Energy pipeline strength evaluation and reliability technology based on Fuzzy deep learning network algorithm

oleh: Wei Zhang, JinLing Zhang, XiaoJun Li, Feng Chen, Jun Guo, Wenwei Li, Jie Cai

Format: Article
Diterbitkan: Elsevier 2022-11-01

Deskripsi

For formulate an effective maintenance scheme of submarine pipeline and effectively ensure the safe operation of submarine pipeline, a strength evaluation and reliability technology of energy pipeline based on Fuzzy depth learning network algorithm is proposed. Firstly, the influence factors of marine environment on submarine pipeline corrosion are described. Secondly, the reliability model of corroded submarine pipeline is established. Given the uncertainty of the relevant parameters of the corrosion defect, the equation of state of the corrosion protection pipe shall be determined on the basis of the corrosion pressure analysis of the corrosion protection pipe. A vague in-depth networking algorithm is used to calculate the probability of a rusty pipeline failure. The results show that the probability of corrosion of the pipeline increases rapidly over time. When the time is 22 years, the failure probability is 2 × 10−4. When the time is 30a, the failure probability is 3.1 × 10−3. The feasibility of fuzzy deep learning network algorithm is verified.