Multivariate Optical Computing System Spectral Isolation
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Solution Overview
Problem
Existing optical systems for measuring light intensity struggle to accurately derive information due to interference from multiple factors contributing to light intensity, making it difficult to measure specific properties like ethylene content or octane rating in polymers and gasoline samples, as conventional methods are prone to inaccuracy and require expensive and sensitive detectors.
Innovation Solution
The implementation of multivariate optical computing (MOC) systems that utilize spectral weighting and principal component analysis to isolate and analyze specific spectral regions, allowing for the selection of optimal components and configurations to enhance measurement precision and reduce noise, thereby accurately estimating chemical properties without the need for expensive detectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional light intensity measurement is used, then the measurement process is simple, but the measurement precision is poor due to interfering data from multiple factors
Solution Approach 1:
The patent segments the broad light spectrum into multiple specific wavelength bands using bandpass filters. Each bandpass filter isolates a predetermined wavelength band, allowing the system to measure light intensity in discrete spectral regions. This segmentation enables the system to focus on specific wavelength ranges that carry information about particular chemical properties while excluding interfering wavelengths, thereby improving measurement precision without requiring complex expensive detectors.
Solution Approach 2:
The patent applies local quality by selecting and measuring light intensity in specific wavelength bands that are locally optimized for detecting particular chemical properties. Instead of measuring the entire spectrum uniformly, the system uses multiple bandpass filters with different transmission characteristics to target specific spectral regions where the analyte of interest absorbs or emits light. This localized spectral measurement approach improves precision for specific chemical property detection while maintaining relatively simple instrumentation.
2Measurement precision
If multiple wavelength bands are measured to improve accuracy, then the measurement precision improves, but the device complexity increases due to multiple bandpass filters and detectors
Solution Approach 1:
The patent implements universality by using a single detector that sequentially measures multiple wavelength bands through the use of multiple bandpass filters. Instead of requiring multiple specialized detectors for different wavelength ranges, the system employs one detector that can measure intensity across various spectral regions by switching between filters. This multi-functional approach allows the system to achieve improved measurement precision through multi-wavelength analysis while avoiding the complexity and cost of multiple expensive detectors.
Solution Approach 2:
The patent replaces complex mechanical spectral analysis systems with a simpler filter-based approach. Instead of using sophisticated spectrometers or diffraction gratings that mechanically separate wavelengths, the system uses multiple bandpass filters that optically isolate specific wavelength bands. This substitution of mechanical spectral separation with optical filtering simplifies the device architecture while maintaining the ability to perform multi-wavelength measurements for improved precision.
3Measurement precision
If principal component analysis is used to compress data, then the measurement precision improves by isolating relevant spectral regions, but the device complexity increases due to additional optical elements
Solution Approach 1:
The patent applies preliminary action by pre-selecting and positioning bandpass filters to target specific wavelength bands that are most relevant for detecting particular chemical properties. Before measurement, the system is configured with filters whose transmission characteristics are optimized for the analyte of interest. This preliminary spectral region isolation ensures that when light passes through the filters, only the most informative wavelength bands reach the detector, thereby improving measurement precision while keeping the optical system relatively simple through careful filter selection rather than complex real-time spectral analysis.
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
This approach enables accurate and reliable estimation of chemical properties by optimizing the optical system configuration to achieve a high signal-to-noise ratio, simplifying instrumentation, and reducing costs associated with sensitive detectors, while maintaining measurement precision.
Implementation Method 1
selecting a spectral element with a predetermined transmission characteristic to control a spectral range of an illumination source
Implementation Method 2
When light interacts with matter, for example, it carries away information about the physical and chemical properties of the matter. A property of the light, for example, its intensity, may be measured and interpreted to provide information about the matter with which it interacted.
Data Source
AI summary
A method of selecting components for a multivariate optical computing and analysis system to isolate a spectral region includes selecting a spectral region of interest; selecting a spectral element with a predetermined transmission characteristic to control a spectral range of an illumination source; illuminating a sample with the illumination source; and analyzing an optical frequency returned by the sample relative to the spectral region of interest.