Optical Fiber Technology最新文献

With the increasing integration of RDTS technology into disaster monitoring systems, such as pipeline leak detection and fire surveillance, promptly and precisely identifying small-scale anomaly temperature zones characterized by short lengths and low temperature variations within RDTS data is crucial for effective early warning systems. Current anomaly detection algorithms for RDTS, including PCA and CNN-based approaches, are typically designed to identify large-scale anomaly temperature zones, which exceed spatial resolution and exhibit temperature values significantly above room temperature. To address this gap, we have introduced an innovative RDTS anomaly detection model that incorporates global and local feature extraction modules, a multi-head cross-attention fusion module, a self-attention module, and an AR module. Additionally, we developed a label generation method based on K-Means clustering that adaptively generates labels using anomaly scores. We collected four distinct types of RDTS data with varying temperature zone distributions and conducted performance evaluation experiments on our model. On test dataset, our proposed model achieved a peak F1 score of 0.772, which improved to 0.832 after employing the K-Means clustering-based label generation method. These findings demonstrate that our model possesses superior capability in detecting small-scale abnormal temperature zones in RDTS data. Moreover, the proposed K-Means clustering approach for data label generation significantly enhances the model’s detection performance. The refined model consistently performs anomaly detection tasks on RDTS data with temperature zone lengths equivalent to or greater than the sampling interval (40 cm) and holds potential for widespread application in RDTS-based disaster monitoring scenarios.

ZrGeTe₄ as a layered semiconductor material with good stability and optoelectronic properties, and excellent saturable absorption characteristics, but its application in fiber lasers is still insufficient. In order to explore its application in fiber lasers, we prepared ZrGeTe₄-PVA thin film by liquid phase exfoliation and performed a series of characterizations. A modulation depth of 13.15 %, a non-saturated loss of 6.4 %, and a saturation intensity of 5.5 MW/cm² were obtained. Then used the ZrGeTe₄-PVA thin film as the saturable absorber (SA) in an Er-doped fiber laser (EDFL), the large-energy operation could be realized. In the case of a cavity length of 234 m, when the pump power was increased to 1229 mW, a maximum single pulse energy of about 32.72 nJ was achieved, with a repetition frequency of 859 kHz. To the best of our knowledge, this is the highest single-pulse energy achieved in an EDFL based on ZrGeTe₄-SA. This experiment shows that the ZrGeTe₄ is a promising two-dimensional (2D) material with good nonlinear absorption properties, proving that it is a promising pulse modulation of SA and laying a foundation for its subsequent study in fiber lasers.

This paper investigates the design and properties of the conventional all-solid silica based flat dispersion specialty optical fiber. The design utilizes depressed-clad type of refractive index profile which allows for precise control of the optical fiber modal properties, particularly the chromatic dispersion. Specifically designing the dopants concentrations and depressed clad to core diameter ratio allows to obtain optical fibers with flat chromatic dispersion ranging from anomalous to normal dispersion regime. The regime and the values of chromatic dispersion in optical fibers is obtained through the change of the core diameter with the refractive index profile being the same in all optical fibers. The influence of the dopant choice on the mechanical and optical properties is shown using finite element method (FEM) studies. The study demonstrates that fluorine is a better candidate than boron for optical fiber designs that require precise chromatic dispersion characteristics. Six optical fibers were manufactured with the same refractive index profile differing with core radius. This allowed to obtain optical fibers that have chromatic dispersion in anomalous region (17.82 ps/(nm∙km) at 1.96 µm) for the fiber DCFDF1 and normal region (−115.14 ps/(nm∙km) at 1.57 µm) for the fiber DCFDF6.

We present a novel vector bending sensor that enables simultaneous measurement of the bending response in six outer cores of a seven-core fiber (SCF) without the need for fan-in/fan-out configurations. Utilizing femtosecond laser technology, we inscribe seven Fiber Bragg Gratings (FBGs) with distinct wavelengths across the SCF cores. The sensor’s tapering process, tailored for the bending sensing scenario, effectively combines the reflection peaks of the FBGs into one detection channel, thereby substantially improving the measurement efficiency. Our experimental results demonstrate a strong directional dependence of the bending response, with a maximum sensitivity of 127 pm/m⁻¹. The bending angle and curvature magnitude are reconstructed by analyzing the wavelength shifts of any two non-diagonal outer cores, offering a versatile solution for real-time monitoring applications. This sensor design, by eliminating the need for additional fan-in/fan-out devices, simplifies the system architecture and reduces both measurement time and sensor size, making it highly suitable for applications in precision manufacturing, environmental monitoring, and robotics.

The Total Variation Deconvolution (TVD) algorithm plays an important role in signal reconstruction, however, when it is used to improve the spatial resolution of Raman Distributed Temperature Sensor (RDTS), there are certain challenges in parameter settings. This paper proposes to use Fully-Connected Neural Network to identify the length of small-scale thermal regions(SSTR), and based on the recognition results to set the TVD parameters automatically. We constructed training sets based on the periodic changes of SSTR signals in RDTS (which we call Thermal Region Response Modes, TRRM), to verify performance, we conducted comparative experiments between models obtained from a training set containing 100 types of TRRMs and 25 types of TRRMs, the Macro-F1 value of the former one is 0.2749 higher, reaching 0.9087, performed well in SSTR length recognition tasks. the traditional TVD assisted by this model can increase the spatial resolution of RDTS from 1.6 m to 0.4 m without manual intervention, which complements the lack of automation in applications of TVD and has practical value.

This paper investigates the impact of environmental changes on silver nanoparticles (AgNp) immobilized sensor probe within strong and weak plasmonic coupling regimes. To monitor these interaction regimes, evanescent wave absorption based on fiber optic and attenuated total reflection techniques have been employed. In the weak coupling regime, variations in refractive index (RI) primarily affect intensity rather than wavelength. Conversely, in the strong coupling regime, intensity decreases, while wavelength sensitivity increases with changes in RI. Our findings qualitatively agree with a theoretical framework based on the discrete dipole approximation (DDA) for two-particle interacting systems, providing valuable insights for optimizing plasmonic interactions to enhance sensitivity. This information will aid the scientific and industrial community in understanding the plasmonic interaction region for maximizing sensitivity of Localized surface plasmon resonance (LSPR) based photonic devices.