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柱塞式生物质环模成型机环模凹模磨损预测

德雪红, 俞国胜, 陈忠加, 郭文斌

德雪红, 俞国胜, 陈忠加, 郭文斌. 柱塞式生物质环模成型机环模凹模磨损预测[J]. 北京林业大学学报, 2015, 37(6): 112-119. DOI: 10.13332/j.1000-1522.20140410
引用本文: 德雪红, 俞国胜, 陈忠加, 郭文斌. 柱塞式生物质环模成型机环模凹模磨损预测[J]. 北京林业大学学报, 2015, 37(6): 112-119. DOI: 10.13332/j.1000-1522.20140410
DE Xue-hong, YU Guo-sheng, CHEN Zhong-jia, GUO Wen-bin. Prediction of wear about ring die of plunger biomass briquetting machine[J]. Journal of Beijing Forestry University, 2015, 37(6): 112-119. DOI: 10.13332/j.1000-1522.20140410
Citation: DE Xue-hong, YU Guo-sheng, CHEN Zhong-jia, GUO Wen-bin. Prediction of wear about ring die of plunger biomass briquetting machine[J]. Journal of Beijing Forestry University, 2015, 37(6): 112-119. DOI: 10.13332/j.1000-1522.20140410

柱塞式生物质环模成型机环模凹模磨损预测

基金项目: 

“十二五”国家科技支撑计划项目(2012BAD30B0205)、国家自然科学基金项目(61265011)。

详细信息
    作者简介:

    德雪红,博士。主要研究方向:机械设计及理论。Email:dexuehong@126.com 地址:010018 内蒙古呼和浩特市内蒙古农业大学机电工程学院。责任作者: 俞国胜,教授,博士生导师。主要研究方向:林业与园林机械。Email:dexuehong@126.com 地址:100083 北京市清华东路35号北京林业大学工学院。

    德雪红,博士。主要研究方向:机械设计及理论。Email:dexuehong@126.com 地址:010018 内蒙古呼和浩特市内蒙古农业大学机电工程学院。责任作者: 俞国胜,教授,博士生导师。主要研究方向:林业与园林机械。Email:dexuehong@126.com 地址:100083 北京市清华东路35号北京林业大学工学院。

Prediction of wear about ring die of plunger biomass briquetting machine

  • 摘要: 为研究柱塞式生物质环模成型机的磨损特性及预测磨损程度,利用分形理论及磨损机理,建立了环模凹模的磨损预测模型,并对凹模进行磨损预测和分析,用试验验证模型的正确性。结果表明:新型柱塞式环模的主要磨损部位在环模凹模模孔内壁处,其表面临界微凸体接触面积由表面形貌及材料属性决定;考虑了物料及环模凹模物理特性的环模凹模磨损预测模型的预测结果是正确的;探讨了几种典型参数与平均磨损率的关系,得知随着分形参数、成型压力、当量成型速度的增大,其平均磨损率也增大。试验用2种典型材质的环模凹模和2种成型物料形成的4组摩擦副中, 42CrMo-秸秆的平均磨损率最慢,45钢-木屑的磨损率最快。
    Abstract: This study was designed to explore wear characteristics and to predict the wear degree of biomass ring plunger molding machine. Fractal theory and wear mechanism were applied to establish model predicting ring mold die wear. Model-based die wear prediction and analysis were verified experimentally. The results showed that the main wear part of ring mold took place at the inner die wall of the latest designed ring mold plunger. Critical asperity contact surface area ac was dependent on the surface topography and material properties. We validated the established die wear prediction equation taking into account the material and the physical characteristics of the ring mold, and examined the relationship between the average wear rate and several typical parameters. The average wear rate increased with the increase of fractal parameters, molding pressure and equivalent forming speed. Among the two typical ring mold materials and two typical biomass materials, 42CrMo/straw had the lowest average wear rate while 45 steel/wood had the highest average wear rate.
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