Wireless sensor networks are useful complements to existing monitoring systems in underground mines. They play an important role of enhancing and improving coverage and flexibility of safety monitoring systems.Regions...Wireless sensor networks are useful complements to existing monitoring systems in underground mines. They play an important role of enhancing and improving coverage and flexibility of safety monitoring systems.Regions prone to danger and environments after disasters in underground mines require saving and balancing energy consumption of nodes to prolong the lifespan of networks.Based on the structure of a tunnel,we present a Long Chain-type Wireless Sensor Network（LC-WSN）to monitor the safety of underground mine tunnels.We define the optimal transmission distance and the range of the key region and present an Energy Optimal Routing（EOR）algorithm for LC-WSN to balance the energy consumption of nodes and maximize the lifespan of networks.EOR constructs routing paths based on an optimal transmission distance and uses an energy balancing strategy in the key region.Simulation results show that the EOR algorithm extends the lifespan of a network,balances the energy consumption of nodes in the key region and effectively limits the length of routing paths,compared with similar algorithms.展开更多
Resource management in Underground Wireless Sensor Networks(UWSNs)is one of the pillars to extend the network lifetime.An intriguing design goal for such networks is to achieve balanced energy and spectral resource ut...Resource management in Underground Wireless Sensor Networks(UWSNs)is one of the pillars to extend the network lifetime.An intriguing design goal for such networks is to achieve balanced energy and spectral resource utilization.This paper focuses on optimizing the resource efficiency in UWSNs where underground relay nodes amplify and forward sensed data,received from the buried source nodes through a lossy soil medium,to the aboveground base station.A new algorithm called the Hybrid Chaotic Salp Swarm and Crossover(HCSSC)algorithm is proposed to obtain the optimal source and relay transmission powers to maximize the network resource efficiency.The proposed algorithm improves the standard Salp Swarm Algorithm(SSA)by considering a chaotic map to initialize the population along with performing the crossover technique in the position updates of salps.Through experimental results,the HCSSC algorithm proves its outstanding superiority to the standard SSA for resource efficiency optimization.Hence,the network’s lifetime is prolonged.Indeed,the proposed algorithm achieves an improvement performance of 23.6%and 20.4%for the resource efficiency and average remaining relay battery per transmission,respectively.Furthermore,simulation results demonstrate that the HCSSC algorithm proves its efficacy in the case of both equal and different node battery capacities.展开更多
Karstic aquifers in Southwest China are largely located in mountainous areas and groundwater level observation data are usually absent. Therefore, numerical groundwater models are inappropriate for simulation of groun...Karstic aquifers in Southwest China are largely located in mountainous areas and groundwater level observation data are usually absent. Therefore, numerical groundwater models are inappropriate for simulation of groundwater flow and rainfall-underground outflow responses. In this study, an artificial neural network （ANN） model was developed to simulate underground stream discharge. The ANN model was applied to the Houzhai subterranean drainage in Guizhou Province of Southwest China, which is representative of karstic geomorphology in the humid areas of China. Correlation analysis between daily rainfall and the outflow series was used to determine the model inputs and time lags. The ANN model was trained using an error backpropagation algorithm and validated at three hydrological stations with different karstic features. Study results show that the ANN model performs well in the modeling of highly non-linear karstic aquifers.展开更多
A prediction method of strata movement in underground metal mines is put forward, in which fuzzy BP neural network is applied. The results show that there is a strong nonlinear relation between the selected factors an...A prediction method of strata movement in underground metal mines is put forward, in which fuzzy BP neural network is applied. The results show that there is a strong nonlinear relation between the selected factors and strata movement angle, the anticipant and the actual output results are very similar. It is proved that the numerical value of movement angle is correlated with the selected factors in theory. The scope of strata and surface movement due to mining can be predicted. This research provides a thought to study the movement scope of strata due to mining.展开更多
