DocumentCode
3221412
Title
The Kalman filter as a way to estimate the life-model parameters of insulating materials and system
Author
Tambini, G. ; Montanari, G.C. ; Cacciari, M.
Author_Institution
Istituto di Elettrotecnica Ind., Bologna Univ., Italy
fYear
1992
fDate
22-25 Jun 1992
Firstpage
523
Lastpage
527
Abstract
The Kalman filter algorithm is applied to linear life models, valid for insulating materials subjected to electrical and multiple thermal-electrical stresses. Expressions for the state-space equations, and then for the prediction and updating equations, are obtained on the basis of inverse-power and exponential models, thus providing a useful tool for insulating-material characterization. In particular, the extrapolation to stresses lower than the test stresses and the estimation of the endurance coefficient become very sensitive to the test results at the lowest stresses, thus providing evaluations which could be more representative of the service conditions than the normal regression procedure. Examples are reported relevant to the results of life tests performed on XLPE (cross-linked polyethylene) cable models
Keywords
Kalman filters; cable insulation; insulation testing; life testing; organic insulating materials; parameter estimation; polymers; Kalman filter algorithm; XLPE; cable models; electrical stresses; endurance coefficient; exponential models; insulating materials; life tests; life-model parameters; linear life models; multiple thermal-electrical stresses; prediction equations; state-space equations; updating equations; Dielectrics and electrical insulation; Equations; Extrapolation; Life estimation; Life testing; Parameter estimation; Performance evaluation; Polyethylene; Predictive models; Thermal stresses;
fLanguage
English
Publisher
ieee
Conference_Titel
Conduction and Breakdown in Solid Dielectrics, 1992., Proceedings of the 4th International Conference on
Conference_Location
Sestri Levante
Print_ISBN
0-7803-0129-3
Type
conf
DOI
10.1109/ICSD.1992.225021
Filename
225021
Link To Document