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HS-RNN在机械主轴振动预报方法中的研究

Study on HS-RNN in Vibration Prediction of Mechanical Spindle

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【作者】 片锦香; 智杰峰;

【Author】 PIAN Jin-xiang;ZHI Jie-feng;School of Information and Control Engineering,Shenyang Jianzhu University;

【机构】 沈阳建筑大学信息与控制工程学院学院;

【摘要】 机械主轴在高速运行过程中由于转子质量分布不均,造成主轴振动,从而影响其加工精度,因此常常采用动平衡方法来降低此类原因造成的振动。由于机械主轴长时间工作在变化频繁的工况条件下,难以在较短的时间内对主轴振动值进行准确调节,因此机械主轴振动预报模型对动平衡调节有着重要意义。机械主轴振动预报模型机理复杂,振动幅值具有随转速变化而非线性变化的特性,难以建立精确的机械主轴振动预报模型。且内置平衡块位置的选择忽略了变化工况对位置更新参数的影响,导致机械主轴振动预报模型精度较低。采用RNN(Recurrent Neural Network)递归神经网络建立机械主轴振动预报模型,对内置平衡块不同位置和主轴转速下的振动幅值预报,并引入HS(Harmony Search)和声搜索算法对平衡块位置参数通过自学习更新,从而提高机械主轴振动预报模型的精度。实验结果表明,提出的基于HSRNN的机械主轴振动预报方法能够自动确定网络结构,并对机械主轴的振动幅值进行准确预报。

【Abstract】 Mechanical spindle in the high-speed operation due to uneven distribution of the rotor mass,causing the spindle vibration,thus affecting its machining accuracy,so often used to reduce the balance of vibration caused by such causes.Because the mechanical spindle is working under the condition of frequent changes for a long time,it is difficult to accurately adjust the vibration value of the spindle in a short period of time. Therefore,the model of mechanical spindle vibration prediction is of great significance to the dynamic balance adjustment. The mechanism of mechanical spindle vibration prediction is complex,and the amplitude of vibration varies nonlinearly with the speed. It is difficult to establish accurate model of mechanical spindle vibration prediction. And the choice of the position of the built-in balance weight ignores the influence of the changing working conditions on the position update parameters,resulting in the low accuracy of the mechanical spindle vibration prediction model. RNN(Recurrent Neural Network)recurrent neural network is used to establish the model of mechanical spindle vibration prediction. The vibration amplitude of the built-in balance block at different positions and spindle speeds is predicted. Harmony Search(HS)Through self-learning update,thereby improving the accuracy of the mechanical spindle vibration prediction model. The experimental results show that the HS-RNN-based mechanical spindle vibration prediction method proposed in this paper can automatically determine the network structure and accurately predict the vibration amplitude of the mechanical spindle.

【基金】 辽宁省自然科学基金资助(20170540764)
  • 【文献出处】 机械设计与制造 ,Machinery Design & Manufacture , 编辑部邮箱 ,2020年08期
  • 【分类号】TH133.2;TH113.1
  • 【被引频次】1
  • 【下载频次】73
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