پیش بینی پرتاب سنگ ناشی از آتشباری با استفاده از تکنیک درختی M5P | ||
| روش های تحلیلی و عددی در مهندسی معدن | ||
| مقاله 4، دوره 8، شماره 16، آبان 1397، صفحه 45-55 اصل مقاله (1.42 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.29252/anm.8.16.45 | ||
| نویسنده | ||
| ابراهیم قاسمی* | ||
| دانشکده مهندسی معدن، دانشگاه صنعتی اصفهان | ||
| چکیده | ||
| پرتاب سنگ یکی از مسائل بحرانی عملیات آتشباری در معادن روباز است که به شدت ایمنی پرسنل و تجهیزات را تحت تأثیر قرار میدهد. یکی از راههای کاهش ریسک حوادث ناشی از پرتاب سنگ، پیشبینی دقیق آن است. طی سالیان گذشته با استفاده از روشهای هوش مصنوعی، مدلهای تجربی بسیاری برای پیشبینی پرتاب سنگ توسعه داده شده است. اغلب این مدلها شفاف و قابل فهم نبوده و در آنها ارتباط بین پارامترهای ورودی و خروجی به وضوح نشان داده نشده است. هدف از این مقاله ارائه مدلی صریح و قابل فهم برای پیشبینی پرتاب سنگ است. برای این منظور از تکنیک M5P استفاده و به کمک آن ساختاری درخت مانند برای تخمین فاصله پرتاب سنگ ارائه شده است. در این مدل پرتاب سنگ بر اساس یک سری معادلههای خطی پیشبینی میشود، از اینرو استفاده از آن بسیار ساده است. به منظور آموزش و آزمایش مدل درختی پیشنهادی، دادههای آتشباری معدن مس سونگون به کار گرفته شده است. در این مدل فاصله پرتاب سنگ با استفاده از مهم‌ترین پارامترهای قابل کنترل آتشباری یعنی بار سنگ، فاصلهداری چالها، طول گلگذاری، طول چال، قطر چال، خرج ویژه و متوسط خرج در هر چال تخمین زده میشود. دقت و کارایی مدل پیشنهادی با استفاده از شاخصهای آماری R2، VAF و RMSEمورد ارزیابی قرار گرفت. مقدار این شاخصها به ترتیب 1/92 درصد، 92 درصد و 9/3 به دست آمدند. بنابراین میتوان نتیجه گرفت که تکنیک درختی M5P ابزاری مفید و قدرتمند برای پیشبینی پرتاب سنگ است. همچنین، نتایج نشان داد که بار سنگ و قطر چال به ترتیب با اهمیتترین و کم اهمیتترین پارامترها در پیشبینی پرتاب سنگ هستند. | ||
| کلیدواژه‌ها | ||
| معادن روباز؛ آتشباری؛ پرتاب سنگ؛ مدل درختی؛ تکنیک M5P؛ معدن مس سونگون | ||
| عنوان مقاله [English] | ||
| Prediction of blasting-induced flyrock using M5P tree technique | ||
| نویسندگان [English] | ||
| Ebrahim Ghasemi | ||
| Dept. of Mining, Isfahan University of Technology | ||
| چکیده [English] | ||
| Summary Based on statistics, flyrock is the main reason of 20 to 40% of blasting induced accidents in mines. Therefore, the accurate prediction of flyrock has a remarkable role on reducing its detrimental effects. In this paper, a model tree was developed for flyrock prediction using M5P technique. This model was trained and tested by the blasting database of Sungun copper mine. The results showed that the proposed model can estimate the flyrock with an acceptable error. Introduction Flyrock is one of the most challenging safety issues of blasting operation in open pit mines, which always threatens the safety of personnel and equipment. Thus, the accurate prediction of flyrock seems necessary for determination of safe blasting zone. During past years, many empirical models have been developed using artificial intelligence techniques for flyrock prediction. Most of these models do not indicate the relationship between input and output parameters, leading to ambiguous relation of input and output. The main purpose of this paper is to construct a transparent and understandable model for flyrock prediction. Methodology and Approaches In this paper, a model is developed for flyrock prediction using M5P technique. This technique presents a tree structure which contains linear equations in its leaves and using these equations the flyrock can be predicted easily. In this model, the flyrock distance is estimated using the most important controllable blasting parameters (i.e. burden, spacing, stemming, blasthole length, blasthole diameter, powder factor and mean charge per blasthole). Results and Conclusions The accuracy and efficiency of the proposed model was evaluated using various statistical indices such as coefficient and determination (R2), variance account for (VAF) and root mean square error (RMSE). These indices were obtained 92.1%, 92%, and 3.9, respectively. Therefore, it can be concluded that M5P technique is a suitable and efficient means that provides an acceptable prediction for flyrock. Furthermore, the results indicated that the burden and blasthole diameter are the most and the least effective parameters on flyrock prediction, respectively. The output of this model can be considered as a preliminary estimation of flyrock, based on which the risk of hazards and potential accidents can be reduced to a desirable extent. | ||
| کلیدواژه‌ها [English] | ||
| Open pit mines, Blasting, Flyrock, Model tree, M5P technique, Sungun Copper Mine | ||
| مراجع | ||
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