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基于MATLAB清雪铲高速公路除雪的运动分析OA

Kinematic Analysis of Snowplow Snow Removal on Highways Based on MATLAB

中文摘要英文摘要

针对北方冬季雪期对我国城市高速公路造成的通行阻塞和安全隐患,基于刚体动力学通过对清雪铲除雪的动态静力学分析及建立雪颗粒接触的力学模型,完善了高速公路清雪铲进行除雪作业的理想模型;利用SolidWorks对清雪铲进行结构设计,建立了高速公路清雪铲的三维模型.通过MATLAB将理论模型进行拟合分析,并且转化为可视化结果,得到雪粒处于清雪铲铲面以及被雪铲抛离后的运动轨迹曲面,仿真结果表明高速公路清雪铲采用切削角为35.9°、行进角为51.9°、行进速度为28.7 m/s进行除雪,单位时间除雪体积可达5.74 m3/s,较未优化前除雪率平均可提高5.18%,此时,积雪抛射垂直高度最小达1.5 m,路面横向位移最小达2.5 m,验证了仿真试验和运动模型的可靠性.研究结果为高速公路清雪铲的结构参数优化设计提供参考.

Traffic congestion and safety hazards caused by winter snowfall on urban expressways in northern China are addressed.Based on rigid body dynamics,an idealized model is established through kinetostatic analysis of snow removal and mechanical modeling of snow particle interactions.The idealized operational model for expressway snowplows is refined.Structural design of the snowplow is conducted using SolidWorks,and a 3D model of the expressway snowplow is developed.Theoretical models are fitted and analyzed using MATLAB,then converted into visualizations.Motion trajectory surfaces of snow particles are obtained both on the blade surface and after ejection.Simulations demonstrate that optimal snow removal is achieved with a cutting angle of 35.9°,travel angle of 51.9°,and operating speed of 28.7 m/s.The snow removal volume reaches 5.74 m³/s under these parameters.This represents a 5.18%average increase in volumetric removal rate compared to the pre-optimization baseline.At these parameters,ejected snow attains a minimum vertical height of 1.5 m and minimum lateral displacement of 2.5 m.The reliability of the simulation methodology and kinematic model is thereby verified.These findings provide critical references for structural parameter optimization of expressway snowplows.

孔诚琳;刘向东;吴洪山

佳木斯大学 机械工程学院,黑龙江 佳木斯 154007佳木斯大学 机械工程学院,黑龙江 佳木斯 154007佳木斯山友机械科技有限公司,黑龙江 佳木斯 154000

机械制造

清雪铲高速公路刚体动力学MATLAB运动分析

snowplowexpresswayrigid body dynamicsMATLABkinematic analysis

《机电工程技术》 2026 (10)

45-51,59,8

佳木斯大学重点研发计划项目(SZDYF202303)黑龙江省科研业务费项目(2021-KYYWF-0559)

10.3969/j.issn.1009-9492.2025.00087

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