DocumentCode
3297621
Title
Parameter estimation in degradation modelling: A case study using condition monitoring data from wood pole inspections
Author
Welte, T.M. ; Kile, Hakon
Author_Institution
Dept. of Energy Syst., SINTEF Energy Res., Trondheim, Norway
fYear
2011
fDate
19-23 June 2011
Firstpage
1
Lastpage
7
Abstract
Estimating model parameters is a major challenge in degradation modelling. This paper presents an approach where sojourn time distribution parameters were estimated based on censored observations from condition monitoring. A maximum likelihood approach for parameter estimation is described, and the requirements related to type and amount of data are discussed. It is shown that feasible parameter estimates can be obtained when sufficient amount of data is available, even though the data is heavily censored. A case study is presented where data from wood pole inspections were applied for parameter estimation. The data were collected by a Norwegian electricity distribution company during condition monitoring of their power lines. The case study showed that parameter estimates can be established based on such type of data. However, the case study also revealed challenges and limitations because of missing or inconsistent information in the database. The paper discusses these aspects. Furthermore, suggestions on improvement of data collection and parameter estimation are given.
Keywords
condition monitoring; inspection; maximum likelihood estimation; poles and towers; wood; Norwegian electricity distribution company; condition monitoring data; degradation modelling; maximum likelihood approach; model parameter estimation; power line; time distribution parameter; wood pole inspection; Condition monitoring; Degradation; Inspection; Maximum likelihood estimation; Parameter estimation; Poles and towers; Time series analysis; Deterioration; Markov processes; inspection; parameter estimation; sojourn time;
fLanguage
English
Publisher
ieee
Conference_Titel
PowerTech, 2011 IEEE Trondheim
Conference_Location
Trondheim
Print_ISBN
978-1-4244-8419-5
Electronic_ISBN
978-1-4244-8417-1
Type
conf
DOI
10.1109/PTC.2011.6019168
Filename
6019168
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