| Autor: |
Guo Qing, Yang Shuzhen, Yu Tao |
| Jazyk: |
English<br />French |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
MATEC Web of Conferences, Vol 257, p 02007 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2261-236X |
| DOI: |
10.1051/matecconf/201925702007 |
| Popis: |
In view of the technological requirements of the development of green shipbuilding technology on the effect of ship surface rust removal, the premixed abrasive jet technology is used to remove rust. Because the rust removal of ships with premixed abrasive jet is influenced by multiple parameters and has a high nonlinear relationship between various parameters, the accurate process model of it is difficult to establish. On the basis of artificial neural network modelling technology, the model of ship rust removal with premixed abrasive jet is built. The model takes the system pressure, the target distance, the moving speed of the spray gun and the particle size of the abrasive as input parameters, and the score which can most reflect the effect of the rust removal as output parameter. The test results show that the prediction error of the model is small, and it can better reflect the process rule between the effect of the premixed abrasive jet and the process parameters. We can guide the selection of process parameters according to the model. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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