Abstract: Systems, methods, and structures for efficiently identifying individual fibers located in a deployed cable that advantageously reduces laborious field efforts while reducing service outage time. The systems and methods locate a targeted fiber in a cable (“Cable ID”) and then identify the targeted fiber (“Fiber ID”) by detecting DFOS signal attentions—without cutting the optical fiber. Two distinct determinations may be made namely, Cable ID and Fiber ID. DFOS operation detects vibration signals occurring along a sensor fiber. As implemented, Cable ID is an interactive-machine learning-based algorithm that automatically locates cable position along a sensor fiber route. Fiber ID detects a signal attenuation by bending a group of fibers with bifurcation to pinpoint a targeted individual fiber within a fiber cable.

Abstract: Systems, methods, and structures for colorless distributed fiber optic sensing/distributed vibration sensing (DOFS/DVS) over dense wavelength division multiplexing (DWDM) telecommunications facilities that operate over a C-band wavelength range spanning from 1525 nm to 1565 nm wherein the DOFS/DVS systems exhibit suitable reconfigurability of its wavelength to match a wavelength of a desired testing channel and may advantageously provide DOFS/DVS capabilities to existing DWDM communications infrastructure as a retrofit.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously sense/monitor outdoor facilities and structures including outdoor cabinets containing fiber optic facilities in which the cabinet/fiber optic cable contained therein are configured to provide superior acoustic sensing. Further outdoor facilities and structures that are monitored include manhole structures. Superior DFOS/DAS monitoring results are obtained by employing a machine learning-based analysis method that employs a temporal relation network (TRN).

Abstract: Distributed fiber optic sensing (DFOS) systems and methods that automatically detect vibration signal patterns from waterfall data recorded by DFOS system operations in real- time and associate the detected vibration signal patterns to GPS location coordinates without human intervention or interpretation. When embodied as a computer vision-based operation according to aspects of the present disclosure, our inventive systems and method provide accurate, cost-efficient, and objective determination without relying on humans and their resulting bias' and inconsistencies.

Abstract: A procedure to solve the DFOS placement problem that uses a genetic algorithm to achieve a global optimization of sensor placement. First, our procedure according to aspects of the present disclosure defines a fitness function that counts the number of DFOS sensors used. Second, the procedure uses a valid DFOS placement assignment to model an individual in the genetic algorithm. Each individual consists of N genes, where N is the number of nodes in the given network infrastructure, e.g., N=|V|. Each gene has two genomes: (1) a list of 0s and/or 1s, in which is represent the network nodes that are equipped with DFOS sensors, and 0s represent the nodes that are not equipped with DFOS sensors; (2) a list of sensing fiber routes. An individual that has smallest number of is in their genes will be considered as the strongest individual. Thirdly, the procedure randomly generates a population of individuals.

Abstract: Aspects of the present disclosure describe a method of placement of sensors for DFOS systems, methods, and structures that advantageously employ concurrent sensing. In sharp contrast to the prior art, our inventive method—a heuristic method based on the Explore-and-Pick (EnP) algorithm, which we call a modified EnP (mEnP) method—includes two procedures. The first procedure of our mEnP method explores all possible sensing fiber routes (both linear and star-like routes) for each node in the given network. The second procedure applies a modified greedy algorithm for minimum set cover to select the minimum set of DFOS assignment to fully cover all the links in the given network.

Abstract: Aspects of the present disclosure describe DFOS systems, methods, and structures that advantageously extract road traffic from DFOS vibration patterns such that anomaly detection is possible. Sensed vibration data is represented accurately as a set of points, where each point is denoted as a tuple with elements indicating a time stamp, a location along a length of a DFOS optical sensing cable, and vibration strength detected at the location at the time. Traffic pattern detection is based on a progressive probabilistic Hough transform (PPHT) that exploits global information from an entire spatial-temporal data snapshot to assess a cause of detected vibrations.

