One of the principal application of acoustic imaging techniques is to identify the acoustic sources over a surface. The purpose of this study is to show the relevance of acoustic imaging as a fault detection tool. A rotating machine bench is used to generate experimentally bearings and gears faults configurations. A 45 microphones array with a spiral distribution is used to register the acoustic radiation. Before applying the acoustic imaging technique, several operations are applied to the recorded signals. The signals are firstly angularly resampled thanks to an angle encoder. Secondly, the synchronous average is used on the signals in order to separate the synchronous and random parts with regard to the mechanism periodicity. Beamforming is then applied to both extracted signals in order to visualize the synchronous and the random acoustic sources. The gears and shaft signals are theoretically synchronous with the mechanism frequency while bearing is not necessarily. The fault signature extracted can be visualized spatially thanks to beamforming.