Tool Condition Monitoring Based on Fuzzy Clustering of Wavelet Coefficients
Апстракт
Environmental consciousness is an imperative in all phases of product life cycle, including its manufacturing. In automated manufacturing processes tool condition monitoring becomes one of the most important issues, which provides higher reliability of the system, as well as the reduction of harmful environmental effects. In this paper a new method for tool failure detection based on fuzzy clustering of wavelet coefficients, gained by discrete wavelet transform of signal acquired by recording of vibrations caused by machining process is proposed. This method is experimentally tested and the results of experiments are given.
Кључне речи:
Tool Condition Monitoring / Classification / Wavelet TransformИзвор:
Proceedings of 11th International CIRP Life Cycle Engineering Seminar, 2004, 93-100Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Jakovljević, Živana AU - Petrović, Petar B. PY - 2004 UR - https://machinery.mas.bg.ac.rs/handle/123456789/5210 AB - Environmental consciousness is an imperative in all phases of product life cycle, including its manufacturing. In automated manufacturing processes tool condition monitoring becomes one of the most important issues, which provides higher reliability of the system, as well as the reduction of harmful environmental effects. In this paper a new method for tool failure detection based on fuzzy clustering of wavelet coefficients, gained by discrete wavelet transform of signal acquired by recording of vibrations caused by machining process is proposed. This method is experimentally tested and the results of experiments are given. C3 - Proceedings of 11th International CIRP Life Cycle Engineering Seminar T1 - Tool Condition Monitoring Based on Fuzzy Clustering of Wavelet Coefficients EP - 100 SP - 93 UR - https://hdl.handle.net/21.15107/rcub_machinery_5210 ER -
@conference{ author = "Jakovljević, Živana and Petrović, Petar B.", year = "2004", abstract = "Environmental consciousness is an imperative in all phases of product life cycle, including its manufacturing. In automated manufacturing processes tool condition monitoring becomes one of the most important issues, which provides higher reliability of the system, as well as the reduction of harmful environmental effects. In this paper a new method for tool failure detection based on fuzzy clustering of wavelet coefficients, gained by discrete wavelet transform of signal acquired by recording of vibrations caused by machining process is proposed. This method is experimentally tested and the results of experiments are given.", journal = "Proceedings of 11th International CIRP Life Cycle Engineering Seminar", title = "Tool Condition Monitoring Based on Fuzzy Clustering of Wavelet Coefficients", pages = "100-93", url = "https://hdl.handle.net/21.15107/rcub_machinery_5210" }
Jakovljević, Ž.,& Petrović, P. B.. (2004). Tool Condition Monitoring Based on Fuzzy Clustering of Wavelet Coefficients. in Proceedings of 11th International CIRP Life Cycle Engineering Seminar, 93-100. https://hdl.handle.net/21.15107/rcub_machinery_5210
Jakovljević Ž, Petrović PB. Tool Condition Monitoring Based on Fuzzy Clustering of Wavelet Coefficients. in Proceedings of 11th International CIRP Life Cycle Engineering Seminar. 2004;:93-100. https://hdl.handle.net/21.15107/rcub_machinery_5210 .
Jakovljević, Živana, Petrović, Petar B., "Tool Condition Monitoring Based on Fuzzy Clustering of Wavelet Coefficients" in Proceedings of 11th International CIRP Life Cycle Engineering Seminar (2004):93-100, https://hdl.handle.net/21.15107/rcub_machinery_5210 .