Tension screening technique for communication cables based on wave propagation and distributed acoustic sensing

Abstract

It is a tension screening technology for communication cables based on wave propagation and distributed acoustic sensing (DAS) that first determines the position of utility poles related to optical fiber cables using wave propagation technology and obtains the tension. Vibration data generated from mechanical impacts on utility poles is converted into an image indicating the position of the utility poles using an edge detection algorithm. Advantageously, by using the edge detection method and wave propagation analysis of the present invention to obtain the tension, the tension of the optical fiber cable can be measured quickly, reliably, and accurately.

Description

[Technical Field]

[0001] This application relates generally to distributed fiber optic sensing (DFOS) systems, methods, structures and related techniques, and more particularly to strain screening techniques for telecommunication cables based on wave propagation and distributed acoustic sensing (DAS). [Background technology]

[0002] The majority of modern fiber optic communication networks involve aerial cables suspended from utility poles. The tension experienced by installed fiber optic cables varies over time. Fluctuations in cable tension often lead to structural degradation of the structures supporting the fiber optic cables. Therefore, telecommunication service providers need to monitor the tension of aerial fiber optic cables to ensure reliable telecommunication services.

[0003] Traditional tension monitoring methods use tension meters to precisely measure the correct tension in a fiber optic cable. In operation, the tension meters are clamped to the fiber optic cable or wire rope, measure the deflection, and convert the measured deflection into a tension measurement. This traditional method requires the installation of tension meters between multiple posts of the fiber optic cable where tension needs to be measured. Such a procedure is expensive, time-consuming, and requires a significant amount of technician time. Summary of the Invention

[0004] Aspects of the present disclosure provide an advancement in the art directed to tension screening techniques for telecommunication cables based on wave propagation and distributed acoustic sensing (DAS).

[0005] In contrast to the prior art, from a first perspective, the technology of the present invention uses the communication optical fiber cable itself as the sensing medium to provide rapid tension screening of the communication optical fiber cable along its route, providing real-time tension screening / determination along the entire route of the optical fiber cable.

[0006] From another perspective, the technique of the present invention can be summarized by the following process: (1) Integrate a DFOS system with an interrogator with a target telecommunications fiber optic cable path, thereby making the entire fiber optic cable path a fiber optic sensor; (2) A field technician applies a mechanical impact to the utility pole from which the fiber optic cable is suspended. The impact has a time interval t0. A machine learning process determines the wave velocity associated with the impact; and (4) Determine the tension using wave propagation theory.

[0007] In operation, existing fiber optic cables provide vibration sensing along their entire length without the need for an external power source or a communication channel for data transfer or control. Sensing along the entire length of the fiber optic cable is performed with extremely high accuracy and sensitivity from one end of the fiber optic cable.

[0008] To determine cable tension along a cable, a wave propagation technique is employed to first determine the position of the utility pole relative to the fiber optic cable and obtain the tension. Vibration data resulting from mechanical impact on the utility pole is converted into an image that provides pole localization using an edge detection algorithm. Advantageously, by using the edge detection method and wave propagation analysis of the present invention to determine tension, fiber optic cable tension can be measured quickly, reliably, and accurately. [Brief explanation of the drawings]

[0009] [Figure 1(A)] FIG. 1(A) is a schematic diagram showing an example of a conventional non-coded DFOS system. [Figure 1(B)] FIG. 1(B) is a schematic diagram showing an example of a conventional coded DFOS system.

[0010] [Figure 2] FIG. 2 is a schematic diagram illustrating an exemplary system and method for tension screening of telecommunications cables, according to an embodiment of the present disclosure.

[0011] [Figure 3] FIG. 3 is a schematic block diagram illustrating an exemplary flow chart of a process according to an embodiment of the present disclosure.

[0012] [Figure 4] FIG. 4 is a schematic diagram illustrating static balance of a cable mass under tension, according to an embodiment of the present disclosure.

