Simultaneous measurement of displacement and torsion in a fiber specklegram sensor

The fiber specklegram sensor (FSS) shows potential for mechanical parameter measurement, yet simultaneous displacement and torsion sensing remains unexplored. Here, a coupled-mode-theory-based model elucidating torsion-induced specklegram evolution is developed, and an efficient algorithm is devised to determine specklegram rotation angles. Experiments demonstrate that within a defined torsion range, the rotation angle varies linearly with torsion while specklegram morphology remains invariant, which is confirmed to be affected by off-axis offset, fiber length, and core diameter. Beyond this range, a hybrid framework integrating Laplacian eigenmaps with a particle swarm optimization-enhanced neural network enables torsion measurement. Simultaneous displacement and torsion sensing was achieved within the dual-output framework, and the potential for decoding multiple displacement and torsion stimuli was first confirmed in FSS. The system surpasses the existing similar fiber sensors in terms of displacement range and torsional resolution and first demonstrates FSS's extrapolation ability.