Single Fault Diagnosis Method of Sensors in Cascade System Based on Data-Driven

The reliability and safety of the cascade system, which is widely applied, have attached attention increasingly. Fault detection and diagnosis can play a significant role in enhancing its reliability and safety. On account of the complexity of the double closed-loop system in operation, the problem of fault diagnosis is relatively complex. For the single fault of the second-order valued system sensors, a real-time fault diagnosis method based on data-driven is proposed in this study. Off-line data is employed to establish static fault detection, location, estimation, and separation models. The static models are calibrated with on-line data to obtain the real-time fault diagnosis models. The real-time calibration, working flow and anti-interference measures of the real-time diagnosis system are given. Experiments results demonstrate the validity and accuracy of the fault diagnosis method, which is suitable for the general cascade system.

Automated summary

A real-time fault diagnosis method based on data-driven is proposed in this study for the single fault of the second-order valued system sensors. Static fault detection, location, estimation, and separation models are established using off-line data, and calibrated with on-line data to obtain real-time fault diagnosis models. The experiments results show the validity and accuracy of the proposed method, which is suitable for the general cascade system.