Mechanical condition assessment of circuit breakers (CBs) in the power system, if correctly applied, can make an optimal decision on whether, where, and how to perform maintenance. This article presents a new approach to the detection and identification of CB's mechanical states, using its vibration data during switching operations. The morphological correlation coefficient (MCC), which can detect whether or not a fault is present in a CB, is introduced first. Then, a quantitative methodology to specify the specific fault type of the CB, i.e., the ensemble empirical mode decomposition (EEMD)-Hilbert marginal spectrum energy entropy (HMSEE), combined with a classifier [e.g., support vector machine (SVM)], is proposed. By using this approach, the mechanical condition of CBs can be reliably estimated. Some typical mechanical faults of a 12-kV vacuum CB were simulated in the test laboratory to evaluate the effectiveness of the proposed approach. The application in two field cases demonstrates the applicability of the proposed approach.