摘要
为优化秸秆墙板压缩成型工艺,促进秸秆的建材化利用,实现变废为宝。本文通过单因素试验探究试验因素(压力、喂入量、压缩速度)对试验指标(墙板密度、残余力、设备比能耗)的影响规律,并确定各因素的取值范围为压力0.1 MPa~0.7 MPa,喂入量225 g~375 g,压缩速度50 mm/min~150 mm/min。在此基础上,根据Box-Benhnken中心组合试验与响应面分析法,研究各个因素的交互作用对试验指标的影响,模拟得出回归方程预测模型,从而优化确定秸秆墙板压缩成型工艺参数并通过试验验证了优化结果的可靠性。结果表明:各因素对密度影响的主次顺序为压力 > 喂入量 > 压缩速度,对比能耗影响的主次顺序为压力 > 喂入量 > 压缩速度,对残余力的影响主次顺序为压力 > 压缩速度 > 喂入量。优化确定最佳的参数组合为:压力为0.47 MPa,喂入量为280.98 g,压缩速度为91.42 mm/min。其密度为891.60 kg/m3,比能耗为231.30 J/kg,残余力为0.15 MPa。
In order to optimize the compression molding process of straw wall panels, promote the utilization of building materials of straw, and realize the transformation of waste into treasure. In this paper, the influence of test factors (pressure, feeding amount, compression speed) on test indicators (wall density, residual force, specific energy consumption) of equipment is explored through single-factor experiments, and the value range of each factor is determined to be 0.1 MPa~0.7 MPa, feeding amount 225 g~375 g, and compression speed 50 mm/min~150 mm/min. On this basis, according to the Box-Benhnken central combinatorial test and response surface analysis method, the influ-ence of the interaction of various factors on the test index is studied, and the regression equation prediction model is simulated, so as to optimize and determine the process parameters of straw wall panel compression molding, and verify the reliability of the optimization results through ex-periments. The results show that the primary order of pressure > feeding volume > compression speed of the influence of each factor on density is pressure feeding volume compression speed, the primary order of energy consumption is pressure > feeding volume > compression speed, and the primary and secondary order of influence on residual force is pressure > compression speed > feeding amount. The optimal combination of parameters was determined by the optimum pressure: pressure of 0.47 MPa, feed volume of 280.98 g, and compression speed of 91.42 mm/min. Its densi-ty is 891.60 kg/m3, the specific energy consumption is 231.30 J/kg, and the residual force is 0.15 MPa.
出处
《建模与仿真》
2023年第1期534-548,共15页
Modeling and Simulation