[0013] [Figure 5] FIG. 5 is a schematic force diagram illustrating exemplary forces acting on a cable element, according to an embodiment of the present disclosure.

[0014] [Figure 6] FIG. 6 is a schematic diagram illustrating exemplary features of systems and methods according to embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0015] The following merely illustrates the principles of the present disclosure, and it should thus be understood that those skilled in the art will be able to devise various arrangements which embody the principles of the present disclosure, even though not explicitly described or shown herein, and which are within the spirit and scope of the present disclosure.

[0016] Furthermore, all examples and conditional language provided herein are meant to be for educational purposes only to aid in understanding the principles of the present disclosure and concepts provided by the inventors to further the present technology, and should not be construed as being limited to the specifically listed examples and conditions.

[0017] Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Furthermore, such equivalents are intended to include both currently known equivalents and equivalents developed in the future, i.e., elements developed that perform the same function, regardless of structure.

[0018] Thus, for example, it will be appreciated by those skilled in the art that any block diagrams herein are conceptual diagrams illustrating illustrative circuitry embodying the principles of the present disclosure.

[0019] Unless otherwise specified, the drawings herein, including the figures, are not drawn to scale.

[0020] As additional background, note that a distributed fiber optic sensing system interconnects an optoelectronic integrator to an optical fiber (or cable), transforming the optical fiber into an array of sensors distributed along the fiber. In effect, the fiber becomes the sensor, and the interrogator generates / injects laser light energy into the fiber to sense / detect events along the fiber.

[0021] As those skilled in the art will understand and appreciate, DFOS technology can be utilized to continuously monitor vehicle movement, foot traffic, drilling operations, seismic activity, temperature, structural integrity, liquid and gas leaks, and many other conditions and activities. It is used worldwide to monitor power plants, communications networks, railroads, roads, bridges, borders, critical infrastructure, onshore and offshore power and pipelines, and downhole applications in oil, gas, and enhanced geothermal power generation. Distributed fiber optic sensing has the advantage of being unconstrained by line-of-sight or remote power access and can be deployed over continuous lengths of more than 30 miles, sensing / detecting at any point along its length, depending on the system configuration. As a result, the cost per sensing point over long distances is unmatched by competing, commonly used technologies.

[0022] Distributed fiber optic sensing measures changes in the "backscatter" of light that occurs within an optical sensing fiber when the sensing fiber encounters an environmental change, such as a vibration, strain, or temperature change event. As described above, the sensing fiber acts as a sensor along its entire length, providing real-time information about the physical / environmental surroundings and the integrity / security of the fiber. Furthermore, distributed fiber optic sensing data pinpoints the precise location of events and conditions occurring at or near the sensing fiber.

[0023] A schematic diagram illustrating the general layout and operation of a distributed optical fiber sensing system that advantageously includes artificial intelligence / machine learning (AI / ML) analysis is illustrated in Figure 1(A). Referring to Figure 1(A), it is observed that the optical sensing fiber is connected to an interrogator. Although not shown in detail, the interrogator may include a coded DFOS system, which may employ a coherent receiver configuration known in the art, such as that shown in Figure 1(B).

[0024] As is well known, a modern interrogator is a system that generates an input signal to an optical sensing fiber and detects and analyzes the reflected / backscattered received signal. The received signal is analyzed to generate an output that is indicative of environmental conditions occurring along the fiber. The received backscattered signal is caused by reflections within the fiber, such as Raman backscattering, Rayleigh backscattering, and Brillion backscattering.

[0025] As understood, modern DFOS systems include an interrogator that periodically generates a light pulse (or any coded signal) and launches it into an optical fiber, where it is transmitted along the fiber.

[0026] At locations along the fiber, a small portion of the signal is backscattered / reflected back to the interrogator where it is received. The backscattered / reflected signal carries information that the interrogator uses to detect, for example, changes in power level indicative of mechanical vibrations.

