Multi-Sensor Intelligent Systems for Structural Health Monitoring

We propose to develop neural net processing to interpret data from multi-sensor fiberoptic systems and diagnose structural responses on legacy aircraft such as the C-141. Our team of IPITEK, Lockheed Martin Aeronautics Company (LMAero), and the GeorgiaInstitute of Technology will develop complete systems using multiplexed fiberoptic sensors, smart self-diagnosing instrumentation, advanced data processing such as pattern recognition, multi-sensor correlation, trending, on-line dynamic finite elementanalysis and neural networks. Using aircraft network capability developed by IPT and LMAero, these systems can be integrated into an aircraft-wide structural monitoring system which can exchange data with other health monitoring and flight systems as wellas provide data to maintenance personnel, thereby reducing the need for periodic inspection and maintenance and lowering the cost of keeping aging fleets aloft.The need for health monitoring in aging aircraft is by no means restricted to the military, withthe average age of much of the commercial fleet now well past the design lifetime of 20 years. These systems can also be applied to civil structures (such as the aging US bridge system), industrial automation, and advanced robotics and aerospace vehicles.