...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Fuel >Application of artificial neural network to study the performance of jig for beneficiation of non-coking coal
【24h】

Application of artificial neural network to study the performance of jig for beneficiation of non-coking coal

机译：人工神经网络在非焦煤选矿夹具性能研究中的应用

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Non-coking coal is the major resource of energy in India. Apart from its utilization in energy sector, the other major application of this coal is in metallurgical sector. The resource of high quality of non-coking coal is not available as per demand; as a result beneficiation of non-coking coal is now becoming essential. Jigging is one of the economical physical beneficiation processes for Indian high ash non-coking coal. At present scenario in coal washery in India, below 3 mm size is not being processed. Attempt has been taken to beneficiate the fine size non-coking coal fractions generated at different sizes of bed materials, feed rates and water rates using laboratory Denver mineral jig. The performance of jig was evaluated in term of Ep and imperfection value. Furthermore artificial neural network (ANN) model has been developed for determining combustible recovery and ash percent of the concentrate. The ANN architecture is made up of three layers (input - hidden - output). A back propagation algorithm was used for training of the ANN model. It has been observed that the predicted values by ANN model are in good agreement with the experimental results.
机译：非炼焦煤是印度的主要能源。除了在能源领域的利用外，这种煤炭的另一个主要用途是在冶金领域。无法按需求提供高质量的非焦煤资源；结果，非焦煤的选矿现在变得至关重要。跳汰是印度高灰分非炼焦煤的经济物理选矿工艺之一。目前在印度的洗煤厂中，小于3 mm的尺寸尚未得到处理。已经尝试使用实验室丹佛矿物夹具来受益于在不同尺寸的床料，进料速率和水速率下产生的细粒度非焦煤馏分。用Ep和缺陷值评估夹具的性能。此外，已经开发了人工神经网络（ANN）模型，用于确定精矿的可燃回收率和灰分百分比。 ANN体系结构由三层组成（输入-隐藏-输出）。反向传播算法用于训练ANN模型。已经观察到，人工神经网络模型的预测值与实验结果吻合良好。

著录项

  • 来源
    《Fuel》 |2012年第2012期|p.151-156|共6页
  • 作者

    Lopamudra Panda; A.K. Sahoo; A. Tripathy; S.K. Biswal; A.K. Sahu;

  • 作者单位

    R&D Tata Steel Limited, Jamshedpur, India;

    Indo Pellets Private Limited, Bhubaneswar, India;

    Institute of Minerals and Materials Technology, Council of Scientific and Industrial Research, Bhubaneswar, India;

    Institute of Minerals and Materials Technology, Council of Scientific and Industrial Research, Bhubaneswar, India;

    Institute of Minerals and Materials Technology, Council of Scientific and Industrial Research, Bhubaneswar, India;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    non-coking coal; jigging; combustible recovery; ANN; back propagation;

    机译：非焦煤跳动可燃物回收;人工神经网络反向传播;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号