Characterization of fragmented rock piles is a fundamental task in the mining and quarrying industries, where rock is fragmented by blasting, transported using wheel loaders, and then sent for further processing. This field report studies a novel method for estimating the relative particle size of fragmented rock piles from only proprioceptive data collected while digging with a wheel loader. Rather than employ exteroceptive sensors (e.g., cameras or LiDAR sensors) to estimate rock particle sizes, the studied method infers rock fragmentation from an excavator's inertial response during excavation. This paper expands on research that postulated the use of wavelet analysis to construct a unique feature that is proportional to the level of rock fragmentation. We demonstrate through extensive field experiments that the ratio of wavelet features, constructed from data obtained by excavating in different rock piles with different size distributions, approximates the ratio of the mean particle size of the two rock piles. Full-scale excavation experiments were performed with a battery electric, 18-tonne capacity, load-haul-dump (LHD) machine in representative conditions in an operating quarry. The relative particle size estimates generated with the proposed sensing methodology are compared with those obtained from both a vision-based fragmentation analysis tool and from sieving of sampled materials.

翻译：碎石堆的表征是采矿和采石行业的一项基本任务，其中岩石通过爆破被破碎，使用轮式装载机运输，然后进行进一步处理。本现场报告研究了一种新颖的方法，该方法仅利用轮式装载机挖掘时收集的本体感知数据来估计碎石堆的相对颗粒尺寸。所研究的方法并非使用外感受传感器（例如相机或激光雷达传感器）来估计岩石颗粒尺寸，而是通过挖掘机在挖掘过程中的惯性响应来推断岩石破碎程度。本文扩展了先前的研究，该研究假设利用小波分析构建一个与岩石破碎程度成比例的独特特征。我们通过大量的现场实验证明，通过在不同尺寸分布的岩石堆中挖掘获得的数据构建的小波特征比值，近似等于两个岩石堆平均颗粒尺寸的比值。在一个运营中的采石场的代表性条件下，使用一台电池供电、18吨载重能力的铲运机（LHD）进行了全尺寸挖掘实验。将所提出的传感方法生成的相对颗粒尺寸估计值，与基于视觉的破碎分析工具以及采样材料筛分所得的结果进行了比较。