Optimal weighted averaging pre-processing schemes for laser absorption spectroscopy

• US 10,641,704 B2
• Filed: 07/15/2019
• Issued: 05/05/2020
• Est. Priority Date: 01/25/2016
• Status: Active Grant

• Current Assignee: ABB Incorporated (ABB Limited)
• Original Assignee: ABB Incorporated (ABB Limited)
• Inventors: Angelosante, Daniele, Fahrland, Andrew, Maas, Deran, Gupta, Manish
• Primary Examiner(s): Diallo, Mamadou L
• Application Number:
  US16/512,320
• Publication Number:
  US 20190339198A1
• Time in Patent Office: 295 Days
• CPC Class Codes: G01J 2003/2853 Averaging successive scans or readings
• CPC Class Codes: G01J 3/027 Control of working procedures of a spectrometer; Failure detection; Bandwidth calculation
• CPC Class Codes: G01J 3/28 Investigating the spectrum using colour filters G01J3/51
• CPC Class Codes: G01J 3/42 Absorption spectrometry; Double beam spectrometry; Flicker spectrometry; Reflection spectrometry beam switching arrangements G01J3/08
• CPC Class Codes: G01J 3/433 Modulation spectrometry; Derivative spectrometry
• CPC Class Codes: G01N 2021/399 Diode laser
• CPC Class Codes: G01N 21/39 using tunable lasers
• CPC Class Codes: G01N 2201/12 Circuits of general importance; Signal processing

Abstract

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.

Claims

1. A spectroscopic instrument comprising:

at least one detector to collect a series of raw intensity measurement data points; and

a processor to;

calculate, based on a determination of whether detector noise or fluctuation noise dominates in the series of raw intensity measurement data points, a set of weighting coefficients for the raw intensity measurement data points, wherein greater weight is given to larger intensity raw measurement data points over smaller raw intensity measurement data points when detector noise dominates, and wherein greater weight is given to smaller intensity raw measurement data points over larger intensity raw measurement data points when fluctuation noise dominates; and

perform a weighted averaging upon the raw intensity measurement data points using the calculated set of weighting coefficients to output, from the spectroscopic instrument, a set of pre-processed measurement data that is characterized by reduced noise contributions.

2. The spectroscopic instrument of claim 1, wherein the at least one detector is to successively receive new raw intensity measurement data points, and the processor is further to perform updated weighted averaging calculations with the new raw intensity measurement data points to output updated pre-processed measurement data.

3. The spectroscopic instrument of claim 1, wherein the processor is to apply weights

4. The spectroscopic instrument of claim 1, wherein the processor is to apply weights

5. The spectroscopic instrument of claim 1, wherein the processor is to apply weights

6. The spectroscopic instrument of claim 1, wherein the processor is a digital signal processor, and wherein the spectroscopic instrument further comprises:

a sample chamber to receive a sample;

a tunable laser diode to illuminate the sample chamber; and

a laser control module connected to the tunable laser diode to control an output wavelength of the tunable laser diode.

7. A tunable diode laser absorption spectroscopy (TDLAS) instrument comprising:

a tunable laser diode to perform a series of laser scans through a sample gas;

at least one detector to measure a transmission amplitude for each laser scan output as a series of raw intensity measurement data points; and

a processor to;

model noise in the raw intensity measurement data points to select weighting coefficients for each laser scan, wherein the selected weighting coefficients are given as

8. The TDLAS instrument of claim 7, wherein the processor is to reduce noise caused by one or more electrical sources.

9. The TDLAS instrument of claim 7, wherein the processor is to reduce noise caused by variations in a process flow.

10. The TDLAS instrument of claim 9, wherein the processor is to reduce noise caused by attenuation due to dust or particulate.

11. The TDLAS instrument of claim 9, wherein the processor is to reduce noise caused by density gradients in the process flow.

12. The TDLAS instrument of claim 9, wherein the processor is to reduce noise caused by time-varying transmission losses.

13. The TDLAS instrument of claim 7, wherein the processor is to determine a peak-to-peak signal amplitude for each laser scan.

14. The TDLAS instrument of claim 7, wherein the processor is to determine a signal amplitude for each laser scan at a predefined measurement point or during a predefined duration of time during a TDLAS trace.

15. The TDLAS instrument of claim 14, wherein the processor is to determine a signal amplitude with a background signal subtracted for each laser scan.

16. The TDLAS instrument of claim 7, wherein the processor is further to determine a slope of a ramp portion of a TDLAS trace.

17. The TDLAS instrument of claim 7, wherein the processor is further to adjust selected weighting coefficients for each laser scan based upon similarity to one or more time-adjacent measurement traces, the adjustment comprising:

calculating differences between a current measurement trace and a time-adjacent measurement trace;

squaring the differences;

calculating an additional weighting factor by summing the squares and taking the inverse of the sum; and

multiplying the additional weighting factor by the selected weighting coefficients to obtain adjusted weighting coefficients to be applied in the weighted average calculation.

18. One or more non-transitory machine-readable media comprising a plurality of instructions stored thereon that, when executed, cause a spectroscopic instrument to:

collect a series of raw intensity measurement data points;

calculate, based on a determination of whether detector noise or fluctuation noise dominates in the series of raw intensity measurement data points, a set of weighting coefficients for the raw intensity measurement data points, wherein greater weight is given to larger intensity raw measurement data points over smaller raw intensity measurement data points when detector noise dominates, and wherein greater weight is given to smaller intensity raw measurement data points over larger intensity raw measurement data points when fluctuation noise dominates; and

perform a weighted averaging upon the raw intensity measurement data points using the calculated set of weighting coefficients to output from the spectroscopic instrument a set of pre-processed measurement data that is characterized by reduced noise contributions.

19. The one or more non-transitory machine-readable media of claim 18, wherein the instructions further cause the spectroscopic instrument to:

successively receive new raw intensity measurement data points; and

perform updated weighted averaging calculations with the new raw intensity measurement data points to output updated pre-processed measurement data.

20. The one or more non-transitory machine-readable media of claim 18, wherein the instructions further cause the spectroscopic instrument to apply weights