Chromatogram Component Identification Method
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Solution Overview
Problem
Existing data processing systems require trial and error to set an appropriate identification method for components in chromatograms, leading to a user burden in achieving accurate identification results.
Innovation Solution
A computer-executable setting method that determines whether each component is distinguishable based on peak information, setting a first identification method for distinguishable components and another identification method for indistinguishable components, using peak parameters such as area, height, and position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If trial and error method is used to set identification method, then appropriate identification method can be found, but user burden increases and time is consumed
Solution Approach 1:
The system performs preliminary analysis of peak information (area, height, position) before the user needs to set the identification method. By pre-evaluating the distinguishability of each component based on these parameters, the system prepares the necessary data and recommendations in advance, eliminating the need for trial-and-error adjustments during the actual identification process.
Solution Approach 2:
The system automatically determines the appropriate identification method for each component by analyzing peak information itself, without requiring user intervention or trial-and-error testing. The system serves itself by autonomously evaluating component distinguishability and selecting the most suitable identification method based on the analyzed data.
2Measurement precision
If trial and error method is used to set identification method, then appropriate identification method can be found, but operation complexity increases
Solution Approach 1:
The system automatically determines the appropriate identification method for each component by analyzing peak information itself, without requiring user intervention or trial-and-error testing. The system serves itself by autonomously evaluating component distinguishability and selecting the most suitable identification method based on the analyzed data.
Solution Approach 2:
The system introduces an intermediary analysis layer that processes peak information (area, height, position) and translates it into recommended identification methods. This intermediary process bridges the gap between raw chromatogram data and identification method selection, eliminating the need for users to manually test different methods.
3Ease of operation
If automatic identification is implemented, then user burden is reduced, but identification accuracy may deteriorate without proper method selection
Solution Approach 1:
The system analyzes multiple parameters (peak area, height, position) to determine component distinguishability and selects identification methods based on these parameter variations. By dynamically adjusting the identification approach according to the specific parameter characteristics of each component, the system maintains high accuracy while automating the process.
Solution Approach 2:
The system applies different identification methods to different components based on their individual characteristics analyzed from peak information. Instead of using a uniform approach, each component receives a tailored identification method suited to its specific distinguishability properties, ensuring optimal accuracy for each case.
Data Source
AI summary
A processor of a setting device obtains a plurality of pieces of peak information respectively corresponding to a plurality of components, determines whether or not one component of the plurality of components is distinguishable from another component other than the one component based on a value of a first peak parameter indicating a feature of a peak included in each of the plurality of pieces of peak information, sets, to a first identification method that is based on the first peak parameter, an identification method for a component that is distinguishable from the other component based on the first peak parameter among the plurality of components, and sets, to another identification method different from the first identification method, an identification method for a component that is not distinguishable from the other component among the plurality of components based on the first peak parameter.


