Electronic Nose Analyte Characterization with Parasitic Species Correction
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Solution Overview
Problem
The presence of parasitic chemical species in gas samples, such as water molecules, introduces measurement noise that degrades the quality of analyte characterization in electronic nose systems, particularly due to variations in relative humidity affecting the intensity of optical measurement signals and causing time drift in signatures.
Innovation Solution
A method is developed to characterize analytes by correcting measurement signals for interactions with both the analyte and parasitic species, using a matrix of signatures and relative concentration vectors to minimize measurement noise, thereby improving the accuracy of analyte characterization. This involves fluid injection phases with carrier gas and gas samples, determining measurement signals, and forming corrected signatures that isolate the analyte's interaction patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If carrier gas containing parasitic species is used during initial phase, then measurement baseline is established, but measurement noise is introduced due to concentration variations of parasitic species
Solution Approach 1:
The patent performs preliminary characterization of parasitic species interactions during the initial phase (Ph1) before the main analyte measurement. By pre-determining the measurement signals associated with parasitic species in the carrier gas, the system can later subtract these contributions from total measurements to isolate analyte signals, thereby eliminating measurement noise while maintaining baseline establishment.
Solution Approach 2:
The patent introduces an intermediary correction model that separates parasitic species contributions from analyte signals. This model acts as a mediator by calculating the impact of parasitic species (water molecules, CO2, etc.) on measurement signals and using this information to correct the total measurements, thereby removing harmful noise while preserving useful analyte information.
2Reliability
If relative humidity varies between phases, then parasitic species interactions change, but signature time drift occurs degrading characterization quality
Solution Approach 1:
The patent implements feedback correction by continuously monitoring humidity conditions and adjusting the correction model accordingly. The system uses feedback information about relative humidity variations to dynamically update the parasitic species interaction parameters, ensuring that signature measurements remain consistent and drift-free even when environmental humidity changes between phases.
Solution Approach 2:
The patent accounts for parameter changes by explicitly modeling how relative humidity variations affect parasitic species interactions. The correction model incorporates humidity-dependent parameters to calculate and subtract parasitic contributions, thereby maintaining signature stability despite changes in environmental conditions between Ph1 and Ph2.
3Measurement precision
If multiple gas phases are used for characterization, then analyte interaction patterns are captured, but measurement noise from parasitic species concentration changes is introduced
Solution Approach 1:
The patent segments the measurement process into distinct phases: Ph1 for characterizing parasitic species interactions in carrier gas, and Ph2 for measuring total interactions in gas sample. By separating these functions into distinct temporal segments, the system can independently characterize and correct for parasitic contributions, thereby capturing accurate analyte interaction patterns without contamination from parasitic species noise.
Solution Approach 2:
The patent converts the harmful effect of parasitic species into a beneficial correction opportunity. By deliberately measuring parasitic species interactions during Ph1, the system gains the information needed to construct correction models that remove parasitic contributions from Ph2 measurements. This transforms the previously harmful noise into a useful calibration reference for improving measurement accuracy.
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 or eliminates measurement noise associated with parasitic species, leading to improved quality and consistency of analyte characterization, even with varying concentrations of parasitic species, resulting in more accurate and reliable signatures.
Implementation Method 1
the analyte present in a gas sample interacts by adsorption/desorption with receptors located at several distinct sensitive sites of a functionalised measuring surface
Implementation Method 2
In an electronic nose using SPR or MZI technology, the analyte present in a gas sample interacts by adsorption/desorption with receptors located at several distinct sensitive sites of a functionalised measuring surface. It consists of detecting in real time a measurement signal associated with each of the sensitive sites, which is representative of adsorption/desorption interactions between the analyte and the receptors in response to a primary signal.
Implementation Method 3
The measurement signals can be optical signals representative of a temporal variation in the local refractive index due to interactions of the analyte with the receptors
Data Source
AI summary
A method for characterizing an analyte A present in a gas sample using an electronic nose including M sensitive site, a parasitic chemical species P being present in the gas sample, the method include: a phase 100 of acquiring N first signatures, where N>1, of the gas samples containing the analyte A and the parasitic species P, the gas samples exhibiting deviations ΔcP(n) which differ from one gas sample to the next; a phase 200 of solving an optimization problem so as to obtain N corrected signatures, characterising the analyte A present in the N gas samples, from the N first signatures, by optimizing to objective functions.