【摘要】：目前,我國對于提高礦山自動化、信息化的需求日益迫切,礦體圈定是礦山勘探開發(fā)、生產(chǎn)過程中重要的過程,礦體圈定的結果直接影響著礦山后續(xù)開發(fā)和生產(chǎn)的效率,礦山普遍使用的基于專家經(jīng)驗的手工圈定方法具有效率和準確性較低的特點,基于神經(jīng)網(wǎng)絡、地質(zhì)統(tǒng)計學等圈定算法未能完善的解決圈定過程中主觀隨意性、自動圈定、成礦機理表述不清、計算數(shù)據(jù)要求高等問題。盡管許多新技術、新方法被引入到礦山勘探開發(fā)工程中,但是由于金屬礦床形成機制復雜、空間分布具有隨機性、礦區(qū)采樣有限等因素,導致礦體圈定算法發(fā)展緩慢,因此設計出高效、準確的圈定算法成為礦山勘探開發(fā)過程中亟需解決的重要課題。在當前的技術條件下,以多學科、多技術融合的方式,研究控礦約束特征,構建合適的數(shù)據(jù)模型實現(xiàn)算法創(chuàng)新,建立顧及控礦約束的礦體圈定新算法成為解決上述問題的可能途徑。本論文以該需求為驅(qū)動,研究顧及控礦約束的金屬礦體圈定算法,主要研究內(nèi)容和結論包含如下兩個方面:(1)通過綜合分析國內(nèi)外使用的礦體圈定方法,對各主要圈定方法的優(yōu)劣和發(fā)展趨勢進行了概括和研究,然后系統(tǒng)介紹了礦體圈定的相關概念并分析了成礦與控礦理論。在此基礎上,針對隱伏式金屬礦體圈定的地質(zhì)特征、成礦規(guī)律和已有礦體圈定方法的不足,分析礦體成礦過程、不同地質(zhì)條件下的控礦機理和地質(zhì)要素的空間特征以及分析礦山普遍采集的涉及地下礦體認識的數(shù)據(jù)特征,在GIS空間數(shù)據(jù)管理的基礎上,構建包含基于GIS的控礦約束數(shù)據(jù)模型、礦體圈定計算數(shù)據(jù)數(shù)據(jù)模型以及繪制數(shù)據(jù)模型在內(nèi)的礦體圈定數(shù)據(jù)模型,其中控礦約束數(shù)據(jù)模型為定量化表達礦體約束和算法創(chuàng)新提供重要支撐。(2)針對隱伏式金屬礦山,根據(jù)建立的礦體圈定數(shù)據(jù)模型,在GIS空間數(shù)據(jù)管理和分析方法的支持下,對傳統(tǒng)基于專家知識規(guī)則的礦體圈定方法進行改進,同時借助SD法中的圈礦理論,在合理利用控礦數(shù)據(jù)的約束作用下,提出了一套顧及控礦約束的礦體圈定算法,實現(xiàn)了控礦約束數(shù)據(jù)的定量化表達、描述、計算,解決以往圈定算法中存在的具有主觀隨意性、圈定效率低下、成礦機理表述不清以及計算數(shù)據(jù)要求較高等問題。以寶鋼梅山鐵礦為試驗區(qū)域,對礦體圈定算法進行了實踐和驗證,結果表明本文的圈定算法較好的實現(xiàn)了預期目標。
[Abstract]:At present, the demand for improving mine automation and informatization is becoming more and more urgent in our country. Orebody delineation is an important process in mine exploration and development, and the result of orebody delineation directly affects the efficiency of mine subsequent development and production. The manual delineation method based on expert experience, which is widely used in mines, has the characteristics of low efficiency and accuracy. Based on neural network, geostatistics and other delineation algorithms, it is not perfect to solve the subjective arbitrariness and automatic delineation in the process of delineation. The metallogenic mechanism is not clearly expressed and the calculation data are required to be high. Although many new technologies and methods have been introduced into mine exploration and development projects, due to the complex formation mechanism of metal deposits, randomness of spatial distribution, limited sampling in mining areas and other factors, the development of orebody delineation algorithm is slow. Therefore, the design of efficient and accurate delineation algorithm has become an important issue to be solved in the process of mine exploration and development. Under the current technical conditions, the characteristics of ore control constraints are studied in the way of multi-disciplinary and multi-technology fusion, and the appropriate data model is constructed to realize the algorithm innovation. The establishment of a new algorithm for orebody delineation considering ore control constraints is a possible way to solve the above problems. Driven by this demand, this paper studies the ore body delineation algorithm considering ore control constraints. The main research contents and conclusions include the following two aspects: (1) through comprehensive analysis of ore body delineation methods used at home and abroad, The advantages, disadvantages and development trends of the main delineation methods are summarized and studied, and then the related concepts of orebody delineation are systematically introduced and the metallogenic and ore-control theories are analyzed. On this basis, in view of the geological characteristics of concealed metal orebodies, metallogenic laws and the shortcomings of existing ore body delineation methods, the metallogenic process of orebodies is analyzed. The mechanism of ore control under different geological conditions and the spatial characteristics of geological elements, as well as the data characteristics commonly collected by mines involving underground orebodies, are analyzed. On the basis of GIS spatial data management, the data model of ore control constraints based on GIS is constructed. The ore body delineation calculation data model and the ore body delineation data model, including the drawing data model, which provide important support for quantitative expression of orebody constraints and algorithm innovation. (2) for hidden metal mines, According to the established orebody delineation data model, with the support of GIS spatial data management and analysis method, the traditional orebody delineation method based on expert knowledge rules is improved, and with the help of the ore circle theory in SD method, Under the restriction of reasonable utilization of ore control data, a set of orebody delineation algorithm considering ore control constraint is proposed, which realizes the quantitative expression, description and calculation of ore control constraint data, and solves the subjective arbitrariness existing in the previous delineation algorithm. The efficiency of delineation is low, the expression of metallogenic mechanism is not clear and the requirements of calculation data are high. Taking Meishan Iron Mine of Baosteel as the test area, the ore body delineation algorithm is practiced and verified. The results show that the delineation algorithm in this paper achieves the expected goal well.
【學位授予單位】：南京師范大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TD851

【相似文獻】

相關期刊論文 前10條

1 李偉忠;馬小剛;徐兵;;基于GIS的多工程礦體圈定模型分析與實現(xiàn)[J];有色金屬(礦山部分);2009年02期

2 張清;改進礦體圈定方法,提高礦山經(jīng)濟效益[J];有色金屬礦產(chǎn)與勘查;1997年02期

3 莫德，

本文編號：2487556