Risk assessment of the mine environment information based on multi-sensor information fusion

In recent years there has been frequent mine incidents in China. The scene of the accident leaves a lot of information and the remnants of environmental information. Following an accident, the coal mine is a dangerous environment. The authors developed a risk assessment approach based on multi-sensor information fusion (MSF) of the coal mine environment. Risk assessment of the new algorithm, which adopts BP neural network algorithm and establishes model of coal mine environmental information risk of neural network model predicted the three-layer back propagation neural network, the neural network to connect the entire network structure is 5 – 12 – 5, the five input variables are the H2S (%), temperature (°C), wind speed (m/s), methane (%), CO (%), the five output value is the level of security. The simulation experiments show that the model can accurately assess environmental risk coal mine the extent of the model and can verify the effectiveness and feasibility. The application result shows that the prediction with this method can achieve higher better utility and expensive value.

Authors: Song, Qiang; Wang, Ai-Min; Shi, Hui-Chaoa ;Full Source: Energy Procedia [fusion_builder_container hundred_percent=”yes” overflow=”visible”][fusion_builder_row][fusion_builder_column type=”1_1″ background_position=”left top” background_color=”” border_size=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none”][online computer file] 2011, 11, 47-52 (Eng) ;