Autofocus for sparse array imaging

If sparse arrays are attached to structures for the purposes of structural health monitoring it is likely that there will be variation in the placement of the sensors, resulting in deviation from the assumed locations. In addition, poor knowledge of the material through which the signals are propagating can result in the use of incorrect velocities, or failing to take account of delays inherent in the equipment. These deviations will result in reduced performance in terms of defect detectability and characterisation. This paper outlines an autofocus approach whereby the transducer locations and material properties can be estimated from the experimental data to ensure the highest levels of defect detectability. The approach is validated using both models and a more complex real world structure. The performance of the approach is considered across a range of potential operating conditions to demonstrate its robustness. Finally limitations and potential solutions to these are addressed.