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.

    ROBOTIC NAVIGATION AND TRANSPORT OF OBJECTS
    3.
    发明申请

    公开(公告)号:WO2023069567A1

    公开(公告)日:2023-04-27

    申请号:PCT/US2022/047200

    申请日:2022-10-20

    Abstract: Navigational systems and methods include building a topological graph of an environment using nodes that represent locations in the space and associated directions, with frontiers associated with particular nodes and directions within the topological graph. An action is determined using a policy trained with an action reward function that weighs exploration to find new objects and moving objects to a goal. An agent navigates within the environment in accordance with the determined action.

    LEARNING ORDINAL REPRESENTATIONS FOR DEEP REINFORCEMENT LEARNING BASED OBJECT LOCALIZATION

    公开(公告)号:WO2022217122A1

    公开(公告)日:2022-10-13

    申请号:PCT/US2022/024118

    申请日:2022-04-08

    Abstract: A reinforcement learning based approach to the problem of query object localization, where an agent is trained to localize objects of interest specified by a small exemplary set. We learn a transferable reward signal formulated using the exemplary set by ordinal metric learning. It enables test-time policy adaptation to new environments where the reward signals are not readily available, and thus outperforms fine-tuning approaches that are limited to annotated images. In addition, the transferable reward allows repurposing of the trained agent for new tasks, such as annotation refinement, or selective localization from multiple common objects across a set of images. Experiments on corrupted MNIST dataset and CU-Birds dataset demonstrate the effectiveness of our approach.

    HIGH DYNAMIC RANGE DISTRIBUTED TEMPERATURE SENSING (DTS) USING PHOTON COUNTING DETECTION

    公开(公告)号:WO2021211307A1

    公开(公告)日:2021-10-21

    申请号:PCT/US2021/025476

    申请日:2021-04-01

    Abstract: Aspects of the present disclosure describe distributed fiber optic sensing systems (DFOSa), methods, and structures for distributed temperature sensing (DTS) that 1) employs a GmAPD instead of a traditional LmAPD detector which advantageously produces a 10~20 dB gain improvement of SNR for a far-end weak signal, thereby improving long range detectability; 2) employs an inventive gating scheme that advantageously and surprisingly overcomes the dead time problem for GmAPD working in SPC mode that plagues Geiger mode operation; and 3) third, employs an inventive post-processing technique that advantageously allows our methods to correct any dark noise caused signal distortion.

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