Abstract: A multilinear domain-specific domain generalization (MDSDG) approach that utilizes information stored in multilinear indices of data domains to improve machine learning. In particular—based on limited sample size(s) in observed scenarios—an array of models is jointly trained, which advantageously are generalized to a new, unseen scenario, where only domain descriptions in the form of multilinear indices are available.

Abstract: Physimetric-based data security for coded distributed temperature sensing (DTS) in which physimetric information is extracted from a coded-DTS interrogator which is unique for each interrogator at each operating run time—and used to reconstruct a final temperature determination from DTS data. The physimetric information includes coded-DTS pulse code and coded-DTS pulse profile information as a key to permit secure sharing with authorized users. The pulse code and pulse profile information are encrypted and made available to an authorized user. The authorized user can then decrypt the pulse code and pulse profile information and subsequently use this key information (pulse profile and pulse code files) to retrieve temperature information from for example, a remote computer providing a continuous raw data feed—without being susceptible to eavesdropping.

Abstract: Aspects of the present disclosure describe systems, methods. and structures for vibration detection using phase recovered from an optical transponder with coherent detection. Advantageously, our systems, methods, and structures leverage contemporary digital coherent receiver architecture in which various adaptive DSP operations performed to recover transmitted data track optical phase. The phase is extracted at low overhead cost, allowing a digital coherent transponder to perform vibration detection/monitoring as an auxiliary function to data transmission. Demonstration of vibration detection and localization based on the extraction of optical phase from payload-carrying telecommunications signal using a coherent receiver in a bidirectional WDM transmission system is shown and described.

Abstract: An advance in the art is made according to aspects of the present disclosure directed to the detection and localization of a substantially static weight situated on aerial telecommunications fiber optic cable through the effect of phase-distributed acoustic sensing (?-DAS) and signal analysis of ambient data. In sharp contrast to the prior art, our inventive method does not require a special optical fiber arrangement or type of fiber nor is it susceptible to range limitations that plague the prior art.

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: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously extend DFOS techniques to anomaly detection using optical magnetism switches (OMC) that are integrated into the DFOS system.

Abstract: Aspects of the present disclosure describe estimating/measuring core-cladding concentricity error in optical fibers. In sharp contrast to the prior art, our inventive method is based on measuring a seemingly unrelated property of fibers called guided acoustic wave Brillouin scattering (GAWBS). As we shall show and describe, by analyzing this GAWBS property we advantageously determine what level of CCCE is exhibited by the optical fiber.

Abstract: Aspects of the present disclosure describe an unsupervised context encoder-based fiber sensing method that detects anomalous vibrations proximate to a sensor fiber that is part of a distributed fiber optic sensing system (DFOS) such that damage to the sensor fiber by activities producing and anomalous vibrations are preventable. Advantageously, our method requires only normal data streams and a machine learning based operation is utilized to analyze the sensing data and report abnormal events related to construction or other fiber-threatening activities in real-time. Our machine learning algorithm is based on waterfall image inpainting by context encoder and is self-trained in an end-to-end manner and extended every time the DFOS sensor fiber is optically connected to a new route. Accordingly, our inventive method and system it is much easier to deploy as compared to supervised methods of the prior art.

Abstract: A fiber optic sensing technology for vehicle run-off-road incident automatic detection by an indicator of sonic alert pattern (SNAP) vibration patterns. A machine learning method is employed and trained and evaluated against a variety of heterogeneous factors using controlled experiments, demonstrating applicability for future field deployment. Extracted events resulting from operation of our system may be advantageously incorporated into existing management systems for intelligent transportation and smart city applications, facilitating real-time alleviation of traffic congestion and/or providing a quick response rescue and clearance operation.

