| Abstract [eng] |
In aviation, structural health monitoring relies solely on continuous sensing of the structure's behaviour to detect damage and monitor load conditions. Aircraft are subjected to cyclic and mechanical loadings in extreme environmental conditions during their operational life. Hence, detecting structural degradation early is critical for maintaining safety and airworthiness. Though conventional sensor technologies are effective, they are quite expensive, need a complex installation procedure and are very difficult to customise for complex structures. These limitations have led to the search for an alternative sensing approach that can be readily integrated into structures. Additive manufacturing poses as a suitable alternative as it enables us to fabricate the sensing elements directly within or on the structure at low cost, and with a high geometric customisation flexibility. Fused Deposition Modelling using conductive polymer filaments has emerged as a particularly accessible approach; however, the existing research has remained at the basic testing level with limited investigation of real structural integration and combined loading conditions. This project developed and evaluated 3D printed strain sensors using the FDM technique with conductive polymer filaments. Two evaluated filaments were Protopasta Conductive Pla and Filaflex conductive TPU. The materials were evaluated in both single extrusion and integrated into a simple sensor geometry. In both cases, Protopasta PLA exhibited significantly lower resistance of approximately 275 kΩ compared to approximately 1100 kΩ for TPU-based, hence Protopasta PLA was selected as a suitable material for subsequent development. Two full Wheatstone bridge layouts were designed and fabricated. Layout I adopted a longitudinal configuration of a total bridge resistance of 137 kΩ, while layout II adopted a more compact geometry with a total bridge resistance of 100 kΩ approximately. For establishing electrical connections, conductive thermal bonding was chosen as the method of contact, as it yields stable and repeatable measurements. Data acquisition was performed using an NI 9237 bridge input module and an NI cDAQ-9173 chassis, with signal processing carried out in MATLAB. Both the layouts were characterised under tensile and three-point bending loading conditions using a Tinius Olsen universal testing machine. Under tensile loading, Layout II achieved a gauge factor of 1.27, compared to 0.398 for Layout I. Under three-point bending, Layout II achieved a gauge factor of 1.20, compared to 1.0 for Layout I. A temperature drift experiment from 20°C to 60°C revealed that layout II is much more thermally stable. The improved sensitivity and thermal stability of the second layout are attributed to its compact and symmetrical bridge geometry, efficient strain transfer and uniform heating distribution in the sensing elements. The compact sensor layout was integrated into a 13-inch FPV arm and was evaluated under bending and torsional loading conditions. Three sensors were embedded at different locations along the arm. The two aligned sensors near the fixed and mid-span determine the bending strain, while one 45° orientation placed near the free end captures the shear and normal strain under torsional loading. Under cantilever bending, the sensors captured the expected strain distribution, with experimental values within approximately 10% of theoretical predictions near the fixed support and within 15 20% at mid-span. A gauge factor of approximately 1.07 was extracted for the bending sensors. Under combined bending and torsional loading, a gauge factor of 0.97 was obtained for the 45° sensor using strain superposition of bending and torsional contributions. The results confirm that 3D printed strain gauges are a feasible and low-cost solution for structural state monitoring in lightweight UAV structures. Temperature sensitivity and fabrication repeatability remain areas requiring further investigation before deployment in real operational environments. Future work should focus on multi-specimen repeatability testing, active temperature compensation, and long-term durability evaluation under cyclic loading conditions. |
