传统燃煤锅炉煤耗统计方法具有统计偏差大、数据不稳定等问题，为有效提高煤耗统计的准确性，给燃煤供给的科学配置提供可靠依据，提出一种基于加权Markov链的煤耗量预测分析方法。通过选取日均回水温度、供回水温差、日均气温和最低气温等指标为状态参数值，基于Markov链建模思想，以日煤耗量为数据样本，建立了基于加权Markov链的燃煤锅炉的煤耗量预测分析模型。实验结果表明，该模型能够充分利用已有的数据信息，实现良好的预测效果，并真实反映实际的煤耗情况，给燃煤的最佳供给与科学控制提供可靠依据，具有工程应用价值。%There are such problems as great deviation in statistics and instability of data etc .with the traditional coal-fired boiler coal consumption statistical method .In order to improve the accuracy of coal consumption statistics and provide a reliable basis for the scientific allocation of coal-fire supplication , the paper proposes a weighted Markov chain based coal consumption prediction analysis method .By selecting daily average return water temperature , temperature difference between supply water and return water , daily average temperature , lowest temperature and other indices as status parameter values , based on Markov chain modeling thought , taking daily coal consumption as data sample, it establishes a weighted Markov chain based coal-fired boiler’s coal consumption prediction analysis model .Experiment results show that the model can fully take advantage of existing data information , achieve good prediction effects and truly reflect actual coal consumption situation, so that it provides reliable basis for coal-fire's optimal supplication and scientific control .Thus it is of engineering application value.
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