当前位置: X-MOL 学术Arab. J. Geosci. › 论文详情
Prediction of drilling rate index from rock strength and cerchar abrasivity index properties using fuzzy inference system
Arabian Journal of Geosciences ( IF 1.327 ) Pub Date : 2021-02-22 , DOI: 10.1007/s12517-021-06647-w
Utku Sakız, Gulhan Ustabas Kaya, Olgay Yaralı

Rock drillability characteristic is one of the important properties for mining and tunneling operations. The rock drillability can be determined by using the drilling rate index (DRI) for engineering applications. The present study attempts to develop a practical and convenient DRI estimation model by using rock strength and abrasivity properties. For this purpose, fuzzy inference system (FIS) being an accurate prediction model was applied to predict DRI by using experimental data obtained with 37 different rocks. The predictive FIS based on experts knowledge by taking mechanical and abrasivity properties as input parameters was created on MATLAB. This structure was carried out by using Mamdani extraction method. DRI values obtained experimentally and estimated from the FIS model were compared. This comparison is given with statistically reliable (R2=0.9277) results. In order to prove the validity of the FIS model for DRI prediction, a validation process has been performed by using test data as well. The performance determination coefficients (R2) are found as 0.9513 by using test data. As a result, it was found that DRI values can be predicted very efficiently and accurately with the proposed prediction method.



中文翻译:

基于模糊推理系统的岩石强度和煤char石磨耗指数特性预测钻井速率指数

岩石可钻性是采矿和隧道作业的重要属性之一。可以通过在工程应用中使用钻速指数(DRI)来确定岩石的可钻性。本研究试图通过利用岩石强度和耐磨性来开发一种实用且方便的DRI估算模型。为此,通过使用在37种不同岩石上获得的实验数据,将作为准确预测模型的模糊推理系统(FIS)应用于DRI预测。在MATLAB上创建了基于专家知识的预测性FIS,该预测性FIS将机械和磨蚀性作为输入参数。该结构通过使用Mamdani提取方法进行。比较了实验获得的DRI值和从FIS模型估算的DRI值。这种比较在统计上可靠(R 2 = 0.9277)结果。为了证明FIS模型对于DRI预测的有效性,还通过使用测试数据执行了验证过程。使用测试数据发现性能确定系数(R 2)为0.9513。结果,发现利用所提出的预测方法可以非常有效且准确地预测DRI值。

更新日期:2021-02-22
全部期刊列表>>
2021新春特辑
SN Applied Sciences期刊征稿中
JCR Q1医学全学科
虚拟特刊
亚洲大洋洲地球科学
NPJ欢迎投稿
自然科研论文编辑
ERIS期刊投稿
欢迎阅读创刊号
自然职场,为您触达千万科研人才
spring&清华大学出版社
城市可持续发展前沿研究专辑
Springer 纳米技术权威期刊征稿
全球视野覆盖
施普林格·自然新
chemistry
物理学研究前沿热点精选期刊推荐
自然职位线上招聘会
欢迎报名注册2020量子在线大会
化学领域亟待解决的问题
材料学研究精选新
GIANT
ACS ES&T Engineering
ACS ES&T Water
屿渡论文,编辑服务
阿拉丁试剂right
上海中医药大学
南科大-连续三周2.26
西湖大学
化学所
北京大学
山东大学
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
南方科技大学
张凤娇
中国石油大学
天合科研
x-mol收录
试剂库存
down
wechat
bug