大型储罐声发射技术下的安全评价方法

Gaofeng Song, Yanbing Zhang, Peipei Sun, Shuoxun Shen, Zhirong Wang

科研成果: 期刊稿件文章同行评审

摘要

In order to explore variation characteristics of related parameters of corrosion acoustic emission signals, experiment was carried out with a common vertical metal storage tank as research object to study characteristics of its acoustic emission source for corrosion. Then, a safety evaluation model based on BP neural network was established, and case study of its application was carried out. The results show that acoustic emission activity and intensity will change along with severity of corrosion reaction, and wave forms of corrosion signals in different periods of corrosion activity will exhibit three types, continuous, abrupt and hybrid types with its frequencies mainly concentrating between 20-60 kHz. The output of BP neural network model is consistent with actual evaluation results, which proves its feasibility and effectiveness.

投稿的翻译标题Safety evaluation method based on acoustic emission technology for large-scale storage tanks
源语言繁体中文
页(从-至)60-66
页数7
期刊China Safety Science Journal
30
3
DOI
出版状态已出版 - 3月 2020

关键词

  • acoustic emission activity and intensity
  • acoustic emission monitoring
  • back propagation (BP) neural network model
  • corrosion signal
  • large storage tank

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