Automatic Fiber Loss Detection Using Coherent OTDR

Abstract

In optical fiber loss detection using coherent optical time division reflectometry (C-OTDR), optical fiber loss detection is performed using only C-OTDR while maintaining the vibration / acoustic signal detection function and the endpoint detection function, and large loss events are automatically identified and located without manual inspection. The method of the present invention bypasses the high-pass filtering stage when calculating the intensity change of COTDR and uses the power profile for analysis. Further, the method of the present invention minimizes the noise in the power profile data of the fiber section. Advantageously, by monitoring the change in the noise-removed power profile, fiber loss events can be automatically detected and located.

Description

Technical Field

[0001] This application generally relates to optical fiber communication test and measurement systems and methods. More specifically, this application relates to optical fiber loss detection using coherent optical time domain reflectometry (C-OTDR).

Background Art

[0002] Optical time domain reflectometry is a technique widely used to test the integrity of optical fibers used in optical fiber communication facilities. OTDR can measure the static state of the fiber, such as the fiber end point, high loss points, and attenuation profiles. OTDR can also monitor changes in the state of the fiber, such as changes due to loss changes or fiber cuts. Considering its importance, the improvement of OTDR technology is a welcome thing for the technology.

Summary of the Invention

[0003] According to aspects of the present disclosure related to optical fiber loss detection using coherent optical time domain reflectometry (C-OTDR), progress in the art is achieved.

[0004] From one aspect, the systems and methods of the present invention according to aspects of the present disclosure perform fiber loss detection using only C-OTDR while maintaining the vibration / acoustic signal sensing function and endpoint detection function, and automatically identify and locate any large loss event without manual inspection. In the method of the present invention, the high-pass filtering stage is bypassed when calculating the intensity change of C-OTDR, and the power profile is used for analysis. Further, the method of the present invention minimizes the noise in the power profile data of the fiber section. Advantageously, by monitoring the change in the noise-removed power profile, fiber loss events can be automatically detected and located.

[0005] In contrast to the prior art, the systems and methods according to aspects of the present disclosure: 1) use a DSP approach to generate a power profile along a sensing range, 2) remove noise from the power profile data, 3) monitor the fluctuations of the noise-removed power profile, calculate the event location using noise-removal parameters when loss fluctuations are observed, and 4) continuously monitor fiber loss events using this approach.

Brief Description of the Drawings

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Mode for Carrying Out the Invention

[0015] The following merely illustrates the principles of the present disclosure. Accordingly, it will be understood by those skilled in the art that although not explicitly described or illustrated herein, various configurations that embody the principles of the present disclosure and are within its spirit and scope can be devised.

[0016] Furthermore, all examples and conditional terms described herein are intended solely for the educational purpose of assisting the reader in understanding the concepts contributed by the inventors to facilitate the principles and techniques of the present disclosure, and should not be construed as being limited to such specifically recited examples and conditions.

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

[0018] Thus, for example, it will be understood by those skilled in the art that any block diagram in this specification represents a conceptual diagram of an exemplary circuit that implements the principles of the present disclosure.

[0019] Unless otherwise specified in this specification, the figures constituting the drawings are not drawn to scale.

[0020] As some additional background, note that an OTDR (Optical Time Domain Reflectometer) is a common technique used in optical fiber systems to test the integrity of optical fibers. An OTDR can measure static states of a fiber, such as the fiber's endpoints, high-loss points, and attenuation profiles. An OTDR can also monitor changes in the state of the fiber, such as fiber cuts or changes in losses.

[0021] FIG. 1 is a schematic diagram showing an exemplary OTDR arrangement according to an aspect of the present disclosure.

[0022] OTDR is based on Rayleigh backscattering and uses reflectance measurement techniques to monitor the entire fiber with fine spatial resolution. Since the light sources (such as wide-linewidth lasers and LEDs) used in conventional OTDRs are inherently non-coherent, conventional OTDRs are not affected by vibrations in the fiber.

