Validated Uncertainty Evaluation for Self-Validating Sensor
This paper evaluates the validated uncertainty in SEVA sensor by integrating fault detection, identification and reconstruction (FDIR) and reliability engineering. The impact of each fault mode on measurement quality is evaluated quantitatively by using a priori sensor reliability information to investigate the impact of incomplete fault coverage, FDIR and manual maintenance intervention. Bayesian probabilistic approach and uncertainty calculus are employed to model the impact of sensor validation on parameter uncertainty and to fuse the individual modes into a complete sensor model. A simulation of SEVA pressure sensor example illustrates the concept and conclusions.
Wei Gao, Yasuhiro Takaya, Yongsheng Gao and Michael Krystek
Z. G. Feng et al., "Validated Uncertainty Evaluation for Self-Validating Sensor", Key Engineering Materials, Vols. 381-382, pp. 419-422, 2008