Optical fiber fault detection method and device

Abstract

The embodiment of the invention provides an optical fiber fault detection method and device, and the method comprises the steps: detecting a reference optical signal in a reference optical fiber and a to-be-detected optical signal in a to-be-detected optical fiber through an optical detector, and carrying out the coherent interference of the reference optical signal and the to-be-detected optical signal, and obtaining an interference signal; performing fast Fourier transform on the interference signal, and extracting a phase signal from a transformed frequency domain signal; measuring a group delay distribution curve based on the phase signal; fault features are detected based on the group delay distribution curve; and determining a fault type according to the fault feature and a preset fault type template. According to the invention, the detection precision and reliability of tiny damage and non-reflective faults of the optical fiber can be realized.

Description

Technical Field

[0001] This application relates to the field of optical fiber detection technology, and in particular to an optical fiber fault detection method and apparatus. Background Technology

[0002] Optical fiber is a crucial infrastructure supporting highly reliable information transmission and synchronous distribution. Breaks, poor splices, minor bends, or degradation due to environmental changes can lead to communication interruptions, data loss, and synchronization deviations, impacting system stability and security. Therefore, timely, accurate, and reliable status monitoring and fault diagnosis of optical fiber links are essential to ensure the normal and stable operation of the system. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a fiber optic fault detection method and apparatus.

[0004] To achieve the above objectives, this application provides a fiber optic fault detection method, comprising: A photodetector is used to detect the reference optical signal in the reference optical fiber and the optical signal to be tested in the optical fiber under test. The reference optical signal and the optical signal to be tested are then coherently interfered to obtain an interference signal. Perform a fast Fourier transform on the interference signal and extract the phase signal from the transformed frequency domain signal; Based on the phase signal, measure the group delay distribution curve; Based on the group delay distribution curve, fault characteristics are detected; The fault type is determined based on the fault characteristics and the preset fault type template.

[0005] Optionally, based on the phase signal, the group delay distribution curve is measured, including: The phase signal is subjected to phase expansion processing to obtain the processed absolute phase spectrum; Calculate the first derivative of the absolute phase spectrum to obtain the group delay distribution curve; The group delay distribution curve is smoothed by filtering to obtain the filtered group delay distribution curve.

[0006] Optionally, the group delay distribution curve is smoothed by filtering to obtain a filtered group delay distribution curve, including: For each data point within the selected window, calculate the local amplitude change rate, the deviation amplitude from the maximum and minimum values, and the local noise level of each data point within the preset range; For each data point, the weight of the data point is set according to the relationship between the local amplitude change rate of the data point and the preset change rate threshold, and / or the relationship between the deviation amplitude and the preset deviation threshold, and / or the relationship between the local noise level and the preset noise threshold. Within the window, a polynomial fit is performed based on the weights of each data point to calculate the smoothed value of each data point.

[0007] Optionally, based on the filtered group delay distribution curve, fault characteristics are detected, including: Based on the group delay distribution curve, detect the slope abrupt change points in the curve, as well as the abrupt change amplitude, abrupt change range, slope change rate, and abrupt change pattern of the slope abrupt change points; Based on the abrupt change amplitude, abrupt change range, slope change rate, and abrupt change pattern of the slope abrupt change point, it is determined whether the slope abrupt change point belongs to peak feature, step feature, slope drift feature, or periodic fluctuation feature.

[0008] Optionally, based on the group delay distribution curve, detecting abrupt slope changes in the curve includes: Within the selected detection window, calculate the rate of curvature change of the group delay distribution curve; When the rate of change of curvature exceeds the set curvature threshold or a local extremum occurs, it is marked as a slope abrupt change point; wherein, the curvature threshold is dynamically adjusted according to the mean and standard deviation of the historical stable segment.

[0009] Optionally, based on the abrupt change amplitude, abrupt change range, slope change rate, and abrupt change pattern of the slope abrupt change point, it can be determined whether the slope abrupt change point belongs to a peak feature, a step feature, a slope drift feature, or a periodic fluctuation feature, including: The slope mutation point where the mutation amplitude is greater than the peak threshold, the mutation range is within the peak range, and there is only one or a finite number of peak mutations is determined as the peak feature; A slope mutation point whose mutation amplitude is greater than the step threshold, whose mutation range is within the step range, and whose mutation range exhibits a plateau step characteristic is defined as a step feature. The slope mutation point that has a mutation amplitude greater than the fluctuation threshold, a mutation range within the fluctuation range, and a periodic occurrence is defined as a periodic fluctuation feature. The slope abrupt change point where the slope change rate is greater than the slope change threshold and the slope change speed is less than the preset smooth threshold is determined as the slope drift feature.

