dc.creator | Petrović, Petar B. | |
dc.creator | Jakovljević, Živana | |
dc.date.accessioned | 2023-03-05T16:29:26Z | |
dc.date.available | 2023-03-05T16:29:26Z | |
dc.date.issued | 2004 | |
dc.identifier.isbn | 3-938153-30-X | |
dc.identifier.uri | https://machinery.mas.bg.ac.rs/handle/123456789/5208 | |
dc.description.abstract | In digital factory environment, continuous cutting tool condition monitoring becomes one of the most important issues, which leads to the higher performance and reliability of manufacturing system. In this paper a new approach to real time tool condition/breakage detection and cutting process monitoring based on hierarchical fuzzy clustering of features obtained by discrete wavelet transform of acquired signals correlated with cutting force is given. Proposed pattern recognition machine considers not only the membership of patterns to certain clusters, but also their evolution in time. | sr |
dc.language.iso | en | sr |
dc.rights | closedAccess | sr |
dc.source | Proceedings of International IEEE Conference Mechatronics & Robotics | sr |
dc.subject | Digital factory | sr |
dc.title | Intelligent Real-time Cutting Tool Condition Monitoring Based on Discrete Wavelet Transform and Fuzzy Force Pattern Recognition | sr |
dc.type | conferenceObject | sr |
dc.rights.license | ARR | sr |
dc.citation.epage | 1083 | |
dc.citation.rank | M33 | |
dc.citation.spage | 1078 | |
dc.citation.volume | III | |
dc.identifier.rcub | https://hdl.handle.net/21.15107/rcub_machinery_5208 | |
dc.type.version | publishedVersion | sr |