Top

The International Journal of Advanced Manufacturing Technology

Published in:

16-11-2019 | ORIGINAL ARTICLE

Online chatter detection in milling process based on VMD and multiscale entropy

Authors: Kai Li, Songping He, Bo Luo, Bin Li, Hongqi Liu, Xinyong Mao

Published in: The International Journal of Advanced Manufacturing Technology | Issue 12/2019

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Chatter is a kind of self-excited vibration, which always has a negative impact on production efficiency. In this paper, a novel online chatter detection method for milling processes is proposed. In this method, firstly, the spindle revolution period component is extracted by angular synchronous averaging (ASA) the vibration signals generated in different cutting conditions. Then, the residual part related to chatter is calculated by subtracting the periodic component. Subsequently, the filtered signal is decomposed into a set of intrinsic mode functions (IMFs) using variational mode decomposition (VMD) to obtain chatter information. Finally, the multiscale permutation entropy (MPE) and multiscale power spectral entropy (MPSE) of the selected IMFs are calculated, and Laplacian score (LS) for feature selection is applied to select the optimal sensitive scale features with generalization. Online chatter detection based on selected sensitive scale features by splitting signal up into overlapping frames in milling process. The analysis results show that the proposed method can effectively detect the chatter under stable cutting conditions and variable cutting conditions.

previous article Optimization analysis considering the cutting effects for high-speed five-axis down milling process by employing ball end mill

next article Strength properties and structure of CuCrZr alloy subjected to low-temperature KOBO extrusion and heat treatment

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Quintana G, Ciurana J (2011) Chatter in machining processes: A review. Int J Mach Tools Manuf 51(5):363–376CrossRef

Altintas Y, Weck M (2004) Chatter stability of metal cutting and grinding. CIRP Ann Manuf Technol 53(2):619–642CrossRef

Altintaş Y, Budak E (1995) Analytical prediction of stability lobes in milling. CIRP Ann-Manuf Technol 44(1):357–362CrossRef

Tlusty J, Zaton W, Ismail F (1983) Stability lobes in milling. CIRP Ann- Manuf Technol 32(1):309–313CrossRef

Bayly PV, Halley JE, Mann BP, Davies MA (2003) Stability of interrupted cutting by temporal finite element analysis. J Manuf Sci Eng 125(2):220–225CrossRef

Yang K, Wang G, Dong Y, Zhang Q, Sang L (2019) Early chatter identification based on an optimized variational mode decomposition. Mech Syst Signal Process 115:238–254CrossRef

Lamraoui M, Thomas M, El Badaoui M (2014) Cyclostationarity approach for monitoring chatter and tool wear in high speed milling. Mech Syst Signal Process 44(1-2):177–198CrossRef

Cao H, Zhou K, Chen X (2015) Chatter identification in end milling process based on EEMD and nonlinear dimensionless indicators. Int J Mach Tools Manuf 92:52–59CrossRef

Shao Y, Deng X, Yuan Y, Mechefske CK, Chen Z (2014) Characteristic recognition of chatter mark vibration in a rolling mill based on the non-dimensional parameters of the vibration signal. J Mech Sci Technol 28(6):2075–2080CrossRef

10.

Zhang Z, Li H, Meng G, Tu X, Cheng C (2016) Chatter detection in milling process based on the energy entropy of VMD and WPD. Int J Mach Tools Manuf 108:106–112CrossRef

11.

Liu C, Zhu L, Ni C (2018) Chatter detection in milling process based on VMD and energy entropy. Mech Syst Signal Process 105:169–182CrossRef

12.

Huang P, Li J, Sun J, Zhou J (2013) Vibration analysis in milling titanium alloy based on signal processing of cutting force. Int J Adv Manuf Technol 64(5-8):613–621CrossRef

13.

Soliman E, Ismail F (1997) Chatter detection by monitoring spindle drive current. Int J Adv Manuf Technol 13(1):27–34CrossRef

14.

Liu Y, Wang X, Lin J, Zhao W (2016) Early chatter detection in gear grinding process using servo feed motor current. Int J Adv Manuf Technol 83(9-12):1801–1810CrossRef

15.

Aslan D, Altintas Y (2018) On-line chatter detection in milling using drive motor current commands extracted from CNC. Int J Mach Tools Manuf 132:64–80CrossRef

16.

