Wear experiments are performed to explore dynamic states changes of friction noise signals. A new characteristic parameter, moving cut data-approximate entropy (MC-ApEn), is adopted to quantitatively recognize dynamic states. Additionally, determinism (DET), one key parameter of recurrence quantification analysis, is applied to verify the reliability of recognition results of MC-ApEn. Results illustrate that MC-ApEn of friction noise has distinct changes in different wear processes, and it can accurately detect abrupt change points of dynamic states for friction noise. Furthermore, DET of friction noise rapidly declines first, then fluctuates around a small value, and finally increases sharply, which just corresponds to the evolution process of MC-ApEn. So, the reliability of wear state recognition on the basis of MC-ApEn can be confirmed. It makes it possible to accurately and reliably recognize wear states of friction pairs based on MC-ApEn.
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September 2018
Research-Article
Dynamic States Recognition of Friction Noise in the Wear Process Based on Moving Cut Data-Approximate Entropy
Cong Ding,
Cong Ding
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: dingcong@cumt.edu.cn
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: dingcong@cumt.edu.cn
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Hua Zhu,
Hua Zhu
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: zhuhua83591917@163.com
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: zhuhua83591917@163.com
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Guodong Sun,
Guodong Sun
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: guodongsun@cumt.edu.cn
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: guodongsun@cumt.edu.cn
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Yu Jiang,
Yu Jiang
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: Jiangyu@cumt.edu.cn
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: Jiangyu@cumt.edu.cn
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Chunling Wei
Chunling Wei
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: clweilove@126.com
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: clweilove@126.com
Search for other works by this author on:
Cong Ding
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: dingcong@cumt.edu.cn
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: dingcong@cumt.edu.cn
Hua Zhu
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: zhuhua83591917@163.com
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: zhuhua83591917@163.com
Guodong Sun
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: guodongsun@cumt.edu.cn
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: guodongsun@cumt.edu.cn
Yu Jiang
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: Jiangyu@cumt.edu.cn
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: Jiangyu@cumt.edu.cn
Chunling Wei
School of Mechatronic Engineering,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: clweilove@126.com
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: clweilove@126.com
1Corresponding author.
Contributed by the Tribology Division of ASME for publication in the JOURNAL OF TRIBOLOGY. Manuscript received November 26, 2017; final manuscript received February 7, 2018; published online April 5, 2018. Assoc. Editor: Daejong Kim.
J. Tribol. Sep 2018, 140(5): 051604 (8 pages)
Published Online: April 5, 2018
Article history
Received:
November 26, 2017
Revised:
February 7, 2018
Citation
Ding, C., Zhu, H., Sun, G., Jiang, Y., and Wei, C. (April 5, 2018). "Dynamic States Recognition of Friction Noise in the Wear Process Based on Moving Cut Data-Approximate Entropy." ASME. J. Tribol. September 2018; 140(5): 051604. https://doi.org/10.1115/1.4039525
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