Infrared and Laser Engineering, Volume. 48, Issue 10, 1013002(2019)

Fast white light interference signal processing method based on effective signal extraction

Ma Long, Jia Jun, Pei Xin, Hu Yanmin, Zhou Hang, and Sun Fengming
Author Affiliations
  • [in Chinese]
  • show less

    Focusing on the measurement efficiency of white light interferometry in vertical large-scale scanning process, a fast white light interference signal processing method based on effective signal extraction was proposed. The bimodal spectrum distribution model of the white LED light source was established, and the simulation experiments were carried out by using this model. From the simulation results, the minimum sampling interval length required by different algorithms at a specific sampling step was given, which reduced data volume without changing the measurement accuracy and allowed the calculation to start before the end of sampling. To eliminate the fluctuation of background value in vertical large-scale scanning process, a background value extraction method based on background set was introduced. By comparing with several signal processing methods, it was proved that the extraction method can effectively eliminate the influence on measurement accuracy. Finally, the proposed method was applied to the self-designed white light interferometer and a U disk interface was tested in using Fourier transform method. The results show that the total time from scanning to obtaining surface height information is reduced by 49.02%.

    Tools

    Get Citation

    Copy Citation Text

    Ma Long, Jia Jun, Pei Xin, Hu Yanmin, Zhou Hang, Sun Fengming. Fast white light interference signal processing method based on effective signal extraction[J]. Infrared and Laser Engineering, 2019, 48(10): 1013002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: 光电测量

    Received: May. 5, 2019

    Accepted: Jun. 15, 2019

    Published Online: Nov. 19, 2019

    The Author Email:

    DOI:10.3788/irla201948.1013002

    Topics