Applied Research on Segmented-Hilbert-Huang Transform Algorithm in Fault Feature Extraction of Main Reducer

Abstract:

For the multi-time scale characteristics of vibration signal, a composite multi-frequency dictionary combining the low-frequency Fourier dictionary and the high-frequency impulse time-frequency dictionary is constituted, to decompose multi-component vibration signal into the combination of several one-component signals. The use of empirical model decomposition (EDM) in high-frequency impulse Component signal including feature information is to realize segmented Hilbert-Huang transform of signal and to acquire the time-frequency representation of every one-component signal, which is the process of fault information extraction of vibration signal. The application of the method in main reducer fault diagnosis verifies the engineering practicability and validity of the new algorithm.

• Periodical: Advanced Materials Research (Volume 823)
• Pages: 417-421
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.823.417
• Online since: October 2013
• Authors: Feng Yun Huang, Huan Huan Sun, Hao Pan, Wei Ru Zhang
• Keywords: Empirical Model Decomposition, Fault Feature Extraction, Main Reducer, Segmented Hilbert-Huang Transform

References

[1] Zhijin Bai, Jiexiong Ding, Lijuan Yao. Research on Discriminant Method of Main Reducer Assembly Quantity[J]. Journal of Mechanical Transmission, 2009, 32(5): 78-81.

[2] Yude Jie, Junsheng Cheng, Yu Yang. Application Hilbert-Huang Transform to Gear Fault Diagnosis[J]. Journal of Mechanical Engineering, 2005, 41(6): 102-107.

DOI: 10.3901/jme.2005.06.102

[3] Chinfeng Lin, Jinde Zhu. Hilbert-Huang Transformation-based Time-Frequency Analysis Methods in Biomedical Signal Applications[J]. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 2012, 226(3), 208-216.

DOI: 10.1177/0954411911434246

[4] Aijun Hu, Jingjing Sun, Ling Xiang. Mode Mixing in Empirical Mode Decomposition[J]. Journal of Vibration Measurement and Diagnosis, 2011, 31(4): 429-434.

[5] Stephane G. Mallat, Zhifeng Zhang. Matching Pursuits With Time-Frequency Dictionaries[J]. IEEE Trans. on Signal Processing, 2011, 41(12): 3397-3415.

DOI: 10.1109/78.258082

[6] Eluo Chen. Separation and Extraction Signal Processing Methods of Mechanical Fault Vibration Signal Characteristics[J]. Coal Mine Mechanical, 2008, 29(2): 197-199.

[7] Chenhui Kang, Lingli Cui, Jing Wang, Lixin Gao, Yonggang Xu. Research on the Composite Dictionary Multi-atoms Matching Algorithm Based on the Signal Character[J]. Journal of Mechanical Engineering, 2012, 48(12): 1-6.

DOI: 10.3901/jme.2012.12.001

[8] Lingli Cui, Chenhui Kang, Huaqing Wang, Peng Chen. Composite Dictionary Multi-Atoms Matching for Gear Fault[J]. Sensors (Basel, Switzerland), 2011, 11 (6): 5981-6002.

DOI: 10.3390/s110605981