[0010] Optionally, the fault type template includes periodicity indicators, amplitude indicators, range indicators, and slope change rate indicators; Based on the fault characteristics and the preset fault type template, the fault type is determined, including: Calculate the similarity between the fault features and each fault type template, determine the fault type template with the highest similarity as the matching fault type template, and determine the fault type corresponding to the fault type template.

[0011] Optionally, the method further includes: The fault location of the optical fiber under test is located based on the frequency point corresponding to the slope abrupt change point.

[0012] Optionally, the fault location of the optical fiber under test can be located based on the frequency point corresponding to the slope abrupt change point, using the following method: (2) Where c is the speed of light in a vacuum. Let be the group refractive index of the optical fiber under test. For frequency step interval, f 0 is the starting frequency. f d denoted as the frequency corresponding to the abrupt change in slope, and z as the position of the fault point relative to the scan start point.

[0013] This application embodiment also provides an optical fiber fault detection device, including: The detection module is used to detect the reference optical signal in the reference optical fiber and the optical signal to be tested in the optical fiber under test using a photodetector, and to perform coherent interference on the reference optical signal and the optical signal to be tested to obtain an interference signal. The extraction module is used to perform a fast Fourier transform on the interference signal and extract the phase signal from the transformed frequency domain signal; The measurement module is used to measure the group delay distribution curve based on the phase signal; The detection module is used to detect fault characteristics based on the group delay distribution curve; The determination module is used to determine the fault type based on the fault characteristics and a preset fault type template.

[0014] As can be seen from the above description, the fiber optic fault detection method and apparatus provided in this application utilize a photodetector to detect a reference optical signal in a reference fiber and a test optical signal in the fiber under test. The reference optical signal and the test optical signal undergo coherent interference to obtain an interference signal. A fast Fourier transform is performed on the interference signal, and a phase signal is extracted from the transformed frequency domain signal. Based on the phase signal, a group delay distribution curve is measured. Based on the group delay distribution curve, fault characteristics are detected. The fault type is determined according to the fault characteristics and a preset fault type template. This application can achieve high accuracy and reliability in detecting minor damage and non-reflective faults in optical fibers. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the method flow of an embodiment of this application; Figure 2 This is a schematic diagram of the group delay distribution curve in an embodiment of this application; Figure 3 This is a block diagram of the device structure according to an embodiment of this application; Figure 4 This is a block diagram of the electronic device structure according to an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this disclosure pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] In related technologies, optical fiber fault detection utilizes an optical time-domain reflectometer (OTDR). This involves emitting short pulses of light into the fiber and detecting the return signals caused by Rayleigh scattering or Fresnel reflection to construct a power distribution curve as a function of distance. By identifying abrupt changes in the power-distance curve, the location of potential faults or damage in the fiber optic link can be preliminarily determined. This method is effective for detecting breaks, significant damage, or strong reflection faults. However, its detection capability is significantly limited for conditions such as micro-bends, minor connection defects, and aging connectors. Its spatial resolution is constrained by pulse width and modulation bandwidth, making it difficult to capture minute structural damage and meet high-precision detection requirements. Furthermore, it only utilizes optical power (amplitude) information and fails to fully leverage rich physical characteristics such as phase, group delay, phase jitter, and frequency stability for detection, resulting in insufficient ability to identify and locate non-reflective faults (such as micro-bends and stress). In addition, OTDRs are typically used as offline or periodic testing tools and are not suitable for real-time, continuous online monitoring of critical links; reflection blind spots, repetitive echoes, and noise can also reduce their diagnostic reliability in complex structures or densely connected environments.

[0020] In view of this, embodiments of this application provide an optical fiber fault detection method, which performs frequency domain processing on the interference signal formed by the optical signal under test and the reference optical signal, extracts the phase signal, measures the group delay distribution curve based on the phase signal, detects fault characteristics based on the group delay distribution curve, and analyzes the fault type corresponding to the fault characteristics, thereby achieving accurate and reliable detection of minor structural damage and non-reflective faults.

