Nondestructive Inspection of Metal Matrix Composites Using Guided Waves

MMCs have some good properties such as light-weight, resistance to temperature, and wear. For the above advantages to materialize, the SiC in the MMC must be free of defects such as porosity and disbond between the aluminum and SiC layer. This is a verychallenging task. The anisotropic nature of MMCs is responsible for: a directional dependence on wave speed, a difference between phase and group velocity, wave skewing, etc. Only a strong theoretical and experimental understanding of wave propagation inanisotropic materials will enable effective application of ultrasonic testing techniques in MMC components.Here we propose to apply latest developments in guided wave technology to detect and classify defects in MMC. Over the past twenty years, Prof. Joe Rose at Penn State has accumulated extensive experience in using guided waves for different applicationssuch as pipes, plates, rails, etc. The objective of the technical work, Phase I through Phase III, is to develop guided wave technology applicable to both in-situ inspection of MMCs during manufacture and in-service inspection of MMC components. Thedeveloped technology will result in an increase in inspection efficiency and inspection unit autonomy while reducing the demand on DOD maintenance personnel and the total ownership cost for a given DOD asset. The proposed MMC defect detection and diagnosis system is novel by itself and will have many practical applications in other structural diagnostics applications. The system combines latest development in sensor technology with most recent theories inneural networks to detect and classify MMC failures and hence will provide valuable information that could save costs and will also help to make structures safe. The system has low computation burden and hence is suitable for real-time applications. Anautomatic tool for diagnosis will be very useful for structural integrity applications. We estimate the overall cost of the proposed system will be less than $50,000. We expect the market for this system will be in excess of $900 million.