房破坏预测提供了一种行之有效的新方法,可以在实际相关工程中展开使用。

参数优化GA-ELM模型在露天煤矿抛掷爆破的预测

为有效指导露天煤矿制定正确生产计划,提高露天煤矿抛掷爆破预测的准确率,在分析露天煤矿抛掷爆破影响因素的基础上,通过"试错法"确定模型最优隐含层节点参数,进而提出一种参数优化后遗传算法(GA)和极限学习机(ELM)相结合的抛掷爆破预测模型。选取网络的输入输出相关参数,针对现有ELM输入权值矩阵和隐含层偏差,采用遗传算法对其进行优化选择;利用某露天煤矿抛掷爆破监测数据对该模型进行实例分析,并将RBF,BP,SVM,GA-BP模型预测结果与该模型进行对比分析;并引入Weibull模型,通过预测控制参数ɑ,β模拟爆堆形态。研究结果表明:(1)通过"试错法"确定GA-ELM模型最优隐含层节点数为39,有效降低系统的仿真误差,该参数下仿真误差值为0.137 7;(2)相较于传统ELM预测模型,通过遗传算法优化后,有效抛掷率,松散系数以及抛掷距离均得出更小的均方误差MSE值(0.258 0,1.748 5×10-4,3.618 4)和更高的决定系数R2值(0.986 4,0.995 3,0.970 6),改进后的GA-ELM具有更好的拟合效果和泛化能力;(3)通过与其他智能算法如BP,RBF,SVM,GA-BP相比,改进后的GA-ELM测试结果(均方误差,决定系数,仿真误差)明显优于其他预测模型,有效提高预测精度;(4)利用训练完成的GA-ELM网络预测爆堆形态时,控制参数a,β的预测误差均未超过5%,预测爆堆曲线接近真实爆堆曲线。

基于连续-非连续单元方法的露天矿三维台阶爆破全过程数值模拟

爆破开采是露天矿采选总成本控制的首要环节,数值模拟是进行露天矿爆破开采优化设计及爆破效果分析的有效手段。利用连续-非连续单元方法(continuum-discontinuum element method,CDEM)对露天矿的三维台阶爆破过程进行了模拟,通过朗道爆炸模型实现了爆炸作用力的精确计算,通过弹性-损伤-断裂本构实现了岩体损伤破裂过程的描述,通过半弹簧-目标面及半棱-目标棱的联合接触算法实现了破碎岩块碰撞、飞散及堆积过程的高效模拟。开展了小尺度单自由面爆破过程的数值模拟,计算给出的块度分布曲线、爆破漏斗体积等参数与文献中模型实验的结果基本一致,证明了CDEM及本文所述各类模型在模拟爆炸破岩方面的精确性。以鞍千矿南采区的露天铁矿爆破开采为研究对象,建立了3排21炮孔的三维台阶爆破概化模型,模拟了从炸药起爆、岩体损伤破裂到最后爆堆形成的全过程;计算结果表明,除后缘拉裂槽外,数值计算给出的爆堆形态、顶部鼓起高度等与现场的测试结果基本一致,证明了利用CDEM开展三维露天台阶爆破全过程模拟的可行性。

基于CEEMD的露天深孔爆破振动信号降噪光滑模型

由于爆破区域地形地质条件的复杂、监测仪器的误差、振动传播介质的反射以及磁场的干扰等原因,采集的原始爆破振动信号常常会掺杂大量的噪声,针对此问题提出了基于互补集合经验模态分解(CEEMD)的信号降噪光滑模型。此模型将爆破振动信号进行CEEMD,基于分解所得到的IMF分量建立低通滤波算法。根据滤波算法的相似度与光滑度,构造目标函数并计算最优解,其对应的滤波算法模型即为爆破振动信号的最优降噪光滑模型。通过构造仿真信号验证了降噪光滑模型算法的可行性,并将模型应用了实际露天深孔爆破振动信号的研究。采用信噪比和均方根误差两种指标对比经验模态分解(EMD)方法、小波阈值法、CEEMD-小波阈值法与滤波算法模型BP3的降噪效果,验证了降噪光滑模型在对露天矿山爆破振动信号降噪方面的有效性,并通过频谱分析进一步验证了降噪光滑模型较CEEMD-小波阈值法的优越性。结果表明:基于CEEMD的露天深孔爆破振动信号降噪光滑模型具有良好的降噪能力,能够在保留原始爆破振动信号真实特征信息的前提下对信号进行降噪,且降噪效果优于EMD方法、小波阈值法和CEEMD-小波阈值法。

基于SPH露天台阶的爆破优化

针对露天深孔台阶爆破容易出现块度不均匀、大块率高等问题,运用经验公式法对台阶爆破参数进行计算并确定爆破方案,建立基于光滑粒子流体动力学(SPH)的台阶数值模型,对深孔台阶爆破孔排距共同作用下的岩体损伤情况及孔间应力大小进行研究。结果表明:孔排距会影响炮孔间的应力叠加作用,模拟过程中SPH粒子能良好地模拟出爆破过程中岩石运动状态和岩石损伤范围,当孔间距为8.5 m、排间距为5.0 m,爆破效果最佳。将模拟结果应用于现场试验,大块率较优化前降低了10.3%,块度平均合格率提高了5.2%,现场试验与模拟结果最优爆破方案效果高度一致,说明利用SPH的数值模拟方法研究台阶爆破是合理可行的。研究结果可为相关台阶爆破孔排距选择提供依据和参考。

巴润矿露天开采贫化控制技术研究及应用

在分析巴润矿贫化原因基础上,结合矿山生产实际,对巴润露天矿矿岩交界处的贫化率进行控制,提出了通过穿孔取样的方式精准确定矿岩边界、矿岩爆破分离、混合爆堆中矿岩石边界的精准识别及优化铲装技术等措施,有效降低了矿岩混杂情况,贫化率降到了2%以下,回采指标明显改善。

基于PCA-ELM模型的露采爆破振动对民房破坏的预测分析

针对露天采矿爆破振动对民房破坏的预测问题,采用主成分分析(PCA)和极限学习机(ELM)方法,选取爆破振幅、主频率、主频率持续时间、灰缝强度、砖墙面积率、房屋高度、屋盖形式、圈梁立柱、施工质量、场地条件10个主要影响因素。引入相关性分析在主成分分析过程中,对相关性高的指标进行降维,把得到的3个综合因子和爆破振幅、主频率、主频率持续时间、砖墙面积率作为输入变量,构建露天煤矿PCA-ELM预测模型。选取露天矿实际爆破过程中测量的100组数据作为模型训练样本,用另外20组数据作为测试样本进行预测。结果表明:对民房破坏影响因素中灰缝强度、房屋高度、屋盖形式、圈梁立柱、施工质量、场地条件之间具有较高的关联度。该模型处理高维数据时较传统的ELM算法具有预测精度高、稳定性好等特点,可准确预测爆破振动对民房的破坏程度,误判率为1/20。