Over the past few decades, optical fibers have been widely deployed to implement various applications in high-speed long-distance telecommunication, optical imaging, ultrafast lasers, and optical sensors. Distributed optical fiber sensors characterized by spatially resolved measurements along a single continuous strand of optical fiber have undergone significant improvements in underlying technologies and application scenarios, representing the highest state of the art in optical sensing. This work is focused on a review of three types of distributed optical fiber sensors which are based on Rayleigh, Brillouin, and Raman scattering, and use various demodulation schemes, including optical time-domain reflectometry, optical frequency-domain reflectometry, and related schemes. Recent developments of various distributed optical fiber sensors to provide simultaneous measurements of multiple parameters are analyzed based on their sensing performance, revealing an inherent trade-off between performance parameters such as sensing range, spatial resolution, and sensing resolution. This review highlights the latest progress in distributed optical fiber sensors with an emphasis on energy applications such as energy infrastructure monitoring, power generation system monitoring, oil and gas pipeline monitoring, and geothermal process monitoring. This review aims to clarify challenges and limitations of distributed optical fiber sensors with the goal of providing a pathway to push the limits in distributed optical fiber sensing for practical applications.

Over the last three decades, fiber optic sensors (FOS) have gained a lot of attention for their wide range of monitoring applications across many industries, including aerospace, defense, security, civil engineering, and energy. FOS technologies hold great promise to form the backbone for next‐generation intelligent sensing platforms that offer long‐distance, high‐accuracy, distributed measurement capabilities and multiparametric monitoring with resilience to harsh environmental conditions. The major limitations posed by FOS are 1) cross‐sensitivity, 2) enormous volume and large data generation, 3) low data processing speed, 4) degradation of signal‐to‐noise ratio over the fiber length, and 5) overall cost of sensor and interrogator systems. These challenges can be overcome by building advanced data analytics engines enabled by recent breakthroughs in machine learning (ML) and artificial intelligence (AI). This article presents a comprehensive review of recent studies that integrate ML and AI algorithms with FOS technologies. This review also highlights several FOS technology development directions that promise a significant impact on widespread use for several industrial applications, with an emphasis on energy systems monitoring. A perspective on future directions for further research development is also provided.

Modern high-temperature processes such as fossil energy production, nuclear reactors, and chemical reactors lack robust, distributed sensing systems to map temperatures in these high-value harsh-environment systems. Regular silica-fiber-based distributed temperature sensing (DTS) systems usually only operate at temperatures below about 800 °C. In this paper, we present the design, implementation, and testing of a distributed ultra-high temperature sensing system using Raman scattering intensity, which operates from room temperature to above 1400 °C. Consideration is given to the impacts of thermal radiation, fluorescence, and the multimode nature of unclad single-crystal fiber to optimize the system. Results from picosecond and sub-nanosecond lasers were compared. Measurements were taken with a ~2 m sapphire optical fiber; which represents the longest commercially available length. A spatial resolution of 12.4 cm and position standard deviation of 0.28 mm were achieved up to the maximum testing temperature of 1400 °C, which is a new record for distributed temperature sensing systems.

One of the major challenges for metal-powder-based additive manufacturing is measuring and mitigating residual strain induced during the manufacturing processes. This paper reports distributed fiber optic sensors embedded in Inconel alloy components as experimental means to validate numerical models of additive manufacturing process. Electroplating was used to deposit a metal protective jacket onto standard telecom single-mode fibers for strain measurements, Fiber sensors were embedded in an Inconel alloy substrate using the Laser Engineered Net Shaping (LENS) process. Using a Rayleigh-scattering optical frequency domain reflectometer (OFDR), temperature changes and residual strain in the metal substrate were monitored with 5 mm spatial resolution during the LENS process. Using finite element analysis, temperature and strain profiles induced by the LENS deposition processes were also numerically studied. Discrepancies between the simulated temperature and strain profiles and those measured directly were less than 10%. Results presented in this paper demonstrates a digital twin approach to fuse modeling results with distributed fiber sensor measurement data to study additive manufacturing process toward design and fabrication process optimization.

To achieve very low $NOx$ emission levels, lean-premixed gas turbine combustors have been commercially implemented that operate near the fuel-lean flame extinction limit. Near the lean limit, however, flashback, lean blow off, and combustion dynamics have appeared as problems during operation. To help address these operational problems, a combustion control and diagnostics sensor (CCADS) for gas turbine combustors is being developed. CCADS uses the electrical properties of the flame to detect key events and monitor critical operating parameters within the combustor. Previous development efforts have shown the capability of CCADS to monitor flashback and equivalence ratio. Recent work has focused on detecting and measuring combustion instabilities. A highly instrumented atmospheric combustor has been used to measure the pressure oscillations in the combustor, the $OH$ emission, and the flame ion field at the premix injector outlet and along the walls of the combustor. This instrumentation allows examination of the downstream extent of the combustion field using both the $OH$ emission and the corresponding electron and ion distribution near the walls of the combustor. In most cases, the strongest pressure oscillation dominates the frequency behavior of the $OH$ emission and the flame ion signals. Using this highly instrumented combustor, tests were run over a matrix of equivalence ratios from 0.6 to 0.8, with an inlet reference velocity of $25m∕s$ $(82ft∕s)$. The acoustics of the fuel system for the combustor were tuned using an active-passive technique with an adjustable quarter-wave resonator. Although several statistics were investigated for correlation with the dynamic pressure in the combustor, the best correlation was found with the standard deviation of the guard current. The data show a monotonic relationship between the standard deviation of the guard current (the current through the flame at the premix injector outlet) and the standard deviation of the chamber pressure. Therefore, the relationship between the standard deviation of the guard current and the standard deviation of the pressure is the most promising for monitoring the dynamic pressure of the combustor using the flame ionization signal. This addition to the capabilities of CCADS would allow for dynamic pressure monitoring on commercial gas turbines without a pressure transducer.

Concerns about climate change have encouraged significant interest in concepts for ultralow or “zero”-emissions power generation systems. In a concept proposed by Clean Energy Systems, Inc., nitrogen is removed from the combustion air and replaced with steam diluent. In this way, formation of nitrogen oxides is prevented, and the exhaust stream can be separated into concentrated $CO2$ and water streams. The concentrated $CO2$ stream could then serve as input to a $CO2$ sequestration process. In this study, experimental data are reported from a full-scale combustion test using steam as the diluent in oxy-fuel combustion. This combustor represents the “reheat” combustion system in a steam cycle that uses a high and low-pressure steam expansion. The reheat combustor serves to raise the temperature of the low-pressure steam turbine inlet, similar to the reheat stage of a conventional steam power cycle. Unlike a conventional steam cycle, the reheat enthalpy is actually generated by oxy-fuel combustion in the steam flow. This paper reports on the unique design aspects of this combustor, as well as initial emissions and operating performance.