Abstract: An optical fiber sensing system with reduced spatial resolution and noise for multiple applications and method of operating same that employs a coherent receiver configured to detect and digitize both I and Q signals in two polarizations and performs signal beating in a digital signal processor (DSP) using the polarization-diverse signals to obtain beating results for multiple polarization state pairs that effectively reduces polarization induced fading effect(s) while providing faster sensing speed(s) and more efficient filtering. Since Rayleigh signals are captured in two orthogonal polarizations, four beating products are determined at once in the DSP and all are used for fiber strain determination thereby avoiding polarization fading.

Abstract: Aspects of the present disclosure describe optical fiber sensing systems, methods and structures disclosing a distributed optical fiber sensor network constructed on a switched optical fiber telecommunications infrastructure to detect temperatures, acoustic effects, and vehicle traffic—among others—demonstrated with a number of different network topologies.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensor systems, methods, and structures that advantageously enable/provide for the proper placement/assignment of sensors in the DFOS network to provide for high reliability, fault tolerant operation that survives fiber failures.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously employ a flexible resource sharing that balances sending distance requirements and route requirements. Such flexibility is achieved by including an ultra-fast 1×N optical switch with a DFOS interrogator and N fiber optic sensor routes. Synchronous control provides for real-time configuration/reconfiguration of the DFOS system.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that employ a distributed fiber optic sensor placement procedure that advantageously provides a desirable sensor coverage over a network at minimal cost.

Abstract: Aspects of the present disclosure describe single mode fiber distributed temperature sensing (DTS) with improved noise characteristics employing superluminescent emitting diodes (SLEDs) and/or amplified spontaneous emission (ASE) light sources.

Abstract: Aspects of the present disclosure describe improved distributed acoustic sensing using dynamic range suppression of optical time domain reflectometry either by using a feedback loop comprising optical and electrical elements or using a nonlinear element in the electrical domain after coherent detection. When using a feedback loop, the amplitude of the periodic waveform of coherent OTDR can be inverted. This allows optical pre-compensation of the received optical signal before coherent detection with the goal of minimizing amplitude dynamic range. Alternatively, a nonlinear element in the electrical domain can reduce amplitude dynamic range before sampling by analog-to-digital converters (ADC).

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously provide traffic monitoring. and traffic management which improves the safety and efficiency of a roadway.

Abstract: Aspects of the present disclosure describe optical fiber sensing systems, methods and structures disclosing a distributed optical fiber sensor network constructed on a switched optical fiber telecommunications infrastructure to detect temperatures, acoustic effects, and vehicle traffic—among others—demonstrated with a number of different network topologies.

Abstract: Aspects of the present disclosure describe single mode fiber distributed temperature sensing (DTS) with improved noise characteristics employing superluminescent emitting diodes (SLEDs) and/or amplified spontaneous emission (ASE) light sources.

Abstract: Aspects of the present disclosure describe systems, methods, and structures for the machine learning based regression of complex coefficients of a linear combination of spatial modes from a multimode optical fiber.

Abstract: Aspects of the present disclosure describe optical fiber sensing systems, methods and structures disclosing a distributed fiber sensor network constructed on an existing, live network, data carrying, optical fiber telecommunications infrastructure to detect temperatures, acoustic effects, and vehicle traffic—among others. Of particular significance, sensing systems, methods, and structures according to aspects of the present disclosure may advantageously identify specific network locations relative to manholes/handholes and environmental conditions within those manholes/handholes namely, normal, flooded, frozen/iced, etc.

Abstract: Aspects of the present disclosure describe optical fiber sensing systems, methods and structures disclosing a distributed fiber sensor network constructed on an existing, live network, data carrying, optical fiber telecommunications infrastructure to detect temperatures, acoustic effects, and vehicle traffic—among others. Of particular significance, sensing systems, methods, and structures according to aspects of the present disclosure may advantageously identify specific network locations relative to manholes/handholes and environmental conditions within those manholes/handholes namely, normal, flooded, frozen/iced, etc.