There are fundamentally two different communication media in wireless underground sensor networks. The first of these is a solid medium where the sensor nodes are buried underground and wirelessly transmit data from u...There are fundamentally two different communication media in wireless underground sensor networks. The first of these is a solid medium where the sensor nodes are buried underground and wirelessly transmit data from underground to aboveground. The second is an underground medium such as tunnel, cave etc. and the data is transmitted from underground to the aboveground through partially solid medium. The quality of communication is greatly influenced by the humidity of the soil in both environments. The placement of wireless underground sensor nodes at hard-to-reach locations makes energy efficient work compulsory. In this paper, rule based collector station selection scheme is proposed for lossless data transmission in underground sensor networks. In order for sensor nodes to transmit energy-efficient lossless data, rulebased selection operations are carried out with the help of fuzzy logic. The proposed wireless underground sensor network is simulated using Riverbed software, and fuzzy logic-based selection scheme is implemented utilizing Matlab software. In order to evaluate the performance of the sensor network;the parameters of delay, throughput and energy consumption are investigated. Examining performance evaluation results, it is seen that average delay and maximum throughput are accomplished in the proposed underground sensor network. Under these conditions, it has been shown that the most appropriate collector station selection decision is made with the aim of minimizing energy consumption.展开更多
Based on the analysis of main causes of rockburst,the compressive strength,tensile strength,elastic energy index of rock and the maximum tangential stress of the cavern wall are chosen as the criterion indexes for roc...Based on the analysis of main causes of rockburst,the compressive strength,tensile strength,elastic energy index of rock and the maximum tangential stress of the cavern wall are chosen as the criterion indexes for rockburst prediction.A new approach using neural method is proposed to predict rockburst occurrence and its intensity.The prediction results show that it is feasible and appropriate to use artificial neural network model for rockburst prediction.展开更多
One of the most serious conundrum facing the stope production in underground metalliferous mining is uneven break （UB： unplanned dilution and ore-loss）. Although the UB has a huge economic fallout to the entire min...One of the most serious conundrum facing the stope production in underground metalliferous mining is uneven break （UB： unplanned dilution and ore-loss）. Although the UB has a huge economic fallout to the entire mining process, it is practically unavoidable due to the complex causing mechanism. In this study, the contribution of ten major UB causative parameters ha,; been scrutinised based on a published UB predicting artificial neuron network （ANN） model to put UB under the engineering management. Two typical ANN sensitivity analysis methods, i.e., connection weight algorithm （CWA） and profile method （PM） have been applied. As a result of CWA and PM applications, adjusted Qrate （AQ） revealed as the most influential parameter to UB with contribution of 22,40% in CWA and 20,48% in PM respectively. The findings of this study can be used as an important reference in stope design, production, and reconciliation stages on underground stoping mine.展开更多
Plumb line variations (PLV) of points at Tangshan and Midu during 1985-1998 are determined by using the 46 batch repeated gravity observations of the Beijing-Tangshan network and 32 batch repeated gravity observations...Plumb line variations (PLV) of points at Tangshan and Midu during 1985-1998 are determined by using the 46 batch repeated gravity observations of the Beijing-Tangshan network and 32 batch repeated gravity observations of the West-Yunan network. As for Tangshan region, relation between underground matter change (UMC) and the PLV on ground are discussed and approach of determining the UMC by a derived regional PLV is found. The UMC before and after earthquake(1995.10.05, Mb 5.0)in Tangshan region, as an example, is studied, giving the location and depth of the mass center of underground disturbing body as well as its mass quantity.展开更多
As air descends the intake shaft, its infrastructure, lining and the strata will emit heat during the night when the intake air is cool and, on the contrary, will absorb heat during the day when the temperature of the...As air descends the intake shaft, its infrastructure, lining and the strata will emit heat during the night when the intake air is cool and, on the contrary, will absorb heat during the day when the temperature of the air becomes greater than that of the strata. This cyclic phenomenon, also known as the "thermal damping effect" will continue throughout the year reducing the effect of surface air temperature variation. The objective of this paper is to quantify the thermal damping effect in vertical underground airways. A nonlinear autoregressive time series with external input(NARX) algorithm was used as a novel method to predict the dry-bulb temperature(Td) at the bottom of intake shafts as a function of surface air temperature. Analyses demonstrated that the artificial neural network(ANN) model could accurately predict the temperature at the bottom of a shaft. Furthermore, an attempt was made to quantify typical "damping coefficient" for both production and ventilation shafts through simple linear regression models. Comparisons between the collected climatic data and the regression-based predictions show that a simple linear regression model provides an acceptable accuracy when predicting the Tdat the bottom of intake shafts.展开更多
