Application of an Expert System to Predict Maximum Explosive Charge Used Per Delay in Surface Mining

The present paper mainly deals with the prediction of maximum explosive charge used per delay (Q _MAX) using an artificial neural network (ANN) incorporating peak particle velocity (PPV) and distance between blast face to monitoring point (D). One hundred and fifty blast vibration data sets were monitored at different vulnerable and strategic locations in and around major coal producing opencast coal mines in India. One hundred and twenty-four blast vibrations records were used for the training of the ANN model vis-à-vis to determine site constants of various conventional vibration predictors. The other 26 new randomly selected data sets were used to test, evaluate and compare the ANN prediction results with widely used conventional predictors. Results were compared based on coefficient of correlation (R), mean absolute error and mean squared between measured and predicted values of Q _MAX. It was found that coefficient of correlation between measured and predicted Q _MAX by ANN was 0.985, whereas it ranged from 0.316 to 0.762 by different conventional predictor equations. Mean absolute error and mean squared error was also very small by ANN, whereas it was very high for different conventional predictor equations.     

Application of an Expert System for the Assessment of Blast Vibration

The purpose of this article is to evaluate and predict the blast induced ground vibration using different conventional vibration predictors and artificial neural network (ANN) at a surface coal mine of India. Ground Vibration is a seismic wave that spread out from the blast hole when detonated in a confined manner. 128 blast vibrations were recorded and monitored in and around the surface coal mine at different strategic and vulnerable locations. Among these, 103 blast vibrations data sets were used for the training of the ANN network as well as to determine site constants of various conventional vibration predictors, whereas rest 25 blast vibration data sets were used for the validation and comparison by ANN and empirical formulas. Two types of ANN model based on two parameters (maximum charge per delay and distance between blast face to monitoring point) and multiple parameters (burden, spacing, charge length, maximum charge per delay and distance between blast face to monitoring point) were used in the present study to predict the peak particle velocity. Finally, it is found that the ANN model based on multiple input parameters have better prediction capability over two input parameters ANN model and conventional vibration predictors.     

Multivariate statistical analysis approach for prediction of blast-induced ground vibration

Excavation of coal, overburden, and mineral deposits by blasting is dominant over the globe to date, although there are certain undesirable effects of blasting which need to be controlled. Blast-induced vibration is one of the major concerns for blast designers as it may lead to structural damage. The empirical method for prediction of blast-induced vibration has been adopted by many researchers in the form of predictor equations. Predictor equations are site specific and indirectly related to physicomechanical and geological properties of rock mass as blast-induced ground vibration is a function of various controllable and uncontrollable parameters. Rock parameters for blasting face and propagation media for blast vibration waves are uncontrollable parameters, whereas blast design parameters like hole diameter, hole depth, column length of explosive charge, total number of blast holes, burden, spacing, explosive charge per delay, total explosive charge in a blasting round, and initiation system are controllable parameters. Optimization of blast design parameters is based on site condition and availability of equipment. Most of the smaller mines have predesigned blasting parameters except explosive charge per delay, total explosive charge, and distance of blast face from surface structures. However, larger opencast mines have variations in blast design parameters for different benches based on strata condition: Multivariate predictor equation is necessary in such case. This paper deals with a case study to establish multivariate predictor equation for Moher and Moher Amlohri Extension opencast mine of India. The multivariate statistical regression approach to establish linear and logarithmic scale relation between variables to predict peak particle velocity (PPV) has been used for this purpose. Blast design has been proposed based on established multivariate regression equation to optimize blast design parameters keeping PPV within legislative limits.     

