Utility Pole Hazardous Event Localization

US2022329068A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2022329068-A1
Application numberUS-202217717112-A
CountryUS
Kind codeA1
Filing dateApr 10, 2022
Priority dateApr 12, 2021
Publication dateOct 13, 2022
Grant date

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

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Distributed fiber optic sensing (DFOS) and artificial intelligence (AI) systems and methods for performing utility pole hazardous event localization that advantageously identify a utility pole that has undergone a hazardous event such as being struck by an automobile or other detectable impact. Systems and methods according to aspects of the present disclosure employ machine learning methodologies to uniquely identify an affected utility pole from a plurality of poles. Our systems and methods collect data using DFOS techniques in telecommunication fiber optic cable and use an AI engine to analyze the data collected for the event identification. The AI engine recognizes different vibration patterns when an event happens and advantageously localizes the event to a specific pole and location on the pole with high accuracy. The AI engine enables analyses of events in real-time with greater than 90% accuracy.

First claim

Opening claim text (preview).

1 . A utility pole hazardous event localization method comprising: providing a distributed fiber optic sensing system (DFOS), said system including a length of aerial optical sensor fiber, said aerial optical sensor fiber suspended from a plurality of utility poles; and a DFOS interrogator and analyzer in optical communication with the length of optical fiber; wherein each of the plurality of utility poles suspends in addition to the aerial optical fiber additional utility wires/cables including electrical power wires and telecommunications cables; operating the DFOS system and generating a trained model in response to DFOS signals received during operation; and continuously operating the DFOS system and upon detecting an anomaly, using the trained model to determine a particular utility pole and location on the particular utility pole affected by the anomaly. 2 . The method of claim 1 further comprising determining whether the location on the affected utility pole is above or below a location on the affected pole where the optical sensor fiber is attached to that pole. 4 . The method of claim 3 further comprising storing information about the anomaly is stored in a cloud storage facility. 5 . The method of claim 4 wherein said generation of a trained model is performed using data generated in response to mechanical impacts made to the plurality of utility poles. 6 . The method of claim 6 wherein the mechanical impacts made to the plurality of utility poles are made above and below the attachment location of the optical sensor fiber to the each one of the plurality of utility poles.

Assignees

Inventors

Classifications

  • Transmission line or load transient problems, e.g. overvoltage, resonance or self-excitation of inductive loads (H02J3/01 takes precedence) · CPC title

  • using fibre optic sensors (light guides per se G02B6/00, acousto-optical devices specially adapted for gating or modulating in optical wave guides G02F1/125) · CPC title

  • Particular layout of the fiber · CPC title

  • using backscattering to detect the measured quantity · CPC title

  • H02J3/001Primary

    Arrangements for handling faults or abnormalities, e.g. emergencies or contingencies · CPC title

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What does patent US2022329068A1 cover?
Distributed fiber optic sensing (DFOS) and artificial intelligence (AI) systems and methods for performing utility pole hazardous event localization that advantageously identify a utility pole that has undergone a hazardous event such as being struck by an automobile or other detectable impact. Systems and methods according to aspects of the present disclosure employ machine learning methodolog…
Who is the assignee on this patent?
Nec Lab America Inc
What technology area does this patent fall under?
Primary CPC classification G01D5/35358. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Oct 13 2022 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 2 related publications on this page (citations in our corpus or others sharing the same primary CPC).