NMR Spectrogram Analysis via Loading Plot Coordinate Alignment
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Solution Overview
Problem
Existing NMR data processing techniques fail to provide effective methods for identifying sample components that contribute to attribute differences among multiple samples, as they lack the ability to feed back evaluation results into analysis parameters and investigate factors affecting these differences.
Innovation Solution
A data processing apparatus and method that acquire and analyze multiple spectrograms from NMR measurements, generating loading plots to identify primary components and correct analysis parameters, allowing for targeted multivariable analysis and improved time-frequency resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multivariable analysis is performed on spectrograms to identify sample components, then the ability to identify factors contributing to attribute differences is improved, but the complexity of the analysis system increases
Solution Approach 1:
The patent segments the complex analysis system into distinct functional modules: a multivariable analysis unit that performs PCA on spectrograms to generate score plots, and a loading plot generation unit that creates loading plots showing variable contributions. This segmentation allows each module to handle specific tasks independently, improving identification accuracy while managing system complexity through modular design.
Solution Approach 2:
The patent introduces loading plots as an intermediary visualization tool between the raw spectrogram data and the final sample classification results. The loading plots serve as a mediator that displays the contribution of each variable (time-frequency point) to the principal components, enabling researchers to identify significant sample components without directly analyzing complex multivariable data structures.
2Ease of operation
If the coordinate system of the loading plot is made identical to the spectrogram coordinate system, then the ease of comparison and interpretation is improved, but the flexibility in analysis approaches is reduced
Solution Approach 1:
The patent applies equipotentiality by setting the loading plot's coordinate system to be identical to the spectrogram's coordinate system. This creates a unified reference frame where both visualizations share the same time and frequency axes, allowing direct overlay and comparison without coordinate transformation. Users can easily identify which time-frequency regions in the spectrogram correspond to high-loading regions in the loading plot, significantly improving ease of operation and interpretation.
Data Source
AI summary
A multivariable analyzer executes multivariable analysis on a data set formed from a plurality of spectrograms acquired from a plurality of samples, and identifies a primary component of the data set, as a result of the multivariable analysis. Each spectrogram has a first coordinate system. A distribution generator generates a loading distribution corresponding to the primary component, as a result of the multivariable analysis. A plot generator generates a loading plot having a second coordinate system, based on the loading distribution. The second coordinate system is identical to the first coordinate system.