[0023] It is worth noting that there is another type of device based on Rayleigh backscattering. However, since this uses a narrow-linewidth laser with a very long coherence length (tens to hundreds of kilometers, or more), it is sensitive to microfiber elongation and changes in the microrefractive index caused by vibrations, and can detect vibrations along the fiber from low-frequency mechanical movements to high-frequency acoustic and ultrasonic signals. This type of sensor is commonly referred to as a Distributed Vibration Sensor (DVS) or a Distributed Acoustic Sensor (DAS) based on its function. Based on its operating principle, it is also called a Coherent OTDR (C-OTDR) or a Phase-Sensitive OTDR (φ-OTDR). In the remainder of this document, the terms C-OTDR, φ-OTDR, DVS, and DAS are used interchangeably, regardless of whether the emphasis is on the principle or the function.

[0024] DAS / DVS is a type of distributed fiber optic sensor (DFOS) that can sense various physical phenomena (such as temperature, vibration, and strain) with fine spatial resolution over long distances (tens or hundreds of kilometers) of optical fiber. Each DFOS system sensor fiber functions as substantially thousands of sensors along the sensor fiber. Therefore, it has many useful applications, such as traffic monitoring along highways, temperature monitoring of power lines, earthquake monitoring, health monitoring of civil infrastructure, and border intrusion detection.

[0025] C-OTDR can detect vibration signals and acoustic signals with high sensitivity, but it is not effective for measuring the fiber break position or the fiber end point even in the analysis based on relative phase change or optical signal intensity change. By bypassing the high-pass filtering stage when calculating the intensity change and processing the data, the fiber end point can be automatically identified. However, in this method, the change in fiber loss, which is an important function of conventional OTDR, cannot be effectively monitored by C-OTDR.

[0026] In conventional OTDR, the optical attenuation profile along the fiber is measured. If there is a change in the attenuation profile, such as an increase in loss at a certain location, an anomaly can be reported and addressed. Figure 1 shows an example of an increase in loss at the central part of an optical fiber observed by conventional OTDR.

[0027] In standard C-OTDR operation, the output is a vibration signal and the power profile information is not shown. Although the power profile can be obtained by using a specific method, the noise becomes very high.

[0028] Figure 2 is a graph showing an exemplary example of the loss variation measured by conventional OTDR and the new attenuation profile after a large loss occurred according to the aspects of the present disclosure.

[0029] An example is shown in Fig. 2. This graph of the measurement data shows the power profile curves before (green) and after (red) a major loss event. As expected, the fiber endpoints (at ~2600 m) can be clearly identified. However, even though it can be visually seen that the power drops at the position of ~1950 m, due to the large noise in the power profile, it is difficult for the measuring instrument to automatically identify it. For example, in the section before the major loss point (i.e., before 1950 m), there is no consistent relationship between the power profile values between one curve and the other (they are assumed to be the same). At certain positions, the value of one curve may be several times higher or lower than that of the other curve. Also, in the section after the major loss occurs, at a certain position, the value of one curve is actually lower than that of the other curve. Therefore, it is not possible to directly compare the values between these two curves to monitor whether a major loss event occurs.

[0030] In many DFOS applications, there is a strong demand to monitor the loss along the fiber while performing vibration sensing. For example, if improper operations are carried out near or on an optical fiber cable, the optical fiber may be damaged and a large loss may occur. By simultaneously monitoring vibration and loss and analyzing both data, it is possible to easily and quickly identify events and causes such as the damage worsening and the fiber being cut. Therefore, it is important to find a solution that not only identifies the fiber endpoints with C-OTDR but also automatically monitors the fiber loss.

[0031] The simplest method is to combine C-OTDR with a conventional OTDR that displays the position of the optical fiber endpoints and has a function to monitor the loss. However, this method is not economical.

[0032] As an improvement measure, there is a method of installing two types of light sources (a broadband light source for a conventional OTDR machine and a narrow linewidth light source for a C-OTDR machine) in the system and sharing the remaining optoelectronic components. This method is more economical than having two systems in parallel, but still requires two light sources (usually lasers) and an electronic circuit for switching these light sources to perform different functions.

[0033] As other techniques for improving this, for example, there are methods of sweeping the laser wavelength, collecting data multiple times at different wavelengths and calculating an average signal, or using an optoelectronic scrambler to scramble the signal multiple times and then collecting data to calculate an average signal. In these methods, multiple measurements are required each time, so the time efficiency is not good. Also, additional hardware components (adjustable lasers, scramblers, their respective control circuits, etc.) are required, increasing the cost, size, and control complexity of the system.