This paper attempts to provide an overview of risk assessment and management practice in underground rock engineering based on a review of the international literature and some personal experience. It is noted that th...This paper attempts to provide an overview of risk assessment and management practice in underground rock engineering based on a review of the international literature and some personal experience. It is noted that the terminologies used in risk assessment and management studies may vary from country to country. Probabilistic risk analysis is probably the most widely-used approach to risk assessment in rock engineering and in geotechnical engineering more broadly. It is concluded that great potential exists to augment the existing probabilistic methods by the use of Bayesian networks and decision analysis techniques to allow reasoning under uncertainty and to update probabilities, material properties and analyses as further data become available throughout the various stages of a project. Examples are given of the use of these methods in underground excavation engineering in China and elsewhere, and opportunities for their further application are identified.展开更多
基金Financial support for this work,provided by the National Natural Science Foundation of China(No.50904070)the Science and Technology Foundation of China University of Mining & Technology (Nos.2007A046 and 2008A042)the Joint Production and Research Innovation Project of Jiangsu Province (No.BY2009114)
文摘Wireless sensor networks are useful complements to existing monitoring systems in underground mines. They play an important role of enhancing and improving coverage and flexibility of safety monitoring systems.Regions prone to danger and environments after disasters in underground mines require saving and balancing energy consumption of nodes to prolong the lifespan of networks.Based on the structure of a tunnel,we present a Long Chain-type Wireless Sensor Network（LC-WSN）to monitor the safety of underground mine tunnels.We define the optimal transmission distance and the range of the key region and present an Energy Optimal Routing（EOR）algorithm for LC-WSN to balance the energy consumption of nodes and maximize the lifespan of networks.EOR constructs routing paths based on an optimal transmission distance and uses an energy balancing strategy in the key region.Simulation results show that the EOR algorithm extends the lifespan of a network,balances the energy consumption of nodes in the key region and effectively limits the length of routing paths,compared with similar algorithms.
文摘Resource management in Underground Wireless Sensor Networks(UWSNs)is one of the pillars to extend the network lifetime.An intriguing design goal for such networks is to achieve balanced energy and spectral resource utilization.This paper focuses on optimizing the resource efficiency in UWSNs where underground relay nodes amplify and forward sensed data,received from the buried source nodes through a lossy soil medium,to the aboveground base station.A new algorithm called the Hybrid Chaotic Salp Swarm and Crossover(HCSSC)algorithm is proposed to obtain the optimal source and relay transmission powers to maximize the network resource efficiency.The proposed algorithm improves the standard Salp Swarm Algorithm(SSA)by considering a chaotic map to initialize the population along with performing the crossover technique in the position updates of salps.Through experimental results,the HCSSC algorithm proves its outstanding superiority to the standard SSA for resource efficiency optimization.Hence,the network’s lifetime is prolonged.Indeed,the proposed algorithm achieves an improvement performance of 23.6%and 20.4%for the resource efficiency and average remaining relay battery per transmission,respectively.Furthermore,simulation results demonstrate that the HCSSC algorithm proves its efficacy in the case of both equal and different node battery capacities.
基金supported by the National Basic Research Program of China (973 Program, Grant No 2006CB403200)the National Natural Scientific Foundation of China (Grant No 50679025)the 111 Project of the Ministry of Education and the State Administration of Foreign Expert Affairs, China (Grant No. B08048)
文摘Karstic aquifers in Southwest China are largely located in mountainous areas and groundwater level observation data are usually absent. Therefore, numerical groundwater models are inappropriate for simulation of groundwater flow and rainfall-underground outflow responses. In this study, an artificial neural network （ANN） model was developed to simulate underground stream discharge. The ANN model was applied to the Houzhai subterranean drainage in Guizhou Province of Southwest China, which is representative of karstic geomorphology in the humid areas of China. Correlation analysis between daily rainfall and the outflow series was used to determine the model inputs and time lags. The ANN model was trained using an error backpropagation algorithm and validated at three hydrological stations with different karstic features. Study results show that the ANN model performs well in the modeling of highly non-linear karstic aquifers.
文摘A prediction method of strata movement in underground metal mines is put forward, in which fuzzy BP neural network is applied. The results show that there is a strong nonlinear relation between the selected factors and strata movement angle, the anticipant and the actual output results are very similar. It is proved that the numerical value of movement angle is correlated with the selected factors in theory. The scope of strata and surface movement due to mining can be predicted. This research provides a thought to study the movement scope of strata due to mining.