[0021] like Figure 1 As shown in the figure, this application provides a fiber optic fault detection method, including: S101: Use a photodetector to detect the reference optical signal in the reference optical fiber and the optical signal to be tested in the optical fiber under test, and perform coherent interference on the reference optical signal and the optical signal to be tested to obtain the interference signal; In this embodiment, an optical frequency comb with ultra-narrow linewidth and stable frequency output capability is selected as the light source. The optical frequency comb has a defined comb tooth spacing (e.g., on the GHz scale), high spectral purity, and low phase noise characteristics. The output end of the optical frequency comb is connected to a precision temperature control and current drive module. A mode-locked feedback mechanism ensures that the output frequency is traceable to an external stable reference (e.g., an optical clock or rubidium clock), achieving high-precision optical frequency synchronization output. The output signal from the optical frequency comb is split into two paths using an optical fiber coupler. The two signals are input to the two ends of the fiber under test, respectively. Each end of the fiber under test is equipped with a reference fiber and a main optical path under test. The two optical frequency comb signals can propagate in the fiber in two directions, forming a closed-loop symmetrical transmission structure. The reference fiber is a short-distance stable fiber, and the main optical path under test is the part that runs through the fiber under test, ensuring that coherent detection has sufficient sensitivity to changes in the propagation structure.

[0022] In some methods, a bidirectional symmetrical coherent interference structure is employed. The light generated by the optical frequency comb source is split into two paths by an optical fiber coupler, and transmitted to ends A and B of the fiber under test (DUT). Detection unit A and detection unit B are respectively located at ends A and B. The core of each detection unit is a 2×2 optical fiber coupler. In detection unit A, the optical fiber coupler splits the received optical signal into two paths: one path is fed into a highly stable reference fiber to form the local reference light at end A; the other path is injected into the DUT as the test light transmitted from end A to end B. When the test light from end B, having traversed the entire fiber, reaches end A, it merges with the returning reference light at end A in the same optical fiber coupler and undergoes coherent interference, generating an interference signal. This interference signal is received and detected by detection unit A, and contains all the link effects experienced by the optical signal during its transmission from end B to end A. The completely symmetrical process occurs synchronously in detection unit B, which receives and detects the test light from end A and interferes with the reference light at end B to form an interference signal. In this way, the system simultaneously acquires independent interference signals from two propagation directions on the optical fiber under test, from end A to end B and from end B to end A, laying the physical foundation for subsequent high-precision and high-reliability fault location and identification through group delay analysis.

[0023] In some methods, an adjustable optical attenuator can be installed on the optical transmission path to control the power of the input optical signal, ensuring the signal strength remains within the dynamic range of the photodetector while avoiding nonlinear interference. The entire structure maintains a mirror-symmetric layout to minimize system errors introduced by differences in equipment and coupling offsets, thereby improving the accuracy of subsequent measurements. Components such as optical isolators and wavelength division multiplexers can also be introduced into the optical transmission path to enhance anti-crosstalk and multiplexing capabilities, adapting to the application requirements of multi-node deployments.

[0024] This embodiment introduces a high-frequency stable optical comb and a coherent time-frequency transmission structure to obtain high-precision phase and propagation delay information of the optical fiber link. It effectively reflects the changes in propagation characteristics caused by structural disturbances in the optical fiber link, breaks through the sensitivity limitations of traditional detection methods, and can accurately capture group delay changes caused by minor structural damage.

[0025] During testing, a photodetector is used to detect the reference optical signal and the optical frequency comb signal propagating in the fiber under test (DUT) from the reference optical signal and the DUT optical signal. Coherent interference is then performed on the reference and DUT optical signals to obtain an interference signal containing amplitude and phase information. The DUT optical signal is affected by changes in the fiber link structure and environment (such as micro-bends and connector damage) during propagation in the DUT, causing changes in its phase, propagation delay, and other physical characteristics. Coherent interference between the DUT optical signal and the reference optical signal produces an interference signal that reflects the changes in the propagation state in the DUT optical fiber. The interference signal is then converted into a digital signal by an analog-to-digital converter for subsequent digital signal processing.