[0027] The received backscattered signal is converted to the electrical domain and processed by an interrogator. Based on the time of the input pulse and the time the signal is detected, the interrogator can determine from which location along the optical sensing fiber the received signal originates and sense motion at each location along the optical sensing fiber. The classification method may further be used to detect and identify events or other environmental conditions along the optical sensing fiber, including acoustic and / or vibration and / or heat.

[0028] As described above, the system and method of the present disclosure employ distributed fiber optic sensing (DFOS) / distributed acoustics (DAS) / distributed vibration sensing (DVS) to collect vibration data from an optical fiber sensor cable supported at least in part by a utility pole. Wave propagation and edge detection techniques are utilized to obtain the tension of the optical fiber cable. Advantageously, existing optical fiber communications carrying live traffic may also serve as DFOS sensors along their entire length without requiring additional power or communication channels. Vibration behavior along the entire length of the optical fiber sensor cable can be monitored from one end. As will be described in more detail, the method of the present invention employs wave propagation techniques to obtain the tension of the optical fiber sensor cable. To determine the wave velocity, our method first determines the location of the utility pole along the optical fiber sensor cable from which the cable is suspended. Vibration data resulting from a mechanical impact applied to the utility pole is detected / received by the DFOS system and converted into an image for locating the utility pole using edge detection techniques. The tension acting on the optical fiber sensor cable is then determined.

[0029] FIG. 2 is a schematic diagram illustrating an exemplary system and method for tension screening of telecommunication cables according to an embodiment of the present disclosure, showing the overall structure according to the present disclosure.

[0030] As shown, a series of utility poles are shown suspending telecommunications cables, which become fiber optic sensors with the addition of a DOFS / DAS system including an interrogator and analyzer, as previously described. As shown, the DAS provides data collection, which is subsequently analyzed to determine pole location and wave velocity. Such determinations are used, through visualization operations, to determine tension along the fiber optic sensor cable. When used in unison, the system of the present invention provides tension screening. As shown, the tension screening system of the present invention includes data collection operations, data processing operations, and data reporting operations.

[0031] Consider a scenario in which a technician applies five mechanical shocks to a utility pole, from which a fiber optic sensor cable is suspended, at time intervals t0 (t0>5s). These mechanical shocks cause the utility pole to vibrate.

[0032] The vibrating utility pole induces vibrations in the fiber optic sensor cable, which are detected by the DAS data collection operation. As is well known, DAS vibration sensing can detect / collect mechanical vibrations in the fiber optic sensor cable up to a range of approximately 100 km with a resolution of approximately 50 cm. Advantageously, such mechanical sensing can be provided by existing fiber optic communication cables that are already deployed or that carry live communication traffic.

[0033] The received raw vibration signals are pre-processed to identify the position of the pillar and obtain the wave velocity. Such signals are typically depicted as waterfall images, which are then converted to grayscale.

[0034] FIG. 3 is a schematic block diagram illustrating an exemplary flow chart of a process according to an embodiment of the present disclosure.

[0035] During visualization, the tension in each section of the fiber optic sensor cable along the path is shown. The derivation of the tension acting on the fiber optic sensor cable is as follows:

[0036] Consider a mass component Δx from a cable of length l. The mass component is in static equilibrium, with tension forces F acting on both sides of the mass component. T are equal in magnitude and opposite in direction.

[0037] The tension F in the string acting in the positive and negative x directions T is approximately constant and independent of position and time. Because the x-components of the tension cancel, the resultant force is equal to the sum of the y-components of the forces, as shown in Figure 4, which is a schematic diagram illustrating static balance of a cable mass under tension according to an embodiment of the present disclosure. With continued reference to this figure, we can see that:

number

number

[0038] The resultant force for the small mass component can be written as

number

[0039] Using Newton's second law, the resultant force is equal to mass times acceleration.

number

[0040] FIG. 5 is a schematic force diagram illustrating exemplary forces acting on a cable element, according to an embodiment of the present disclosure.

