Coordinator: Dr. Mannur Sundaresan, Department of Mechanical Engineering

Participating faculty:

• Dr. Albert Esterline, Department of Computer Science
• Dr. P. Frank Pai, Department of Mechanical and Aerospace Engineering, University of Missouri

Monitoring damage development

Work is under way on techniques for monitoring damage development in composite specimens using acoustic emission, thermographic test techniques, and fiber optic strain measurements. This research is being carried out in collaboration with engineers at the NASA Armstrong Flight Research Center.

2.1  Sensor Development

PI: Dr. Sundaresan

The goal is to develop sensors and sensor arrays that can record stress waves with high fidelity and sensitivity as required for both Lamb wave and AE techniques. Sensors integrated into a structure must meet several criteria, including noise immunity, environmental resistance, and durability. Finally, sensors, leads, electronics, and software must be matched.

2.2  Numerical Analysis, signal processing and data fusion for integrated vehicle health management (IVHM)

PI: Dr. Sundaresan, Co-Investigators: Dr. Esterline and Dr. Pai

Understanding the nature of AE-related stress waves and the corresponding signals through numerical simulations can help in the identification of source mechanisms operating in metallic and composite materials. Detailed knowledge of the signals due to the stress waves is essential for the discrimination of noise related signals from damage related signals. Further, the waveforms in AE signals change considerably depending on a variety of contributing factors. Hence, determining of the source and its intensity depend on the understanding of elements of the waveform. Signal processing techniques decompose the features for this purpose.

2.3  Software Health Management

PI: Dr. Esterline and Dr. Sundaresan

We have nearly completed a prototype workflow engine that forms a component of the agent- and web-based prototype architecture for structural health monitoring that we are developing.  In this architecture, as regards deployment of the computational resources, the agents provide the “brains,” while the workflow engine provides the “brawn.”  That is, the agents negotiate to determine what techniques will be used for diagnosis and prognosis and how they will be combined, and the workflow engine connects the processes that implement these techniques.

2.4  Testing and Validation

PI: Dr. Sundaresan

Test techniques are needed for understanding and verification of the physical mechanisms active during the failure process and the resulting signals. In addition, the success of various techniques including sensor development and signal processing has to be verified by applying them to predict the damage growth rates in representative laboratory scale models.