Component Analysis Device Using PARAFAC With Reference Data
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Solution Overview
Problem
Existing spectral fluorescence analysis methods, such as EEM with PARAFAC, face challenges in accurately separating peaks from complex data, often requiring preparatory data and boundary conditions, which can lead to incorrect peak separation or the need for extensive sample preparation, limiting their effectiveness in component analysis of analytes like food and water.
Innovation Solution
A component analysis device and method that utilize a data acquisition circuit to gather spectral data and an analysis circuit performing parallel factor analysis with a reference spectral data set, allowing for accurate separation of components without the need for extensive preparatory data, thereby enhancing separation accuracy and simplifying the analysis process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing spectral fluorescence analysis methods (EEM with PARAFAC) are used to analyze complex analytes, then component separation can be performed, but extensive preparatory data and boundary conditions are required, leading to incorrect peak separation
Solution Approach 1:
The patent applies preliminary action by pre-storing reference spectral data sets of multiple substances in the storage unit before actual analysis. These reference data sets are prepared in advance and organized by analyte type, allowing the analysis circuit to directly compare and identify components without requiring extensive preparatory data collection during the analysis process itself
Solution Approach 2:
The patent uses copying by creating and storing reference spectral data sets that represent the spectral characteristics of various substances. These reference copies are stored in the storage unit and used for comparison during analysis, eliminating the need to collect preparatory data from actual samples and avoiding the complexity of boundary condition specifications
2Measurement precision
If existing spectral fluorescence analysis methods are used, then component analysis can be performed, but extensive sample preparation and boundary conditions are needed, limiting effectiveness
Solution Approach 1:
The system performs preliminary action by pre-organizing reference spectral data sets according to analyte types in the storage unit. This preliminary organization allows the analysis to proceed directly with minimal sample preparation, as the reference data is already categorized and ready for comparison with the measured spectral data
Solution Approach 2:
The analysis circuit performs self-service by automatically comparing the measured spectral data with the stored reference spectral data sets and identifying components based on the best matches. This automated process eliminates the need for manual boundary condition specification and reduces operational complexity
3Measurement precision
If reference spectral data sets corresponding to analyte types are used in parallel factor analysis, then separation accuracy is enhanced, but data storage requirements increase
Solution Approach 1:
The patent applies local quality by organizing reference spectral data sets locally according to analyte types in the storage unit. Each type of analyte has its corresponding reference data sets stored together, allowing the analysis circuit to efficiently retrieve only the relevant reference data needed for the specific analysis, thus optimizing storage utilization
Solution Approach 2:
The reference spectral data sets are prepared and stored in advance in an organized manner by analyte type. This preliminary organization allows for efficient retrieval during analysis without requiring additional storage overhead beyond what is needed to store the reference data itself, eliminating the need for repeated data collection
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 approach enables high-accuracy component analysis of analytes like food and water, improving the identification and quantification of substances, and evaluating water purification efficiency, without the necessity for extensive sample preparation or boundary conditions.
Implementation Method 1
spectral fluorescence analysis methods, such as EEM with PARAFAC
Implementation Method 2
measuring a spectrum of the analyte
Data Source
AI summary
A component analysis device includes a data acquisition circuit that acquires spectral data of an analyte containing components, the spectral data being obtained by measuring a spectrum of the analyte with a sensor, a type acquisition circuit that acquires information indicating a type of the analyte, a storage that stores a reference spectral data set including multiple spectral data of substances each of which is estimated to be included in the analyte, the reference spectral data set corresponding to the type of the analyte, and an analysis circuit that performs a parallel factor analysis by using, as input data, the spectral data of the analyte and the reference spectral data set.