Environmental impact of blasting at Drenovac limestone quarry (Serbia)

In present paper, the blast-induced ground motion and its effect on the neighboring structures are analyzed at the limestone quarry "Drenovac" in central part of Serbia. Ground motion is examined by means of existing conventional predictors, with scaled distance as a main influential parameter, which gave satisfying prediction accuracy (R > 0.8), except in the case of Ambraseys–Hendron predictor. In the next step of the analysis, a feed-forward three-layer back-propagation neural network is developed, with three input units (total charge, maximum charge per delay and distance from explosive charge to monitoring point) and only one output unit (peak particle velocity). The network is tested for the cases with different number of hidden nodes. The obtained results indicate that the model with six hidden nodes gives reasonable predictive precision (R ≈ 0.9), but with much lower values of mean-squared error in comparison to conventional predictors. In order to predict the influence level to the neighboring buildings, recorded peak particle velocities and frequency values were evaluated according to United States Bureau of Mines, USSR standard, German DIN4150, Australian standard, Indian DMGS circular 7 and Chinese safety regulations for blasting. Using the best conventional predictor, the relationship between the allowable amount of explosive and distance from explosive charge is determined for every vibration standard. Furthermore, the effect of air-blast overpressure is analyzed according to domestic regulations, with construction of a blasting chart for the permissible amount of explosive as a function of distance, for the allowable value of air-blast overpressure (200 Pa). The performed analysis indicates only small number of recordings above the upper allowable limit according to DIN4150 and DMGS standard, while, for all other vibration codes the registered values of ground velocity are within the permissible limits. As for the air-blast overpressure, no damage is expected to occur.     

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.     

An assessment of environmental impacts of quarry-blasting operation: a case study in Istanbul, Turkey

This study evaluates the impacts resulting from quarry-blasting operation on nearby buildings and structures as it generates ground vibration, air blast, and fly rocks. In this paper, first blasting operation and its possible environmental effects are defined. Then the methods of blast-vibration prediction and commonly accepted criteria to prevent damage were introduced. A field experimental work was conducted to minimize the vibration effects at Saribayir quarry as it is an identical case for the many quarries situated in and around Istanbul, Turkey. Although the local surrounding geology and rock mechanics have great influence on vibrations as uncontrollable parameter, the charge weight per delay, delay period, geometric parameters of the blasts were changed to solve the existing vibration problem in the studied quarry. To obtain a realistic result, 10 blasts were carried out and 30 seismic records were made in different places mainly very close the buildings and the other vulnerable structures around the quarry. The evaluation is performed whether the vibration level are within safe limits or not. The prediction equation based on scaled distance concept is also determined, however, it is a site-specific model and need to be updated when the quarry advances. The safe blast parameters which minimize the environmental effect were determined for the Saribayir quarry.     

Allowed Quantity of Explosive Charge Depending on the Distance from the Blast

This paper analyses results of trial, construction and quarry blasting, carried out in sediment rock deposits, mainly limestone and dolomite. Based on results of seismic measurements and engineering geological observations in sedimentary formation, an empirical relationship was established between ground vibration and geological strength index (GSI). The charge weight of explosive that may be detonated per delay for any given distance of nearby structures from the blast is approximately determined by using the concept of the scaled distance (SD) along with the DIN 4150 standard.     

Measurement and analysis of near-field blast vibration and damage

Summary Blast vibration and its attenuation within the rock mass immediately adjacent to a blast hole (2–15 m) were monitored for a blast hole diameter of 100 mm and a 2.4 m column of an emulsion explosive charge. Peak particle velocities calculated from the measured accelerations were compared with predictions from the charge-weight scaling law using typical site parameters which would be adopted for many far-field vibration predictions. It was found that the vibration amplitudes predicted by the conventional charge-weight scaling law are significantly lower than measured values. Strain and strain rates at different monitoring holes were calculated from experimental data. Using attenuation analysis of different frequency bands of measured acceleration signals, it was found that blast vibration attenuation between 2 m and 4 m depended not only on frequency but also on amplitude. A failure wave was postulated based on observations at the monitoring hole 2 m from the blast. A blast damage zone was evaluated using borehole camera and cross hole seismic studies. The damage zone in the rock was also analysed according to acceleration waveforms measured at different monitoring locations. The use of different techniques to measure blast damage provided an accurate assessment of the blast damage volume.     

