为满足矿井变频通风系统对井下空气质量监测的需求,提出了一种基于改进随机森林的矿井空气质量评价方法,旨在精确监测矿井内部的空气质量,为变频通风系统推广应用提供重要参考,有效保障安全生产和矿工身体健康.首先,分析了矿井空气中污染物来源及其对矿工健康的潜在危害,选取CO、SO2、H2S、NO2 和粉尘这 5 项主要污染物作为评价因子,建立了评价标准.其次,利用受试者工作特征(Receiver Operating Characteristic,ROC)曲线下的面积(Area Under Curve,AUC)改进随机森林算法,对矿井空气质量进行了综合评价.试验结果表明:模型性能较优,泛化误差最小值仅为0.017 7,测试数据分类准确性最高达97.72%.基于改进算法开发的矿井空气质量评价系统,能够有效实现对矿井空气质量评价,具有较高的鲁棒性和准确性,为智慧矿山建设和矿井空气质量评价提供了新思路.
Design and Application of Mine Air Quality Evaluation System Based on Improved Random Forests
To meet the requirements of the mine's variable frequency ventilation system for underground air quality moni-toring,a mine air quality evaluation method based on an improved Random Forest algorithm is proposed.The method aims to accurately monitor the air quality inside the mine,providing important references for the popularization and application of the variable frequency ventilation system to effectively ensure safe production and protect miners' health.Firstly,the sources of pol-lutants in the mine air and their potential hazards to miners' health are analyzed,and five major pollutants(CO,SO2,H2S,NO2,and dust)are selected as evaluation factors to establish the evaluation standards.Secondly,the Random Forest algorithm is improved using the Area Under the Curve(AUC)of the Receiver Operating Characteristic(ROC)curve to comprehensively evaluate mine air quality.The experimental results show that the model performs well,with a minimum generalization error of only 0.017 7 and a maximum classification accuracy of 97.72%on the test data.Based on the improved algorithm,a mine air quality evaluation system was developed.This system can effectively assess mine air quality with high robustness and accuracy,providing new insights for smart mine construction and mine air quality evaluation.
smart minerandom forestsmine air qualityevaluation standard
万方数据
维普
