Chromatographic Peak Detection With Dual-Database Data Integrity
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Solution Overview
Problem
Existing chromatographic analysis systems face challenges in data integrity and security, particularly in managing raw data and ensuring accurate detection of chromatographic peaks, especially in complex scenarios with overlapping peaks and varying peak types, and lack sufficient intelligence and interaction friendliness.
Innovation Solution
A dual-database architecture is implemented, with separate databases for raw data and management data, utilizing MongoDB and MySQL, and an intelligent auxiliary unit with an intelligent chromatographic expert system for peak detection and method optimization, along with a pattern matching method combined with curvature detection to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single database is used to store both raw data and management data, then device complexity is reduced, but data integrity and security cannot be ensured
Solution Approach 1:
The patent divides the database into two separate parts: a first database for storing raw data and a second database for storing management data. This segmentation ensures that raw data has dedicated storage with enhanced integrity and security, while management data is separately managed. The separation resolves the contradiction by sacrificing architectural simplicity to gain data reliability.
2Measurement precision
If traditional peak detection methods (time window or derivative methods) are used, then the process is simple, but peak detection accuracy deteriorates in complex scenarios with overlapping peaks
Solution Approach 1:
The patent combines pattern matching method with curvature detection method to achieve superior peak detection accuracy. The pattern matching method identifies peak positions based on waveform correlation, while the curvature detection method validates peaks by analyzing the second derivative of the chromatogram. This merging of two complementary methods resolves the contradiction by achieving high measurement precision through integrated algorithmic approach.
3Object-affected harmful factors
If pattern matching method is used for peak identification, then insensitivity to noise and peak width changes is improved, but universality deteriorates due to threshold setting requirements
Solution Approach 1:
The patent uses curvature detection as a feedback mechanism to validate and correct peak positions identified by pattern matching. The curvature analysis provides real-time feedback on whether detected peaks are genuine, allowing the system to adapt to different chromatographic conditions. This feedback loop resolves the contradiction by maintaining noise insensitivity while improving universality through dynamic validation.
4Productivity
If amplitude threshold is set to detect all peaks, then completeness of peak detection is improved, but false positive rate increases due to noise peaks
Solution Approach 1:
The patent employs dynamic threshold adjustment based on the chromatogram's actual characteristics. Instead of using a fixed amplitude threshold, the system adapts the detection criteria by analyzing the curvature and pattern of the chromatogram signal. This dynamic approach resolves the contradiction by maintaining high completeness while filtering out false positives through adaptive validation.
Data Source
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AI summary
The present disclosure relates to a chromatographic analysis system, a chromatogram detection and analysis method and an electronic device, belonging to that technical field of chromatographic analysis, wherein the system comprises a data acquiring unit, which is configured to acquire raw data generated by a chromatographic analysis instrument; an analysis processing unit, which is configured to analyze the raw data based on the analysis operation configured by a user to obtain analysis data; a storing and managing unit, which is configured to store raw data and analysis data, and store method parameters and management data of the analysis system; a client unit, which is configured to provide the interactive interface of the system to a user; wherein the storing and managing unit comprises a first database for storing raw data and analysis data and a second database for storing method parameters and management data of the analysis system. The present disclosure is beneficial to ensuring the integrity and security of the acquired raw data and meeting the new demands in the industry practice.