Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challe...Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.展开更多
In order to reduce the horizontal crossing transportation problems between coal trucks and stripping trucks,large and small vehicles,and transport trucks and belt conveyors at key points of open pit mine in production...In order to reduce the horizontal crossing transportation problems between coal trucks and stripping trucks,large and small vehicles,and transport trucks and belt conveyors at key points of open pit mine in production,the separate transportation mode of underpass bridge and overpass steel trestle is proposed to optimize the open pit development transportation system,so as to solve the practical problems that the horizontal cross of transport vehicles causes vehicle blockage,affects production schedule and production safety.The results show that the horizontal crossing road can be changed into a separate type of overpass steel trestle,which can realize the classified transportation of large and small vehicles,reduce the traffic density,make vehicles with different functions go their own way,eliminate the hidden danger of traffic accidents,and improve the production efficiency.展开更多
In the process of intelligent mine construction in open-pit mine, in order to improve the safety monitoring ability of mine transportation system, solve the problems of large human interference and blind Angle detecti...In the process of intelligent mine construction in open-pit mine, in order to improve the safety monitoring ability of mine transportation system, solve the problems of large human interference and blind Angle detection by existing conventional monitoring methods, this paper establishes an open-pit mine monitoring data set, and proposes a real-time intelligent monitoring model based on UAV. The reasoning component with strong computing power and low power consumption is selected, and the lightweight object detection model is selected for the experiment. A quantitative standard of dynamic energy consumption detection by evaluation algorithm is proposed. Through experimental comparison, it is found that YOLOv4-tiny has the highest comprehensive grade in detection accuracy, speed, energy consumption and other aspects, which is suitable for application in the above model.展开更多
A new pseudolites （PLs） structure optimization model of global navigation satellite system （GNSS）/PLs integration positioning system used in deep open-pit mine was presented. Position dilution of precision （Pdop...A new pseudolites （PLs） structure optimization model of global navigation satellite system （GNSS）/PLs integration positioning system used in deep open-pit mine was presented. Position dilution of precision （Pdop） and reliability were selected as the optimization indicators to build a multi-objective optimization model to decide the optimum PLs location. A scheme was designed by establishing a four-dimensional model taking azimuth （a）, elevation angle （e） and epoch （t） of satellites as the input independent variables and Pdop as the dependent variable to calculate the optimum PLs location zone considering the real circumstances. And then the ultimate PLs location can be fixed by testing the curves of Pdop along time. A field collected Trimble R8 GPS data set in China University of Mining and Technology （CUMT） campus was used for the model test to show the effectiveness, and the proposed PLs optimum design scheme was used at the west open-pit mine of Fushun mining group Co., Ltd., in China, better Pdop and reliability have been achieved for the integration system. Both experiments show that the proposed scheme is excellent in designing GNSS/PLs system which is helpful for improving the performance of the positioning system and reducing the cost.展开更多
A modified algorithm of combined GPS/GLONASS precise point positioning （GG-PPP） was developed by decreasing the number of unknowns to be estimated so that accurate position solutions can be achieved in the case of l...A modified algorithm of combined GPS/GLONASS precise point positioning （GG-PPP） was developed by decreasing the number of unknowns to be estimated so that accurate position solutions can be achieved in the case of less number of visible satellites. The system time difference between GPS and GLONASS （STDGG） and zenith tropospheric delay （ZTD） values were firstly estimated in an open sky condition using the traditional GG-PPP algorithm. Then, they were used as a priori known values in the modified algorithm instead of estimating them as unknowns. The proposed algorithm was tested using observations collected at BJFS station in a simulated open-pit mine environment. The results show that the position filter converges much faster to a stable value in all three coordinate components using the modified algorithm than using the traditional algorithm. The modified algorithm achieves higher positioning accuracy as well. The accuracy improvement in the horizontal direction and vertical direction reaches 69% and 95% at a satellite elevation mask angle of 50°, respectively.展开更多
The warming effect of Chaoyang efficient agriculture was analyzed using nearly 60 years of climatic date and 30 years of agricultural material from three aspects including corn cultivation area,facility agriculture in...The warming effect of Chaoyang efficient agriculture was analyzed using nearly 60 years of climatic date and 30 years of agricultural material from three aspects including corn cultivation area,facility agriculture in protective field,gross agricultural output value.The results showed that climate warming had a very significant positive effect on the development of high-active agriculture in Chaoyang.展开更多
The failure characteristic of talus-derived rock mass continues to challenge quantitative hazard assessments in open-pit mining. Physical model test was used to assess the failure modes and mechanisms on talus-derived...The failure characteristic of talus-derived rock mass continues to challenge quantitative hazard assessments in open-pit mining. Physical model test was used to assess the failure modes and mechanisms on talus-derived rock mass. The different types of failure modes of the talus-derived rock mass were introduced and a possible failure mechanism relation between the failure zone and the structure of the talus-derived rock mass was also shown. The physical model test results indicate that the rainfall has significant influence on the stability and failure modes of talus-derived rock mass during open-pit mining. The development of the seepage area caused by rainfall initiates the localized failure in that particular area, and the initiation of localized instability is mainly induced by stress changes concentrated in the seepage area.展开更多
