Composites are prone to impact damage resulting in delamination and /or fibre breakage.  Current practice of detecting  damage categorised as Barely Visible Impact Damage (BVID) includes inspecting structures for surface dents of up to 0.2mm depth or a more elaborate non-destructive inspection approach during maintenance. The surface dents tend to be inconsistent  depending on the  mass of the impactor and  as the result  composites are design much thicker than strictly necessary. 

Our research has shown the use of sensors on panels can provide the information we need to reduce the maintenance costs and weight while increasing/maintaining safety. One way to do this is by detecting BVID in the structure, the design of the composite can be less conservative and weigh savings can be achieved.

Engineering structures such as Aircraft experience impact by foreign objects routinely during their normal operation.  Uncertainties related to frequency of impact and  its likelihood to cause damage  have resulted in utilization of thicker composites (i.e. heavier parts) than strictly necessary.  Through the combination of advanced Machine  Learning Techniques, non-linear Finite Element  and Experimental Measurements we have developed a Passive SHM system capable of predicting the impact  location with almost pinpoint accuracy and more importantly discriminating between the event s (energies, impact forces) that are likely to cause BVID and others below the critical threshold.  

By combining  novel impact detection methodology and signal processing with an Innovative  Microelectronic technology we have  developed a passive SHM system that is small and light enough to be placed permanently on-board of an aircraft and record critical impact events likely to cause damage. The PMCU system being the first ever technology of its kind (Patent pending) can be interrogated wirelessly by engineers  on ground or on-board as required.

A wireless compact active sensing unit has been designed by our group for data acquisition and equiped with energy harvesting capabilities. The design of the WiAct module has been optimized to achieve certain required optimum operative features. The innovative features which makes the system attractive for application to large-scale structures in operation, are:

• Low-power consumption: 81.7 µA – sleep mode 53 mA – active mode
• Multiple sensing channel: 8 (up to 24)
• Wireless communication: 60 m indoor
• Battery-powered system: AA battery
• Low channel cross-talk
• Miniaturized in dimension: 80 mm × 65 mm
• High sampling rate: 1.8 Msps for Sensing; 5.3 Msps for Actuating
• Multiple operation mode: Sleep/Active
• Energy harvesting

Selected Publications:

H Fu, Z Sharif-Khodaei, MHF Aliabadi, An energy-efficient cyber-physical system for wireless on-board aircraft structural health monitoring, Mechanical systems and signal processing 128, 352-368, https://doi.org/10.1016/j.ymssp.2019.03.050

Our group have designed a novel on-board wireless passive sensing system for impact detection of composite airframe. The WiPas system, the first of its kind, offers an invaluable tool for monitoring impact events on critical structures. The unit is battery operated and light, therefore it  can remain  on-board of an aircraft .

Several modules, including filtering, impact detection, local processing and wireless transmission modules have been specifically designed and evaluated for detecting rare, random and transitory impact events. An event-triggered mechanism with high responsiveness is adopted to reduce the system power and to maintain the detection effectiveness. This design allows the system to be adaptive, energy-efficient and highly responsive to impacts. This innovative system provides a low-power, high-responsiveness passive on-board sensing system.

Selected Publications:

Hailing Fu, Zahra Sharif Khodaei and M.H. Ferri Aliabadi, „An Event-Triggered Energy-Efficient Wireless Structural Health Monitoring System for Impact Detection in Composite Airframes“, IEEE Internet of Things Journal 2018, DOI 10.1109/JIOT.2018.2867722.