ROAD SURFACE CONDITIONS DETECTION BY DISTRIBUTED OPTIC FIBER SYSTEM

    公开(公告)号:WO2023091447A1

    公开(公告)日:2023-05-25

    申请号:PCT/US2022/050044

    申请日:2022-11-16

    Abstract: A fiber optic sensing cable located along a side of a paved road and runs parallel to a driving direction is monitored by distributed fiber optic sensing (DFOS) using Rayleigh backscattering generated along the length of the optical sensor fiber cable under dynamic vehicle loads. The interaction of vehicles with roadway locations exhibiting distressed pavement generates unique patterns of localized signals that are identified/distinguished from signals resulting from vehicles operating on roadway exhibiting a smooth pavement surface. Machine learning methods are employed to estimate an overall road surface quality as well as localizing pavement damage. Power spectral density estimation, principal component analysis, support vector machine (SVM) combined with principal component analysis (PCA), local binary pattern (LBP), and convolutional neural network (CNN) are applied to develop the machine learning models.

    FIBER IDENTIFICATION WITHOUT CUT POINT USING DISTRIBUTED FIBER OPTIC SENSING

    公开(公告)号:WO2023091450A1

    公开(公告)日:2023-05-25

    申请号:PCT/US2022/050049

    申请日:2022-11-16

    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.

    UNDERGROUND CABLE LOCALIZATION BY FAST TIME SERIES TEMPLATE MATCHING

    公开(公告)号:WO2023081249A1

    公开(公告)日:2023-05-11

    申请号:PCT/US2022/048763

    申请日:2022-11-03

    Abstract: A method for underground cable localization by fast time series template matching and distributed fiber optic sensing (DFOS) includes: providing the DFOS system including a length of optical sensor fiber; a DFOS interrogator in optical communication with the optical sensor fiber, said DFOS interrogator configured to generate optical pulses, introduce the generated pulses into the length of optical sensor fiber, and receive backscattered signals from the length of the optical sensor fiber; and an intelligent analyzer configured to analyze DFOS data received by the DFOS interrogator and determine from the backscattered signals, vibrational activity occurring at locations along the length of the optical sensor fiber; deploying a programmable vibration generator to a field location proximate to the length of optical sensor fiber; transmitting to the programmable vibration generator a unique vibration pattern to be generated by the vibration generator; and operating the programmable vibration generator to generate the unique vibration pattern transmitted; and operating the DFOS system and collecting / analyzing the determined vibrational activity to further determine vibrational activity indicative of the unique vibration pattern generated by the vibration generator.

    NETWORK SENSING TOPOLOGIES FOR FIBER OPTIC SENSING

    公开(公告)号:WO2021207097A1

    公开(公告)日:2021-10-14

    申请号:PCT/US2021/025817

    申请日:2021-04-05

    Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously utilize existing telecommunications facilities that serve as not only to convey telecommunications traffic - but as a sensor medium providing useful sensory information. In sharp contrast to the prior art - a DFOS system when so deployed may advantageously exploit network topologies and optical switches to provide novel sensing features including the detection of environmental events including acoustic, temperature, and vibrational events that may be indicative of societal activity including traffic and/or emergency events.

    OPTICAL FIBER SENSING FOR HIGHWAY MAINTENANCE

    公开(公告)号:WO2020006414A1

    公开(公告)日:2020-01-02

    申请号:PCT/US2019/039838

    申请日:2019-06-28

    Abstract: Aspects of the present disclosure describe systems, methods and structures employing optical fiber sensing to monitor highway/roadway/street conditions (i.e., potholes, pavement cracks, etc.) in real-time, continuously, and while the highway/roadway/street remains in operation (in-service monitoring). Systems, methods, and structures according to aspects of the present disclosure may employ machine learning (ML) algorithms including neural networks to provide and or report on highway conditions so monitored/sensed. Of further advantage, systems, methods, and structures for optical fiber sensing for highway maintenance may operate in real-time, continuously, long-term, in-service, and may employ existing telecommunications optical cables without additional deployment cost(s) or disruption of telecommunications traffic.

    VEHICLE-ASSISTED BURIED CABLE LOCALIZATION USING DISTRIBUTED FIBER OPTIC SENSING

    公开(公告)号:WO2023004084A1

    公开(公告)日:2023-01-26

    申请号:PCT/US2022/037941

    申请日:2022-07-21

    Abstract: Systems, and methods for automatically identifying an underground optical fiber cable length from DFOS systems in real time and pair it with GPS coordinates that advantageously eliminate the need for in-field inspection / work by service personnel to make such real-time distance / location determinations. As such, inefficient, error-prone and labor-intensive prior art methods are rendered obsolete. Operationally, our method disclosure involves driving vehicles including GPS to generate traffic patterns and automatically mapping traffic trajectory signals from a deployed buried fiber optic cable to locate geographic location(s) of the buried fiber optic cable. Traffic patterns are automatically recognized; slack in the fiber optic cable is accounted for; location of traffic lights and other traffic control devices/structures may be determined; and turns in the fiber optic cable may likewise be determined.

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