A common reclamation practice for closed coal surface mines is filling them with water to form pit lakes.The creation and sustainability of these lakes are significantly affected by the stability of the corresponding ...A common reclamation practice for closed coal surface mines is filling them with water to form pit lakes.The creation and sustainability of these lakes are significantly affected by the stability of the corresponding slopes.The present study provides a general framework for analyzing the water filling’s effect on slope stability based on a new water filling index,which can indirectly consider the factors affecting the process and efficiently quantify the filling speed’s influence.The assumptions of the proposed approach are thoroughly discussed,and the range of the water filling index is identified.Furthermore,the safety factor is calculated using the finite element method with the shear strength reduction technique during the filling process for various conditions(soil properties,slope geometry,hydraulic conditions,and water filling speed).Results are presented as normalized stability charts for practical use.During the water filling,the stability gradually decreases until the reservoir reaches a critical level of 10%e40%of the total height;it then increases to even more stable conditions than the initial one.Overall,the present analysis allows for the preliminary stability evaluation of a coal mine during the formation of a pit lake and the appropriate quantification of the water filling’s effect.展开更多
In this study,twelve machine learning(ML)techniques are used to accurately estimate the safety factor of rock slopes(SFRS).The dataset used for developing these models consists of 344 rock slopes from various open-pit...In this study,twelve machine learning(ML)techniques are used to accurately estimate the safety factor of rock slopes(SFRS).The dataset used for developing these models consists of 344 rock slopes from various open-pit mines around Iran,evenly distributed between the training(80%)and testing(20%)datasets.The models are evaluated for accuracy using Janbu's limit equilibrium method(LEM)and commercial tool GeoStudio methods.Statistical assessment metrics show that the random forest model is the most accurate in estimating the SFRS(MSE=0.0182,R2=0.8319)and shows high agreement with the results from the LEM method.The results from the long-short-term memory(LSTM)model are the least accurate(MSE=0.037,R2=0.6618)of all the models tested.However,only the null space support vector regression(NuSVR)model performs accurately compared to the practice mode by altering the value of one parameter while maintaining the other parameters constant.It is suggested that this model would be the best one to use to calculate the SFRS.A graphical user interface for the proposed models is developed to further assist in the calculation of the SFRS for engineering difficulties.In this study,we attempt to bridge the gap between modern slope stability evaluation techniques and more conventional analysis methods.展开更多
基金This work was supported by the Pilot Seed Grant(Grant No.RES0049944)the Collaborative Research Project(Grant No.RES0043251)from the University of Alberta.
文摘Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.
文摘In order to reduce the horizontal crossing transportation problems between coal trucks and stripping trucks,large and small vehicles,and transport trucks and belt conveyors at key points of open pit mine in production,the separate transportation mode of underpass bridge and overpass steel trestle is proposed to optimize the open pit development transportation system,so as to solve the practical problems that the horizontal cross of transport vehicles causes vehicle blockage,affects production schedule and production safety.The results show that the horizontal crossing road can be changed into a separate type of overpass steel trestle,which can realize the classified transportation of large and small vehicles,reduce the traffic density,make vehicles with different functions go their own way,eliminate the hidden danger of traffic accidents,and improve the production efficiency.
文摘In the process of intelligent mine construction in open-pit mine, in order to improve the safety monitoring ability of mine transportation system, solve the problems of large human interference and blind Angle detection by existing conventional monitoring methods, this paper establishes an open-pit mine monitoring data set, and proposes a real-time intelligent monitoring model based on UAV. The reasoning component with strong computing power and low power consumption is selected, and the lightweight object detection model is selected for the experiment. A quantitative standard of dynamic energy consumption detection by evaluation algorithm is proposed. Through experimental comparison, it is found that YOLOv4-tiny has the highest comprehensive grade in detection accuracy, speed, energy consumption and other aspects, which is suitable for application in the above model.
基金Project(2013RC16)supported by the Fundamental Research Funds for the Central Universities,China
文摘A new pseudolites （PLs） structure optimization model of global navigation satellite system （GNSS）/PLs integration positioning system used in deep open-pit mine was presented. Position dilution of precision （Pdop） and reliability were selected as the optimization indicators to build a multi-objective optimization model to decide the optimum PLs location. A scheme was designed by establishing a four-dimensional model taking azimuth （a）, elevation angle （e） and epoch （t） of satellites as the input independent variables and Pdop as the dependent variable to calculate the optimum PLs location zone considering the real circumstances. And then the ultimate PLs location can be fixed by testing the curves of Pdop along time. A field collected Trimble R8 GPS data set in China University of Mining and Technology （CUMT） campus was used for the model test to show the effectiveness, and the proposed PLs optimum design scheme was used at the west open-pit mine of Fushun mining group Co., Ltd., in China, better Pdop and reliability have been achieved for the integration system. Both experiments show that the proposed scheme is excellent in designing GNSS/PLs system which is helpful for improving the performance of the positioning system and reducing the cost.
