The study of vibrations generated by mechanical structures and electrical machines are very important. The advent of machines and processes that are more and more complex and the ever increasing exploitation and production costs have favored the emergence of several application fields requiring vibration analysis. Among these application fields, we find machine monitoring, modal analysis, quality control, and environment tests. These functions are used in fields such as aeronautics, space industry, automotive industry, energy production, civil engineering, and audio equipment. The signal processing application described here uses a laser-based vibrometer in order to analyze the vibrations exhibited by mechanical systems. This technique can be used in the numerous applications mentioned above. The problem is to develop an intelligent system that has the ability to determine the system conditions based on a classification of the possible vibration signatures, detect changes in the vibration signature, and analyze their trends. The classification of the various possible vibration signatures requires a priori knowledge of the mechanical system under healthy conditions as well as for the various fault conditions; when possible a mathematical model of the system should be provided. The latter is often crucial for the good interpretation of the observations, since it predicts the dynamic behavior of the structure and thus the healthy vibration signature.