Variable Energy Explosives for Soft Ground Blasting

A range of bulk explosives, the NOVALITE range hay been specifically developed for soft ground blasting. These explosives can be used in both wet and dry blasting conditions, range in density from 0.3-1.2 g/cc and range in VoD from 2-4.5 km/s. This range of explosives hay the potential to be tailored to ground type and is predicted to be suitable for a variety of applications which include: blasting in soft to medium overburden, coal blasting, wall control, and low vibration blasting. Trials have been conducted in several applications with encouraging results. Several cast/throw blasts have been conducted with these products partially replacing either ANFO or Heavy ANFO. The results from the blast have been equivalent in cast (per cent) and at reduced cost per unit volume. These products have also been used in presplit blasting and have again achieved equivalent or better results when compared to conventional presplit blasting at a lower cost per unit volume. This product has also been used in a vibration sensitive area replacing traditional explosive products, and generating excellent fragmentation and digging whilst maintaining vibration limits. This new range of products, NOVALITE, has shown great potential in many applications either reducing cost per unit volume, improving wall quality or improving productivity in environmentally sensitive areas.     

砂土地震液化预测的GA_SVM_Adaboost模型

为快速准确地对砂土液化情况作出预测,选取地震烈度、地下水位、覆盖厚度、标贯击数、平均粒径、地貌单元、土质及不均匀系数为主要影响因素,运用相关性分析和因子分析模型对其进行分析和属性约减,采用遗传算法（GA）对支持向量机（SVM）的参数寻优,结合Adaboost迭代算法,建立预测砂土地震液化的GA_SVM_Adaboost模型。选用唐山地震砂土液化现场勘察资料中的329组数据对模型进行训练,利用该模型对剩余68组砂土液化数据进行预测。最后,将预测结果与GA_SVM和SVM模型预测结果进行比较。结果表明,3个模型的平均预测准确率分别为100%、98.04%、89.71%,基于因子分析的GA_SVM_Adaboost模型的预测准确性优于GA_SVM模型和SVM模型,是一种解决砂土地震液化预测问题的有效方法,具有一定的应用参考价值。      

Bench blasting design based on site-specific attenuation formula in a quarry

This research was performed on the quarry that will be opened to produce aggregates and rock filling material at Catalagzi region at Zonguldak province in Turkey. However, there are some structures which can be adversely affected by blasting at the quarry. These structures are a methane exploration drill hole and a house at the distances of 340 and 390 m, respectively. One of the main goals of this study is to perform a preliminary assessment of possible damage effect of ground vibrations induced by blasting on these structures by risk analysis based on ground vibration measurements. In order to propose a preliminary blast design models separately for aggregate and rock filling material production, six test shots with different maximum charge per delay were planned and fired at the quarry. In these shots, 90 events were recorded. To predict peak particle velocity (PPV), the relationship between the recorded peak particle velocities and scaled distances were investigated. During this investigation, the data pairs were statistically analyzed and a PPV prediction equation specific to this site with 95% prediction line were obtained. And also, this equation was used in the derivation of the practical blasting charts specific to this site as a practical way of predicting the peak particle velocity and maximum charge per delay for future blasting. A risk analysis was performed by using this equation. In the light of this analysis, preliminary blast design models were proposed to be used in this quarry for aggregate and rock filling material production.     

On the Study of Pile Driving Formula Based on Blow Counts

Accuracy of predicting pile capacities by pile driving formulas have been investigated. Five test piles were driven up to a depth of about 9 m of clay deposit and the penetrations due to final blows were recorded. The pile bearing capacity of each pile was predicted using 6 different pile driving formulas and the predicted pile capacity was compared with measured pile capacity from the pull up tests. Hiley formula, Modified Engineering News Record (ENR) formula, Janbu formula, Dutch formula, Danish formula, and Gates formula were used. The performance and accuracy of each formula was evaluated and the correlation coefficient of each pile driving formula was determined for a more accurate pile capacity prediction. Methods used to evaluate the performance of each formula were; (1) the best fit line for Q _p versus Q _m (2) cumulative probability for Q _p/Q _m and (3) the arithmetic mean and standard deviation for Q _p/Q _m. From the study, it was found that using Dutch formula provided the most accurate pile capacity estimate compared to the other formulas with an average of 7% deviation from value obtained from the field pull up test. It was followed by the Danish formula, Janbu formula, Hiley formula, Modified ENR formula, and Gates formula. The ability to predict the accuracy of estimating pile capacity using an appropriate method is very important and valuable to contractors, developers, geotechnical engineers, and manufacturers.     

