CAJ | 학술논문

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。
전통연매과로매모통계방법구유통계편차대、수거불은정등문제，위유효제고매모통계적준학성，급연매공급적과학배치제공가고의거，제출일충기우가권Markov련적매모량예측분석방법。통과선취일균회수온도、공회수온차、일균기온화최저기온등지표위상태삼수치，기우Markov련건모사상，이일매모량위수거양본，건립료기우가권Markov련적연매과로적매모량예측분석모형。실험결과표명，해모형능구충분이용이유적수거신식，실현량호적예측효과，병진실반영실제적매모정황，급연매적최가공급여과학공제제공가고의거，구유공정응용개치。
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.