Recursive Kalman Filter for Gas Analysis Light Source Drift
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Solution Overview
Problem
Existing optical measurement methods for gas analysis, particularly using NDIR detection, are affected by noise in reference photodetectors, leading to uncertainty in estimating gas concentrations due to temporal drift in light source intensity.
Innovation Solution
A method and device that utilize a recursive Kalman filter to estimate and account for the intensity of the reference light wave, reducing noise and fluctuations by iteratively updating the estimated intensity based on previous measurements, thereby improving the accuracy of gas analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a reference photodetector is used to measure the reference light wave intensity, then the gas concentration can be determined, but noise and temporal drift in the light source intensity cause uncertainty in the measurements
Solution Approach 1:
The patent implements a recursive estimation algorithm that continuously updates the reference light wave intensity based on previous measurements and current observations. This feedback mechanism allows the system to adapt to temporal drift in the light source intensity and reduce the impact of noise, thereby improving both measurement precision and reliability
Solution Approach 2:
The patent changes the parameter estimation approach from direct measurement to recursive estimation. By modeling the reference intensity as a time-varying parameter and using sequential estimation, the system can track drift while filtering noise, resolving the contradiction between precision and reliability
2Ease of manufacture
If simple and inexpensive photodetectors are used, then device cost is reduced, but noise in the reference photodetector increases, impacting the estimation of reference wave intensity
Solution Approach 1:
The patent converts the harmful effect of noise from inexpensive photodetectors into a beneficial outcome by using recursive estimation. The algorithm treats noise as random variations that can be filtered out through temporal averaging and statistical processing, allowing cheap components to achieve precision comparable to expensive detectors
Solution Approach 2:
The patent introduces a computational intermediary (the recursive estimation algorithm) between the noisy photodetector output and the final measurement result. This intermediary processing layer filters noise and extracts the true signal, enabling the use of simple photodetectors without sacrificing measurement precision
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method effectively reduces noise and accounts for temporal variations in light source intensity, leading to more accurate and stable estimates of gas concentrations, minimizing uncertainty in gas analysis.
Implementation Method 1
The technical field of the invention is the use of a light source, in particular of the blackbody or greybody type
Implementation Method 2
the species composing a gas exhibit different spectral absorption properties
Implementation Method 3
its concentration can be determined by estimating the absorption of light passing through the gas, using Beer-Lambert's law
Implementation Method 4
a photodetector measures a light wave transmitted by the gas being analyzed
Data Source
Figure 1A~1C
Figure 2A~2B
Figure 3A~3B
AI summary
A method for analysing a gaseous sample (13) by performing a comparison between a light wave (12) incident on the sample and a light wave (14) transmitted by the sample, the method comprising the following steps: i) illuminating the sample (13) with a light source (11), the light source emitting the incident light wave (12) propagating up to the sample; ii) detecting, using a photodetector, called the measurement photodetector (20), a light wave (14) transmitted by the sample, the transmitted light wave resulting from an attenuation of the incident light wave by the sample; iii) detecting a light wave, called the reference light wave (12ref), using a reference photodetector (20ref), the reference light wave (12ref) being emitted by the light source (11), the reference light wave representing a light wave reaching the reference photodetector without interacting with the sample; iv) repeating steps i) to iii) at different instants (k), called measurement instants; v) estimating, on the basis of each reference light wave (12ref) detected during the various steps iii), at each measurement instant, an intensity (îref, k) of the reference light wave (12ref) at said measurement instants, by implementing the following sub-steps: b) estimating the intensity of the reference light wave (îref, k |k-1) at a measurement instant (k), as a function of an initial intensity (Iref, k=o) or an estimate of the intensity (îref, k) of the reference light wave at a prior measurement instant (k-1); c) measuring the intensity (Iref, k) of the reference light wave (12), detected at the measurement instant; d) updating the estimate of the intensity of the reference light wave (îref, k) at the measurement instant, as a function of the intensity (Iref, k) measured during the sub-step c), and of the intensity (îref, k|k-1) estimated during the sub-step b); e) repeating sub-steps b) to d), on the basis of the estimate of the intensity of the reference light wave (îref, k) obtained during the sub-step d), by incrementing the measurement instant; vi) taking into account the intensity of the estimated reference light wave (îref, k), at each measurement instant, resulting in the step v), and an intensity (Ik) of the transmitted light wave (14) detected during the step ii) in order to perform a comparison (att k), at each measurement instant, on the basis of the reference light wave (12ref), and of the light wave (14) transmitted by the sample (13); and vii) analysing the gaseous sample (13) as a function of the comparison performed in step vi).