[0026] S102: Perform a fast Fourier transform on the interference signal and extract the phase signal from the transformed frequency domain signal; In this embodiment, after the interference signal is converted into a digital signal, a Fast Fourier Transform is performed to obtain the transformed frequency domain signal. This frequency domain signal contains an amplitude signal component and a phase signal component. The phase signal is then extracted from the frequency domain signal. This phase signal records the total phase accumulation of the optical signal during propagation and is highly correlated with fiber length, refractive index perturbation, microbending structure, etc.

[0027] S103: Measure the group delay distribution curve based on the phase signal; In this embodiment, based on the extracted phase signal measurement group delay distribution curve, the group delay change characteristics are used as the key criterion to construct the correspondence between propagation characteristics and the physical state of the optical fiber link. The fault feature pattern is extracted from the group delay change trend, which improves the classification ability of non-reflective faults and enables differentiated identification of fault types such as breakage, microbending, and poor connection.

[0028] In some embodiments, the group delay distribution curve is measured based on the phase signal, including: The phase signal is subjected to phase expansion processing to obtain the processed absolute phase spectrum; Calculate the first derivative of the absolute phase spectrum to obtain the group delay distribution curve; The group delay distribution curve is smoothed by a filter to obtain the filtered group delay distribution curve.

[0029] In this embodiment, considering the 2π periodic transition of the phase signal, it is necessary to adjust the phase signal... (f) Perform phase expansion processing to restore the continuously changing absolute phase spectrum. Optionally, the phase expansion algorithm can use standard algorithms such as the sliding window method or the cosine coherence criterion method, and should avoid misjudgment and regression caused by noise interference. Then, the absolute phase spectrum is calculated. The first derivative is used to obtain the group delay distribution curves at various frequencies. The calculation method is as follows: (1) The group delay distribution curve reflects the subtle differences in the propagation speed of different frequency components in the optical fiber under test. These differences are usually caused by physical disturbances in the optical fiber link (such as stress concentration, microbending, aging joints, etc.). Therefore, the group delay distribution curve can be used as a highly sensitive sensing basis for changes in the structural state of the optical fiber link to detect and characterize potential structural faults in the optical fiber.

[0030] After calculating the group delay distribution curve, a smoothing filter is applied to it to obtain the filtered group delay distribution curve. In some methods, the Savitzky-Golay filter can be used to perform local polynomial fitting on the group delay distribution curve, resulting in a smoothed curve. This effectively suppresses noise interference, preserves local abrupt changes near fault feature points, and improves the accuracy of fault feature extraction.

[0031] In some embodiments, the group delay distribution curve is smoothed by filtering to obtain a filtered group delay distribution curve, including: For each data point within the selected window, calculate the local amplitude change rate, the deviation amplitude from the maximum and minimum values, and the local noise level of each data point within the preset range; For each data point, the weight of the data point is set according to the relationship between the local amplitude change rate of the data point and the preset change rate threshold, and / or the relationship between the deviation amplitude and the preset deviation threshold, and / or the relationship between the local noise level and the preset noise threshold. Within this window, a polynomial fit is performed based on the weights of each data point to calculate the smoothed value of each data point.

[0032] In this embodiment, to improve the processing capability of the group delay distribution curve in a strong noise environment while retaining key abrupt change feature information, a weighted polynomial fitting is used in each sliding window based on Savitzky-Golay filtering to determine the local rate of change, deviation amplitude, and local noise level of each data point. According to the local rate of change, deviation amplitude, and local noise level of the data points, corresponding weights are assigned to the data points. Data points with higher weights have a greater impact on the fitting process, making the fitting process focus more on structural abrupt change regions rather than background smooth regions.

[0033] Specifically, for each data point within the selected window, the local amplitude change rate within a preset range, the deviation from the maximum and minimum values ​​within that range, and the local noise level within that range are calculated. For each data point, if the local amplitude change rate reaches a preset change rate threshold, and / or the deviation from the maximum and minimum values ​​reaches a preset deviation threshold, and / or the local noise level reaches a preset noise threshold, the weight of that data point is set to the first weight. If the local amplitude change rate does not reach the change rate threshold, the deviation does not reach the deviation threshold, and the local noise level does not reach the noise threshold, the weight of that data point is set to the second weight. The first weight is greater than the second weight; that is, data points with greater changes are assigned a higher weight to highlight the characteristics of abrupt changes and improve the resolution of subsequent detection, especially for the accurate detection of sub-meter-level structural anomalies such as micro-bending and micro-damage.

