UTILITY POLE LOCALIZATION BY DISTRIBUTED FIBER SENSING OF AERIAL FIBER CABLE
20220120925 · 2022-04-21
Assignee
Inventors
- Yue Tian (Princeton, NJ, US)
- Shaobo HAN (Princeton, NJ, US)
- Sarper OZHARAR (Princeton, NJ, US)
- Yangmin DING (East Brunswick, NJ, US)
- You LU (Blacksburg, VA, US)
Cpc classification
G01D5/35361
PHYSICS
International classification
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.
Claims
1. A method for determining the location of a utility pole, said method comprising: providing a distributed fiber optic sensing system (DFOS), said system including a length of aerial optical fiber, said aerial optical fiber suspended from the utility pole; and a DFOS interrogator and analyzer in optical communication with the length of optical fiber; said method comprising: operating the DFOS system; providing a mechanical impact on the utility pole; determining, by the DFOS, that the mechanical impact occurred by detecting signals produced by mechanical vibrations induced in the aerial optical fiber from the mechanical impact; performing a spatial and temporal analysis on the detected signals; determining an earliest vibration from the analysis; and outputting one or more indicia of the location of the utility pole from the determined earliest vibration.
2. The method of claim 1 wherein the detected signals are indicative of both the location and time of the mechanical vibrations.
3. The method of claim 2 further comprising plotting the detected signals according to location and time such that the resulting plot exhibits a “V” shape.
4. The method of claim 3 wherein a point located at the vertex of the “V” represents the earliest vibration time and its position (distance) from the interrogator.
5. The method of claim 4 wherein the detected signals represent distributed acoustic sensing (DAS)/distributed vibration sensing (DVS) signals.
6. The method of claim 4 wherein the DFOS analyzer includes a deep learning neural network comprising a residual neural network.
Description
BRIEF DESCRIPTION OF THE DRAWING
[0008] A more complete understanding of the present disclosure may be realized by reference to the accompanying drawing in which:
[0009]
[0010]
[0011]
[0012]
[0013] The illustrative embodiments are described more fully by the Figures and detailed description. Embodiments according to this disclosure may, however, be embodied in various forms and are not limited to specific or illustrative embodiments described in the drawing and detailed description.
DESCRIPTION
[0014] The following merely illustrates the principles of the disclosure. It will thus be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the disclosure and are included within its spirit and scope.
[0015] Furthermore, all examples and conditional language recited herein are intended to be only for pedagogical purposes to aid the reader in understanding the principles of the disclosure and the concepts contributed by the inventor(s) to furthering the art and are to be construed as being without limitation to such specifically recited examples and conditions.
[0016] Moreover, all statements herein reciting principles, aspects, and embodiments of the disclosure, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure.
[0017] Thus, for example, it will be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative circuitry embodying the principles of the disclosure.
[0018] Unless otherwise explicitly specified herein, the FIGs comprising the drawing are not drawn to scale.
[0019] By way of some additional background—and with reference to
[0020] As will be appreciated, a contemporary DFOS system includes an interrogator—and accompanying analysis structure/functions—that periodically generates optical pulses (or any coded signal) and injects them into an optical fiber. The injected optical pulse signal is conveyed along the optical fiber.
[0021] At locations along the length of the fiber, a small portion of signal is reflected and conveyed back to the interrogator. The reflected signal carries information the interrogator uses to detect, such as a power level change that indicates—for example—a mechanical vibration.
[0022] The reflected signal is converted to electrical domain and processed inside the interrogator. Based on the pulse injection time and the time signal is detected, the interrogator determines at which location along the fiber the signal is coming from, thus able to sense the activity of each location along the fiber. As we shall show further—and according to aspects of the present disclosure—the interrogator may be in communication with further computing/data/storage resources including neural networks that may advantageously provide further detection/analysis capability to an overall DOFS system.
[0023] As we have noted previously, our inventive method—and systems—according to aspects of the present disclosure advantageously localize a location of a utility supporting an optical fiber cable through the effect of DAS and/or DVS technology further involving an instant mechanical impact on a pole and an inventive signal processing method.
[0024]
[0025] According to aspects of the present disclosure, while the DAS/DVS interrogator is continuously interrogating the optical fiber cable, an instant mechanical impact—such as a hammer knock/impact—is made to one of the poles (target pole) that is suspending an aerial portion of the optical fiber cable. As those skilled in the art will understand and appreciate, while the DAS/DVS operation involves an optical fiber interrogation, we use the term optical fiber cable which may include multiple fibers, high tensile strength materials, and weatherproof cladding, or other elements. Accordingly, such operations described according to the present disclosure may employ the interrogation of a single optical fiber that is included as part of an optical fiber cable.
[0026] Continuing with our discussion of
[0027] As a result of the impact, mechanical vibrations are created in the optical fiber cable, which are subsequently detected, captured, recorded as a DAS/DVS signal by the continuously operating interrogator system. The data so recorded is further analyzed and processed employing an edge detection and deep learning methodology to determine an earliest vibration resulting from the instant mechanical impact. Advantageously, our signal processing method and techniques automate the determining process and achieve a fast, cost-effective, and objective determination without human intervention or expertise. Of further advantage, a single DAS/DVS interrogator may determine the location of all poles along an optical fiber route by this procedure.
[0028] As illustratively shown in the figure, the location of the earliest vibration involves an analysis if the signal data in which an edge is first detected. At that edge, a further analysis takes place in an attempt to locate a “v” shape or localized minima. If no such “v” shape is detected, a deep learning network (i.e., ResNet) may be employed to obtain a vertex of a “v” shape. From that vertex, the location of the pole to which the impact was applied is made.
[0029]
[0030] To an existing fiber optic cable suspended at least in part by utility poles, optically/mechanically connect a DAS/DVS interrogator to one end of the fiber optic cable and detect DAS/DVS signals resulting from mechanical vibrations experienced by the cable and record them as DAS/DVS signals.
[0031] Next, an instant mechanical impact, such as hammer knock, is applied onto a target pole at any position or direction as shown illustratively in
[0032] The mechanical impact event is captured by DAS/DVS interrogator and recorded as DAS/DVS signal.
[0033]
[0034] An exemplary DAS/DVS signal of a hammer knock on a pole is visualized as in
[0035] To automate the search of the bottom vertex by computer, a novel signal processing method is applied on the DAS/DVS signal as indicated in
[0036] Firstly, the DAS/DVS signal is processed by an edge detection method, for example a Canny edge detection. If a “V” shape signal is successfully detected from the vibration DAS/DVS signal by the edge detection method, the bottom vertex of the “V” shape can be determined (local minimum). If the edge detection method fails, a pre-trained deep learning method, e.g. ResNet, is employed to locate the vertex of a “V” shape in DAS/DVS signal. Since the vertex of the “V” shape is the earliest vibration, its location along the fiber cable is the target pole's location. Thus the target pole is successfully localized.
[0037] At this point, while we have presented this disclosure using some specific examples, those skilled in the art will recognize that our teachings are not so limited. Accordingly, this disclosure should be only limited by the scope of the claims attached hereto.