CHEN, Xihui ;CHENG, Gang ;LI, Hongyu ;LI, Yong . Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 63, n.1, p. 45-55, june 2018. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/sl/article/research-of-planetary-gear-fault-diagnosis-based-on-multi-scale-fractal-box-dimension-of-ceemd-and-elm/>. Date accessed: 23 apr. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2016.3811.
Chen, X., Cheng, G., Li, H., & Li, Y. (2017). Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM. Strojniški vestnik - Journal of Mechanical Engineering, 63(1), 45-55. doi:http://dx.doi.org/10.5545/sv-jme.2016.3811
@article{sv-jmesv-jme.2016.3811,
author = {Xihui Chen and Gang Cheng and Hongyu Li and Yong Li},
title = {Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {63},
number = {1},
year = {2017},
keywords = {fault diagnosis; planetary gear; CEEMD; multi-scale; fractal box dimension; ELM},
abstract = {The planetary gear is the most critical part of a drive transmission system, and its faults will affect the reliability of the equipment, and even cause accidents. Therefore, it is of great significance to study the fault diagnosis of the planetary gear. A method of planetary gear fault diagnosis based on the multi-scale fractal box dimension of complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM) is proposed. The original vibration signal is decomposed by CEEMD, and a series of intrinsic mode functions (IMFs) are obtained. Some effective IMFs are extracted, and their reconstructed signal associated with the feature information is obtained. The reconstructed signal is analysed with multi-scale analysis, and the fault feature information contained in the signals with different scales is quantified and extracted via a fractal box dimension. The status recognition of planetary gear is achieved by combining ELM. The experiments show that the proposed method is effective at diagnosing planetary gear faults.},
issn = {0039-2480}, pages = {45-55}, doi = {10.5545/sv-jme.2016.3811},
url = {https://www.sv-jme.eu/sl/article/research-of-planetary-gear-fault-diagnosis-based-on-multi-scale-fractal-box-dimension-of-ceemd-and-elm/}
}
Chen, X.,Cheng, G.,Li, H.,Li, Y. 2017 June 63. Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 63:1
%A Chen, Xihui %A Cheng, Gang %A Li, Hongyu %A Li, Yong %D 2017 %T Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM %B 2017 %9 fault diagnosis; planetary gear; CEEMD; multi-scale; fractal box dimension; ELM %! Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM %K fault diagnosis; planetary gear; CEEMD; multi-scale; fractal box dimension; ELM %X The planetary gear is the most critical part of a drive transmission system, and its faults will affect the reliability of the equipment, and even cause accidents. Therefore, it is of great significance to study the fault diagnosis of the planetary gear. A method of planetary gear fault diagnosis based on the multi-scale fractal box dimension of complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM) is proposed. The original vibration signal is decomposed by CEEMD, and a series of intrinsic mode functions (IMFs) are obtained. Some effective IMFs are extracted, and their reconstructed signal associated with the feature information is obtained. The reconstructed signal is analysed with multi-scale analysis, and the fault feature information contained in the signals with different scales is quantified and extracted via a fractal box dimension. The status recognition of planetary gear is achieved by combining ELM. The experiments show that the proposed method is effective at diagnosing planetary gear faults. %U https://www.sv-jme.eu/sl/article/research-of-planetary-gear-fault-diagnosis-based-on-multi-scale-fractal-box-dimension-of-ceemd-and-elm/ %0 Journal Article %R 10.5545/sv-jme.2016.3811 %& 45 %P 11 %J Strojniški vestnik - Journal of Mechanical Engineering %V 63 %N 1 %@ 0039-2480 %8 2018-06-27 %7 2018-06-27
Chen, Xihui, Gang Cheng, Hongyu Li, & Yong Li. "Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM." Strojniški vestnik - Journal of Mechanical Engineering [Online], 63.1 (2017): 45-55. Web. 23 Apr. 2024