[0034] In polynomial fitting, a low-order fitting is used for regions with drastic changes in the group time delay distribution curve (such as abrupt change points or points of rapid slope change) to highlight the boundary of change, while a high-order fitting is used for regions with stable changes to enhance the overall smoothness of the curve and reduce the impact of noise. At the same time, an outlier identification and replacement mechanism is adopted. For suspected outliers, local interpolation of surrounding data is used to avoid them causing pseudo-abrupt interference to the fitted curve and improve robustness.

[0035] S104: Detecting fault characteristics based on group delay distribution curves; In this embodiment, considering that different types of faults exhibit unique morphologies in the group delay curve—for example, fracture faults cause sharp, isolated peaks, micro-bending faults typically form periodic disturbances, and poorly welded or aged joints generally exhibit gentle, step-like abrupt changes—a high-fidelity group delay distribution curve is obtained through filtering. The curve's amplitude, slope change rate, peak width, and other multi-dimensional characteristics are then analyzed to accurately determine the fault characteristics. Specifically, this includes: Based on the group delay distribution curve, detect the slope abrupt change points in the curve, as well as the abrupt change amplitude, abrupt change range, slope change rate, and abrupt change pattern of the slope abrupt change points; Based on the amplitude, range, rate of change, and pattern of slope abrupt change, the slope abrupt change point can be determined to belong to peak characteristics, step characteristics, slope drift characteristics, or periodic fluctuation characteristics.

[0036] In this embodiment, based on the group delay distribution curve, a slope abrupt change point detection is performed on the curve using a sliding window approach. Within the selected detection window, the rate of change of curvature of the curve is calculated. When the rate of change of curvature exceeds a set curvature threshold or a local extremum occurs, it is marked as a slope abrupt change point. To avoid false triggering by noise, a local statistical filtering mechanism is employed. The curvature threshold is dynamically adjusted based on the mean and standard deviation of historical stable segments to achieve adaptive noise suppression, thereby improving the accuracy and robustness of abrupt change point detection.

[0037] After identifying the slope abrupt change point, further analyze the magnitude of the abrupt change, such as the difference between the first and second amplitudes when the amplitude of the data point changes from the first amplitude to the second amplitude; analyze the range of the slope abrupt change point, such as the range from the beginning of the slope abrupt change to the return to the normal slope, or the half-width at half-maximum (WHM) of the abrupt change range; analyze the slope change rate of the slope abrupt change point, such as the relationship between the slope change rate and the set slope change threshold; analyze the abrupt change pattern of the slope abrupt change point, such as the fluctuation change occurring at certain intervals, or only one or a limited number of peak abrupt changes, or only one or a limited number of step abrupt changes, etc.

[0038] like Figure 2 As shown, by analyzing the mutation amplitude, mutation range, slope change rate, and mutation pattern of slope abrupt change points, slope abrupt change points with mutation amplitude greater than the peak threshold, mutation range within the peak range, and only one peak abrupt change are identified as peak features, such as... Figure 2 The purple shaded area in the image, located approximately 71–74 km in the fiber under test, exhibits a peak amplitude close to 60 ps, ​​lasting only a few kilometers (less than 5 kilometers), demonstrating strong local abrupt change characteristics. A step-change point is defined as a slope abrupt change point where the abrupt change amplitude exceeds the step threshold, the abrupt change range is within the step range, and the abrupt change range exhibits plateau-like step characteristics. Figure 2 The blue shaded area, located approximately 50–60 km along the fiber under test, exhibits a sudden change in amplitude of about 20 ps, ​​lasting for 10 km, with a stable slope and a gradual upward trend. Slope abrupt changes that exceed the fluctuation threshold, fall within the fluctuation range, and occur periodically are defined as periodic fluctuation characteristics. Figure 2 The green shaded area in the image shows a single fluctuation located approximately 10–30 km along the fiber under test, with a typical amplitude of ±10 ps. This fluctuation exhibits periodic variations over a range of several kilometers, forming a multi-period sinusoidal wave pattern. Affected by gradual disturbances such as thermal stress, slope abrupt changes where the slope change rate exceeds the slope change threshold and the slope change is slow (the slope change rate is less than a preset smoothing threshold) are considered slope drift characteristics.

