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Bul. Inst. Polit. Iaşi, t. LVI (LX), f. 2, 2010 131
4. Gearbox Diagnosis using the AEP Processing in Frequency Domain
There is also a very important experimental research resource useful in
gearbox diagnosis. The AEP or IEP evolution in steady-state it is a mixture of
many variable components. Each variable signal’s component describes the
behavior of a gearbox’s part (belts, spindles, gears, et cetera). The identification
of these components can be done [1] by computer assisted AEP or IEP power
spectral density (PSD) analysis using Fast Fourier Transform (FFT). The
correlation between signal’s components and gearbox’s parts can be done using
the frequency and the speed of rotation. Figure 7 presents a zoom on the PSD of
the AEP evolution in steady state on 1000 rpm (already described before; see on
Fig. 4 the encircled area).
On Fig. 7 there are a lot of different peaks, each one described by the frequency
and the amplitude (the higher peak’s amplitude are not clearly indicated because
Fig. 7 – The evolution of power spectral density of the
AEP signal absorbed on 1000 rpm (steady-state).
of zoom). The PSD amplitude is proportional with the amplitude of signal
component. Each peak has a number, for each one there is a short description
about the frequency and the correspondence with the gearbox parts (see Fig. 2).
The peak 5 is associated with the spindle II behaviour, the peak 7 with the
spindles III and V, the peak 9 with the spindle I and the peak 10 with the
EDM’s rotor (24.84 Hz frequency, for 1490.4 rpm the real speed of rotation).
The peak 9 is generated by the driving belt pulley run-out error motion (65 μm).
There are also some harmonics of these peaks. There is a very interesting
research result, with certain scientific priority, here is very well mirrored the