Abstract
Real-time mine ventilation network solution is the core way to realize the actual intelligent ventilation, and ventilation friction resistance coefficient is a significant parameter of network solution. With the help of fractal theory to characterize the three-dimensional roughness characteristics of tunnel surrounding rock. A method to describe the roughness by fractal dimension and fractal intercept. We put the fractal dimension and fractal intercept into Matlab to randomly generate three-dimensional laser scanning data of tunnels. The fusion of the two fractal parameters made the three-dimensional roughness surface information more comprehensive. It has been applied to field practice accurately. Compared to the simulation results show that the relative error of the new prediction results is 3%. Comprehensive evaluation analysis shows that the new friction wind resistance formula can fully reflect the influence of three-dimensional rough surfaces on airflow friction resistance. With the help of three-dimensional laser scanning technology, we can calculate the airflow friction resistance of the tunnel quickly and accurately, which provides a reference for the development of key technology and the theory of intelligent ventilation parameter measurement.
Highlights
Real-time mine ventilation network solution is the core way to realize the actual intelligent ventilation, and ventilation friction resistance coefficient is a significant parameter of network solution
To apply fractal dimension to empirical formulas in various fields, some scholars studied the relationship between fractal dimension and three-dimensional roughness parameters to establish the nonlinear law between t hem[22,23,24]
This study proposes a new prediction algorithm for ventilation friction resistance coefficient with three-dimensional point cloud and fractal theory
Summary
The tunnel surface is scanned at different scales to acquire points, and we can use the small scale to obtain dense sections. Scanning section density changes are the spatial form of the triangular mesh changes, and the airflow obstacle angle changes. The unique representation of roughness can be achieved by analyzing the relationship between the density change of the point cloud in the spatial sequence and the obstacle angle. Further analysis shows that the fractal dimension is a relative roughness index that measures the complexity of the surface and has nothing to do with the measurement scale. It can be seen that a single fractal parameter is not comprehensive to describe the roughness of the joint surface, so it is necessary to consider the influence of fractal dimension and fractal intercept together.
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