[0041] F TDivide by Δx and take the limit as Δx approaches zero.

number

[0042] Recall that the linear wave equation is:

number

[0043] Therefore, the result is as follows:

number

[0044] That is, the tension acting on the cable is:

number

[0045] Data Collection. The DAS is connected to a path of interest and records hammer strike data for each pole. The raw vibration data recorded from the hammer strikes is displayed as a waterfall image. Such a waterfall image resulting from the hammer strikes on a utility pole generally exhibits a "V" shape. The location in the image corresponding to the tip of the "V" is the location of that utility pole relative to the fiber optic sensor cable. As one skilled in the art will understand and appreciate, determining such distances differs from, for example, GPS location information, which is unrelated to the fiber optic sensor cable. (Applying edge detection algorithm to identify pillar location)

[0046] To indicate the edges of the waterfall image, Canny edge detection is performed. The Canny edge detection algorithm includes the following operation processes:

[0047] (1) Grayscale conversion: Convert a color image to grayscale.

[0048] (2) Noise removal. Apply Gaussian blurring with image convolution techniques to smooth grayscale images and reduce noise. The kernel size is determined by the expected blurring effect. The following formula shows the kernel of a Gaussian filter of size (2k+1) × (2k+1):

number

[0049] (3) Gradient calculation. In a grayscale image, an edge corresponds to a change in pixel intensity. By calculating the gradient of the image using an edge detection operator, the strength and direction of the edge can be detected.

[0050] (4) Non-Maximum Suppression: Non-maximum suppression is applied to the gradient magnitude matrix to find the pixel with the maximum value at the edge.

[0051] (5) Two thresholds: The two thresholds identify three types of pixels: high intensity pixels that contribute to the final edge, low intensity pixels, and other pixels.

[0052] (6) Edge tracking with hysteresis: Based on the result of thresholding, hysteresis can convert a low intensity pixel into a high intensity pixel if at least one of the pixels surrounding the processed pixel is a high intensity pixel. (Wave velocity and tension calculation)

[0053] Once the edges of the "V" shape are determined, the wave velocity can be calculated from the processed waterfall image.

number

[0054] FIG. 6 is a schematic diagram illustrating exemplary features of systems and methods according to embodiments of the present disclosure.

[0055] While the present disclosure has been illustrated herein using certain specific examples, those skilled in the art will recognize that the present teachings are not limited thereto. Accordingly, the present disclosure should be limited only by the scope of the claims appended hereto.

Claims

1. 1. A method for tension screening of telecommunication cables using wave propagation and distributed fiber optic sensing / distributed acoustic sensing (DFOS / DAS), comprising: an optical sensor fiber at least a portion of which is suspended from a plurality of utility poles; an optical interrogator in optical communication with the optical sensor fiber configured to generate optical pulses, input the generated optical pulses into the optical sensor fiber, and receive backscattered signals from the optical sensor fiber; an analyzer configured to collect and analyze the backscattered signals, generate a waterfall image to identify the location of the utility pole, determine a wave velocity of vibrations propagating through the optical sensor fiber, and determine tension in the optical sensor fiber; the distributed fiber optic sensing / distributed acoustic sensing (DFOS / DAS) system, Operate the DFOS / DAS while applying mechanical impacts to a plurality of the utility poles; generating a color waterfall image as the waterfall image from the backscattered signals resulting from the mechanical shock; determining a location along the optical sensor fiber of the pole that received the mechanical shock; determining the wave velocity of vibrations propagating through the optical sensor fiber due to the mechanical shock; determining tension in the optical sensor fiber.

2. The method of claim 1 , further comprising applying a Canny edge detection operation to the color waterfall image generated from the backscattered signal resulting from the mechanical shock.

3. The method of claim 2 , further comprising converting the color waterfall image to a grayscale image.

4. The method of claim 3 , further comprising applying a Gaussian blur with image convolution to smooth the grayscale image.

5. 5. The method of claim 4, further comprising determining the wave velocity of vibrations propagating in the optical sensor fiber from the smoothed grayscale image, and determining tension in the optical sensor fiber from the determined wave velocity.

Images