Optimal weighted averaging pre-processing schemes for laser absorption spectroscopy

• US 10,359,360 B2
• Filed: 01/25/2016
• Issued: 07/23/2019
• Est. Priority Date: 01/25/2016
• Status: Active Grant

• Current Assignee: ABB Schweiz AG (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:
  US15/005,384
• Publication Number:
  US 20170212042A1
• Time in Patent Office: 1,275 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 method of measuring absorption using a spectroscopic instrument, the method comprising:

initiating absorption measurements with the spectroscopic instrument and receiving a series of raw intensity measurement data points from at least one detector of the spectroscopic instrument;

determining if detector noise or fluctuation noise dominates in the series of raw intensity measurement data points;

calculating, by a digital signal processor and based on the determination, 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

performing, by the digital signal processor, 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 method as in claim 1, further defined by continuously operating the spectroscopic instrument to successively receive new raw intensity measurement data points with the same or updated weighting coefficients, and performing updated weighted averaging calculations with the new raw intensity measurement data points to output updated pre-processed measurement data.

3. The method of claim 1, wherein calculating the set of weighting coefficients and performing the weighted averaging of the raw intensity measurement data points applies weights

4. The method of claim 1, wherein calculating the set of weighting coefficients and performing the weighted averaging of the raw intensity measurement data points applies weights

5. The method of claim 1, wherein calculating the set of weighting coefficients and performing the weighted averaging of the raw intensity measurement data points applies weights

6. A method as in claim 1, wherein the spectroscopic instrument is a tunable diode laser absorption spectroscopy (TDLAS) system.

7. A method of processing tunable diode laser absorption spectroscopy (TDLAS) signals to improve measurement precision, the method comprising:

performing, using a TDLAS instrument, a series of laser scans through a sample gas and measuring a transmission amplitude for each laser scan output as a series of raw intensity measurement data points;

modeling, by a digital signal processor, 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 method as in claim 7, wherein the noise to be reduced is caused by electrical sources.

9. The method as in claim 7, wherein the noise to be reduced is caused by process flow variations.

10. The method as in claim 9, wherein the noise to be reduced is caused by attenuation due to dust or particulate.

11. The method as in claim 9, wherein the noise to be reduced is caused by density gradients in the process flow.

12. The method as in claim 9, wherein the noise to be reduced is caused by time-varying transmission losses.

13. The method as in claim 7, wherein the transmission amplitude for each laser scan is determined by peak-to-peak signal amplitude.

14. The method as in claim 7, wherein the transmission amplitude for each laser scan is determined by signal amplitude at a specific measurement point or during a specific duration of time during a TDLAS trace.

15. The method as in claim 14, wherein the transmission amplitude for each laser scan is determined by signal amplitude with a background signal subtracted.

16. The method as in claim 7, wherein the transmission amplitude for each laser scan is determined by a slope of a ramp portion of a TDLAS trace.

17. The method as in claim 7, wherein the selected weighting coefficients are further adjusted for each laser scan based upon similarity to one or more time-adjacent measurement traces either prior or post to a current measurement trace, the adjustment comprising:

calculating differences between the 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 this additional weighting factor by the selected weighting coefficients to obtain adjusted weighting coefficients to be applied in the weighted average calculation.