Lifespan Modeling of Low Voltage Machines Insulation Materials

Lifespan Modeling of Low Voltage Machines Insulation Materials

Antoine Picot David Malec Marie Chabert Pascal Maussion 

Université de Toulouse; INPT, UPS, CNRS; LAPLACE, ENSEEIHT;2 rue Charles Camichel, BP 7122, 31071 Toulouse cedex 7, France

Université de Toulouse; INPT, UPS, CNRS; LAPLACE;Université Paul Sabatier;118 route de Narbonne,31062 Toulouse cedex 7, France

Université de Toulouse ; INPT, UPS, CNRS; IRIT, ENSEEIHT;2 rue Charles Camichel, BP 7122; 31071 Toulouse cedex 7, France

Corresponding Author Email: 
david.malec@laplace.univ-tlse.fr
Page: 
291-306
|
DOI: 
https://doi.org/10.3166/EJEE.17.291-306
Received: 
2 March 2015
| |
Accepted: 
27 August 2015
| | Citation

OPEN ACCESS

Abstract: 

This paper deals with the modeling of insulation material lifespan in a partial discharge regime. Accelerated aging tests are carried out to determine the lifespan of polyester-imide insulation films under different various stress conditions. The insulation lifespan logarithm is modeled as a function of different factors: the electrical and frequency stress logarithms and an exponential form of the temperature. The model parameters are estimated on a training set. The significance of the factors is evaluated through the analysis  of variance (ANOVA). In a first step, the design of experiments method (DoE) is considered. The associated lifespan model is linear with respect to the factors. This method is well known for reducing the number of experiments while providing a good accuracy. In a second step, the response surface method (RSM) is considered. This method takes also into account some second order terms and thus possible interactions between the stress factors. Performance of the two methods are analyzed and compared on a test set.

Keywords: 

electrical insulation, accelerated aging, lifespan estimation, modeling, response surface, analysis of variance, films, twisted pairs

1. Introduction
2. System Description and State-of-the-Art Doe Method
3. Factor Significance Analysis Using ANOVA
4. Response Surface Method for Model Improvement
5. Modeling Lifespan of Wire
6. Conclusion
  References

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