Respirable coal mine dust represents a serious health hazard for miners. Monitoring methods are needed that enable fractionation of dust into its primary components, and that do so in real time. Near the production face, a simple capability to monitor the coal versus mineral dust fractions would be highly valuable for tracking changes in dust sources—and supporting timely responses in terms of dust controls or other interventions to reduce exposures. In this work, the premise of dust monitoring with polarized light microscopy was explored. Using images of coal and representative mineral particles (kaolinite, crystalline silica, and limestone rock dust), a model was built to exploit birefringence of the mineral particles and effectively separate them from the coal. The model showed >95% accuracy on a test dataset with known particles. For composite samples containing both coal and minerals, the model also showed a very good agreement with results from the scanning electron microscopy classification, which was used as a reference method. Results could further the concept of a “cell phone microscope” type monitor for semi-continuous measurements in coal mines.

中文翻译：

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光学显微镜和图像处理对可吸入煤矿粉尘颗粒分类的演示

可吸入的煤矿粉尘对矿工的健康构成严重危害。需要能够实时将灰尘分馏成主要成分的监测方法。在生产工作面附近，监测煤与矿物粉尘比例的简单功能对于跟踪粉尘源的变化非常有价值——并支持及时响应粉尘控制或其他干预措施以减少暴露。在这项工作中，探索了用偏光显微镜监测灰尘的前提。使用煤和代表性矿物颗粒（高岭石、结晶二氧化硅和石灰石岩尘）的图像，建立了一个模型来利用矿物颗粒的双折射并有效地将它们与煤分离。该模型在具有已知粒子的测试数据集上显示出 >95% 的准确度。对于同时含有煤和矿物的复合样品，该模型也显示出与扫描电子显微镜分类结果非常吻合，用作参考方法。结果可以进一步推广用于煤矿半连续测量的“手机显微镜”型监视器的概念。