Intelligent monitoring of Highly Dynamic Phenomena in Cutting Process Based on Wavelet Transform
Апстракт
This paper presents a new generic approach to real-time monitoring of highly dynamical phenomena that appear in cutting process. Since recognition of such phenomena requires accurate time localization, wavelet transform was chosen as a formal platform for design of discriminative and reliable feature space based on acquired sensory data. Using cluster centers identified by one-pass fuzzy classification algorithm the phenomena of interest can be precisely and robustly recognized.
Кључне речи:
Cutting process monitoring / Vibration Acceleration Measurement / Pattern recognitionИзвор:
Scientific Bulletin of the POLITEHNICA University of Timisoara, 2005, 50, 64, 87-92Колекције
Институција/група
Mašinski fakultetTY - JOUR AU - Petrović, Petar B. AU - Jakovljević, Živana PY - 2005 UR - https://machinery.mas.bg.ac.rs/handle/123456789/5211 AB - This paper presents a new generic approach to real-time monitoring of highly dynamical phenomena that appear in cutting process. Since recognition of such phenomena requires accurate time localization, wavelet transform was chosen as a formal platform for design of discriminative and reliable feature space based on acquired sensory data. Using cluster centers identified by one-pass fuzzy classification algorithm the phenomena of interest can be precisely and robustly recognized. T2 - Scientific Bulletin of the POLITEHNICA University of Timisoara T1 - Intelligent monitoring of Highly Dynamic Phenomena in Cutting Process Based on Wavelet Transform EP - 92 IS - 64 SP - 87 VL - 50 UR - https://hdl.handle.net/21.15107/rcub_machinery_5211 ER -
@article{ author = "Petrović, Petar B. and Jakovljević, Živana", year = "2005", abstract = "This paper presents a new generic approach to real-time monitoring of highly dynamical phenomena that appear in cutting process. Since recognition of such phenomena requires accurate time localization, wavelet transform was chosen as a formal platform for design of discriminative and reliable feature space based on acquired sensory data. Using cluster centers identified by one-pass fuzzy classification algorithm the phenomena of interest can be precisely and robustly recognized.", journal = "Scientific Bulletin of the POLITEHNICA University of Timisoara", title = "Intelligent monitoring of Highly Dynamic Phenomena in Cutting Process Based on Wavelet Transform", pages = "92-87", number = "64", volume = "50", url = "https://hdl.handle.net/21.15107/rcub_machinery_5211" }
Petrović, P. B.,& Jakovljević, Ž.. (2005). Intelligent monitoring of Highly Dynamic Phenomena in Cutting Process Based on Wavelet Transform. in Scientific Bulletin of the POLITEHNICA University of Timisoara, 50(64), 87-92. https://hdl.handle.net/21.15107/rcub_machinery_5211
Petrović PB, Jakovljević Ž. Intelligent monitoring of Highly Dynamic Phenomena in Cutting Process Based on Wavelet Transform. in Scientific Bulletin of the POLITEHNICA University of Timisoara. 2005;50(64):87-92. https://hdl.handle.net/21.15107/rcub_machinery_5211 .
Petrović, Petar B., Jakovljević, Živana, "Intelligent monitoring of Highly Dynamic Phenomena in Cutting Process Based on Wavelet Transform" in Scientific Bulletin of the POLITEHNICA University of Timisoara, 50, no. 64 (2005):87-92, https://hdl.handle.net/21.15107/rcub_machinery_5211 .