Surface characteristic profile extraction based on Hilbert–Huang transform
Surface characteristic profile extraction based on Hilbert–Huang transform
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DOI：
10.1016/j.measurement.2013.08.066
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发表时间：
2014
期刊：
影响因子：
5.6
通讯作者：
Chunlin Xia;Yangfang Wu;Qianqian Lu;Bingfeng Ju
中科院分区：
文献类型：
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作者：
Chunlin Xia;Yangfang Wu;Qianqian Lu;Bingfeng Ju
工程表面由广泛的空间频率组成。在进行数值表征之前，应对此类表面的测量数据进行分解和过滤。本文介绍了一种利用希尔伯特-黄变换提取感兴趣表面不同频率成分的新技术。Hilbert-Huang变换的主要特点是它的自适应信号分解和时间/空间域滤波。在两种情况下测量的数据，一个跳动测量的转向滑轮和地面轮廓扫描，分别使用Hilbert-Huang变换进行了分析，并与使用鲁棒零阶高斯回归滤波器得到的结果进行了比较。分析过程和结果表明，新技术是有用的，并补充了其他现有的技术。
Engineering surfaces consist of a wide range of spatial frequencies. Prior to numerical characterization, the decomposition and filtration of the data measured for such surfaces should be performed. This paper introduces a new technique for the extraction of different frequency components of surfaces of interest by applying the Hilbert–Huang transform. The main features of the Hilbert–Huang transform are its adaptive signal decomposition and time/space domain filtering. The data measured in two cases, a runout measurement for a turning pulley and ground surface profile scanning, respectively, were analyzed using the Hilbert–Huang transform, and some results are compared with those obtained using robust zero-order Gaussian regression filters. The analysis process and results show that the new technique proposed is useful and complementary to other existing techniques.