This study suggests a simple two-step method for structural vibration-based health monitoring for beam-like structures which only utilizes mode shape curvature and few natural frequencies of the structures in order to detect and localize cracks. The method is firstly based on the application of wavelet transform to detect crack locations from mode shape curvature. Then particle swarm optimization is applied to evaluate crack depth. As the Rayleigh quotient is introduced to estimate natural frequencies of cracked beams, the relationship of natural frequencies and crack depths can be easily obtained with only a simple formula. The method is demonstrated and validated numerically, using the numerical examples (cantilever beam and simply supported shaft) in the literature, and experimentally for a cantilever beam. Our results show that mode shape curvature and few estimated natural frequencies can be used to detect crack locations and depths precisely even under a certain level of noise. The method can be extended for health monitoring of other more complicated structures.