[0034] Furthermore, these methods still rely on human visual analysis to find losses and determine their positions and cannot provide an automatic endpoint detection method.

[0035] According to the present disclosure, a method of performing fiber loss detection using only the hardware of C-OTDR (while maintaining the same vibration / acoustic signal sensing function and endpoint detection function) is described. This method can automatically identify and locate large loss events without manual inspection. Therefore, additional costs can be saved and human operation costs can be reduced.

[0036] Similar to the fiber endpoint detection method, in this method, the high-pass filtering stage is bypassed when calculating the intensity change in C-OTDR, and the analysis is performed using the power profile. Furthermore, a processing procedure for minimizing the noise of the power profile data of a certain section of the fiber is added. By monitoring the change in the noise-removed power profile, fiber loss events can be automatically detected and located.

[0037] Figure 3 is a schematic flowchart showing the method of the present invention according to an aspect of the present disclosure. As shown in this block flowchart, it is a method for detecting fiber loss using C-OTDR. The section within the dashed box is the main procedure. The overall flowchart shows the operation of the entire optical fiber sensor system, such as normal vibration detection operations and fiber end point identification functions.

[0038] Referring to Figure 3, it can be seen that in the operation of the C-OTDR sensor, optical pulses from a laser light source are periodically transmitted to a sensing fiber (the fiber under test). The Rayleigh backscattering signals generated from each pulse at each position on the fiber are received by an optical receiver when they return to the sensor (also called an interrogator). These signals are digitized and used for DSP (digital signal processing). These are the raw data from the sensor

[0101] . For each position on the fiber, the raw data of the received Rayleigh backscattering signals from the periodic pulses are individually serialized into separate time series

[0102] . The subsequent processing steps are then performed on each time series data as shown in the figure, and each time series data corresponds to one position on the sensing fiber.

[0039] In a normal C-OTDR, the subsequent steps are to perform vibration calculations to obtain the vibration information of the fiber, which includes steps such as setting a high-pass filter (HPF) to remove baseband noise near DC

[0105] , then setting a low-pass filter (LPF) to remove high-frequency noise and aliasing

[0106] , then calculating the vibration signal at each position using the filtered data

[0107] , and then combining the vibration signals from all positions to generate the vibration information of the entire sensing fiber

[0108] , etc. In some alternative implementations, the HPF and LPF are replaced by an equivalent band-pass filter (BPF) to remove DC offset and high-frequency noise.

[0040] For the new function of monitoring fiber loss (and detecting fiber ends), the serialized data is processed in different ways. First, the DSP (FPGA firmware or software on a computer) determines which function to execute based on the functions required at that time

[0103] . If the vibration calculation function is selected

[0104] , the data goes through the same processing as above [105 - 108], but if the loss detection function and / or the end point detection function is selected

[0109] , different processing steps are executed as shown in the blue dashed box

[0110] .

[0041] In the loss detection and / or end point detection operation, the first step is to turn off (or bypass) the HPF function of the vibration calculation process

[0111] . Examples of the HPF function include using an IIR digital filter to obtain the DC signal and subtracting it from the input signal. Even if baseband (low-frequency) noise from the optoelectronic hardware remains, it is within the acceptable range for the end point detection function. Subsequent LPF steps such as averaging are not changed

[0112] . In the case of a BPF, the band-pass filter is reconfigured to maintain the DC offset at this step.

[0042] From the filtered signal, the optical power at each position can be calculated

[0113] . The calculation process is similar to the vibration calculation step 107, but the calculation result includes not only the vibration signal but also low-frequency noise. Combine the optical power calculated from all positions to generate the power profile of the entire sensing fiber

[0114] .

[0043] Figure 4 is a graph showing an exemplary example of the calculated C-OTDR power profile according to an aspect of the present disclosure, which is very noisy. This is sufficient for the purpose of end point detection, but it cannot be used to obtain fiber attenuation information like a conventional OTDR.

