| TY type heavy dump truck is often used in mines and construction sites,driving in severe road conditions,working in poor conditions and carrying large weight.Frame as a dump truck carrying matrix,which not only bears the weight of the engine,chassis and goods,but also takes all kinds of force and moment in the process of driving.Consequently,the frame structure is easy to produce cracks,which causes the fatigue damage.To predict the fatigue life of TY-2 dump truck main one-piece frame,the CAE technology such as the finite element analysis,multi-body dynamics simulation,the fatigue life analysis and structure optimization are applied to the design of frame structure in this paper.The main research contents include:(1)First of all,the finite element model of dump truck frame was established in Hypermesh.Frame static strength were analyzed in static load bending,lifting 0° and lifting 45° condition,and the dynamic strength were also analyzed in horizontal bending,ultimate torsion and emergency braking condition.The frame structure modal was analyzed,and the credibility of the finite element analysis method was verified by modal test.(2)Combined with frame modal neutral file generated by the frame finite element model,the vehicle rigid-flexible coupling dynamics model of dump truck was established in the ADAMS/Car.And vehicle dynamics simulation was doing under class D road spectrum,getting dynamic load time history of frame under the full condition.(3)According to frame material S-N curve,the nominal stress approach was used to predict frame fatigue life in MSC.Fatigue based on statics and dynamics analysis.(4)The optimal design variables were determined based on the theory of sensitivity analysis.The lightweight optimization design was applied in the frame under the premise of guaranteeing the strength.And the strength,modal and fatigue life of the optimized frame were checked again.The results show that the strength and fatigue life of optimized frame improved,and frame mass reduced by 34kg,which verified the feasibility of optimization design. |
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