Monitoring of rotating machines is usually performed on vibration signals and associated signal processing tools focus on extracting weak cyclic information induced by faults on mechanical components like bearings. Their sensitivity to operating conditions in speed and torque are of huge interest in recent research activities. An alternative signal consists in measuring Instantaneous Angular Speed (IAS) of the machine which has been empirically demonstrated as a good vector of information. Angularly sampled by nature, this signal investigates other transfer paths from fault to transducer and introduces new challenges in understanding the relationships between operating conditions and effects of faults on the rotating speed of the machine. The main contribution of this paper lies on the introduction of basic signal processing techniques in order to analyze the shape of rotating speed fluctuations introduced by bearing faults. Modifications due to operating conditions and size of the defect are clearly separated in our suggested analysis on IAS. Another point of interest relies on the fact that this tool can be used in stationary or non-stationary operating conditions. All the analysis are given on experimental data performed on a specific test bench with different artificial bearing faults in various operating conditions.