Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals

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XU, Chuangwen ;CHEN, Hualing ;LIU, Zhe ;CHENG, Zhongwen .
Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 55, n.1, p. 15-25, august 2017. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/condition-monitoring-of-milling-tool-wear-based-on-fractal-dimension-of-vibration-signals/>. Date accessed: 06 jun. 2020. 
doi:http://dx.doi.org/.
Xu, C., Chen, H., Liu, Z., & Cheng, Z.
(2009).
Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals.
Strojniški vestnik - Journal of Mechanical Engineering, 55(1), 15-25.
doi:http://dx.doi.org/
@article{.,
	author = {Chuangwen  Xu and Hualing  Chen and Zhe  Liu and Zhongwen  Cheng},
	title = {Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {55},
	number = {1},
	year = {2009},
	keywords = {tool wear; milling; fractal dimension; },
	abstract = {The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining systems. A major topic relevant to metal-cutting operations is monitoring tool wear, which affects process efficiency and product quality, and implementing automatic tool replacements. In this paper, pattern recognition is described for the milling tool wear conditions by means of chaotic theory. Factors influencing the consistency of the calculated fractal dimension based on fractal dimension of vibration signals are analyzed. Angle domain tracing method is adopted during acquisition of vibration signals to minimize the effect from spindle speed. A new method for calculating the fractal unscale range is proposed in determining fractal dimension. The experiment results show that the fractal theory is leaded into monitoring field for milling tool wear to be practicable.},
	issn = {0039-2480},	pages = {15-25},	doi = {},
	url = {https://www.sv-jme.eu/article/condition-monitoring-of-milling-tool-wear-based-on-fractal-dimension-of-vibration-signals/}
}
Xu, C.,Chen, H.,Liu, Z.,Cheng, Z.
2009 August 55. Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 55:1
%A Xu, Chuangwen 
%A Chen, Hualing 
%A Liu, Zhe 
%A Cheng, Zhongwen 
%D 2009
%T Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals
%B 2009
%9 tool wear; milling; fractal dimension; 
%! Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals
%K tool wear; milling; fractal dimension; 
%X The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining systems. A major topic relevant to metal-cutting operations is monitoring tool wear, which affects process efficiency and product quality, and implementing automatic tool replacements. In this paper, pattern recognition is described for the milling tool wear conditions by means of chaotic theory. Factors influencing the consistency of the calculated fractal dimension based on fractal dimension of vibration signals are analyzed. Angle domain tracing method is adopted during acquisition of vibration signals to minimize the effect from spindle speed. A new method for calculating the fractal unscale range is proposed in determining fractal dimension. The experiment results show that the fractal theory is leaded into monitoring field for milling tool wear to be practicable.
%U https://www.sv-jme.eu/article/condition-monitoring-of-milling-tool-wear-based-on-fractal-dimension-of-vibration-signals/
%0 Journal Article
%R 
%& 15
%P 11
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 55
%N 1
%@ 0039-2480
%8 2017-08-21
%7 2017-08-21
Xu, Chuangwen, Hualing  Chen, Zhe  Liu, & Zhongwen  Cheng.
"Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals." Strojniški vestnik - Journal of Mechanical Engineering [Online], 55.1 (2009): 15-25. Web.  06 Jun. 2020
TY  - JOUR
AU  - Xu, Chuangwen 
AU  - Chen, Hualing 
AU  - Liu, Zhe 
AU  - Cheng, Zhongwen 
PY  - 2009
TI  - Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - tool wear; milling; fractal dimension; 
N2  - The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining systems. A major topic relevant to metal-cutting operations is monitoring tool wear, which affects process efficiency and product quality, and implementing automatic tool replacements. In this paper, pattern recognition is described for the milling tool wear conditions by means of chaotic theory. Factors influencing the consistency of the calculated fractal dimension based on fractal dimension of vibration signals are analyzed. Angle domain tracing method is adopted during acquisition of vibration signals to minimize the effect from spindle speed. A new method for calculating the fractal unscale range is proposed in determining fractal dimension. The experiment results show that the fractal theory is leaded into monitoring field for milling tool wear to be practicable.
UR  - https://www.sv-jme.eu/article/condition-monitoring-of-milling-tool-wear-based-on-fractal-dimension-of-vibration-signals/
@article{{}{.},
	author = {Xu, C., Chen, H., Liu, Z., Cheng, Z.},
	title = {Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {55},
	number = {1},
	year = {2009},
	doi = {},
	url = {https://www.sv-jme.eu/article/condition-monitoring-of-milling-tool-wear-based-on-fractal-dimension-of-vibration-signals/}
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TY  - JOUR
AU  - Xu, Chuangwen 
AU  - Chen, Hualing 
AU  - Liu, Zhe 
AU  - Cheng, Zhongwen 
PY  - 2017/08/21
TI  - Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 55, No 1 (2009): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - tool wear, milling, fractal dimension, 
N2  - The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining systems. A major topic relevant to metal-cutting operations is monitoring tool wear, which affects process efficiency and product quality, and implementing automatic tool replacements. In this paper, pattern recognition is described for the milling tool wear conditions by means of chaotic theory. Factors influencing the consistency of the calculated fractal dimension based on fractal dimension of vibration signals are analyzed. Angle domain tracing method is adopted during acquisition of vibration signals to minimize the effect from spindle speed. A new method for calculating the fractal unscale range is proposed in determining fractal dimension. The experiment results show that the fractal theory is leaded into monitoring field for milling tool wear to be practicable.
UR  - https://www.sv-jme.eu/article/condition-monitoring-of-milling-tool-wear-based-on-fractal-dimension-of-vibration-signals/
Xu, Chuangwen, Chen, Hualing, Liu, Zhe, AND Cheng, Zhongwen.
"Condition Monitoring of Milling Tool Wear based on Fractal Dimension of Vibration Signals" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 55 Number 1 (21 August 2017)

Authors

Affiliations

  • Lanzhou Polytechnic College, Xi'an Jiaotong University, Xi'an, Shanxi, China
  • School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shanxi, China
  • Lanzhou Polytechnic College, Xi'an Jiaotong University, Xi'an, Shanxi, China
  • Lanzhou Polytechnic College, Xi'an Jiaotong University, Xi'an, Shanxi, China

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 55(2009)1, 15-25

The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining systems. A major topic relevant to metal-cutting operations is monitoring tool wear, which affects process efficiency and product quality, and implementing automatic tool replacements. In this paper, pattern recognition is described for the milling tool wear conditions by means of chaotic theory. Factors influencing the consistency of the calculated fractal dimension based on fractal dimension of vibration signals are analyzed. Angle domain tracing method is adopted during acquisition of vibration signals to minimize the effect from spindle speed. A new method for calculating the fractal unscale range is proposed in determining fractal dimension. The experiment results show that the fractal theory is leaded into monitoring field for milling tool wear to be practicable.

tool wear; milling; fractal dimension;