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| Remote monitoring and forecasting system of Newton force for landslide geological hazards and its engineering application |
| HE Manchao1，2，REN Shulin1，2，TAO Zhigang1，2 |
(1. State Key Laboratory for Geomechanics and Deep Underground Engineering，China University of Mining and Technology (Beijing)，Beijing 100083，China；2. School of Mechanics and Civil Engineering，China University of Mining and Technology(Beijing)，Beijing 100083，China)
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Abstract Precise monitoring and early warning of landslides are crucial to disaster prevention and mitigation. At present，landslide monitoring and early warning have a low success rate and a lagging early-warning time. In response to these problems，a new monitoring and early warning method was proposed based on the academic idea of “the sufficient and necessary condition for landslides is the change of Newton force”. Besides，a remote monitoring and forecasting system of Newton force for landslide geological hazards was developed. Four aspects of the system including theory，equipment，technology and engineering application were summarized in this article. First，the Newton force change law of geological catastrophes was proposed for the first time in the field of rock mechanics and a double-block mechanical model was constructed based on Newton force change measurement，forming a complete set of landslide Newton force measurement theory. Subsequently，a monitoring and early warning system and negative Possion¢s ratio(NPR) anchor cables suitable for landslide monitoring with high constant resistance，large deformation and super energy absorption characteristics, were developed. Landslide warning modes and warning levels based on Newton force measurement were proposed and an integrated landslide control technology was formed. Finally，the system was implemented at 543 monitoring points in 26 demonstration areas in China. All 16 landslide disasters within the deployment scope were successfully warned，which saved more than 100 lives and hundreds of millions of equipment and property. The scientific problem of short-term landslide prediction was successfully solved.
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2021, Vol. 40 