基金Project(41004011)supported by the National Natural Science Foundation of ChinaProject(2014M550425)supported by the China Postdoctoral Science Foundation
文摘A modified algorithm of combined GPS/GLONASS precise point positioning （GG-PPP） was developed by decreasing the number of unknowns to be estimated so that accurate position solutions can be achieved in the case of less number of visible satellites. The system time difference between GPS and GLONASS （STDGG） and zenith tropospheric delay （ZTD） values were firstly estimated in an open sky condition using the traditional GG-PPP algorithm. Then, they were used as a priori known values in the modified algorithm instead of estimating them as unknowns. The proposed algorithm was tested using observations collected at BJFS station in a simulated open-pit mine environment. The results show that the position filter converges much faster to a stable value in all three coordinate components using the modified algorithm than using the traditional algorithm. The modified algorithm achieves higher positioning accuracy as well. The accuracy improvement in the horizontal direction and vertical direction reaches 69% and 95% at a satellite elevation mask angle of 50°, respectively.
文摘The warming effect of Chaoyang efficient agriculture was analyzed using nearly 60 years of climatic date and 30 years of agricultural material from three aspects including corn cultivation area,facility agriculture in protective field,gross agricultural output value.The results showed that climate warming had a very significant positive effect on the development of high-active agriculture in Chaoyang.
基金Project (41202220) supported by the National Natural Science Foundation of ChinaProject (2-9-2012-65) supported by the Fundamental Research Funds for the Central Universities, ChinaProject (20120022120003) supported by the Ph.D Program Foundation of Ministry of Education of China
文摘The failure characteristic of talus-derived rock mass continues to challenge quantitative hazard assessments in open-pit mining. Physical model test was used to assess the failure modes and mechanisms on talus-derived rock mass. The different types of failure modes of the talus-derived rock mass were introduced and a possible failure mechanism relation between the failure zone and the structure of the talus-derived rock mass was also shown. The physical model test results indicate that the rainfall has significant influence on the stability and failure modes of talus-derived rock mass during open-pit mining. The development of the seepage area caused by rainfall initiates the localized failure in that particular area, and the initiation of localized instability is mainly induced by stress changes concentrated in the seepage area.
基金This work has received funding from the European Union’s Research Fund for Coal and Steel under the projects RAFF grant agreement No.847299 and POMHAZ grant agreement No.101057326.Financial assistance by the European Commission is much appreciated.
文摘A common reclamation practice for closed coal surface mines is filling them with water to form pit lakes.The creation and sustainability of these lakes are significantly affected by the stability of the corresponding slopes.The present study provides a general framework for analyzing the water filling’s effect on slope stability based on a new water filling index,which can indirectly consider the factors affecting the process and efficiently quantify the filling speed’s influence.The assumptions of the proposed approach are thoroughly discussed,and the range of the water filling index is identified.Furthermore,the safety factor is calculated using the finite element method with the shear strength reduction technique during the filling process for various conditions(soil properties,slope geometry,hydraulic conditions,and water filling speed).Results are presented as normalized stability charts for practical use.During the water filling,the stability gradually decreases until the reservoir reaches a critical level of 10%e40%of the total height;it then increases to even more stable conditions than the initial one.Overall,the present analysis allows for the preliminary stability evaluation of a coal mine during the formation of a pit lake and the appropriate quantification of the water filling’s effect.
基金supported via funding from Prince Satam bin Abdulaziz University project number (PSAU/2024/R/1445)The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large Group Research Project (Grant No.RGP.2/357/44).
文摘In this study,twelve machine learning(ML)techniques are used to accurately estimate the safety factor of rock slopes(SFRS).The dataset used for developing these models consists of 344 rock slopes from various open-pit mines around Iran,evenly distributed between the training(80%)and testing(20%)datasets.The models are evaluated for accuracy using Janbu's limit equilibrium method(LEM)and commercial tool GeoStudio methods.Statistical assessment metrics show that the random forest model is the most accurate in estimating the SFRS(MSE=0.0182,R2=0.8319)and shows high agreement with the results from the LEM method.The results from the long-short-term memory(LSTM)model are the least accurate(MSE=0.037,R2=0.6618)of all the models tested.However,only the null space support vector regression(NuSVR)model performs accurately compared to the practice mode by altering the value of one parameter while maintaining the other parameters constant.It is suggested that this model would be the best one to use to calculate the SFRS.A graphical user interface for the proposed models is developed to further assist in the calculation of the SFRS for engineering difficulties.In this study,we attempt to bridge the gap between modern slope stability evaluation techniques and more conventional analysis methods.
