The invention discloses a three-dimensional-point-cloud-data-based prevention method of a
coal mine roof disaster.
System equipment comprises a ground analysis device arranged on the ground, an underground center
station, a plurality of three-dimensional
laser scanners having same parameters, and a three-dimensional
point cloud data processing chip, wherein the center
station, the plurality of three-dimensional
laser scanners, and the three-dimensional
point cloud data processing chip are arranged underground. All underground devices are intrinsically safe ones. According to the method, the possibility of roof disaster occurrence is analyzed based on the
point cloud data difference. The
coal mine roof disaster risk is predicted by using a method of analyzing three-dimensional point
cloud data. The structure is simple; the devices are easy to arranged; the adaptability and recognition rate are high; calculation is simple; the operation efficiency is high; manual intervention is reduced; the low cost is low and the adaptability of the
system is high; and hardware and
software can be upgraded or repaired conveniently. A three-dimensional
voxel filtering
algorithm is employ; because of high stability and reliability of the
algorithm,
data compression, being filtering, can be carried out on the collected three-dimensional point
cloud data of the roof rapidly and effectively and the searching can be accelerated greatly. On the basis of a three-dimensional normal distribution transform
algorithm,
rapid convergence can be realized and thus problems of poor registration convergence and frequent occurrence of
local optimum of the common algorithm of the three-dimensional point
cloud data can be solved; and the time is saved and complexity of the common algorithm can be reduced. The method can be applied to monitoring of the roof falling disaster in a complex environment; the monitoring precision and efficiency can be improved effectively; and great convenience is provided for safety production.