OPTIMAL WEIGHTED AVERAGING PRE-PROCESSING SCHEMES FOR LASER ABSORPTION SPECTROSCOPY

    公开(公告)号:US20190339198A1

    公开(公告)日:2019-11-07

    申请号:US16512320

    申请日:2019-07-15

    申请人: ABB, INC.

    摘要: A method of processing raw measurement data from a tunable diode laser absorption spectroscopy (TDLAS) tool or other spectroscopic instrument is provided that determines what types of noise (electronic or process flow) are present in the measurement. Based on that determination, the noise is reduced by performing a weighted averaging using weights selected according to the dominant type of noise present, or a general case is applied to determine weights where neither noise type is dominant. The method also involves performing continuous spectroscopy measurements with the tool, with the data and weighted averaging being constantly updated. Weighting coefficients may also be adjusted based on similarity or difference between time-adjacent traces.

    Optimal weighted averaging pre-processing schemes for laser absorption spectroscopy

    公开(公告)号:US10359360B2

    公开(公告)日:2019-07-23

    申请号:US15005384

    申请日:2016-01-25

    申请人: ABB, Inc.

    摘要: A method of processing raw measurement data from a tunable diode laser absorption spectroscopy (TDLAS) tool or other spectroscopic instrument is provided that determines what types of noise (electronic or process flow) are present in the measurement. Based on that determination, the noise is reduced by performing a weighted averaging using weights selected according to the dominant type of noise present, or a general case is applied to determine weights where neither noise type is dominant. The method also involves performing continuous spectroscopy measurements with the tool, with the data and weighted averaging being constantly updated. Weighting coefficients may also be adjusted based on similarity or difference between time-adjacent traces.