[0039] In this way, by combining multi-dimensional feature parameters, the accuracy of fault identification can be improved, the diagnostic capability for non-reflective faults (such as stress disturbance and refractive index disturbance) can be enhanced, and clear criteria can be provided for subsequent spatial positioning and fault category identification.

[0040] S105: Determine the fault type based on the fault characteristics and the preset fault type template.

[0041] In this embodiment, after analyzing and determining the fault characteristics, the fault characteristics are matched with a preset fault type template to determine the fault type to which the fault characteristics belong. For example, microbending disturbances originate from the modulation effect of small curvature changes in the optical fiber on the group velocity, exhibiting periodic, low-amplitude fluctuation characteristics. Therefore, periodic fluctuation characteristics can be identified as microbending faults; poor fusion splicing causes phase delay accumulation or multipath interference, exhibiting medium-amplitude, wide-range plateau step characteristics. Therefore, step characteristics can be identified as poor fusion splicing faults; breakage faults present abrupt spikes, so peak characteristics can be identified as training faults.

[0042] In some embodiments, the fault type is determined based on fault characteristics and a preset fault type template, including: Calculate the similarity between the fault features and each fault type template, determine the fault type template with the highest similarity as the matching fault type template, and determine the fault type corresponding to the fault type template.

[0043] In this embodiment, the fault type templates are generated based on a large number of high-confidence samples. The templates include periodicity indicators, amplitude indicators, range indicators (such as full width at half maximum), and slope change rate indicators. Fault features are compared and similarity analyzed with each fault type template. Optionally, the similarity between the fault features and each template is calculated using the Pearson correlation coefficient, and the template with the highest similarity is determined as the matching template. The fault type of this template is the determined fault type. This method has strong real-time performance and is suitable for fiber optic structure fault scenarios, especially for fiber optic fault detection with clear group delay distribution curve patterns.

[0044] In some embodiments, the method further includes: The fault location of the optical fiber under test is determined by the frequency point corresponding to the frequency abrupt change. The method is as follows: (2) Where c is the speed of light in a vacuum. The group refractive index of the optical fiber under test is typically 1.468. The frequency step interval is the frequency interval during the scanning process. f 0 is the starting frequency, which is the lowest frequency in the entire sweep frequency measurement. f d The frequency corresponding to the point of abrupt change in slope. zThe location of the fault point relative to the scan start point is expressed in meters.

[0045] According to the frequency distance mapping relationship shown in formula (2), the frequency points can be mapped. f d With the starting frequency f The interval between 0s is mapped to spatial distance. z This means that the frequency domain mutation is precisely located to a specific length position in the optical fiber under test, thereby achieving precise spatial positioning of the fault location with a positioning accuracy of sub-meter level.

[0046] In some implementations, an integrated fiber optic monitoring system is constructed, possessing long-term stable operation capabilities, online link status awareness, and fault early warning functions. This system enables continuous health monitoring and fault risk management of fiber optic infrastructure without interrupting normal service signal transmission. The system is integrated into the fiber optic link structure, utilizing a single optical frequency comb source to achieve both time-frequency synchronization and structural status monitoring. Deployed at the master control nodes at both ends of the fiber optic link, the system periodically performs tasks such as optical signal input, interference signal reception, interference signal processing, fault feature extraction, and fault type diagnosis. It periodically (e.g., at the minute or hour level) generates group delay distribution curves and fault diagnosis results to meet the needs of adjusting the granularity of status awareness in different scenarios.

[0047] When the fiber optic link structure remains stable, the propagation characteristic parameters output by the system will be highly consistent with the benchmark reference model. When a minor disturbance or initial fault occurs in the fiber optic link, the system can immediately capture subtle changes in the group delay distribution curve and complete spatial positioning and fault type identification. All fault diagnosis information can be uploaded to a remote monitoring platform via the network, and anomaly warnings can be generated by combining historical evolution trends, thus generating predictive maintenance recommendations. The system supports integrated operation with clock synchronization devices without interfering with time-frequency distribution functions, achieving a high degree of integration between synchronization and monitoring.

