Blade vibration and blade clearance are effective diagnostic features for the identification of blade damage in rotating machines. Blade tip-timing (BTT) is a noncontact method that is often used to monitor the vibration and clearance of blades in a rotating machinery. Standard signal processing of BTT measurements give one blade response sample per revolution of the machine which is often insufficient for the diagnosis of damage. This paper uses the raw data signals from the sensors directly and employs a wavelet energy-based mistuning index (WEBMI) to predict the presence and locations of damage in rotating blades. The Lipschitz exponent is derived from the wavelet packet coefficients and used to estimate the severity of the damage. In this study, experiments were conducted to obtain BTT measurements on rotating blades at rpm using three different sensors: an active eddy current sensor, a passive eddy current sensor, and an optical sensor. In addition, hammer excitation experiments were conducted for various added mass (damage) cases to compute the damage severity for a bladed disk. To simulate the damage experimentally in the bladed disk and rotating blades, masses were added to the blades to alter their dynamics and mimic the damage. The results indicate that the WEBMI can detect the presence and location of damage in rotating blades using measurements from common BTT sensors. To check the robustness of the proposed damage severity index, the experimental results were compared with numerical simulation for the bladed disk and showed good agreement.