In this paper, a hollow-core negative curvature fiber (HC-NCF) with high birefringence is proposed for low refractive index (RI) sensing based on surface plasmon resonance effect. In the design, the cladding region of the HC-NCF is composed of only one ring of eight silica tubes, and two of them are selectively filled with the gold wires. The influences of the gold wires-filled HC-NCF structure parameters on the propagation characteristic are investigated by the finite element method. Moreover, the sensing performances in the low RI range of 1.20–1.34 are evaluated by the traditional confinement loss method and novel birefringence analysis method, respectively. The simulation results show that for the confinement loss method, the obtained maximum sensitivity, resolution, and figure of merit of the gold wires-filled HC-NCF-based sensor are −5700 nm/RIU, 2.63 × 10⁻⁵ RIU, and 317 RIU⁻¹, respectively. For the birefringence analysis method, the obtained maximum sensitivity, resolution, and birefringence of the gold wires-filled HC-NCF-based sensor are −6100 nm/RIU, 2.56 × 10⁻⁵ RIU, and 1.72 × 10⁻³, respectively. It is believed that the proposed gold wires-filled HC-NCF-based low RI sensor has important applications in the fields of biochemistry and medicine.

In this paper, a surface plasmon resonance (SPR)-based photonic crystal fiber (PCF) sensor is proposed for simultaneously measuring the refractive index (RI) and temperature. In the design, the central air hole and external surface of the proposed PCF are coated with gold films, and an air hole is filled with the temperature-sensitive material (TSM). By introducing the inner and outer gold films and TSM, the RI and temperature can be measured simultaneously at different wavelength regions. The simulation results show that the average wavelength sensitivities of the proposed SPR-based PCF sensor can reach 4520 nm/RIU and 4.83 nm/°C in the RI range of 1.35~1.40 and a temperature range of 20~60 °C, respectively. Moreover, because of using the different wavelength regions for sensing, the RI and temperature detections of the proposed SPR-based PCF sensor can be achieved independently. It is believed that the proposed SPR-based PCF RI and temperature sensor has important applications in biomedicine and in environmental science.

With phase-sensitive optical time-domain reflectometry (Φ-OTDR), an optic fiber can be used as a distributed vibration sensor to perceive the external disturbance along the fiber through the phase variation of the Rayleigh backscatter light. However, due to the inevitable interference fading phenomenon, the signal-to-noise ratio (SNR) of Rayleigh backscatter light at certain points is insufficient, thus affecting the fidelity of vibration sensing. In this paper, we propose the spectrum extraction and the rotated-vector-sum (SERVS) method to suppress the interference fading in the pulse-intensity-coding Φ-OTDR, which applies Golay complementary sequence through acousto-optic modulator (AOM). Benefited from the easier implementation, the experimental results demonstrate that the percentage of fading points can be reduced from 2.98% to 0.33% significantly and the standard deviation of differential phase is also decreased from 0.6556 rad to 0.2901 rad. Also the minimum level of averaged power spectral density (PSD) of the differential phase at whole locations along the fiber is reduced about 6 dB/Hz effectively. For the demodulated disturbance signal, no influence on the SNR is observed thus it maintains a SNR improvement of 8.6 dB compared to the traditional single pulse Φ-OTDR system, achieving a noise floor of 2.38 pϵ/√Hz.

Since the poor quality of signals and redundant features may reduce the accuracy of fault diagnosis of rotating machinery components, an ensemble targeted stacked denoising autoencoders (ETSDAE) method is proposed for machinery running under harsh environment. At first, a targeted denoising strategy is designed for ensemble models to remove noise from time-domain and frequency-domain data in the encode stage. The multidomian data makes up for the limitations of single-domain data while the denoising strategy improves the anti-noise ability of ETSDAE. On the other hand, two indexes based on mutual information are designed into cost function as a soft constraint to learn min-redundant deep features that have max-relevance to the class targets, thus it can get rid of the dependence on additional feature selection procedure. On this basis, integrated deep features are directly input to single-hidden layer feedforward neural network to realize fault diagnosis. Finally, the effectiveness of the proposed method are verified by rolling bearing test rig and industrial reciprocating pump. The results show that ETSDAE has excellent performance in fault diagnosis, especially in terms of anti-noise and feature learning.

Forward-transmission fiber-optic distributed vibration sensors have potential use in long-distance sensing and integration with optical communication networks. However, the ability to localize disturbance events with low-frequency is fairly inferior to high-frequency events, which hinders the broader application of such distributed vibration sensors. To address this problem, we propose a Phase Differentiation Endpoint Amplification (PDEA) method to optimize the sensor’s frequency response for event localization. By differentiating the original extracted phase signal, the proposed method amplifies the amplitude of the endpoints of the disturbance event. Via cross-correlation, the endpoint amplitude amplification reduces the localization errors. Experimental results demonstrate that the forward transmission sensing system using the proposed method maintains a localization accuracy within ±51 m across frequencies from 300 Hz to 10 kHz over a 122 km range. Additionally, the system’s localization capability for low-frequency disturbances occurring at the near-end is notably enhanced. The PDEA algorithm significantly improves the wide-frequency response of forward-transmission fiber-optic distributed vibration sensors. The enhanced localization ability will be beneficial when the sensors are applied in scenarios such as integrated optical sensing and communication (IOSAC).