[0044] If fiber end point information is required, use the power profile data to calculate the fiber end points

[0115] .

[0045] In the next step

[0116] , noise removal is performed on the power profile. The simplest method is to perform a moving average. Usually, the moving average can be performed in the time domain and / or the spatial domain. However, since the power profile of C-OTDR is updated very quickly (multiple times per second), and the signal state at each position usually does not vary much over multiple measurements, performing averaging in the time domain is not effective.

[0046] In this step, performing a moving average in the spatial domain is used. An appropriate sample length for the moving average is selected. If the sample length is too short, the performance of noise removal will deteriorate. If the sample length is too long, some of the loss inflection points may be missed, and the calculation time will be long. However, since it is not common for multiple loss event occurrences to happen simultaneously, and most computers have sufficient computing power, there is no problem in selecting a larger sample length.

[0047] FIG. 5 is a graph showing an exemplary example of a noise-removed C-OTDR power profile according to an aspect of the present disclosure. To monitor loss events in the fiber, changes in the noise-removed power profile are observed. This is done by comparing the latest noise-removed power profile with the previous noise-removed power profile

[0117] .

[0048] FIG. 6 is a graph showing an exemplary example of a noise-removed C-OTDR power profile before and after a loss event according to an aspect of the present disclosure from the example of FIG. 2. Similar to the previous figure, the curves here are the results "before the loss event" and "after the loss event", respectively. Compared with the original power profile data in FIG. 2, the noise-removed power profiles in the section before the loss event position are very close, and the difference between the two curves after the loss event position is very obvious.

[0049] To facilitate the observation and analysis of loss fluctuations, for each location, the ratio of "before loss event" data to "after loss event" data is obtained using the noise-removed power profile.

[0050] Figure 7 is a graph showing an exemplary example of the ratio between the noise-removed C-OTDR power profiles before and after a loss event according to an aspect of the present disclosure, for the graph of Figure 6. As expected, the ratio for the section before the loss event location is about 1, and the ratio for the section after the loss event location is high (about 3 times in this example).

[0051] From this result, it is very easy to check whether there is a major loss event. This can be done by comparing the calculated ratio with a specific pre-set threshold (such as 3 dB or 2 times)

[0118] . If the ratio exceeds the threshold, a major loss event is detected. Then, the location of the event can be calculated

[0119] . The location of the event can be calculated using multiple methods. One method is to use the starting point of the rising edge indicating the location of the fiber loss, as shown in Figure 7. Another method is to find the location of the first peak and then subtract the distance related to the averaged sample length, also shown in Figure 7. Since these methods can be easily performed with simple data processing, the location of the event can be automatically calculated by an ordinary computer. Once the location of the event is identified, an alert notification can be automatically sent to the operator

[0120] .

[0052] After this step, the latest noise-removed power profile data is saved in memory and used for comparison with the next round of noise-removed power profiles

[0121] .

[0053] When the comparison

[0118] indicates that the ratio curve does not exceed the threshold value, it means that no major loss event is detected, and the loss event location identification step is unnecessary. The latest noise-removed power profile data is directly saved in the memory and used for comparison with the next round of noise-removed power profile

[0121] . Then, the process returns to step

[0101] to obtain the data of the next round from the sensor.

[0054] This process is fast because it only requires one set of raw data from the C-OTDR and usually takes less than 1 second. The noise removal process, power profile comparison process, and major loss event location calculation process are simple and easy to understand, and do not require complex analysis such as machine learning. All of these can be executed in an instant using a standard computer with normal computing power. Therefore, the entire process is completed in less than 1 second, and the detection function of the fiber end point (or fiber break point) is also completed simultaneously. In contrast, with a conventional OTDR, it usually takes dozens of seconds to several minutes for one attenuation profile measurement. All of the other methods mentioned above, such as laser wavelength sweeping and the use of an optoelectronic scrambler, require more time.

[0055] Because the processing method is simple, in this proposed method, it is possible to detect changes in loss and automatically identify the location of the loss. The system can provide event information (e.g., a large loss observed at the location of XXX) to the user, so the user does not need to analyze the data curve to confirm whether an event has occurred and manually find its location. In contrast, a conventional OTDR only provides attenuation profile information, and the user needs to manually detect whether an event has occurred and find its location.

