Gearbox fault detection using Hilbert and wavelet packet transform
By Xianfeng Fan, Ming Jian Zuo. 2006
352 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/a799142094d927940e3f474d8d306caf08c1d5a8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Qiang Miao
- Qing Zhao
- Chemseddine Rahmoune
- Rui Kang
- Geoff McDonald
- Djamel Benazzouz
- Dong Wang
- Boualem Merainani
In Mechanical Engineering
- Qiang Miao
- Qing Zhao
- Chemseddine Rahmoune
- Geoff McDonald
- Djamel Benazzouz
- Boualem Merainani
- Min Xie
- Z. Ye
Citations in the corpus
- Early detection of tooth crack damage in gearbox using empirical wavelet transform combined by Hilbert transform (2017, methodology): “The Hilbert transform is an attractive method that has been successfully used for decades in order to demodulate the vibration signals with fault modulation (Fan and Zuo, 2006; Guo et al., 2009).”
- Robust health evaluation of gearbox subject to tooth failure with wavelet decomposition (2009, background): “[11] and Fan and Zuo [12] indicated the feasibility of Daubechies wavelets in their research.”
- Application of mother wavelet functions for automatic gear and bearing fault diagnosis (2010, neutral): “.com (J. Rafiee). combinations (Fan & Zuo, 2006; Farina, Lucas, & Doncarli, 2008) are classic signal processing methods.”
- Multipoint Optimal Minimum Entropy Deconvolution and Convolution Fix: Application to vibration fault detection (2017, methodology): “This data has be en used previously in other machine fault detection studies [4, 20].”