Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals

Peisheng Lou; Kaibo Lu; Hongwei Fan; Wencheng Pan; Fengshou Gu; Andrew Longstaff

doi:10.1109/CYBER50695.2020.9279123

Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals

Peisheng Lou, Kaibo Lu, Hongwei Fan, Wencheng Pan, Fengshou Gu, Andrew Longstaff

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Chatter vibrations during machining operations always restrict the process quality and efficiency, leading to severe damage to the workpiece and shortened tool life. Therefore, accurate and timely diagnosis of chatter will help maintain stable operations. This paper presents an effective method for chatter monitoring in turning operations using wavelet packet energy kurtosis index of the online measured signals. The characteristics of vibration from stable to unstable state are compared in the time, frequency and timefrequency domains, respectively. Considering that the chatter information at its early stage is generally very weak, the wavelet transform is proposed to amplify this feature. Then, the feature information is further explored using wavelet packet decomposition. The wavelet packet energy ratio of each node is calculated to represent the evolution of chatter. Accordingly, the chatter monitoring and prediction indicators using the wavelet energy kurtosis index are constructed. Finally, experimental tests were carried out and the results showed that the proposed method enables to effectively improve the response to chatter vibrations and overcome uncertainties by noises. This study could be beneficial to increasing the time available for the control response to chatter occurrence.

Original language	English
Title of host publication	Proceedings of 10th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	5
ISBN (Electronic)	9781728190105
ISBN (Print)	9781728190112
DOIs	https://doi.org/10.1109/CYBER50695.2020.9279123
Publication status	Published - 11 Dec 2020
Event	2020 IEEE International Conference on CYBER Technology in Automation, Control and Intelligent Systems - Xi'an, China Duration: 10 Oct 2020 → 14 Oct 2020 https://ieee-cyber.org/2020/

Conference

Conference	2020 IEEE International Conference on CYBER Technology in Automation, Control and Intelligent Systems
Abbreviated title	IEEE-CYBER 2020
Country/Territory	China
City	Xi'an
Period	10/10/20 → 14/10/20
Internet address	https://ieee-cyber.org/2020/

Access to Document

10.1109/CYBER50695.2020.9279123Licence: Unspecified

Cite this

Lou, P., Lu, K., Fan, H., Pan, W., Gu, F., & Longstaff, A. (2020). Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals. In Proceedings of 10th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems [9279123] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CYBER50695.2020.9279123

@inproceedings{234b1a3af87e4a48a36351f7e7e93a6a,

title = "Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals",

abstract = "Chatter vibrations during machining operations always restrict the process quality and efficiency, leading to severe damage to the workpiece and shortened tool life. Therefore, accurate and timely diagnosis of chatter will help maintain stable operations. This paper presents an effective method for chatter monitoring in turning operations using wavelet packet energy kurtosis index of the online measured signals. The characteristics of vibration from stable to unstable state are compared in the time, frequency and timefrequency domains, respectively. Considering that the chatter information at its early stage is generally very weak, the wavelet transform is proposed to amplify this feature. Then, the feature information is further explored using wavelet packet decomposition. The wavelet packet energy ratio of each node is calculated to represent the evolution of chatter. Accordingly, the chatter monitoring and prediction indicators using the wavelet energy kurtosis index are constructed. Finally, experimental tests were carried out and the results showed that the proposed method enables to effectively improve the response to chatter vibrations and overcome uncertainties by noises. This study could be beneficial to increasing the time available for the control response to chatter occurrence.",

keywords = "Vibrations, Wavelet packets, Monitoring, Acceleration, Time-frequency analysis, Time-domain analysis, Discrete wavelet transform",

author = "Peisheng Lou and Kaibo Lu and Hongwei Fan and Wencheng Pan and Fengshou Gu and Andrew Longstaff",

year = "2020",

month = dec,

day = "11",

doi = "10.1109/CYBER50695.2020.9279123",

language = "English",

isbn = "9781728190112",

booktitle = "Proceedings of 10th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2020 IEEE International Conference on CYBER Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2020 ; Conference date: 10-10-2020 Through 14-10-2020",

url = "https://ieee-cyber.org/2020/",

}

Lou, P, Lu, K, Fan, H, Pan, W , Gu, F & Longstaff, A 2020, Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals. in Proceedings of 10th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems., 9279123, Institute of Electrical and Electronics Engineers Inc., 2020 IEEE International Conference on CYBER Technology in Automation, Control and Intelligent Systems, Xi'an, China, 10/10/20. https://doi.org/10.1109/CYBER50695.2020.9279123

Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals. / Lou, Peisheng; Lu, Kaibo; Fan, Hongwei et al.

Proceedings of 10th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems. Institute of Electrical and Electronics Engineers Inc., 2020. 9279123.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals

AU - Lou, Peisheng

AU - Lu, Kaibo

AU - Fan, Hongwei

AU - Pan, Wencheng

AU - Gu, Fengshou

AU - Longstaff, Andrew

PY - 2020/12/11

Y1 - 2020/12/11

N2 - Chatter vibrations during machining operations always restrict the process quality and efficiency, leading to severe damage to the workpiece and shortened tool life. Therefore, accurate and timely diagnosis of chatter will help maintain stable operations. This paper presents an effective method for chatter monitoring in turning operations using wavelet packet energy kurtosis index of the online measured signals. The characteristics of vibration from stable to unstable state are compared in the time, frequency and timefrequency domains, respectively. Considering that the chatter information at its early stage is generally very weak, the wavelet transform is proposed to amplify this feature. Then, the feature information is further explored using wavelet packet decomposition. The wavelet packet energy ratio of each node is calculated to represent the evolution of chatter. Accordingly, the chatter monitoring and prediction indicators using the wavelet energy kurtosis index are constructed. Finally, experimental tests were carried out and the results showed that the proposed method enables to effectively improve the response to chatter vibrations and overcome uncertainties by noises. This study could be beneficial to increasing the time available for the control response to chatter occurrence.

AB - Chatter vibrations during machining operations always restrict the process quality and efficiency, leading to severe damage to the workpiece and shortened tool life. Therefore, accurate and timely diagnosis of chatter will help maintain stable operations. This paper presents an effective method for chatter monitoring in turning operations using wavelet packet energy kurtosis index of the online measured signals. The characteristics of vibration from stable to unstable state are compared in the time, frequency and timefrequency domains, respectively. Considering that the chatter information at its early stage is generally very weak, the wavelet transform is proposed to amplify this feature. Then, the feature information is further explored using wavelet packet decomposition. The wavelet packet energy ratio of each node is calculated to represent the evolution of chatter. Accordingly, the chatter monitoring and prediction indicators using the wavelet energy kurtosis index are constructed. Finally, experimental tests were carried out and the results showed that the proposed method enables to effectively improve the response to chatter vibrations and overcome uncertainties by noises. This study could be beneficial to increasing the time available for the control response to chatter occurrence.

KW - Vibrations

KW - Wavelet packets

KW - Monitoring

KW - Acceleration

KW - Time-frequency analysis

KW - Time-domain analysis

KW - Discrete wavelet transform

U2 - 10.1109/CYBER50695.2020.9279123

DO - 10.1109/CYBER50695.2020.9279123

M3 - Conference contribution

SN - 9781728190112

BT - Proceedings of 10th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Conference on CYBER Technology in Automation, Control and Intelligent Systems

Y2 - 10 October 2020 through 14 October 2020

ER -

Lou P, Lu K, Fan H, Pan W , Gu F , Longstaff A. Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals. In Proceedings of 10th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems. Institute of Electrical and Electronics Engineers Inc. 2020. 9279123 doi: 10.1109/CYBER50695.2020.9279123

Machining Chatter Monitoring Based on Wavelet Packet Energy Kurtosis Index of Vibration Signals

Abstract

Conference

Access to Document

Fingerprint

Cite this