摘要
首先,以激光切割机伺服电机为振动激励源、激光头振动响应为加工精度评价参数,建立了振动系统仿真模型。接着,采用原点动刚度和振动传递函数评价方法,计算了多工况下激光头振动响应。然后,提出了一种多工况多目标动力学拓扑优化方法,在控制质量的前提下优化了横梁减重孔分布。最后,通过对比分析原横梁结构、横梁无减重孔和优化减重孔3种模型在多工况下的激光头振动响应获知:采用该多工况多目标动力学拓扑优化方法可合理优化横梁减重孔分布,是减小激光头振动响应、提高加工精度的一种有效措施。上述研究成果不但可为激光切割机频域动态力学性能分析提供参考,而且可为伺服电机与激光切割机结构性能匹配设计提供指导,具有良好的工程应用价值。
Firstly,the vibration system simulation model is established with the servo motor of the laser cutting machine as the vibration excitation source and the vibration response of the laser head as the processing accuracy evaluation parameter.The secondly,the vibration response of the laser head under multiple conditions is calculated by using the IPI and VTF evaluation methods.Then,a multi-condition and multi-objective dynamic topology optimization method is proposed,and the distribution of the beam lightening holes is optimized under the premise of controlling the quality.Finally,through the comparative analysis of the laser head vibration responses of the original beam structure,the beam without lightening holes and the optimized lightening holes under multiple conditions,it is known that:the multi-condition and multi-objective dynamic topology optimization method can reasonably optimize the distribution of the beam lightening holes,which is an effective measure to reduce the vibration response of the laser head and improve the machining accuracy.The above research results not only can provide reference for the analysis of the frequency domain dynamic mechanical properties of the laser cutting machine,but also can provide reference for the matching between the servo motor and structural performance,so have a good engineering application value.
作者
张宇
林毓培
舒雷
董俊红
ZHANG Yu;LIN Yupei;SHU Lei;DONG Junhong(School of Intelligent Manufacturing and Automotive,Chongqing Electronic Engineering Vocational College,Chongqing 401331,CHN;National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology,Southwest University,Chongqing 400716,CHN)
出处
《制造技术与机床》
北大核心
2022年第11期65-70,共6页
Manufacturing Technology & Machine Tool
基金
国家重点研发计划(2018YFB1306604)。