The application of the conditional moments analysis to gearbox fault detection—a comparative study using the spectrogram and scalogram

TLDR: In this paper, the application of time-dependent parameters (e.g., instantaneous energy, mean and median frequencies, and bandwidth) in the detection and diagnosis of localised and wear gear failures is discussed.

Abstract: Time–frequency methods, which can lead to the clear identification of the nature of faults, are widely used to describe machine condition. Capabilities of time–frequency distributions in the detection of any abnormality can further be improved when their low-order frequency moments (or time-dependent parameters), which characterise dynamic behaviour of the observed signal with few parameters, are considered. This paper presents the applications of four time-dependent parameters (e.g. the instantaneous energy, mean and median frequencies, and bandwidth) based upon the use of spectrogram and scalogram, and compares their abilities in the detection and diagnosis of localised and wear gear failures. It has been found that scalogram based parameters are superior to those of a spectrogram in the detection and location of a local tooth defect even when the gear load is small, as they result in equally useful parameters in the revelation of gear wear. Moreover, the global values of these time-dependent parameters are found to be very useful and provide a very good basis for reflecting not only the presence of gear damage, but also any change in operating gear load.