An important part of machine condition monitoring and prognostic health monitoring (MCM/PHM) using waveform sensors (such as vibration sensors) is data transformation, where the output from accelerometers is transformed into the time-frequency domain. Although Fourier analysis is a respected time-frequency transform in other application domains, many works in the field of MCM/PHM recommend against it and suggest more elaborate transforms such as wavelet-based approaches. These recommendations are not often justified by experimental data, however. In the present work, we present a discussion of the current state of research on Fourier transforms for MCM/PHM of vibration signals, as well as a case study demonstrating that for some experiments, the Fourier transform can produce very good results.