The problem of predicting adhesive bond performance for both surface preparation and undercure defects has been studied using an ultrasonic, experimental test bed system. This experimental test bed incorporates the ultrasonic and computer equipment necessary to acquire and process data from various types of adhesively bonded test specimens. The computer hardware and software has been developed to allow the design of reliable pattern recognition algorithms for the evaluation of surface preparation and bond cure. The specific problem studied is the inspection of the adhesive bond in an aluminum to aluminum step-lap joint whose strength could be affected by improper surface preparation or undercure. A set of 154 bond specimens was used to design an algorithm that is 91 % reliable for separating the specimens into a good class, those bonds with no defects, or a weak class, bonds with poor surface preparation or undercured adhesive layer. A Fisher Linear Discriminant function was selected by the test bed as the best pattern recognition routine for this classification problem.
All Science Journal Classification (ASJC) codes
- Mechanics of Materials
- Surfaces and Interfaces
- Surfaces, Coatings and Films
- Materials Chemistry