[0048] The system requires no additional excitation light source, pulse modulator, or sensor distribution network; it achieves online diagnostics solely through the propagation state analysis of the high-precision optical frequency comb signal itself. It boasts advantages such as non-intrusiveness, scalability, and high reliability. The system is easy to deploy and operates stably, making it particularly suitable for critical infrastructure projects with extremely high requirements for link continuity and security, such as national time service backbone links, power communication trunk lines, and rail transit control networks.

[0049] The fiber optic fault detection method provided in this application, in terms of detection resolution, overcomes the bottleneck limited by pulse width by extracting phase information in the frequency domain and measuring its group delay distribution curve. This enables precise detection of sub-meter-level structural anomalies such as micro-bending and micro-loss, significantly improving the spatial resolution of fault detection. By introducing an adaptive weighted local polynomial fitting filter method, noise interference can be effectively suppressed, key abrupt change features in the group delay distribution curve can be preserved, and detection sensitivity and resolution can be improved. In terms of fault identification capability, multi-dimensional feature analysis is performed based on the group delay distribution curve to establish the correlation between features such as abrupt change amplitude, abrupt change range, and slope change rate and fault type. Through fault type template matching, fault types such as breakage, poor splicing, and micro-bending can be accurately identified, significantly improving the intelligent level of fault diagnosis, especially suitable for complex and variable fiber optic link structures. In terms of system noise immunity, the group delay distribution curve is smoothed by a filtering algorithm to suppress the influence of background noise, preserve the key abrupt change features of the group delay distribution curve, enhance the detection stability and reliability in complex environments, effectively reduce the false judgment rate caused by environmental noise, and improve robustness.

[0050] Furthermore, the frequency domain analysis architecture adopted in this application has good system compatibility and scalability, and can be effectively integrated with advanced light sources such as optical frequency combs and swept lasers to meet the needs of different application scenarios. Compared with traditional pulse sources or dedicated sensing modules, it reduces hardware investment and has high engineering feasibility and promotional value.

[0051] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0052] It should be noted that the above description describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims may be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] like Figure 3 As shown, this application embodiment provides an optical fiber structure fault detection device, including: The detection module is used to detect the reference optical signal in the reference optical fiber and the optical signal to be tested in the optical fiber under test using a photodetector, and to perform coherent interference between the reference optical signal and the optical signal to be tested to obtain the interference signal. The extraction module is used to perform a fast Fourier transform on the interference signal and extract the phase signal from the transformed frequency domain signal. The measurement module is used to measure the group delay distribution curve based on the phase signal; The detection module is used to detect fault characteristics based on the group delay distribution curve; The determination module is used to determine the fault type based on the fault characteristics and the preset fault type template.

[0054] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing the embodiments of this application, the functions of each module can be implemented in one or more software and / or hardware.

[0055] The apparatus described above is used to implement the corresponding methods in the foregoing embodiments and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0056] Figure 4 This embodiment illustrates a more specific hardware structure of an electronic device. The device may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0057] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0058] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0059] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0060] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0061] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0062] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0063] The electronic devices described above are used to implement the corresponding methods in the foregoing embodiments and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0064] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0065] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this disclosure (including the claims) is limited to these examples; within the framework of this disclosure, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0066] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this disclosure, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0067] Although this disclosure has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0068] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this disclosure.

Claims

1. A fiber optic fault detection method, characterized in that, include: A photodetector is used to detect the reference optical signal in the reference optical fiber and the optical signal to be tested in the optical fiber under test. The reference optical signal and the optical signal to be tested are then coherently interfered to obtain an interference signal. Perform a fast Fourier transform on the interference signal and extract the phase signal from the transformed frequency domain signal; Based on the phase signal, measure the group delay distribution curve; Based on the group delay distribution curve, fault characteristics are detected; The fault type is determined based on the fault characteristics and the preset fault type template.

2. The method according to claim 1, characterized in that, Based on the phase signal, the group delay distribution curve is measured, including: The phase signal is subjected to phase expansion processing to obtain the processed absolute phase spectrum; Calculate the first derivative of the absolute phase spectrum to obtain the group delay distribution curve; The group delay distribution curve is smoothed by filtering to obtain the filtered group delay distribution curve.

