Vibration Signature Analysis Of A Chipped Spur Gear Tooth

Amrinder Singh Minhas, Amardeep Singh


Signal processing is a widely applied tool for condition monitoring of rotating machinery. These techniques are thus utilized extensively to process experimental signals. However, hypothesis about data and computational efforts often restrict the application of some techniques. The empirical mode decomposition (EMD) and Hilbert spectrum allows to overcome these limitations. This paper applies this method to vibration signal analysis for localised gear fault diagnosis. Considering that the gear fault vibration signal generate both the amplitude and frequency demodulated signals, the EMD could exactly decompose these demodulated signals into a number of intrinsic mode functions (IMFs), each of which can be amplitude-demodulated or frequency-demodulated component, the frequency families could be separated effectively from the gear vibration signal by applying EMD to the gear vibration signal. Furthermore, when fault occurs in gears, the energy of the gear vibration signal would change correspondingly, whilst the local Hilbert energy spectrum can exactly provide the energy distribution of the signal in certain frequency range with the change of the time and frequency. Thus, the fault information of the gear vibration signal can be extracted effectively from the local Hilbert energy spectrum.


Gear fault, missing tooth, EMD, IMF, Hilbert energy spectrum.

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