Sample Measurement Device Peak Identification via Quality Indicator Distribution
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Solution Overview
Problem
Existing sample measurement devices struggle to accurately identify peaks of components in samples when peak positions overlap or are too close, requiring skilled inspectors to compare data before and after changing analysis conditions.
Innovation Solution
A sample measurement device and method that includes a measurement unit and a data processing unit. The data processing unit acquires measurement data, calculates a distribution of a measurement quality indicator based on the data, and identifies peaks of components by using this distribution and the measurement parameters, allowing for accurate peak identification regardless of inspector skill level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If analysis conditions are changed to adjust peak position, then peak separation is improved, but identification accuracy deteriorates due to difficulty in comparing actual data
Solution Approach 1:
The system pre-calculates and stores the relationship between measurement conditions and peak positions in a database before actual analysis. When analyzing samples, the system retrieves pre-computed peak position information based on the current measurement conditions, eliminating the need for inspectors to manually compare data before and after condition changes.
Solution Approach 2:
The system introduces an intermediate database that stores the relationship between measurement conditions and peak positions. This database acts as a mediator between the measurement conditions and the peak identification process, providing automated peak position prediction without requiring direct inspector comparison of multiple datasets.
2Adaptability or versatility
If manual comparison of data is required for peak identification, then flexibility in analysis is improved, but ease of operation deteriorates due to dependency on inspector skill level
Solution Approach 1:
The system performs peak identification automatically using pre-stored relationship data between measurement conditions and peak positions. The system serves itself by retrieving and applying the appropriate peak position information based on current measurement conditions, eliminating the need for inspector intervention and skill-dependent manual comparison.
Solution Approach 2:
The system replaces the manual mechanical process of data comparison with an automated information retrieval process. Instead of inspectors manually comparing chromatograms before and after condition changes, the system automatically queries the database for peak position information corresponding to the current measurement conditions and identifies peaks accordingly.
3Reliability
If multiple measurement conditions are tested to separate peaks, then measurement quality is improved, but loss of time increases due to multiple analyses required
Solution Approach 1:
The system pre-calculates peak positions for multiple measurement conditions and stores this information in a database before actual sample analysis. This preliminary computation eliminates the need to perform multiple actual measurements to determine peak positions, as all necessary information is already available for immediate retrieval.
Solution Approach 2:
The system creates a virtual copy of measurement results by retrieving peak position information from the database that was generated under different measurement conditions. This allows the system to predict peak positions for current conditions without actually performing multiple measurements, saving time while maintaining measurement quality.
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 solution enables accurate identification of peaks in sample measurement devices, ensuring measurement quality and reducing reliance on skilled inspectors, as it predicts peak positions based on measurement conditions and quality indicators.
Implementation Method 1
The chromatography assembly includes a stationary phase and a mobile phase, and separates each component contained in the sample based on a difference between the affinity of each component contained in the sample for the stationary phase and the affinity for the mobile phase
Data Source
AI summary
A sample measurement device (100) includes a measurement unit (10) configured to measure a sample containing a plurality of components according to a measurement condition (30) including a plurality of parameters (31), and a data processing unit (20) configured to acquire measurement data, and the data processing unit is configured to acquire a distribution (43) of a measurement quality indicator (42) according to the measurement condition based on the measurement data (40), and identify a peak (41) of each of the components in the measurement data based on the distribution of the measurement quality indicator and the parameters used when the sample is measured.