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车削粗糙表面形貌的小波频谱分析
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国家重大科学仪器设备开发专项(2017YFF0108101).


Wavelet Spectrum Analysis of Turning Rough Surface Morphology
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    摘要:

    为解决分析过程中出现的频率混淆与错误频率产生的问题,对小波变换信号的频谱分析算法进行改进,采用自定义组合函数的方式验证改进算法的正确性与可行性。将信号处理的改进算法应用于车削表面形貌信号的处理,对表面形貌复杂信号进行频带划分,对各频带重构信号进行频谱分析,最终实现信号各频带信号的提取与表征。结合车削加工表面粗糙度形成的各影响因素,得到各频带信号与影响因素之间的对应关系,为改善车削加工表面的粗糙度提供了理论支持。

    Abstract:

    In order to solve the problem of frequency confusion and error frequency in the process of analysis,the spectrum analysis algorithm of wavelet transform signal was improved.The correctness and feasibility of the improved algorithm was verified by the way of selfdefined combination function.The improved algorithm of signal processing was applied to the processing of turning surface topography signals.The frequency domain was divided into complex signals,and the spectrum analysis of each frequency band reconstructed signal was carried out.Finally,the signal extraction and characterization of each frequency band were realized.Combined with the influencing factors of the surface roughness of turning,the corresponding relationship between the signal of each frequency band and the influencing factors was obtained,which provided theoretical support for improving the roughness of the turning surface.

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安琪,索双富,林福严,时剑文.车削粗糙表面形貌的小波频谱分析[J].润滑与密封,2019,44(7):96-102.
. Wavelet Spectrum Analysis of Turning Rough Surface Morphology[J]. Lubrication Engineering,2019,44(7):96-102.

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  • 在线发布日期: 2020-03-12
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