Predicted CO2 emissions from maceral concentrates of high volatile bituminous Kentucky and Illinois coals

A large collection of well-characterized coals, documented in the Center for Applied Energy Research's (CAER) database, was used to estimate the CO₂ content of maceral concentrates from Kentucky and Illinois high volatile bituminous coals. The data showed no correlation between CO₂ versus coal ranks and between CO₂ versus maceral content. Subsequently, eight sets of low-ash density-gradient centrifugation (DGC) maceral concentrates from five coal beds were examined, spanning in the high volatile rank range. Heating value was not determined on the concentrates, but instead was calculated using the Mott–Spooner formula. There was a good correlation between predicted CO₂ and maceral content for the individual iso-rank (based on vitrinite reflectance, analyzed on whole (parent) coal) sets. In general, the predicted CO₂ increases from liptinite-rich through vitrinite-rich to inertinite-rich concentrates (note: no “concentrates” are absolutely monomaceral).     

Evaluation of blast-induced ground vibrations in open-pit mines by using adaptive neuro-fuzzy inference systems

This study addresses the effects of rock characteristics and blasting design parameters on blast-induced vibrations in the Kangal open-pit coal mine, the Tülü open-pit boron mine, the K?rka open-pit boron mine, and the TKI Çan coal mine fields. Distance (m, R) and maximum charge per delay (kg, W), stemming (m, SB), burden (m, B), and S-wave velocities (m/s, Vs) obtained from in situ field measurements have been chosen as input parameters for the adaptive neuro-fuzzy inference system (ANFIS)-based model in order to predict the peak particle velocity values. In the ANFIS model, 521 blasting data sets obtained from four fields have been used (r ² = 0.57–0.81). The coefficient of ANFIS model is higher than those of the empirical equation (r ² = 1). These results show that the ANFIS model to predict PPV values has a considerable advantage when compared with the other prediction models.     

A determination method of rainfall type based on rainfall-induced slope instability

Explosives are still the cheapest source of breaking rock in the mining or tunnelling operation and can be applied in varying geological conditions. It generates various troubles such as ground vibration, air overpressure, and fly rocks. It is well known that the maximum charge per delay (MCPD) has to be optimum for safe blasting and can be achieved through trial blasts, which is a complicated and costly process. Therefore, it is required to reduce the number of trial blasts. In this study, a total of 18 blasts were conducted in an underground coal mine and were simulated using similar ground conditions using Ansys software. The Peak particle velocity values obtained in the mines and through the models were compared. The error in PPV found between the actual and predicted by simulation is less than 15%. It can help us design the MCPD in rock excavation operations, visualise damages using simulation in Ansys software, and economical compared to field trials.

     

基于GA-SVM的矿井涌水量预测

矿井涌水量的准确预测对预防矿山透水事故的发生至关重要,提出利用GA优化的SVM模型（GA-SVM）来实现矿井涌水量的短期准确预测。该方法利用GA的自动寻优功能寻找SVM的最佳参数,提高了预测的准确率。首先,利用微熵率法求矿井涌水量时间序列的最佳嵌入维数和延迟时间,进行相空间重构。其次,采集义煤集团千秋煤矿2011—2015年实际涌水量的时间序列,利用GA-SVM模型对最后12组数据进行预测,其预测平均绝对百分比误差仅为0.92%,最大相对误差为2.62%。最后,与PSO-SVM和BP神经网络预测进行对比,结果表明GA-SVM优化模型适用于矿井涌水量的预测并且预测精度较高。      

