The ongoing need to deliver improved safety, productivity and environmental benefit in coal mining presents an open challenge as well as a powerful incentive to develop new and improved solutions. This paper assesses ...The ongoing need to deliver improved safety, productivity and environmental benefit in coal mining presents an open challenge as well as a powerful incentive to develop new and improved solutions. This paper assesses the critical role that enabling technologies have played in the delivery of remote and automated capability for longwall mining. A brief historical account is given to highlight key technical contributions which have influenced the direction and development of present-day longwall technology. The current state of longwall automation is discussed with particular attention drawn to the technologies that enable automated capability. Outcomes are presented from an independently conducted case study that assessed the impact that CSIRO＇s LASC longwall automation research has made to the longwall mining industry in Australia. Importantly, this study reveals how uptake of this innova- tive technology has significantly benefitted coal mine productivity, improved working conditions for personnel and enhanced environmental outcomes. These benefits have been widely adopted with CSIRO automation technology being used in 60 per cent of all Australian underground operations. International deployment of the technology is also emerging. The paper concludes with future challenges and opportunities to highfight the ongoing scope for longwall automation research and development.展开更多
An efficient and reliable automated model that can map physical Soil and Water Conservation（SWC） structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ...An efficient and reliable automated model that can map physical Soil and Water Conservation（SWC） structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and Arc GIS？ERDAS IMAGINE？and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures：（1） a high-pass spatial filter algorithm was applied to detect linear features,（2） morphological processing was used to remove unwanted linear features,（3） the raster format was vectorized,（4） the vectorized linear features were split per hectare（ha） and each line was then classified according to its compass directionand（5） the sum of all vector lengths per class of direction per ha was calculated. Finallythe direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Thereforethe model is useful for predicting and mapping physical SWC structures areas across diverse areas.展开更多
文摘The ongoing need to deliver improved safety, productivity and environmental benefit in coal mining presents an open challenge as well as a powerful incentive to develop new and improved solutions. This paper assesses the critical role that enabling technologies have played in the delivery of remote and automated capability for longwall mining. A brief historical account is given to highlight key technical contributions which have influenced the direction and development of present-day longwall technology. The current state of longwall automation is discussed with particular attention drawn to the technologies that enable automated capability. Outcomes are presented from an independently conducted case study that assessed the impact that CSIRO＇s LASC longwall automation research has made to the longwall mining industry in Australia. Importantly, this study reveals how uptake of this innova- tive technology has significantly benefitted coal mine productivity, improved working conditions for personnel and enhanced environmental outcomes. These benefits have been widely adopted with CSIRO automation technology being used in 60 per cent of all Australian underground operations. International deployment of the technology is also emerging. The paper concludes with future challenges and opportunities to highfight the ongoing scope for longwall automation research and development.
基金covered by the Swiss National Centre of Competence in Research North-South (NCCR North-South) program
文摘An efficient and reliable automated model that can map physical Soil and Water Conservation（SWC） structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and Arc GIS？ERDAS IMAGINE？and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures：（1） a high-pass spatial filter algorithm was applied to detect linear features,（2） morphological processing was used to remove unwanted linear features,（3） the raster format was vectorized,（4） the vectorized linear features were split per hectare（ha） and each line was then classified according to its compass directionand（5） the sum of all vector lengths per class of direction per ha was calculated. Finallythe direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Thereforethe model is useful for predicting and mapping physical SWC structures areas across diverse areas.
