This research aims to identify misalignment of the rotor dynamics based on sound spectrum characteristic. In this study, rotor dynamics consist of motor, shaft, coupling and bearings. Three types of misalignment were considered, namely parallel, angular, and combination misalignment. In order to obtain the best signal, microphones were used as sensors to capture sound signal placed on coupling and each bearing. The signal obtained was in time series. The sound signal in the time domain is then filtered to remove noise signals, which are then transferred to be signals in the frequency domain using Fast Fourier Transform (FFT). From the test results, it is found that in the case of parallel misalignment, the sound frequency spectrum is obtained with a peak amplitude at 2x rpm. The case of angular misalignment obtained a sound spectrum with a peak amplitude value and is dominant at 1x rpm than 2x rpm. Meanwhile, in the case of a combination of parallel and angular misalignment, a peak amplitude sound spectrum appears at 1x rpm and 2x rpm with relatively close spacing between the peaks of the sound spectrum. The result shows that sound signal can be used for identification of misalignment of the rotor dynamics.
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