The Application of Rough Sets Theory to Design of Weld Defect Classifiers
Source abstract
Abstract
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.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Rough Sets and Fuzzy Logic · Image Processing and 3D Reconstruction · Welding Techniques and Residual Stresses
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (33)
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