基于机器视觉的精煤灰分实时预测
首发时间:2017-05-26
摘要:灰分是煤炭质量重要的指标之一,灰分的快速预测对于选煤行业是非常重要的。针对目前煤样灰分的测量存在严重滞后性的问题,提出了一种基于机器视觉的精煤灰分预测方法。通过图像采集系统采集精煤图像,提取精煤的特征参数,并分别通过拟合函数法和支持向量机法建立了灰分预测模型。对比发现,支持向量机法建立的灰分预测模型的预测准确率高于函数法建立的模型,并可以应用于选煤厂生产。
关键词: 矿物加工工程;机器视觉; 灰分;精煤
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Real-time prediction of clean coal ash based on machine vision
Abstract:Ash is one of the most important indexes of coal quality, and fast prediction of ash is very important to coal preparation industry. There are serious lag problems in light of the measurement of the ash content, this paper proposes a clean coal ash real-time prediction method based on machine vision. Clean coal images were collected by Image acquisition system, characteristic parameters of clean coal were extracted, ash prediction models were established through function and support vector machine separately. Prediction accuracy of ash prediction model through support vector machine is higher than the model through function,and it can be used in the production of coal preparation plant.
Keywords: mineral dressing engineering machine vision ash clean coal
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