A case study in on-line intelligent sensing

Author

Moran, A.W. ; O´Reilly, P. ; Irwin, G.W.

Author_Institution

Sch. of Electr. & Electron. Eng., Queen´´s Univ., Belfast, UK

Volume

6

fYear

2000

fDate

2000

Firstpage

3949

Abstract

A new method is described for online detection of parameter changes in a sensor. This is based on work by Yung and Clarke (1989) which employs a local ARIMA model of the sensor output to generate an innovation sequence. A statistical test, which quantifies the change to the variance of an innovation sequence, is developed and used to provide a decision process based on a likelihood ratio of probabilities. Real-time experimental results for detecting a change in a thermocouple time-constant are presented

Keywords

autoregressive moving average processes; intelligent sensors; online operation; statistical analysis; innovation sequence variance change; likelihood ratio; local ARIMA model; online detection; online intelligent sensing; parameter change detection; real-time experimental results; sensor output; statistical test; thermocouple time-constant; Computer aided software engineering; Control systems; Digital signal processing; Fault detection; Intelligent sensors; Sensor phenomena and characterization; Sensor systems; Signal generators; Technological innovation; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2000. Proceedings of the 2000

Conference_Location

Chicago, IL

ISSN

0743-1619

Print_ISBN

0-7803-5519-9

Type

conf

DOI

10.1109/ACC.2000.876963

Filename

876963