Prediction of blast-induced air overpressure using support vector machine

Prediction of blast-induced air overpressure (AOP) is very complicated and intricate due to the number of influencing parameters affecting air wave propagation. In this paper, an attempt has been made to predict the blast-induced AOP by support vector machine (SVM) using maximum charge per delay and distance from blast-face to monitoring station of AOP. To investigate the suitability of this approach, SVM predictions are compared with a generalized predictor equation. Seventy-five air blasts were monitored at different locations around three mines. AOP data sets of two limestone mines are taken for the training and testing of the SVM network as well as to determine site constants for generalized equation. The remaining mine data sets are used for the validation and comparison of AOP.     

Productivity optimisation in weak sedimentary formations for improved coal production and roof stability—an approach

Far-field peak particle velocity (PPV) measurements were made in the roof while blasting in coal development drivages at Tandsi Mine, Western Coalfields Limited, India. The roof was fragile at this mine and was posing constant support problems for mining, resulting in low productivity. The PPV measurements have been used to decipher the damage zone in the roof. The extent of damage obtained has been compared to establish the threshold limits for the damage zone. Conversely, the maximum charge per delay that can be exploded is calculated and a suitable blast design has been recommended for maintaining the roof stability and pull. A roof vibration predictor equation has been developed that shows a consistent trend indicating that it may have future use in a similar geo-mining setup. The blast pattern recommended has reduced the damage extent, though marginally, but helped in improving pull. Critical PPV for incipient rock damage in underground coal mine development drivages under fragile roof were computed. The PPV level for incipient crack growth was found to vary from 500 to 800 mm/s while for overbreak it varied from 800 to 1200 mm/s. It was also observed that the location of cut holes, charge concentration and firing sequence were found to be responsible for the difference in their damage potential.     

基于VMD和SVM的煤厚预测方法研究

煤厚变化对煤炭安全高效开采具有重要的影响。针对三维地震数据中含有噪声时,易导致煤厚预测结果具有较大误差的问题,提出一种利用变模态分解(VMD)和支持向量机(SVM)方法结合进行煤厚预测的方法。首先,构建煤厚楔形模型并对其进行地震正演模拟,当煤层厚度较薄时,振幅属性和频带宽度属性与煤厚之间具有较好的正相关性,而瞬时频率属性与煤厚具有较好的负相关性;对正演地震记录增加噪声,结果表明噪声对利用地震属性进行煤厚预测具有较大影响。利用VMD进行去噪之后,基于SVM进行煤厚预测,实际地震资料的煤厚预测结果与已有钻孔揭露的煤层信息较为吻合,预测煤厚最小绝对误差仅为0.02 m,最大绝对误差0.52 m,验证了方法的可行性和有效性。研究成果可为低信噪比区的煤厚反演提供参考。      

Active and online prediction of BOD5 in river systems using reduced-order support vector machine

Due to the limitations of hardware sensors for online measurement of the water quality parameters such as 5-day biochemical oxygen demand (BOD₅), the recent research efforts have focused on the software sensors for the rapid prediction of such parameters. The main objective in this research is to develop a reduced-order support vector machine (ROSVM) model based on the proper orthogonal decomposition to solve the time-consuming problem of the BOD₅ measurements. The performance of the newly developed methodology is tested on the Sefidrood River Basin, Iran. Subsequently, the predicted values of BOD₅, resulted from the selected developed ROSVM model, are compared with the results of support vector machine (SVM) model. According to the obtained results, selected ROSVM model seems to be more accurate, showing Person correlation coefficient (R) and root mean square error (RMSE) equal to 0.97 and 6.94, respectively. Further, the investigations based on developed discrepancy ratio (DDR) statistic for selection of the optimum model between the best accurate ROSVM and SVM models are carried out. Results of DDR statistic indicated superior performance of the selected ROSVM model comparing to the SVM technique for online prediction of BOD₅ in the Sefidrood River.