本文選題：精細爆破　切入點：神經(jīng)網(wǎng)絡　出處：《內(nèi)蒙古科技大學》2015年碩士論文

【摘要】：精細爆破以可持續(xù)發(fā)展理論、科學發(fā)展觀和低碳經(jīng)濟為理論指導的，是其在工程爆破領域的重要應用和體現(xiàn)，以實現(xiàn)安全可靠、技術(shù)先進、綠色環(huán)保及經(jīng)濟合理的爆破作業(yè)為目標。白云鄂博西礦現(xiàn)有技術(shù)裝備條件已經(jīng)為精細爆破技術(shù)的實施提供了必要的條件，以“精細爆破”理念指導礦山日常生產(chǎn)爆破，發(fā)揮現(xiàn)有技術(shù)裝備的優(yōu)勢，加快礦山工程爆破的數(shù)字化、信息化建設，提高礦山的生產(chǎn)爆破效率，改善爆破效果，降低爆破危害。本文將結(jié)合實際工程地質(zhì)條件和技術(shù)裝備條件，系統(tǒng)論述精細爆破在白云鄂博西礦的實踐應用，并結(jié)合現(xiàn)場生產(chǎn)試驗數(shù)據(jù)分析驗證，建立并完善適用于西礦的精細爆破體系。 調(diào)研白云鄂博西礦地質(zhì)資料和對現(xiàn)有采掘、裝載、運輸裝備進行系統(tǒng)分析，西礦的各項情況均達到了實施精細爆破的技術(shù)條件，通過構(gòu)建西礦精細爆破技術(shù)體系，，進一步挖掘西礦技術(shù)設備的潛力，如運用定位手段準確反映設備及生產(chǎn)設施位置，使計算機輔助設計系統(tǒng)和礦山設備有機的結(jié)合。提高礦山生產(chǎn)中信息交換速率，加強動態(tài)監(jiān)管，實現(xiàn)生產(chǎn)的可視化調(diào)度，提高爆破工作的整體效能。運用徑向基神經(jīng)網(wǎng)絡RBF分析爆破數(shù)據(jù)，建立實施性強、計算精確的爆破效果預測模型，優(yōu)化爆破設計方案和爆破參數(shù)，提高了爆破設計效率。逐步完善白云鄂博西礦的礦山數(shù)字化建設，使用Surpac軟件建立爆破區(qū)域的三維模型，并進行三維可視化的爆破設計，形象地展示爆破方案，并對爆破結(jié)果進行估算，降低了爆破設計人員的工作量，加快了爆破設計進度。通過對白云鄂博西礦臺階爆破流程的分析，給出了爆破工作流程化、精細化、協(xié)同化和經(jīng)濟化管理的幾點建議，為提高企業(yè)內(nèi)部爆破管理水平提供參考。依據(jù)現(xiàn)場采集的爆破振動數(shù)據(jù)，構(gòu)建基于MATLAB的BP神經(jīng)網(wǎng)路預測模型，精準預測爆破振動，降低爆破振動對工程設備，建筑和巖質(zhì)邊坡的危害。分析爆破飛石產(chǎn)生原因，結(jié)合實際情況給出降低爆破振動和控制飛石發(fā)生的措施。
[Abstract]:Fine blasting, guided by the theory of sustainable development, scientific development and low-carbon economy, is an important application and embodiment in the field of engineering blasting, in order to realize safety and reliability and advanced technology.Green environmental protection and reasonable blasting operation is the goal.The existing technical and equipment conditions of Bayan Obo West Mine have provided necessary conditions for the implementation of fine blasting technology. The concept of "fine blasting" is used to guide the daily production blasting of the mine and give play to the advantages of the existing technology and equipment.To accelerate the digitization and information construction of mine engineering blasting, to improve the efficiency of mine blasting, to improve the blasting effect and to reduce the blasting harm.In this paper, the practical application of fine blasting in Baiyunebo West Mine is systematically discussed in combination with the actual engineering geological conditions and technical equipment conditions, and the fine blasting system suitable for the west mine is established and perfected with the analysis and verification of the field production test data.The geological data of West Bayan Obo Mine and the system analysis of the existing mining, loading and transportation equipment are investigated. All the conditions of the mine have reached the technical conditions of implementing fine blasting, and the technical system of fine blasting in the west mine has been constructed.Further excavating the potential of the technical equipment in the west mine, such as accurately reflecting the location of the equipment and the production facilities by means of positioning, making the computer aided design system and the mining equipment organically combined.To improve the rate of information exchange in mine production, to strengthen dynamic supervision, to realize visual scheduling of production, and to improve the overall efficiency of blasting work.The radial basis function neural network (RBF) is used to analyze the blasting data, to set up a feasible and accurate blasting effect prediction model, to optimize the blasting design scheme and blasting parameters, and to improve the blasting design efficiency.The mine digitization construction of Bayan Obo West Mine is perfected step by step, the 3D model of blasting area is established by using Surpac software, and the 3D visual blasting design is carried out, the blasting scheme is displayed vividly, and the blasting result is estimated.The workload of blasting designers is reduced and the blasting design progress is accelerated.Based on the analysis of bench blasting process in Bayan Obo West Coal Mine, some suggestions for the management of blasting work flow, refinement, coordination and economy are given, which provide a reference for improving the level of blasting management in enterprises.Based on the field data of blasting vibration, BP neural network prediction model based on MATLAB is constructed to accurately predict blasting vibration and reduce the harm of blasting vibration to engineering equipment, building and rock slope.The causes of blasting flying stone are analyzed, and the measures to reduce blasting vibration and control the occurrence of flying stone are given.
【學位授予單位】：內(nèi)蒙古科技大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TD235

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