کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
313057 534359 2014 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Performance prediction of roadheaders in metallic ore excavation
ترجمه فارسی عنوان
پیش بینی عملکرد جاده های هیدرولیکی در حفاری های فلزی
کلمات کلیدی
سرنشینان پیش بینی عملکرد، انرژی خاص سنگ معدن فلزی، خواص فیزیکی و مکانیکی
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات مهندسی ژئوتکنیک و زمین شناسی مهندسی
چکیده انگلیسی


• The performance prediction and cutter consumption of roadheaders for the eight different ore types were investigated.
• The instantaneous cutting rates of a selected roadheader were calculated using the specific energy values.
• Simple and multiple regression models were also derived for the estimation of SE from the ore properties.

Using mechanical miners such as roadheaders may be a solution to increase the production rate and to decrease the costs in metallic mines. In this study, the performance prediction and cutter consumption of roadheaders were investigated for the eight different ore types. Small-scale linear cutting tests, Cerchar abrasivity tests and physico-mechanical tests were carried out on the ore samples collected from the site. The instantaneous cutting rates of a selected roadheader were calculated using specific energy (SE) values and compared to the previous models. The amount of cutter consumption was also calculated for each ore type and it was seen that the estimated cutter consumption values for the tested ores are generally lower than the proposed economical upper limit. Since only the performance prediction and cutter consumption of roadheaders were investigated for the excavation of ores in the current study, analyzing all mining operations is necessary for the adaptation of roadheader excavation to a mine. Simple and multiple regression models were also derived for the estimation of SE from the ore properties. A significant practical model including the Schmidt hammer value and density of ores was produced from the multiple regression analysis. This regression model can be reliably used for the estimation of SE especially for the preliminary studies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Tunnelling and Underground Space Technology - Volume 40, February 2014, Pages 38–45
نویسندگان
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