Nair U, Krishna BM, Namboothiri VNN, Nampoori VPN (2010) Permutation entropy based real-time chatter detection using audio signal in turning process. Int J Adv Manuf Technol 46(1-4):61–68CrossRef

17.

Cao H, Yue Y, Chen X, Zhang X (2017) Chatter detection in milling process based on synchrosqueezing transform of sound signals. Int J Adv Manuf Technol 89(9-12):2747–2755CrossRef

18.

Kang J, Feng C, Hu H, Shao Q (2007) Research on chatter prediction and monitor based on DHMM pattern recognition theory. In 2007 IEEE International Conference on Automation and Logistics (pp. 1368-1372). IEEE

19.

Tangjitsitcharoen S (2009) In-process monitoring and detection of chip formation and chatter for CNC turning. J Mater Process Technol 209(10):4682–4688CrossRef

20.

Choi T, Shin YC (2003) On-line chatter detection using wavelet-based parameter estimation. J Manuf Sci Eng 125(1):21–28CrossRef

21.

Wang L, Liang M (2009) Chatter detection based on probability distribution of wavelet modulus maxima. Robot Comput-Integr Manuf 25(6):989–998CrossRef

22.

Cao H, Lei Y, He Z (2013) Chatter identification in end milling process using wavelet packets and Hilbert–Huang transform. Int J Adv Manuf Technol 69:11–19CrossRef

23.

Li X, Yao ZH, Chen ZC (2010) An Effective EMD-Based Feature Extraction Method for Boring Chatter Recognition. In Applied Mechanics and Materials (Vol. 34, pp. 1058–1063). Trans Tech Publications

24.

Ji Y, Wang X, Liu Z, Yan Z, Jiao L, Wang D, Wang J (2017) EEMD-based online milling chatter detection by fractal dimension and power spectral entropy. Int J Adv Manuf Technol 92(1-4):1185–1200CrossRef

25.

Dragomiretskiy K, Zosso D (2014) Variational mode decomposition. IEEE Trans Signal Process 62(3):531–544MathSciNetCrossRef

26.

W Aziz, M Arif. (2005). Multiscale permutation entropy of physiological time series. In 2005 Pakistan Section Multitopic Conference (pp. 1–6). IEEE

27.

Ouyang G, Dang C, Li X (2011) Complexity analysis of EEG data with multiscale permutation entropy. In Advances in Cognitive Neurodynamics (II) (pp. 741–745). Springer, Dordrecht

28.

Abarbanel HDI, Kennel MB (1993) Local false nearest neighbors and dynamical dimensions from observed chaotic data. Phys Rev E 47(5):3057CrossRef

29.

Finn JT (1993) Use of the average mutual information index in evaluating classification error and consistency. Int J Geogr Inf Sci 7(4):349–366CrossRef

30.

He X, Cai D, Niyogi P (2006) Laplacian score for feature selection. In Advances in neural information processing systems (pp. 507–514)

31.

Zheng J, Pan H, Yang S, Cheng J (2018) Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis. Mech Syst Signal Process 99:229–243CrossRef

Title: Online chatter detection in milling process based on VMD and multiscale entropy
Authors: Kai Li
Songping He
Bo Luo
Bin Li
Hongqi Liu
Xinyong Mao
Publication date: 16-11-2019
Publisher: Springer London
Published in: The International Journal of Advanced Manufacturing Technology / Issue 12/2019
Print ISSN: 0268-3768
Electronic ISSN: 1433-3015
DOI: https://doi.org/10.1007/s00170-019-04478-4

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Other articles of this Issue 12/2019

Microscopic characterization and modeling of oxide layer for electrolytic in-process dressing (ELID) grinding with focus on voltage, electrode-wheel gap, and coolant flow

An improved algorithm based on subdivision for micro surface modeling

Quantitative characterization of mechano-biological interrelationships of single cells

Optimization analysis considering the cutting effects for high-speed five-axis down milling process by employing ball end mill

Microstructural, mechanical and corrosion properties of aluminium MIG welds reinforced with copper powder

Research on machining compacted graphite iron under oil-on-water cooling and lubrication conditions based on modified material model

Premium Partners