| 喻斌斌，谭鹤群.基于有机元素含量的猪粪热值预测模型[J].广东农业科学,2015,42(12):168-173 |
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基于有机元素含量的猪粪热值预测模型 |
| Construction calorific value model for pig manure based on organic element contents |
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| DOI： |
| 中文关键词: 猪粪 有机元素 热值 预测模型 |
| 英文关键词: pig manure organic elements calorific value prediction model |
| 基金项目: |
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| 摘要点击次数: 1834 |
| 全文下载次数: 759 |
| 中文摘要: |
| 探讨利用猪粪有机元素含量预测猪粪热值的可行性，建立基于C、H、N、S、O 等5 种有机元素含量
的高、低位热值预测模型。采集了160 个猪粪样品，利用EA3000 型元素分析仪和IKA-C2000 型氧弹量热仪分
别测定其C、H、N、S、O 元素的含量和高、低位热值。相关分析表明，C、H、N 这3 种元素的含量与热值之间存在
极显著相关，而S、O 这2 种元素含量与热值之间的相关不显著曰利用120 个猪粪样品的测定结果，采用多元线
性回归分析建立的基于C、H、N 含量的热值预测模型可以较准确地利用碳、氢、氮预测猪粪热值，高位热值和低
位热值预测模型的决定系数R2分别为0.836 和0.785。用40 个样品对热值模型进行外部验证，高位热值和低
位热值均方根误差RMSE 分别为621.31、620.85 J/g，相对均方根误差RRMSE 分别为3.74%和4.06%。结果表
明，多元线性回归法建立的基于有机元素含量的猪粪热值预测模型的预测结果较准确，利用猪粪的元素含量
预测其热值是可行的。 |
| 英文摘要: |
| To discuss the feasibility of using organic element contents of pig manure to predict calorific value,
the paper built a prediction model of gross calorific value and net calorific value based on the contents of organic
elements. 160 pig manure samples were collected, and their C,H,N,S,O element contents were measured by EA3000
and gross calorific value and net calorific value were measured by IKA-C2000 bomb calorimeters. Simple correlation
analysis result showed that the contents of C,H,N had very significantly positive correlation with calorific value, while
the contents of S and O had no significantly positive correlation with calorific value. 120 samples were selected to
build the model, results indicated that the calorific value prediction model based on C,H,N element contents using
multiple linear regression analysis could accurately use C,H,N to predict calorific value of pig manure. The
determination coefficient of the prediction model of gross calorific value and net calorific value were 0.836 and 0.785
respectively. In the 40 samples used for the external validation, the root-mean-square error of gross calorific value
was 621.31 J/g, and the relative root-mean-square error was 3.74%; the root-mean-square error of net calorific
value was 620.85 J/g, and the relative root-mean-square error was 4.06%. It was concluded that the calorific value
prediction model of pig manure based on organic element contents by built using multiple linear regression analysis
method could predict the gross and net calorific values accurately. |
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