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The Law Of Seismic Wave Transmit And The Safty Estimate System Of Surface Blasting Seismic Effects Close To Village

Posted on:2004-04-29Degree:MasterType:Thesis
Country:ChinaCandidate:C G LiFull Text:PDF
GTID:2121360242456018Subject:Mining engineering
Abstract/Summary:PDF Full Text Request
Engineering blasting often brings vibration. When vibration reaches some degree of intension, nearby buildings will be destroyed, and psychology of inhabitants will get bad influence. This is blasting seismic effects.According to the analysis of the development of blasting seismic effects'safety criterion and engineering practice, using both vibration velocity and vibration frequency as the safety criterion of blasting vibration is a trend.Recently, engineering technicians use neural network model to forecast blasting seismic effects, this measure has potential of development.Malanzhuang Iron Mine is a large-scale surface Mine in the city of qianan. It has two stopes close to village, its blasting vibration affects buildings and inhabitants. Based on producing blasting of Malanzhuang Iron Mine, this paper analysis the law of blasting seismic wave transmition, and effects to building from frequency, last time and times, etc.At the same time, according to the actual situation of Malanzhuang Mine, find appropriate measure of decreasing vibration, and confirm 25ms as logical delay interval. Reducing seismic radio of millisecond blasting reaches 31.4%. Its reducing seismic effect is very well.Furthermore,interval charging technique reduces producing costs. Because of limited by amount of collected data,decreasing seismic effect needs further observation. In producing blasting of Malanzhuang Iron Mine, a whole neural network model has been set up. This model is trained utilizing actual data, and forecasts seismic effects in producing. Prediction's hit ratio reaches 70%.To similar surfacing blasting close to village , this paper has actual value.
Keywords/Search Tags:Surface blasting seismic effects close to village, the law of blastingseismic wave, frequency of vibration, neural network model of forecast and estimate, measure of reducing vibration
PDF Full Text Request
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