Adaptive fuzzy-statistical decision model to grade sensor data

Author

Rokonuzzaman, M. ; Gosine, R.G.

Author_Institution

Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland, St. John´´s, Nfld., Canada

Volume

2

fYear

1997

fDate

25-28 May 1997

Firstpage

773

Abstract

Data from different sensors are fused to measure process parameters having certain domains of values and variances. The data quality is function of the operating states of the sensors. The measurement of the quality of these data is important for the reliable operation of the system. In this work, a fuzzy-statistical decision model has been proposed to grade sensor data. The proposed method is simple and adaptive. A packet oriented grading scheme has been proposed to detect both intermittent, transient and permanent faults of the sensors in a single session

Keywords

adaptive signal processing; decision theory; fault location; fuzzy set theory; sensor fusion; statistical analysis; adaptive fuzzy-statistical decision model; data fusion; data quality; fuzzy-statistical decision model; intermittent faults; packet oriented grading scheme; permanent faults; process parameter measurement; sensor data grading; transient faults; Circuit faults; Circuit noise; Fault detection; Intelligent sensors; Noise measurement; Power system modeling; Sensor fusion; Signal processing; Temperature sensors; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 1997. Engineering Innovation: Voyage of Discovery. IEEE 1997 Canadian Conference on

Conference_Location

St. Johns, Nfld.

ISSN

0840-7789

Print_ISBN

0-7803-3716-6

Type

conf

DOI

10.1109/CCECE.1997.608356

Filename

608356