Machine fault diagnosis through an effective exact wavelet analysis

By P. W. Tse, Wenxian Yang, Hon-Yuen Tam. 2004

244 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/1abe7a6be8e832abbec7a10c2c5030bd5a3ad9d4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Xingqing Wang
2. J. Y. Zhang
3. Xuefeng Chen
4. P. W. Tse
5. Robert X. Gao
6. Ruqiang Yan
7. F. Chu
8. Zhike Peng

In Computer Vision and Pattern Recognition

1. Xuefeng Chen
2. Ruqiang Yan
3. Robert X. Gao
4. Xingqing Wang
5. J. Y. Zhang
6. P. W. Tse
7. Zhike Peng

In Control and Systems Engineering

1. Xuefeng Chen
2. Ruqiang Yan
3. Robert X. Gao
4. Xingqing Wang
5. J. Y. Zhang
6. P. W. Tse
7. F. Chu
8. Po-Chun Chen

Citations in the corpus

• An improved Hilbert–Huang transform and its application in vibration signal analysis (2005, background): “Although wavelet transform is capable of analysing nonlinear and non-stationary signals and deemed suitable for vibration-based machine fault diagnosis, many deficiencies have been reported in the use of wavelet transform [3].”
• An expert system for fault diagnosis in internal combustion engines using wavelet packet transform and neural network (2009, unknown): “…distribution (WVD) (Andria, Savino, & Trotta, 1994; Staszewski, Worden, & Tomlinson, 1997) and wavelet transform (WT) (Chen, Sun, Zhang, & Wang, 2005; Lin & Qu, 2000; Prabhakar, Mohanty, & Sekhar, 2002; Serhat & Emine, 2003; Tse, Yang, & Tam, 2004; Wu & Chen, 2006; Zheng, Li, & Chen, 2002) .”
• Blind Source Separation and Blind Equalization Algorithms for Mechanical Signal Separation and Identification (2006, methodology): “Numerous vibration-based machine fault diagnostic methods have been developed, such as exact wavelet analysis (Tse et al., 2004), Hilbert-Huang transform (Peng et al.”
• Comparison of methods for non-stationary hydrologic frequency analysis: Case study using annual maximum daily precipitation in Taiwan (2017, methodology): “…is the order of the mother wavelet function, which was determined in previous papers using trialand-error methods based on the intrinsic characteristics of the data (Wang and McFadden, 1995; Samanta and Al-Balushi, 2003; Peter et al., 2004; Liu, 2005; Kar and Mohanty, 2006; Rafiee et al., 2007).”
• Wavelets for fault diagnosis of rotary machines: A review with applications (2014, methodology): “genetic algorithm [22], and helped to detect faults in a motor pump rotary machine.”