Optical Computing Calibration Using Traceable Filters
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Solution Overview
Problem
Optical computing devices face errors due to fluctuations in light intensity and thermal drift, which are costly and time-consuming to calibrate using real fluid samples.
Innovation Solution
A calibration method using traceable optical filters to generate a mapping function between simulated and real detector responses, allowing for calibration without real fluid samples and enabling real-time recalibration to correct for thermal drift.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real fluid samples are used for calibration, then measurement precision is improved, but cost and time consumption increase significantly
Solution Approach 1:
The patent uses simulated detector responses as a copy or model of real detector responses. By creating a mapping function between simulated and real responses using traceable filters, the system can calibrate using the simpler simulated data while maintaining the accuracy equivalent to using real fluid samples, thereby reducing calibration time and cost.
Solution Approach 2:
The patent introduces traceable optical filters as an intermediary element in the calibration process. These filters serve as a mediator that connects the simulated detector responses to the real detector responses, enabling calibration without directly using real fluid samples while maintaining measurement precision.
2Measurement precision
If real fluid samples are used for calibration, then measurement precision is improved, but cost increases due to expensive and hazardous materials
Solution Approach 1:
The patent replaces expensive and hazardous real fluid samples with simulated detector responses that replicate the essential measurement characteristics. This copying approach maintains calibration accuracy while eliminating the need for costly and hazardous materials, making the calibration process more economical and safer.
Solution Approach 2:
The patent uses traceable optical filters that are simpler, cheaper, and safer alternatives to real fluid samples. These filters can be easily manufactured and disposed of, reducing the overall cost and hazard associated with calibration materials while maintaining measurement precision.
3Measurement precision
If traditional calibration methods are used, then initial calibration accuracy is achieved, but thermal drift causes ongoing measurement errors
Solution Approach 1:
The patent implements periodic recalibration using the mapping function between simulated and real detector responses. This periodic action allows the system to correct for thermal drift and other time-dependent variations, maintaining measurement reliability over extended periods while preserving the initial calibration accuracy.
Solution Approach 2:
The patent enables the optical computing device to perform self-calibration using the mapping function and traceable filters. This self-service capability allows the device to automatically correct for thermal drift and maintain measurement stability without requiring external intervention or complex additional equipment.
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 method provides an efficient, accurate, and cost-effective calibration process that reduces the risk of thermal drift and eliminates the need for expensive and hazardous real fluid sample calibration, ensuring precise measurements.
Implementation Method 1
When electromagnetic radiation interacts with a substance, unique physical and chemical information about the substance is encoded in the electromagnetic radiation that is reflected from, transmitted through, or radiated from the sample
Implementation Method 2
A calibration method using traceable optical filters to generate a mapping function between simulated and real detector responses
Data Source
AI summary
Calibration of optical computing devices is achieved using mapping functions that map real detector responses to simulated detector responses which are simulated using high-resolution spectra of traceable optical filters and optical computing device characteristics.