Study of the influence of the technological parameters on the weld quality using artificial neural networks
This paper presents a study on the weld quality obtained by different values of the input parameters. The weld quality is characterized by two categories of parameters: geometrical parameters and mechanical parameters. They are dependent on the following process parameters: electric arc voltage, ele...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2018-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201817803011 |
| _version_ | 1818849151155175424 |
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| author | Anghel Daniel-Constantin Ene Alexandru |
| author_facet | Anghel Daniel-Constantin Ene Alexandru |
| author_sort | Anghel Daniel-Constantin |
| collection | DOAJ |
| description | This paper presents a study on the weld quality obtained by different values of the input parameters. The weld quality is characterized by two categories of parameters: geometrical parameters and mechanical parameters. They are dependent on the following process parameters: electric arc voltage, electric current intensity, welding speed, the feed wire velocity. Because the dependence between inputs and outputs is a nonlinear one was used an artificial feed forward neural network (ANN). The ANN was trained with the backpropagation algorithm, using as training patterns data measured from the mechanical process. This ANN can be used to estimate some parameters from future experiments of the mechanical process. |
| first_indexed | 2024-12-19T06:28:40Z |
| format | Article |
| id | doaj.art-1f85df494f4849d8a19df0a443ab78b8 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-19T06:28:40Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-1f85df494f4849d8a19df0a443ab78b82022-12-21T20:32:28ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011780301110.1051/matecconf/201817803011matecconf_imanee2018_03011Study of the influence of the technological parameters on the weld quality using artificial neural networksAnghel Daniel-ConstantinEne AlexandruThis paper presents a study on the weld quality obtained by different values of the input parameters. The weld quality is characterized by two categories of parameters: geometrical parameters and mechanical parameters. They are dependent on the following process parameters: electric arc voltage, electric current intensity, welding speed, the feed wire velocity. Because the dependence between inputs and outputs is a nonlinear one was used an artificial feed forward neural network (ANN). The ANN was trained with the backpropagation algorithm, using as training patterns data measured from the mechanical process. This ANN can be used to estimate some parameters from future experiments of the mechanical process.https://doi.org/10.1051/matecconf/201817803011 |
| spellingShingle | Anghel Daniel-Constantin Ene Alexandru Study of the influence of the technological parameters on the weld quality using artificial neural networks MATEC Web of Conferences |
| title | Study of the influence of the technological parameters on the weld quality using artificial neural networks |
| title_full | Study of the influence of the technological parameters on the weld quality using artificial neural networks |
| title_fullStr | Study of the influence of the technological parameters on the weld quality using artificial neural networks |
| title_full_unstemmed | Study of the influence of the technological parameters on the weld quality using artificial neural networks |
| title_short | Study of the influence of the technological parameters on the weld quality using artificial neural networks |
| title_sort | study of the influence of the technological parameters on the weld quality using artificial neural networks |
| url | https://doi.org/10.1051/matecconf/201817803011 |
| work_keys_str_mv | AT angheldanielconstantin studyoftheinfluenceofthetechnologicalparametersontheweldqualityusingartificialneuralnetworks AT enealexandru studyoftheinfluenceofthetechnologicalparametersontheweldqualityusingartificialneuralnetworks |