Triple‐Cavity Cascaded FBG–FPI Hybrid Sensor for Simultaneous Temperature, Pressure, and Humidity Measurement With Sub‐1% Cross‐Sensitivity: A Numerical Design and Simulation Study

Multiparameter fiber optic sensors face a fundamental challenge: cross‐sensitivity between measured parameters compromises accuracy and limits practical deployment. We present a triple‐cavity cascade architecture combining two fiber Bragg gratings (FBGs) and a Fabry–Pérot interferometer (FPI) for the simultaneous measurement of temperature, pressure, and humidity with exceptional numerically‐predicted discrimination performance. The system exploits complementary sensitivity models in a sensitivity matrix with determinant 2.59 and condition number 644, enabling robust parameter recovery through matrix inversion enhanced by a 3–8–8–3 neural network. A comprehensive numerical simulation over the full operating ranges (0–100°C, 100–500 kPa, 5–95%RH) demonstrates simulated accuracies of ±0.011°C in temperature, ±0.012 kPa in pressure, and ±0.021%RH in humidity, with all six cross‐sensitivity pairs suppressed below 1%. This represents a numerically predicted improvement potential of 5×–15× compared to existing two‐parameter systems and is, to our knowledge, the first numerically demonstrated three‐parameter design based on rigorous theoretical analysis. Error budget analysis identifies coating hysteresis (80%) as the primary accuracy limiter for humidity, while wavelength noise (72%) and phase noise (62%) dominate the temperature and pressure uncertainties, respectively. Dynamic response tests over 100 time steps confirm root mean square error (RMSE) values of 0.071°C, 0.313 kPa, and 0.244%RH under simultaneous sinusoidal, step, and random parameter variations. Although experimental validation remains pending, the rigorous theoretical framework provides a model for next‐generation environmental sensing with applications in aerospace monitoring, industrial process control, and precision instrumentation.