Abstract: An advance in the art is made according to aspects of the present disclosure directed to a DAS method that utilizes a differential phase to detect phase change(s) between two locations of a DAS sensing fiber to ascertain vibrational/acoustic activities/environment at intermediary fiber location(s) between the two locations. Additionally, systems, methods, and structures according to aspects of the present disclosure may employ a fiber coil comprising a segment of fiber wrapped in acoustic sensitive material (“acoustic signal collector”). The material responds to an environmental acoustic signal, which results in strain(s) applied to the fiber. Furthermore, rather than using a measured phase difference between the two ends of the fiber coil, systems, methods, and structures according to aspects of the present disclosure utilize all samples collected from one end of the fiber coil to the other end of the fiber coil (the left side of the coil to the right side of the coil)—which may be extended further.

Abstract: Distributed fiber optic sensing (DFOS) systems, methods and structures for determining the proximity of vibration sources located perpendicular to a sensor fiber that is part of the DFOS system that may potentially threaten/damage or otherwise compromise the sensor fiber itself. Systems, methods, and structures according to aspects of the present disclosure employ Artificial Intelligence (AI) methodology(ies) that use as input a fundamental physical understanding of wave propagation and attenuation in the ground along with Bayesian inference and Maximum Likelihood Estimation (MLE) techniques for estimating/determining the proximity of potentially damaging vibration sources to the optical sensor fiber.

Abstract: Aspects of the present disclosure describe systems, methods and structures for coherent distributed sensing that employs a moving average method among locations along a sensing fiber employing a user configured number of taps that involves location grouping and a group's internal phase alignment followed by an inter-group phase alignment and combining. Our method employs two steps of rotation to achieve the alignment: intra-group rotation and inter-group rotation to align the phase of all participating sensing fiber locations.

Abstract: Aspects of the present disclosure describe systems, methods. and structures directed to an integrated 3-way branching unit switch module suitable for undersea application.

Abstract: Aspects of the present disclosure describe systems, methods. and structures in which guided acoustic Brillouin (GAWBS) noise is measured using a homodyne measurement technique and demonstrated using a number of optical fibers, such fibers being commonly used in contemporary optical communications systems. The measurements are made with single spans and determined to be consistent with separate multi-span long-distance measurements. Additionally, a technique for preparing an optical fiber exhibiting superior GAWBS noise characteristics by reducing coherence length of the optical fiber by spinning the fiber at a high rate during the drawing process such that birefringence coherence length is reduced.

Abstract: Aspects of the present disclosure are directed to improved systems, methods, and structures providing coherent detection of DAS. In sharp contrast to the prior art, systems, methods, and structures according to aspects of the present disclosure advantageously reduce the beating diversity terms such that required memory and bandwidth are reduced over the art.

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: A device may receive, from a fiber sensor device, sensing data associated with a fiber optic cable, the sensing data being produced by an activity that poses a threat of damage to the fiber optic cable, and the sensing data identifying: amplitudes of vibration signals, frequencies of the vibration signals, patterns of the vibration signals, times associated with the vibration signals, and locations along the fiber optic cable associated with the vibration signals. The device may process, with a machine learning model, the sensing data to determine a threat level of the activity to the fiber optic cable, the machine learning model having been trained based on historical information regarding detected vibrations, historical information regarding sources of the detected vibrations, and historical information regarding threat levels to the fiber optic cable. The device may perform one or more actions based on the threat level to the fiber optic cable.

Abstract: Aspects of the present disclosure describe DAS/DVS DFOS systems, methods, and structures that advantageously enable/provide OTDR measurement(s).

Abstract: Aspects of the present disclosure describe systems methods and structures for avoiding saturation caused phase jump in systems that extract information from the phase of a complex sequence and exhibit an overflow or “spike” in the output of a high-pass filter. Operationally, during phase unwrapping—when an output signal exceeds a supported range—it is adjusted to be back in range by adding N·2?, to a phase where N is negative or positive integer, depending on the direction to be adjusted.

Abstract: Aspects of the present disclosure describe the localization of a utility pole by distributed fiber sensing of aerial fiber cable suspended from the utility pole.