Detection of gear deterioration under varying load conditions by using the instantaneous power spectrum.

It has already been proven that time-frequency distributions such as the Wigner–Ville and wavelet transforms can be applied to the description of machine condition and may be used as an effective method in machinery fault diagnosis. This paper considers the use of another time-frequency distribution called the instantaneous power spectrum (IPS) in the detection of local faults in helical gears. The paper begins with a fundamental description of the IPS and then examines the capability of the technique in extracting condition indicating information from gear vibration signals and also in assessing the fault severity. The paper then further examines the ability of the IPS to detect faults under varying load conditions. It is shown that the IPS can be used to detect local faults not only under the same dynamic conditions (constant speed and load), but it can also indicate the progression of faults under varying load conditions.