Safe operation of structures requires rapid and early detection of structural degradation. A potential approach was to monitor structural degradation in real-time, including damage/facture due to unforeseen circumstances, by deploying sensors and efficient/effective wireless mesh networks throughout the structure. This proposal addressed the development of suitable combinations of sensors to monitor damage and their prediction during an aerospace structural component’s service life. Diagnostic and prognostic algorithms determined the damage evolution (initiation/propagation) and damage type (i.e., delamination). The research also focused on the development of models to predict failure evolution using FEM-based progressive failure analysis that considers the effect of defects and uncertainties not anticipated during design stage. This covered in-service accidental damage, tracking of repairs and monitoring of sensor changes reported during transmission. Flexible, low-cost, easy-to install solutions for autonomous ad-hoc monitoring will be assessed.
This project determined the feasibility of coordination of data from heterogeneous sensors, with special focus on improving the wireless transmission of data. The aim was to determine and validate the type, number and arrangement of sensors needed to characterize a given structural damage scenario. This project covered five key topics:
- Assess and design the architecture of a smart and flexible wireless sensor network for multiple sensors with on-board processing,
- Design and fabricate prototype sensor modules for selected candidate sensors. The process board will be designed for all sensors so that only one board is necessary with each sensor interfacing the wireless chip, a micro controller and a memory chip,
- Basic sensor module hardware firmware will be written,
- Architect the flexible wireless protocol stack and write the Windows drivers and
- Test, debug and demonstrate the system.
The integrity of aerospace structures is affected by their severe use profiles over a wide range of loads and environments. Thus, development of approaches to monitor excessive and unforeseen loads and forecast the ‘health’ of aerospace structures on a permanent and continuous basis, provide a valuable extension of the structural integrity knowledge gained by regular NDE inspections and enhance the damage tolerance of the structure predicted during the structural design and certification phase.
In addition, rapidly increasing use of advanced composite materials in primary aerospace structures increases the internal structural complexity and their vulnerability to uncertain scenarios which cannot be anticipated during the design of the structure, such as in-service accidental damages, impact events, local buckling, lightning strike, overheating, etc. These uncertain events change the loading history of the aircraft structure and should be tracked and accounted. In addition, most of them cause barely visual damages which change the residual stiffness and strength, therefore, should be detected, monitored and, when exceeding a critical threshold, to be repaired.
Different physical scenarios apply to metallic structures, for instance, local buckling, plastic deformation, fatigue cracks, strike, corrosion etc. While physically different, the need of event detection and damage monitoring remain the same. Therefore, the need to detect of unforeseen events, monitor damage has made the development of new generation of advanced structures with enhanced damage tolerance a major concern for aerospace industry. Considerable research is being directed towards development of structural health monitoring (SHM) approaches and systems. This is fuelled by the availability of new transmitters and sensors suitable for attaching or embedding into the composite structure which provide new capabilities and opportunities for in-situ SHM. Implementation of multiple types of sensors for event and damage detection and correlation between the sensors has also become a great scope of research in the current SHM technology.