FFT Real-Time Low-Cost Data Acquisition System for Acquiring Wing Vibrations Displacement

The high cost and complexity of conventional vibration data acquisition (DAQ) systems limit their widespread use in laboratory experimentation and industrial monitoring. This study presents the design, development, and validation of a low-cost Arduino-based DAQ platform for real-time measurement of dynamic deformations and flexural vibrations up to 250 Hz. The proposed system employs non-contact Time-of-Flight (ToF) optical sensors to monitor deformation-induced displacement variations of a plastic wing representative of automotive applications. Three ToF sensors are positioned along the wing span at 133 mm intervals and interfaced with an Arduino UNO microcontroller to capture spatially distributed vibration responses. The key novelty of this work lies in the unified integration of synchronized time-division multiplexing (TDM) acquisition and evidence-theoretic data fusion for multi-sensor vibration measurement. Hardware-timer interrupts are used to implement jitter-free TDM scheduling, ensuring Nyquist-compliant sampling, minimizing cross-talk, and enabling precise temporal synchronization through Arduino-based timestamping. Measurement robustness is further enhanced using an improved Dempster–Shafer evidence theory framework, where basic probability assignments derived from Gaussian kernel density estimation suppress outliers and improve signal-to-noise ratio. The fused displacement time-series is processed using Hann-windowed fast Fourier transform (FFT) analysis in Scilab, allowing real-time visualization of vibration frequencies. Experimental results are validated against a finite element modal analysis performed in ANSYS® Mechanical, showing excellent agreement with a maximum deviation of approximately 1.89% in identified natural frequencies. Compared to conventional sequential sampling approaches, the proposed framework significantly improves temporal coherence and real-time performance without additional analog hardware, offering a scalable and cost-effective solution for experimental vibration analysis, industrial monitoring, and predictive maintenance.