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Chatter detection using principal component analysis in cold rolling mill

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Most cold rolling mills are prone to chatter problem. Chatter marks are often observed on the strip surface in cold rolling mill leading to downgrade and rejection of rolled material. Chatter impact product quality as well as productivity of mill. In absence of online chatter detection no corrective action can be taken immediately and whole campaign gets affected. Most conventional approach for online chatter detection is by using vibration measurement of mill stands in time & frequency domain. Present work proposes two approaches to detect chatter in cold rolling mill using a statistical technique called Principal Component Analysis (PCA). In this paper two methods are used for chatter detection. First method applies PCA on Fast Fourier Transform (FFT) to differentiate between chatter and non-chatter condition. Second method applies PCA on statistical parameters calculated from raw vibration data to detect chatter.
Czasopismo
Rocznik
Strony
73--81
Opis fizyczny
Bibliogr. 16 poz., rys., tab.
Twórcy
autor
  • Tata Steel Ltd, Jamshedpur, India
autor
  • Tata Steel Ltd, Jamshedpur, India
autor
  • Tata Steel Ltd, Jamshedpur, India
autor
  • Tata Steel Ltd, Jamshedpur, India
autor
  • Tata Steel Ltd, Jamshedpur, India
  • Tata Steel Ltd, Jamshedpur, India
Bibliografia
  • 1. Farley T., Rogers S., Nardini D. Understanding Mill Vibration Phenomena. Innoval Technology Limited, 2008.
  • 2. Tlusty J., Chandra G., Critchley S., Paton D. Chatter in cold rolling, CIRP, 1982, 31(1): 195-199.
  • 3. Klepikov VB. On a functional auto-vibrations in the electrical drives. Electricity Journal, 1986; 4: 54-62.
  • 4. Gasparic JJ. Vibration analysis identifies the cause of mill chatter. AISE Year Book, 1991; 1: 27-29.
  • 5. Bollinger LA., Rapsinski TA. Windibg reel involvement in temper mill chatter. Iron and Steel Eng., 1994; 71(12): 27-29.
  • 6. Nesseler GL., Cory JF. Cause and solution of fifth octave backup roll chatter on 4-h cold mills and temper mills. Iron and Steel Eng., 1989; 10: 23-27.
  • 7. Pimenov VA. On the causes of non stable cold rolling. Izvestiya VUZov. Chornaia Metallurgy, 1990; 8: 36-38.
  • 8. Yarita I., Furakawa K., Seino Y. An analysis of chattering in cold rolling for ultra-thin gauge steel strip. Trans. of the Iron and Steel Inst. of Japan, 1978; 18(1): 1-11.
  • 9. Hardwick BR. Identification and solution of chatter vibration on roll grinding machine. Iron and Steel Eng., 1994; 71(7): 41-46.
  • 10. Hardwick BR. A technique for the detection and measurement of chatter marks on rolls surfaces. Steel Technology, 2003; 4: 64-70.
  • 11. Benhafsi Y. The use of vibration analysis tools to solve chatter problems on rolling mills and roll grinding machines. Proc. of Steel Rolling 2006, the 9th International and 4th European Conference, France, 2006.
  • 12. Holl J, Schlacher K. Analysis and active rejection of chatter in rolling mills. Proc. App. Math. Mech., 2003; 3: 134-135.
  • 13. Petit B, Decrequy D. Global approach of 3rd octave chatter vibrations at Arcelor Mardyck cold rolling mill and analysis of technological interactions. ATS International Steel Making Conference, Paris, December 9-10, 2004.
  • 14. Shao Y, Deng X. Characteristic recognition of chatter mark vibration in a rolling mill based on the non-dimensional parameters of the vibration signal. Journal Of Mechanical Science And Technology, 2014; 28(6): 2075-2080. http://dx.doi.org/10.1007/s12206-014-0106-6
  • 15. Ahmed M, Baqqar M, Gu F, Ball AD. Fault detection and diagnosis using Principal Component Analysis of vibration data from a reciprocating compressor. Proceedings of 2012 UKACC International Conference on Control, p.461-466. http://dx.doi.org/10.1109/CONTROL.2012.6334674
  • 16. Plante T, Stanley L, Nejadpak A, Yang CX. Rotating machine fault detection using principal component analysis of vibration signal. IEEE AUTOTESTCON, 2016, p.1-7. http://dx.doi.org/10.1109/AUTEST.2016.7589634.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-99a37c3d-a693-48f2-bed5-7b25834541be
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