[0056] Similar to the fiber break detection operation, vibrations along the fiber do not affect the characteristics of the power profile results obtained by this method. Therefore, the fiber loss detection method is robust and not affected by movements along the fiber.

[0057] Therefore, the method of the present invention according to the present disclosure has been proven to be an effective solution for automatically and quickly detecting optical fiber loss. The impact on the vibration sensing process is minimal, the sensing time is less than 1 second, and is usually negligible. Since it can be used alternately (interleaved) with vibration sensing, both vibration detection and loss monitoring (and end point monitoring) can be effectively performed simultaneously.

[0058] Compared with the conventional OTDR, this method can perform vibration sensing, which is the main function of C-OTDR. Also, end point information and loss information can be automatically generated. Compared with the modified C-OTDR, such as the addition of a wavelength-swept laser and a scrambler, this method does not require additional hardware or hardware modification, so no additional cost, space, or control complexity is needed. Therefore, adding a loss detection function to C-OTDR is an efficient and cost-effective solution.

[0059] Advantageously, the method of the present invention according to the present disclosure can be applied to the operation of general optical fiber networks.

[0060] FIG. 8 is a schematic diagram showing an operation example of optical fiber loss detection using C-OTDR according to an aspect of the present disclosure. The C-OTDR with the new loss detection function is installed at the central office of the network operator. The C-OTDR continuously monitors the vibration, end point, and loss states on the sensing fiber. If improper operation occurs on-site and a large loss occurs at a specific location, the C-OTDR and the attached processing computer detect it and identify the location using the technology proposed in the present invention. The fiber loss event and the location information can be automatically transmitted to remote users. At the same time, the C-OTDR performs vibration sensing and records the vibration data history at this location. This vibration history information helps to identify the cause of the loss change event. This investigation result is also transmitted to the user to take appropriate measures to prevent the situation from deteriorating (such as the fiber being completely cut).

[0061] Finally, FIG. 9 is a comparison of various schemes comparing the operation of the present invention according to aspects of the present invention with other known methods.

[0062] So far, the present disclosure has been presented using several specific examples, but those skilled in the art will recognize that the present teachings are not so limited. Therefore, the present disclosure should be limited only by the claims appended hereto.

Claims

1. A method for providing automatic optical fiber loss detection using coherent optical time domain reflectometry (C-OTDR), comprising: an optical sensor fiber, a C-OTDR interrogator that optically communicates with the optical sensor fiber, the C-OTDR interrogator being configured to generate an optical pulse, capture the generated pulse into the optical sensor fiber, and receive a backscattered signal from the optical sensor fiber; an analyzer having an advanced processing capability configured to analyze the backscattered signal received by the C-OTDR interrogator and further configured to provide an operating function selected from the group consisting of determining vibration activity at a point along the optical sensor fiber and determining an end point and loss of the optical sensor fiber; providing the C-OTDR system comprising the same; operating the C-OTDR system to determine the vibration activity at a plurality of points along the optical sensor fiber or to determine the end point and loss of the optical sensor fiber selectively configured by a user of the C-OTDR system.

2. The method of claim 1, further comprising digitizing the backscattered signal and then serializing the digitized signal into separate time series for each position along the sensor fiber.

3. The method of claim 2, further comprising selectively configuring the C-OTDR system for a user to determine vibration activity at a plurality of points along the optical sensor fiber.

4. The method of claim 3, further comprising determining vibration activity at each position along the optical sensor fiber from the separate time series of each position.

5. The method of claim 3, further comprising selectively configuring the C-OTDR system for a user to operate to determine the end point of the optical sensor fiber.

6. The method of claim 5, further comprising determining a power level at each position along the optical sensor fiber from the separate time series of each position.

7. The method of claim 6, further comprising determining a power profile of the entire length of the optical sensor fiber by combining the determined power levels at all positions.

8. The method according to claim 7, further comprising determining a fiberless signal level from the end of the fiber and setting a threshold corresponding to the fiberless signal level.

9. The method according to claim 8, further comprising determining a position along the fiber where the signal level exceeds the set threshold and identifying the determined position as an end point.

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