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首页> 外文期刊>The Journal of Engineering >Evaluation method of spindle performance degradation based on VMD and random forests
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Evaluation method of spindle performance degradation based on VMD and random forests

机译:基于VMD和随机林的主轴性能降解评价方法

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摘要

As one of the core components of the machine tool, the reliability of spindle is very important for improving machine tool quality. To effectively evaluate the performance degradation degree of the spindle, a method of degradation evaluation of the spindle performance based on variational mode decomposition (VMD) and random forests (RFs) was proposed. Firstly, VMD is used to process the current signal to obtain several modal components. Then, the time domain and frequency domain features of each modes component are calculated as eigenvalues. Finally, the RFs algorithm is used to classify the eigenvalues. The experimental results show that VMD can decompose the signal better and avoid the phenomenon of the modal mixture. The combination of VMD and RFs can accurately and effectively evaluate the performance degradation of the spindle.
机译:作为机床的核心部件之一,主轴的可靠性对于改善机床质量非常重要。为了有效地评估主轴的性能劣化程度,提出了一种基于变分模式分解(VMD)和随机森林(RFS)的主轴性能的降解评估方法。首先,VMD用于处理当前信号以获得多个模态组件。然后,每个模式分量的时域和频域特征被计算为特征值。最后,RFS算法用于对特征值进行分类。实验结果表明,VMD可以更好地分解信号并避免模态混合物的现象。 VMD和RFS的组合可以准确且有效地评估主轴的性能劣化。

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