Online Sensor Fault Detection Based on an Improved Strong Tracking Filter

Sensors

卷:15

Guohui Wang¹  Lifeng Wu¹  Yong Guan¹  Lijuan Wang¹ 

[1] College of Information Engineering, Capital Normal University, Beijing 100048, China;

关键词: cubature Kalman filter;    fault detection;    strong tracking;    sensor;   

DOI  :  10.3390/s150204578

来源: DOAJ

【 摘 要 】

We propose a method for online sensor fault detection that is based on the evolving Strong Tracking Filter (STCKF). The cubature rule is used to estimate states to improve the accuracy of making estimates in a nonlinear case. A residual is the difference in value between an estimated value and the true value. A residual will be regarded as a signal that includes fault information. The threshold is set at a reasonable level, and will be compared with residuals to determine whether or not the sensor is faulty. The proposed method requires only a nominal plant model and uses STCKF to estimate the original state vector. The effectiveness of the algorithm is verified by simulation on a drum-boiler model.

【 授权许可】

Unknown