| Autor: |
Wang Luohua, Lv Mou, Miao Xiaobo, Li Li, Liang Fengchao |
| Jazyk: |
English<br />French |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
MATEC Web of Conferences, Vol 246, p 02029 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2261-236X |
| DOI: |
10.1051/matecconf/201824602029 |
| Popis: |
Based on the in-depth analysis of the causes of the large-scale water supply pipe network explosion at home and abroad, the paper discusses the neural network modeling technology for quickly and accurately locating the water pipe network. Furthermore, the remedial measures of the pipe network squib in the field were adopted, and the BP neural network deep learning method was proposed to carry out the intelligent positioning of the water pipe network bursting. Based on the construction of a miniature hydraulic model based on BP neural network analysis, through the correlation analysis of the flow change of 5 positions and the pressure monitoring point change of 17 positions when the pipe network bursts, the artificial neural network deep learning is further used to diagnose the position of the pipe network where the pipe burst is located. In this paper, the small-scale water supply pipe network built by the laboratory is taken as an example to verify the research method of the pipe burst positioning. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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