This research aimed to perform a comparative analysis between damage identification methods based on modal analysis, to cooperate with the Structural Health Monitoring (SHM) process in steel beams. To achieve that, steel beam models were be generated via commercial finite elements software Abaqus with differences in parameters such as damage level, damage location and boundary conditions. After obtaining results for mode shape displacement, two more parameters are added: noise level and the use or not of a curve fit to smooth data. As there are four methods of damage identification compared: DCM, DCMM, MSDBI and MSDBIM, it was issued a full factorial Design of Experiments (DOE) to analyze and to check the effectiveness of each method in detecting and possibly localizing damage, in addition to observe the ability to distinguish different levels of damage to each model through statistical analysis that was extended to study the influence of factors in the problem response of each damage identification methods. The results obtained show that the methods have high effectiveness to locate damage in noiseless conditions, however the presence of noise decreases the correct identification of damage, even with regression fit to smooth modal data. The modified methods performed better when compared to the originals, and the methods DCM and DCMM located the damage more easily than MSDBI and MSDBIM.