Nuclear reactor fault diagnosis method and apparatus, computer device, and storage medium
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Solution Overview
Problem
Current nuclear power plant fault diagnosis methods have low sensitivity and accuracy, particularly in detecting faults with small fluctuations in operating data, leading to inefficiencies in maintenance due to the complexity of nuclear power plant systems.
Innovation Solution
A method involving system simulation operation data processing, feature engineering, and statistical analysis using squared prediction error and Hotelling statistics to enhance fault diagnosis sensitivity and accuracy, including norm value determination, feature dimensionality increase, and transformation to amplify fault indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current nuclear power plant fault diagnosis methods are used, then the system complexity is manageable, but the sensitivity and accuracy of fault detection are low
Solution Approach 1:
The patent applies feature dimensionality increase by transforming original operation parameters into expanded feature spaces using kernel functions. This maps low-dimensional operation data into high-dimensional spaces where fault patterns become more distinguishable, thereby improving detection sensitivity without directly increasing physical system complexity
Solution Approach 2:
The patent transforms operation parameters through feature engineering, changing the mathematical representation of parameters from raw values to normalized and transformed features. This parameter transformation enhances the distinguishability of fault states while maintaining manageable computational complexity through systematic processing
2Productivity
If current fault diagnosis methods are used, then the maintenance process is simple, but the maintenance efficiency is low due to inability to detect small fluctuations
Solution Approach 1:
The patent performs preliminary feature engineering and normalization on operation data before fault diagnosis. By pre-processing data to enhance fault indicators and normalize parameters, the system prepares optimized input for diagnosis algorithms, enabling more accurate detection of small fluctuations and improving maintenance efficiency
Solution Approach 2:
The patent replaces traditional mechanical fault detection approaches with data-driven feature engineering and statistical analysis. Instead of relying on simple threshold comparisons, the system uses normalized features and dimensionality-transformed data to detect faults, significantly improving detection accuracy for subtle anomalies
3Measurement precision
If feature engineering processing is performed to amplify fault indicators, then the fault detection sensitivity increases, but the data processing complexity increases
Solution Approach 1:
The patent segments the data processing into distinct stages: data collection, normalization, feature engineering, and diagnosis. By dividing the complex processing task into modular segments, each handling a specific transformation, the system achieves high fault detection sensitivity while keeping overall processing complexity manageable through structured organization
Data Source
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AI summary
The present application relates to a nuclear reactor fault diagnosis method and apparatus, a computer device, and a storage medium. The method includes: obtaining system simulation operation data of a nuclear reactor under different candidate operating conditions (S201); determining norm values corresponding to respective types of fault operating conditions based on the system simulation operation data (S202); in response to presence of any norm value among the norm values corresponding to the types of fault operating conditions being less than a preset norm threshold, performing a feature engineering processing on the system simulation operation data, and re-determining the norm values corresponding to the types of fault operating conditions based on the processed system simulation operation data until the norm values corresponding to the types of fault operating conditions are all greater than or equal to the preset norm threshold (S203); and performing fault diagnosis on a current operating condition of the nuclear reactor based on the processed system simulation operation data and current system operation data of the nuclear reactor under the current operating condition (S204). By means of said method, the sensitivity and accuracy of fault diagnosis of a nuclear reactor can be improved. The above method can improve the sensitivity and accuracy of nuclear reactor fault diagnosis.