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Improving Blast Fragmentation Prediction With New Technologies for Rock Mass Characterization

机译:用新技术改善爆炸碎片预测

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There are many methods used to predict blast fragmentation, including empirical and numerical models, field trials, and experience from ongoing blasting. All of these methods require an accurate measurement or prediction of the rock mass properties. These properties include the characteristics of the rock fractures, including fracture density, friction angle, orientation, length, roughness, fill, etc. They also include the hardness of the intact rock, water content, and other parameters. This paper describes three new technologies that can be used to automatically or semi-automatically obtain rock mass properties: digital image processing, 3D laserscanners, and drill monitoring systems. Each of these technologies is described, including the current state of the art, current limitations, and their future potential. Each of these three technologies has advantages and disadvantages. These new technologies, however, have the potential for providing accurate rock mass information in an automated and real time fashion. This information can then form the basis for a new generation of real-time, database driven blast fragmentation models.
机译:有许多用于预测爆炸碎片的方法,包括实证和数值模型,现场试验以及来自持续爆破的经验。所有这些方法都需要精确的测量或预测岩体质量。这些性质包括岩石骨折的特性,包括断裂密度,摩擦角,取向,长度,粗糙度,填充等。它们还包括完整岩石,含水量和其他参数的硬度。本文介绍了三种新技术,可用于自动或半自动获得岩体质量特性:数字​​图像处理,3D激光器和钻探监控系统。描述了这些技术中的每一个,包括本领域的当前状态,当前限制和它们的未来电位。这三种技术中的每一个都具有优缺点。然而,这些新技术有可能以自动和实时方式提供准确的岩石大众信息。然后,此信息可以为新一代实时,数据库驱动的爆炸碎片模型构成基础。

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