3. The method according to claim 2, characterized in that, The group delay distribution curve is smoothed and filtered to obtain the filtered group delay distribution curve, including: For each data point within the selected window, calculate the local amplitude change rate, the deviation amplitude from the maximum and minimum values, and the local noise level of each data point within the preset range; For each data point, the weight of the data point is set according to the relationship between the local amplitude change rate of the data point and the preset change rate threshold, and / or the relationship between the deviation amplitude and the preset deviation threshold, and / or the relationship between the local noise level and the preset noise threshold. Within the window, a polynomial fit is performed based on the weights of each data point to calculate the smoothed value of each data point.

4. The method according to claim 1, characterized in that, Based on the filtered group delay distribution curve, fault characteristics are detected, including: Based on the group delay distribution curve, detect the slope abrupt change points in the curve, as well as the abrupt change amplitude, abrupt change range, slope change rate, and abrupt change pattern of the slope abrupt change points; Based on the abrupt change amplitude, abrupt change range, slope change rate, and abrupt change pattern of the slope abrupt change point, it is determined whether the slope abrupt change point belongs to peak feature, step feature, slope drift feature, or periodic fluctuation feature.

5. The method according to claim 4, characterized in that, Based on the group delay distribution curve, detect abrupt slope changes in the curve, including: Within the selected detection window, calculate the rate of curvature change of the group delay distribution curve; When the rate of change of curvature exceeds the set curvature threshold or a local extremum occurs, it is marked as a slope abrupt change point; wherein, the curvature threshold is dynamically adjusted according to the mean and standard deviation of the historical stable segment.

6. The method according to claim 4, characterized in that, Based on the abrupt change amplitude, abrupt change range, slope change rate, and abrupt change pattern of the slope abrupt change point, it is determined whether the slope abrupt change point belongs to a peak feature, a step feature, a slope drift feature, or a periodic fluctuation feature, including: The slope mutation point where the mutation amplitude is greater than the peak threshold, the mutation range is within the peak range, and there is only one or a finite number of peak mutations is determined as the peak feature; A slope mutation point whose mutation amplitude is greater than the step threshold, whose mutation range is within the step range, and whose mutation range exhibits a plateau step characteristic is defined as a step feature. The slope mutation point that has a mutation amplitude greater than the fluctuation threshold, a mutation range within the fluctuation range, and a periodic occurrence is defined as a periodic fluctuation feature. The slope abrupt change point where the slope change rate is greater than the slope change threshold and the slope change speed is less than the preset smooth threshold is determined as the slope drift feature.

7. The method according to claim 1, characterized in that, The fault type template includes periodic indicators, amplitude indicators, range indicators, and slope change rate indicators. Based on the fault characteristics and the preset fault type template, the fault type is determined, including: Calculate the similarity between the fault features and each fault type template, determine the fault type template with the highest similarity as the matching fault type template, and determine the fault type corresponding to the fault type template.

8. The method according to claim 4, characterized in that, Also includes: The fault location of the optical fiber under test is located based on the frequency point corresponding to the slope abrupt change point.

9. The method according to claim 8, characterized in that, The fault location of the optical fiber under test is determined based on the frequency point corresponding to the slope abrupt change point. The method is as follows: （2） Where c is the speed of light in a vacuum. Let be the group refractive index of the optical fiber under test. For frequency step interval, f 0 is the starting frequency. f d denoted as the frequency corresponding to the abrupt change in slope, and z as the position of the fault point relative to the scan start point.

10. A fiber optic fault detection device, characterized in that, include: The detection module is used to detect the reference optical signal in the reference optical fiber and the optical signal to be tested in the optical fiber under test using a photodetector, and to perform coherent interference on the reference optical signal and the optical signal to be tested to obtain an interference signal. The extraction module is used to perform a fast Fourier transform on the interference signal and extract the phase signal from the transformed frequency domain signal; The measurement module is used to measure the group delay distribution curve based on the phase signal; The detection module is used to detect fault characteristics based on the group delay distribution curve; The determination module is used to determine the fault type based on the fault characteristics and a preset fault type template.

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