A comprehensive approach to diagnosing rolling bearing damage in permanent magnet synchronous motors (PMSMs) is an important research topic due to the growing use of PMSM drives in industrial systems. The proposed methodology is based on the analysis of diagnostic signals, including mechanical and electrical quantities, obtained under varying operating conditions. Experimental studies were conducted for different motor load levels, as well as for different settings of the current controller parameters in a field-oriented control system. This made it possible to assess the impact of operating conditions and control structure on the effectiveness of bearing damage detection. Particular attention was paid to the process of signal acquisition, preprocessing, and extraction of features characteristic of rolling bearing damage. The selected methods of time and frequency domain signal analysis were used to identify damage-sensitive symptoms associated with bearing component defects. The results obtained show that the effectiveness and sensitivity of individual diagnostic symptoms strongly depend on both the type of signal measured and the operating conditions of the drive system. A comparative evaluation of the extracted features is presented, emphasizing their usefulness for reliable damage detection and accurate condition assessment. The presented approach shows potential for the practical application of signals other than mechanical vibrations.