Fault Diagnosis Based on Characteristic Direction Method
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The fault diagnosis program based on the characteristic direction method demonstrates excellent performance. This program identifies system faults by analyzing eigenvectors through computational algorithms that determine dominant characteristic directions from sensor data. It generates user-friendly diagnostic reports with detailed fault localization and severity analysis. Additionally, the system implements predictive modeling to forecast potential failures and provides corresponding maintenance recommendations, significantly improving troubleshooting efficiency. Key functions include data preprocessing, eigenvector decomposition, fault pattern matching, and automated report generation. Overall, this graduation project serves as a robust tool that delivers reliable and efficient fault diagnosis services through well-structured MATLAB/Python implementations.
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