文摘There are fundamentally two different communication media in wireless underground sensor networks. The first of these is a solid medium where the sensor nodes are buried underground and wirelessly transmit data from underground to aboveground. The second is an underground medium such as tunnel, cave etc. and the data is transmitted from underground to the aboveground through partially solid medium. The quality of communication is greatly influenced by the humidity of the soil in both environments. The placement of wireless underground sensor nodes at hard-to-reach locations makes energy efficient work compulsory. In this paper, rule based collector station selection scheme is proposed for lossless data transmission in underground sensor networks. In order for sensor nodes to transmit energy-efficient lossless data, rulebased selection operations are carried out with the help of fuzzy logic. The proposed wireless underground sensor network is simulated using Riverbed software, and fuzzy logic-based selection scheme is implemented utilizing Matlab software. In order to evaluate the performance of the sensor network;the parameters of delay, throughput and energy consumption are investigated. Examining performance evaluation results, it is seen that average delay and maximum throughput are accomplished in the proposed underground sensor network. Under these conditions, it has been shown that the most appropriate collector station selection decision is made with the aim of minimizing energy consumption.
基金Supported by Chinese National Natural Science Foundaion(49972091)
文摘Based on the analysis of main causes of rockburst,the compressive strength,tensile strength,elastic energy index of rock and the maximum tangential stress of the cavern wall are chosen as the criterion indexes for rockburst prediction.A new approach using neural method is proposed to predict rockburst occurrence and its intensity.The prediction results show that it is feasible and appropriate to use artificial neural network model for rockburst prediction.
文摘One of the most serious conundrum facing the stope production in underground metalliferous mining is uneven break （UB： unplanned dilution and ore-loss）. Although the UB has a huge economic fallout to the entire mining process, it is practically unavoidable due to the complex causing mechanism. In this study, the contribution of ten major UB causative parameters ha,; been scrutinised based on a published UB predicting artificial neuron network （ANN） model to put UB under the engineering management. Two typical ANN sensitivity analysis methods, i.e., connection weight algorithm （CWA） and profile method （PM） have been applied. As a result of CWA and PM applications, adjusted Qrate （AQ） revealed as the most influential parameter to UB with contribution of 22,40% in CWA and 20,48% in PM respectively. The findings of this study can be used as an important reference in stope design, production, and reconciliation stages on underground stoping mine.
文摘Plumb line variations (PLV) of points at Tangshan and Midu during 1985-1998 are determined by using the 46 batch repeated gravity observations of the Beijing-Tangshan network and 32 batch repeated gravity observations of the West-Yunan network. As for Tangshan region, relation between underground matter change (UMC) and the PLV on ground are discussed and approach of determining the UMC by a derived regional PLV is found. The UMC before and after earthquake(1995.10.05, Mb 5.0)in Tangshan region, as an example, is studied, giving the location and depth of the mass center of underground disturbing body as well as its mass quantity.
基金funded by National Institute for Occupational Safety and Health (NIOSH) (No. 2014-N-15795, 2014)
文摘As air descends the intake shaft, its infrastructure, lining and the strata will emit heat during the night when the intake air is cool and, on the contrary, will absorb heat during the day when the temperature of the air becomes greater than that of the strata. This cyclic phenomenon, also known as the "thermal damping effect" will continue throughout the year reducing the effect of surface air temperature variation. The objective of this paper is to quantify the thermal damping effect in vertical underground airways. A nonlinear autoregressive time series with external input(NARX) algorithm was used as a novel method to predict the dry-bulb temperature(Td) at the bottom of intake shafts as a function of surface air temperature. Analyses demonstrated that the artificial neural network(ANN) model could accurately predict the temperature at the bottom of a shaft. Furthermore, an attempt was made to quantify typical "damping coefficient" for both production and ventilation shafts through simple linear regression models. Comparisons between the collected climatic data and the regression-based predictions show that a simple linear regression model provides an acceptable accuracy when predicting the Tdat the bottom of intake shafts.
文摘This paper attempts to provide an overview of risk assessment and management practice in underground rock engineering based on a review of the international literature and some personal experience. It is noted that the terminologies used in risk assessment and management studies may vary from country to country. Probabilistic risk analysis is probably the most widely-used approach to risk assessment in rock engineering and in geotechnical engineering more broadly. It is concluded that great potential exists to augment the existing probabilistic methods by the use of Bayesian networks and decision analysis techniques to allow reasoning under uncertainty and to update probabilities, material properties and analyses as further data become available throughout the various stages of a project. Examples are given of the use of these methods in underground excavation engineering in China and elsewhere, and opportunities for their further application are identified.
