The cyclostationarity method is used in this paper for the diagnosis of a turbo-alternator working in industrial environment for the detection of the defects generated by rolling bearings, journal bearings, and gears. This study shows the advantage of using such analysis as an aid to diagnosis and decision making before a failure caused by bad vibration monitoring of rotating machinery can be produced. In fact, a cyclostationary signal has some hidden periodicities, which mean that it is not strictly periodic, but some statistical properties of the signal are periodic. This periodicity identifies the spectral correlation by integrating the modulation intensity distribution function that depends only of the cyclic frequency, which is an indicator of the presence of modulations. The method was initially applied on a theoretical signal simulating a single bearing fault. The experimental validation is then performed on the machine faults simulator (MFS) for the detection of a bearing fault, and on a turbo-alternator working in real conditions in industrial environment. The application of this method helped to highlight very clearly the presence of defects on the bearings and the gears, which has been difficult to show especially at low frequency by spectral analysis.