Classification and Automatic Feature-Based Extraction Approach for Cylindrical and Milling Parts
| Autor: | Jagadish, Sathish Kumar Adapa, Dowluru Sreeramulu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Mechanical Engineering Logical rules Feature recognition Process (computing) Pattern recognition 02 engineering and technology 010501 environmental sciences 01 natural sciences 020901 industrial engineering & automation Machining Mechanics of Materials Feature (computer vision) Feature based Decomposition (computer science) Artificial intelligence business Java program ComputingMethodologies_COMPUTERGRAPHICS 0105 earth and related environmental sciences |
| Zdroj: | International Journal of Manufacturing, Materials, and Mechanical Engineering. 11:55-73 |
| ISSN: | 2156-1672 2156-1680 |
| DOI: | 10.4018/ijmmme.2021070104 |
| Popis: | This paper reports classification and automatic extraction of various cylindrical and milling features in conventional machining process parts. In this work, various algorithms like hole recognition algorithm (HRA) and milling feature recognition algorithm (MFRA) have been used for identification of different cylindrical and milling features. A cylindrical feature is identified based on specific logical rules, and milling feature is identified based on the concept of concave decomposition of edges. In-house developed JAVA program is used to write algorithm, and then validation of the algorithm is done through two case studies. The HRA and MFRA algorithms extract the cylindrical features (through holes, blind holes, taper holes, and bosses) and milling features (slot, blind slot, step, blind step, pockets) precisely. The current work is well suitable to extract the features in conventional machining parts and thereby improve the downstream applications likes process planning, CAPP, CAM, etc. |
| Databáze: | OpenAIRE |
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