作者:石爱娟, 叶丹
作者单位:安徽文达信息工程学院机械与汽车工程学院,安徽 合肥 231201
关键词:平面磨削表面;小波分析;信号解耦;形貌仿真
摘要:
该文提出一种基于少量参数的平面磨削表面形貌仿真方法。采用小波分析对已成型表面信号进行多尺度分解,结合各尺度下分解信号的小波能量分析,将复杂的平面磨削表面信号按照频率范围划分为低频频段、理论频段和高频频段。并将表面信号中低频频段与高频频段信息叠加形成通用仿真模型。然后结合由砂轮形貌数据与磨削运动学理论所得到的理论形貌,最终实现对平面磨削表面的形貌仿真。文章最后将实测粗糙表面与仿真表面就相关粗糙度参数进行对比分析。对比结果显示,算术平均偏差Sa与均方根偏差Sq的相对误差在3%以内;偏态Ssk与峰态Sku的相对误在5%以内。对比结果证明该文方法准确有效。
Feature decoupling and shape simulation of grinding surface
SHI Aijuan, YE Dan
College of Mechanical & Automotive Engineering, Anhui Wenda University of Information Engineering, Hefei 231201, China
Abstract: A surface topography simulation method based on a few parameters is proposed in this paper. Wavelet analysis is used to decompose the formed surface signal. Combined with the wavelet energy analysis of the decomposed signal at each scale, the complex surface grinding signal is divided into low frequency band, theoretical band and high frequency band according to the frequency range. The low frequency and high frequency information of surface signal are superimposed to form a general simulation model. The final grinding surface topography is obtained by combining the grinding wheel kinematics theory with the grinding surface topography simulation. At the end of the paper, the roughness parameters of the measured surface and the simulated surface are compared and analyzed. The results show that the relative error of the arithmetic mean deviation Sa and the root mean square deviation Sq is less than 3%, and the relative error of skew Ssk and kurtosis Sku is less than 5%. The comparison results verify the correctness and accuracy of this method.
Keywords: grinding surface;wavelet analysis;signal decoupling;topography simulation
2021, 47(5):46-51 收稿日期: 2020-10-17;收到修改稿日期: 2020-12-09
基金项目: 安徽文达信息工程学院校级重点项目(XZR2018A09)
作者简介: 石爱娟(1984-),女,安徽合肥市人,讲师,硕士,研究方向为材料成型及控制工程
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