Degradation and Lifetime Prediction of Epoxy Composite Insulation Materials under High Relative Humidity

Jielin Ma, Yan Yang, Qi Wang, Yuheng Deng, Malvern Yap, Wen Kwang Chern, Joo Tien Oh, Zhong Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Insulation failure of composite epoxy insulation materials in distribution switchgear under the stress of heat and humidity is one of the leading causes of damage to switchgear components. This work prepared composite epoxy insulation materials by casting and curing a diglycidyl ether of bisphenol A (DGEBA)/anhydride/wollastonite composite system, and performed material accelerated aging experiments under three conditions: 75 °C and 95% relative humidity (RH), 85 °C and 95% RH, and 95 °C and 95% RH. Material, mechanical, thermal, chemical, and microstructural properties were investigated. Based on the IEC 60216-2 standard and our data, tensile strength and ester carbonyl bond (C=O) absorption in infrared spectra were chosen as failure criteria. At the failure points, the ester C=O absorption decreased to ~28% and the tensile strength decreased to 50%. Accordingly, a lifetime prediction model was established to estimate material lifetime at 25 °C and 95% RH to be 33.16 years. The material degradation mechanism was attributed to the hydrolysis of epoxy resin ester bonds into organic acids and alcohols under heat and humidity stresses. Organic acids reacted with calcium ions (Ca2+) of fillers to form carboxylate, which destroyed the resin-filler interface, resulting in a hydrophilic surface and a decrease in mechanical strength.

Original languageEnglish
Article number2666
JournalPolymers
Volume15
Issue number12
DOIs
Publication statusPublished - Jun 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 by the authors.

ASJC Scopus Subject Areas

  • General Chemistry
  • Polymers and Plastics

Keywords

  • degradation mechanism
  • epoxy composite
  • lifetime prediction model
  • material properties

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