The Application of Rough Sets Theory to Design of Weld Defect Classifiers
| Autor: | Ryszard Sikora, Barbara Grochowalska, Paweł Waszczuk, Leszek Misztal, Mariusz Szwagiel, Bogdan Grzywacz, Tomasz Chady, Michał Szydłowski |
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| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Engineering business.industry Mechanical Engineering Pattern recognition 02 engineering and technology Welding respiratory system computer.software_genre law.invention 020901 industrial engineering & automation Aircraft industry Welding process Mechanics of Materials law 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Rough set Artificial intelligence Data mining business Classifier (UML) computer |
| Zdroj: | Journal of Nondestructive Evaluation. 36 |
| ISSN: | 1573-4862 0195-9298 |
| DOI: | 10.1007/s10921-017-0420-x |
| Popis: | The innovative method for weld defect classification based on rough set theory is presented in this study. The classification rules have been generated by processing of data base composed of 640 radiographic images referring to certain welding process in aircraft industry. The obtained accuracy of defect identification (from 88% up to 100%, depending on class of defect and choice of classifier) can be evaluated as at least competitive or even better one comparing to results referring to other type of frequently “exploited” classifiers, those mentioned in attached overview section. The identification of weld defects is the final operation which is premised by complicated “chain” of consecutive operations transforming primary radiographs to the form enabling calculation of conditional attributes. That is why brief description of process of transformation of primary radiographs to the forms which are suitable for attributes calculation is included in the paper. |
| Databáze: | OpenAIRE |
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