This paper demonstrates high-frequency dynamic strain measurements using Fiber Bragg Grating (FBG) sensors embedded in metal parts. Using an ultrasonic additive manufacturing (UAM) process, FBGs inscribed in polyimide coated optical fibers were embedded in aluminum parts. An electromagnetic shaker was used to exert dynamic events on the embedded FBG sensors with frequencies from 1–10 kHz. The high-speed interrogation of FBG sensors was accomplished using a tunable vertical-cavity surface-emitting laser (VCSEL) and a high-speed interrogation system sampling at 120 kHz. The strain response measured by the FBG sensors was compared with real-time measurements using a laser velocimeter. Finite Element Analysis was performed to simulate responses to both static strain and high-frequency dynamic strain. Results show that strains as small as 2.5 μ can be resolved at frequencies up to 10 kHz.

We present a highly reproducible method of fabricating a tapered intrinsic Fabry-Perot interferometer (IFPI) device with 5~6-μm diameter at the taper waist. A femtosecond laser was applied to inscribe an IFPI with 3-cm cavity length in a single-mode fiber. A CO ₂ laser heated tapering process enabled by digitally controlled mirrors and a precision motorized fiber feed system was used to create a stable heating zone with the desired temperature profile for tapering the fiber IFPI cavity. The well-engineered tapering process produced tapered IFPI devices with insertion loss less than 0.3-dB at 1550-nm. A strong evanescent field exposed by the taper section was explored for refractive index sensing. Using swept optical frequency domination reflectometry, the tapered IFPI fiber sensor achieved a minimal refractive index sensing resolution 2×10 ^-5 . This paper demonstrates an integrated laser fabrication technique to produce tapered fiber optic devices for sensing applications.

This paper presents a low-cost integrated intrinsic Fabry-Perot interferometer (IFPI) sensor array demodulation algorithm based on local spectral analysis, which exploits multiple local spectra instead of the entire spectrum to achieve ultrasonic vibration measurement well beyond the sweeping period of the tunable laser source. By balancing the demodulation range and the demodulation resolution of IFPIs, this paper divides the entire spectrum produced by a distributed feedback (DFB) laser into 152 local spectra by a sliding window for IFPIs demodulation respectively, thereby implementing up to 160 kHz vibration measurement. To reduce the load on the data acquisition system and simplifies the interrogation system, this paper adopts a nonlinear tuning error compensation method based on an in-line IFPI sensor. In addition, chirp Z-transform is used in this paper to replace the traditional zero-padding-based fast Fourier transform to achieve the local fineness of demodulated optical path difference (OPD) spectrum, so as to reduce the waste of computation caused by zero-padding.

This paper studies the use of MUltiple SIgnal Classification (MUSIC) as a super-resolution algorithm to improve demodulation results for intrinsic Fabry–Perot interferometer (IFPI) sensor arrays. Through distinction between noise and signal subspaces in an observation matrix, this paper shows that a 38-fold improvement in the full width at half maximum (FWHM) estimation of IFPI optical path differences (OPD) can be achieved using this algorithm. Based on this improved method, this paper demonstrates that a tunable laser with a 1.3-nm tuning range can achieve the same sensor demodulation performance as a tunable laser with a 50-nm tuning range if a conventional Fourier transform-based algorithm is used. This paper presents a new approach to analyzing optical signals produced by multiple multiplexed interferometers with similar OPDs with potential applications for both single-mode and multiple-mode devices.

This paper presents a hermitic fiber sensor packaging technique that enables fiber sensors to be embedded in energy systems for performing multi-parameter measurements in high-temperature and strong radiation environments. A high-temperature stable Intrinsic Fabry–Perot interferometer (IFPI) array, inscribed by a femtosecond laser direct writing scheme, is used to measure both temperature and pressure induced strain changes. To address the large disparity in thermo-expansion coefficients (TECs) between silica fibers and metal parts, glass sealants with TEC between silica optical fibers and metals were used to hermetically seal optical fiber sensors inside stainless steel metal tubes. The hermetically sealed package is validated for helium leakages between 1 MPa and 10 MPa using a helium leak detector. An IFPI sensor embedded in glass sealant was used to measure pressure. The paper demonstrates an effective technique to deploy fiber sensors to perform multi-parameter measurements in a wide range of energy systems that utilize high temperatures and strong radiation environments to achieve efficient energy production.

In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.