4.6 Article

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

Journal

SENSORS
Volume 21, Issue 21, Pages -

Publisher

MDPI
DOI: 10.3390/s21217340

Keywords

cascade system; fault diagnosis; sensor; data-driven

Funding

  1. Project of Public Welfare Technology Application Industry Field of Zhejiang Natural Science Foundation Committee [LGG20F030005]

Ask authors/readers for more resources

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.
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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available