Gas Analysis Verification Using Multi-Condition Confidence Intervals
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Solution Overview
Problem
Existing gas analysis systems face challenges in determining the accuracy of their data due to errors in system calibration, environmental influences, and flow rate measurements, leading to inaccuracies in volume and mass concentration calculations.
Innovation Solution
A method and apparatus for verifying a gas analysis system by establishing confidence intervals through testing under standard, simulated, and ideal operating conditions, and combining the results to verify the system's performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gas analysis system testing is performed under multiple operating conditions to determine confidence intervals, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The verification process is segmented into multiple distinct testing phases, each addressing a specific aspect of system accuracy. The method divides the complex verification task into: (1) baseline testing under standard conditions to establish reference linearity curves, (2) simulation testing under ideal conditions to determine theoretical confidence intervals, and (3) actual operation testing to validate real-world performance. This segmentation allows each phase to be independently executed and analyzed, improving measurement precision while managing system complexity through structured decomposition.
Solution Approach 2:
The method performs preliminary testing under controlled standard and ideal conditions before actual operation verification. By first establishing baseline linearity curves and confidence intervals through simulated testing, the system creates a reference framework that guides subsequent actual operation testing. This preliminary action reduces the complexity of final verification by having already characterized system behavior under controlled conditions, allowing focused validation only on deviations from expected performance.
2Reliability
If comprehensive testing under standard, simulated, and actual operating conditions is conducted, then reliability is improved, but loss of time increases
Solution Approach 1:
The verification method implements periodic action by conducting tests at distinct, scheduled intervals under different operating conditions. The system performs baseline testing periodically to establish reference data, followed by simulation testing at scheduled intervals to update confidence intervals, and actual operation testing periodically to validate performance. This periodic structure ensures comprehensive reliability verification while managing time loss through regular, predictable testing cycles rather than continuous verification.
Solution Approach 2:
The method performs preliminary testing under standard and simulated conditions to establish baseline confidence intervals before actual operation verification. By pre-characterizing system behavior under controlled conditions and creating reference linearity curves, the system reduces the time required for final actual operation testing. The preliminary actions of baseline and simulation testing create a framework that accelerates subsequent verification by focusing actual operation testing on validating deviations from expected performance rather than characterizing all parameters from scratch.
3Measurement precision
If multiple confidence intervals are determined through extensive testing, then measurement precision is improved, but loss of information increases due to data complexity
Solution Approach 1:
The method segments the determination of confidence intervals into distinct phases corresponding to different testing conditions. Separate confidence intervals are calculated for baseline testing, simulation testing, and actual operation testing, with each phase producing focused, manageable data sets. This segmentation prevents information loss by organizing complex data into structured, condition-specific intervals that can be independently analyzed and combined, maintaining measurement precision while improving data manageability through systematic organization.
Data Source
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AI summary
Embodiments of the present application provide a method, apparatus, electric device, and computer-readable storage medium for verifying a gas analysis system, relating to the gas detection field. The method includes: verifying the gas analysis system based on a first confidence interval obtained by testing the gas analysis system in standard operating conditions, a second confidence interval obtained by testing the gas analysis system in simulated operating conditions, a third confidence interval obtained by testing the gas analysis system in ideal operating conditions, and a fourth confidence interval obtained by testing the gas analysis system in actual operating conditions. The method for verifying a gas analysis system according to the embodiments of the present application enables the determination of the validity of data measured by the gas analysis system.