APPLICATION OF IMAGE DIGITAL PROCESSING TO EVALUATE ACCURACY IN PREDICTING ROCK FRAGMENTATION INDUCED BY BLASTING

Supandi Sujatono
{"title":"APPLICATION OF IMAGE DIGITAL PROCESSING TO EVALUATE ACCURACY IN PREDICTING ROCK FRAGMENTATION INDUCED BY BLASTING","authors":"Supandi Sujatono","doi":"10.11113/jurnalteknologi.v86.20743","DOIUrl":null,"url":null,"abstract":"Predicting rock fragmentation induced by blasting operation is important in order to evaluate the success of blasting operation. It is necessary to select a method that is in accordance with the characteristics of geological condition and rock mass so that it can quickly provide accurate information. This study aims to evaluate whether Kuz-Ram model is accurate enough in predicting fragmentation of andesite. The analysis was carried out statistically by comparing the andesite fragmentation based on theoretical calculation method by Kuz-Ram model to the fragmentation based on image analysis method by Split Desktop which represents the actual field condition. The data were obtained from 30 blasting operations on andesite. The analysis result shows that the fragmentation based on the theoretical calculation using Kuz-Ram model is not significantly different from the fragmentation based on Split Desktop. The maximum error of percent passing predicted by Kuz-Ram model is around 7% with an average error of 4.94%. Based on the result, calculation using Kuz-Ram theory can be performed to predict fragmentation of andesite.","PeriodicalId":55763,"journal":{"name":"Jurnal Teknologi","volume":"8 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Teknologi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11113/jurnalteknologi.v86.20743","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Predicting rock fragmentation induced by blasting operation is important in order to evaluate the success of blasting operation. It is necessary to select a method that is in accordance with the characteristics of geological condition and rock mass so that it can quickly provide accurate information. This study aims to evaluate whether Kuz-Ram model is accurate enough in predicting fragmentation of andesite. The analysis was carried out statistically by comparing the andesite fragmentation based on theoretical calculation method by Kuz-Ram model to the fragmentation based on image analysis method by Split Desktop which represents the actual field condition. The data were obtained from 30 blasting operations on andesite. The analysis result shows that the fragmentation based on the theoretical calculation using Kuz-Ram model is not significantly different from the fragmentation based on Split Desktop. The maximum error of percent passing predicted by Kuz-Ram model is around 7% with an average error of 4.94%. Based on the result, calculation using Kuz-Ram theory can be performed to predict fragmentation of andesite.
应用图像数字处理技术评估预测爆破引起的岩石破碎的准确性
预测爆破作业引起的岩石破碎对评估爆破作业的成功与否非常重要。有必要选择一种符合地质条件和岩体特征的方法,以便快速提供准确信息。本研究旨在评估 Kuz-Ram 模型在预测安山岩破碎方面是否足够准确。通过比较基于 Kuz-Ram 模型理论计算方法的安山岩破碎率和基于 Split Desktop 图像分析方法的破碎率(Split Desktop 代表现场实际情况),进行了统计分析。数据来自 30 次安山岩爆破作业。分析结果表明,基于 Kuz-Ram 模型的理论计算得出的破碎率与基于 Split Desktop 的破碎率相差不大。Kuz-Ram 模型预测的通过率最大误差约为 7%,平均误差为 4.94%。根据这一结果,可以使用 Kuz-Ram 理论进行计算,预测安山岩的破碎情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
审稿时长
20 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信