Big data-based geological disaster rock mass collapse intelligent monitoring and early warning system

Abstract

The invention discloses a big data-based geological disaster rock mass collapse intelligent monitoring and early warning system. The system comprises a region division module, a detection point distribution module, a pressure detection module, a pressure parameter processing module, a pressure analysis module, an image acquisition module, an image processing module, a crack area detection module,a crack area analysis module, an analysis server, an early warning reminding module, a display terminal and a storage database. According to the system, a to-be-detected rock mass region is divided; an average value of pressure at a central point of each sub-region in each acquisition time period is detected; whether rock mass of each sub-region is in a safe stage or not is analyzed; image acquisition is performed on the surface of the rock mass of each sub-region in a dangerous stage; crack areas in rock mass surface images of the sub-regions are measured; a proportion of the crack areas in the rock mass of each sub-region is calculated; whether the rock mass of each sub-region has a collapse risk or not is judged by comparing; and early warning reminding is performed, so that the life and property safety of surrounding residents is guaranteed.

Description

Technical field[0001]The invention relates to the field of geological disaster monitoring and early warning, and relates to an intelligent monitoring and early warning system for geological disaster rock collapse based on big data.Background technique[0002]Rock collapse is a common bad geological disaster in mountainous areas. Rock collapse has the characteristics of strong suddenness and great destructive power, which seriously threatens the normal production and life of traffic arteries and mountain residents. In my country, it is caused by rock collapses every year. A large number of casualties and heavy economic losses.[0003]At present, traditional rock-mass collapse monitoring technologies generally have some shortcomings. Most of the traditional rock-mass collapse monitoring technologies perform single monitoring on part of the rock mass, and cannot perform real-time monitoring of the entire rock mass area, which has large monitoring limitations. This results in inaccurate mon...

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Problems solved by technology

[0003] At present, the traditional rock mass collapse monitoring technology generally has some deficiencies. The traditional rock mass collapse monitoring technology mostly performs single monitoring on some areas of the rock mass, and cannot monitor the entire rock mass area in real time. There are large monitoring limitations. The monitoring data is inaccurate, leading to false warnings. At the same time, the traditional monitoring method is that people use a ruler to directly measure the width change of the obvious cracks after the rock mass collapses. This measurement accuracy is poor and there is a certain risk. At the same time, the rock mass collapse has Due to the extremely sudden characteristics, it is impossible to realize the early warning effect before the collapse of rock mass, which will affect road traffic safety accidents and threaten the lives and property safety of surrounding residents. In order to solve the above problems, a geological disaster rock mass based on big data is now designed Collapse intelligent monitoring and early warning system

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