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林业科学 ›› 2020, Vol. 56 ›› Issue (4): 150-159.doi: 10.11707/j.1001-7488.20200417

• 论文与研究报告 • 上一篇    下一篇

生物质热压成型温度场分布规律

王金鸣,袁湘月*,陈忠加,张宇崴,王艳明   

  1. 北京林业大学工学院 北京 100083
  • 收稿日期:2019-08-06 出版日期:2020-04-25 发布日期:2020-05-29
  • 通讯作者: 袁湘月
  • 基金资助:
    中央高校中长期科学研究项目(2015ZCQ-GX-02);中央高校基本科研经费(2018ZY11);国家自然科学基金青年科学基金项目(31500478)

Distribution of Temperature Field in Biomass Hot Forming

Jinming Wang,Xiangyue Yuan*,Zhongjia Chen,Yuwei Zhang,Yanming Wang   

  1. School of Technology, Beijing Forestry University Beijing 100083
  • Received:2019-08-06 Online:2020-04-25 Published:2020-05-29
  • Contact: Xiangyue Yuan

摘要:

目的: 探讨单柱塞式生物质成型机生物质热压成型时成型块截面温度场分布情况,为生物质热压成型工艺研究提供参考。方法: 以废弃松木锯屑为试验原料,利用自主研制的单柱塞式生物质成型机,采用成型套筒加热方式,以成型套筒加热温度、原料含水率、单柱塞式生物质成型机电机频率为试验因素设计三因素五水平正交试验,成型套筒加热温度分别设定为155、170、185、200和215℃,原料含水率分别调至10%、12%、14%、16%和18%,单柱塞式生物质成型机电机频率分别设定为14、16、18、20和22 Hz。运用方差分析法分析各成型块整体密度以及成型块截面平均温度、最高温度、中心点温度受不同成型套筒加热温度、原料含水率、单柱塞式生物质成型机电机频率的影响程度;建立多元回归模型,得出成型块整体密度以及成型块截面平均温度、最高温度、中心点温度分别与成型套筒加热温度、原料含水率、单柱塞式生物质成型机电机频率的多元回归模型,并得到经过有效简化的各多元回归模型;分别建立一次、二次、三次多元回归模型,通过对比不同模型的拟合效果,得到成型块整体密度与截面温度场分布的最佳数学模型。结果: 对于成型块整体密度和中心点温度,其主次影响因素依次为原料含水率、单柱塞式生物质成型机电机频率和成型套筒加热温度;对于平均温度,其主要影响因素为成型套筒加热温度和原料含水率,次要影响因素为单柱塞式生物质成型机电机频率;对于最高温度,其主次影响因素依次为成型套筒加热温度、单柱塞式生物质成型机电机频率和原料含水率。各简化多元回归模型与原多元回归模型误差均小于1.5%。得到以生物质成型块整体密度为因变量,以成型块截面平均温度、最高温度、中心点温度为自变量的最佳多元回归模型。结论: 在生物质热压成型实际应用中,成型块截面温度场分布对生物质成型质量影响颇深,本研究探究实际试验中生物质热压成型温度场分布规律,通过分析建模发现成型块整体密度与截面温度场分布存在数学关系,可为后续生物质研究拓宽思路。

关键词: 生物质固体燃料, 热压成型, 温度场分布规律

Abstract:

Objective: The aim of this study was to study the distribution of the temperature field of the section of the molding block during the biomass hot compression molding,which was expected to provide a reference for the study of biomass hot forming technology. Method: This paper took the single plunger biomass molding machine independently developed by the School of Technology of Beijing Forestry University as the experimental equipment,and adopted the heating method of forming sleeve to study the waste pine sawdust used as the experimental materials. The orthogonal test was designed with heating temperature,raw material moisture content and motor frequency as experimental factors. The heating temperature was set as 155,170,185,200 and 215℃,the sawdust moisture content was adjusted to 10%,12%,14%,16% and 18%,and the motor frequency was set as 14,16,18,20 and 22 Hz,respectively. Using the variance analysis method to analyze the overall density of the molding block,the average temperature,the highest temperature and the center point temperature of the molding block section were affected by the experimental temperature,moisture content,and motor frequency. Experimental results showed that by establishing a multivariate regression model,the multiple regression equations could be obtained with the overall density of the molding block,the average temperature,the highest temperature,and the center point temperature of the molding block section as the dependent variables,with the experimental temperature,moisture content,and motor frequency as independent variables,and get a simplified multiple regression equation. Through the establishment of multiple regression models and comparative analysis,the best mathematical model relationships between the overall density of the forming block and the temperature field distribution of the biomass forming block were expected to be found. Result: For the center point temperature,the primary and secondary influencing factors are moisture content,motor frequency and temperature; for the average temperature,the primary influencing factors are temperature and moisture content,the secondary influencing factor is motor frequency; and for the highest temperature,the primary and secondary influencing factors are temperature,motor frequency and moisture content. Our results demonstrated that the error of each simplified multiple regression equation and the original multiple regression equation is less than 1.5%. The best multiple regression model and equations are obtained with the overall density of the biomass molding block as the dependent variable,and the average temperature,the highest temperature,and the center point temperature of the molding block section as the independent variables. Conclusion: In practical applications of biomass hot forming,the distribution of the temperature field of the section of the molding block has a profound effect on the quality of biomass molding. This paper explores the distribution of temperature field in biomass hot forming in actual experiments. Through analysis and modeling,it is found that there is a mathematical relationship between the overall density of the forming block and the distribution of the temperature field of the section of the molding block,which might broaden our ideas for subsequent biomass research.

Key words: biomass solid fuel, hot press forming, distribution of temperature field

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