DocumentCode
300539
Title
On-line sensor validation of single sensors using artificial neural networks
Author
Himmelblau, David M. ; Bhalodia, Mohan
Author_Institution
Dept. of Chem. Eng., Texas Univ., Austin, TX, USA
Volume
1
fYear
1995
fDate
21-23 Jun 1995
Firstpage
766
Abstract
We examine how the signal from a single sensor from a dynamic process might be analyzed to ascertain whether the sensor signal is valid or not. It is quite possible for the signal to indicate a change has occurred in the process when the sensor itself is what has changed. Two possible approaches to sensor validation discussed here are (1) use of second and higher order statistics rather than the mean of a signal, and (2) modeling the sensor signal via artificial neural networks
Keywords
calibration; higher order statistics; neural nets; sensors; signal processing; artificial neural networks; high-order statistics; online sensor validation; sensor signal modeling; Artificial neural networks; Chemical sensors; Higher order statistics; Sensor phenomena and characterization; Sensor systems; Sequential analysis; Signal analysis; Signal processing; Statistical analysis; Temperature sensors;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, Proceedings of the 1995
Conference_Location
Seattle, WA
Print_ISBN
0-7803-2445-5
Type
conf
DOI
10.1109/ACC.1995.529354
Filename
529354
Link To Document