TY - JOUR AU - Chen, Xihui AU - Cheng, Gang AU - Li, Hongyu AU - Li, Yong PY - 2017 TI - Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2016.3811 KW - fault diagnosis; planetary gear; CEEMD; multi-scale; fractal box dimension; ELM N2 - The planetary gear is the most critical part of a drive transmission system, and its faults will affect the reliability of the equipment, and even cause accidents. Therefore, it is of great significance to study the fault diagnosis of the planetary gear. A method of planetary gear fault diagnosis based on the multi-scale fractal box dimension of complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM) is proposed. The original vibration signal is decomposed by CEEMD, and a series of intrinsic mode functions (IMFs) are obtained. Some effective IMFs are extracted, and their reconstructed signal associated with the feature information is obtained. The reconstructed signal is analysed with multi-scale analysis, and the fault feature information contained in the signals with different scales is quantified and extracted via a fractal box dimension. The status recognition of planetary gear is achieved by combining ELM. The experiments show that the proposed method is effective at diagnosing planetary gear faults. UR - https://www.sv-jme.eu/sl/article/research-of-planetary-gear-fault-diagnosis-based-on-multi-scale-fractal-box-dimension-of-ceemd-and-elm/
@article{{sv-jme}{sv-jme.2016.3811},
author = {Chen, X., Cheng, G., Li, H., Li, Y.},
title = {Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {63},
number = {1},
year = {2017},
doi = {10.5545/sv-jme.2016.3811},
url = {https://www.sv-jme.eu/sl/article/research-of-planetary-gear-fault-diagnosis-based-on-multi-scale-fractal-box-dimension-of-ceemd-and-elm/}
}
TY - JOUR AU - Chen, Xihui AU - Cheng, Gang AU - Li, Hongyu AU - Li, Yong PY - 2018/06/27 TI - Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 63, No 1 (2017): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2016.3811 KW - fault diagnosis, planetary gear, CEEMD, multi-scale, fractal box dimension, ELM N2 - The planetary gear is the most critical part of a drive transmission system, and its faults will affect the reliability of the equipment, and even cause accidents. Therefore, it is of great significance to study the fault diagnosis of the planetary gear. A method of planetary gear fault diagnosis based on the multi-scale fractal box dimension of complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM) is proposed. The original vibration signal is decomposed by CEEMD, and a series of intrinsic mode functions (IMFs) are obtained. Some effective IMFs are extracted, and their reconstructed signal associated with the feature information is obtained. The reconstructed signal is analysed with multi-scale analysis, and the fault feature information contained in the signals with different scales is quantified and extracted via a fractal box dimension. The status recognition of planetary gear is achieved by combining ELM. The experiments show that the proposed method is effective at diagnosing planetary gear faults. UR - https://www.sv-jme.eu/sl/article/research-of-planetary-gear-fault-diagnosis-based-on-multi-scale-fractal-box-dimension-of-ceemd-and-elm/
Chen, Xihui, Cheng, Gang, Li, Hongyu, AND Li, Yong. "Research of Planetary Gear Fault Diagnosis Based on Multi-Scale Fractal Box Dimension of CEEMD and ELM" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 63 Number 1 (27 June 2018)
Strojniški vestnik - Journal of Mechanical Engineering 63(2017)1, 45-55
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
The planetary gear is the most critical part of a drive transmission system, and its faults will affect the reliability of the equipment, and even cause accidents. Therefore, it is of great significance to study the fault diagnosis of the planetary gear. A method of planetary gear fault diagnosis based on the multi-scale fractal box dimension of complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM) is proposed. The original vibration signal is decomposed by CEEMD, and a series of intrinsic mode functions (IMFs) are obtained. Some effective IMFs are extracted, and their reconstructed signal associated with the feature information is obtained. The reconstructed signal is analysed with multi-scale analysis, and the fault feature information contained in the signals with different scales is quantified and extracted via a fractal box dimension. The status recognition of planetary gear is achieved by combining ELM. The experiments show that the proposed method is effective at diagnosing planetary gear faults.