This paper focuses on the development of a structural health monitoring system based on guided Lamb waves propagating over the structure and a network of surface acoustic sensors in communication at high frequencies. A time-of-flight (ToF), algorithm and a probabilistic diagnostic imaging and calibration method is developed to detect miniscule material losses or material adhesion as well as the defects like small scale holes and cracks in turbomachinery components like blades, rotors, plates and pipes. Using an advanced ToF algorithm, precise differences in timescales for arrival of symmetric / antisymmetric lamb wave packets are found for all possible combinations of actuator-sensor pairs. This leads to a deterministic mathematical construct for damage localization for various actuator-sensor pairs at focal points. In the probabilistic diagnostic imaging (PDI) method, field value is assigned based on fusion of wave signals rendered by various actuator-sensor paths to indicate the probability of the presence of a damage at a particular location on the structure. Correlation coefficients between healthy and damaged data for each of the actuator-sensor path is used to calculate the field value for each pixel on the structure. Damage calibration curve is developed by progressively increasing the damage and obtaining a magnitude of the probability density function of the severity of the damage. Proposed approach has been validated using experimental data for multiple damage cases on plates, internal surfaces of pipes and impeller blade to successfully detect submillimeter scale holes and cracks, material adhesion as well as rate of pipeline erosion and corrosion.

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