Abstract
The signal is processed by using empirical mode decomposition (EMD) and Hilbert transformation (HT), which can obtain instantaneous frequency, instantaneous amplitude and marginal spectrum as the basis of pattern matching. Simultaneously, the energy distribution of signal at each frequency domain can be used to train a neural network as fault diagnosis tool. However, the influence of noise on EMD of gear operation signal is large. The noise may disturb EMD and generate the mix mode and. In this study, wavelet packet de-noises and Ensemble EMD (EEMD) is used to reduce the influence of noise on EMD. The diagnosis results display these two methods can improve gear fault diagnosis.
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Shen, Pc., Kang, Y., Wang, Cc., Chang, Yp., Lee, Hh. (2009). Study on the Affection of Gear Fault Diagnosis Bases on HHT by Noises. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_10
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DOI: https://doi.org/10.1007/978-3-642-03664-4_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03663-7
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