The magnetostrictive linear displacement sensor is a sensor for measuring absolute displacements. The sensor makes use of the magnetostrictive effect and inverse effect to complete the excitation and reception of ultrasonic guided waves, and from the computed time-of-flight of the guided wave the position of the cursor is determined. To improve the measurement accuracy of the sensor, this paper optimizes the system structure and the signal processing method. Improvement made to the bias magnetic field gave the best transduction efficiency; copper rings were used for accurate control of the dynamic magnetic field range, which enhanced the signal amplitude and effectively reduced the hysteresis impact; two-segment receiving coils were used to improve the SNR; and zero-phase filters were used to remove echo signal noise and phase shift. The delay time difference of the echo signal was determined by the cross-correlation algorithm, which determined accurately the value of displacement. The experimental results put the maximum error of the sensor at $\pm 25 ~\mu {m} $ .

Spectral demodulation is a crucial component of the extrinsic Fabry–Pérot interferometric (EFPI) sensing technology. In this study, a feedback-based linear spectral fitting demodulation method is proposed for interrogating EFPI sensors. This method utilizes a discrete function derivative and a feedback amplitude calibration technique to extract the complete spectral phase, and the cavity length of the EFPI sensor is determined by performing a linear fit to the relationship between the optical frequency and the spectral phase. The experimental results indicated a nonlinearity of 0.134% over a cavity length range of 50–260 μm, and the resolution was 6.6 nm at a cavity length of 170.210 μm. Pressure measurements obtained with the developed sensor exhibited a nonlinearity of 0.401%. Compared to traditional spectral minimum mean square error algorithms, the proposed method is simpler and faster, making it more suitable for implementation on commodity hardware and better aligned with the practical needs of engineering applications.