Distributed acoustic wave detection system and method for microscopic bending damage of optical cable link

Abstract

The invention discloses a distributed acoustic wave detection system and method for microscopic bending damage of an optical cable link, and relates to the technical field of optical fiber sensing, and the method comprises the steps: obtaining a corresponding backward Rayleigh scattering signal sequence through alternately transmitting detection light pulses of a first wavelength and a second wavelength; performing phase demodulation on the signal sequence to obtain the phase variation of the first wavelength and the second wavelength of each position point; performing differential operation to generate a differential bending characteristic signal, and calculating an instantaneous amplitude; judging whether the amplitude is lower than a background noise threshold, and if so, marking as a background noise event; otherwise, calculating an amplitude ratio and judging whether the amplitude ratio falls into a preset range, and if yes, marking as a candidate damage event. And finally, performing neighborhood analysis on the candidate damage event through spatial focusing verification, marking the candidate damage event as a microcosmic bending damage event if the candidate damage event exceeds a preset density threshold, and otherwise, marking the candidate damage event as an interference event. According to the invention, through wavelength response ratio screening and space focusing verification, accurate identification of microscopic bending damage is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of optical fiber sensing technology, in particular to a distributed acoustic wave detection system for micro-bending damage of optical cable link and a method thereof. BACKGROUND

[0002] Long-distance and high-reliability optical cable links such as communication backbone network, power communication network and oil and gas pipeline accompanying optical cable require early, accurate and distributed monitoring and positioning of micro-bending damage of optical fibers.

[0003] The existing Φ-OTDR technology can detect the vibration / acoustic wave along the line by using the phase sensitivity of the backscattering Rayleigh scattering of the optical fiber, and is sensitive to micro-bending; however, the random mode coupling existing in the single-mode optical fiber can introduce phase / intensity noise similar to the real micro-bending damage, resulting in high false alarm rate, and the traditional method is difficult to effectively distinguish and accurately identify the acoustic wave / vibration signal caused by the physical damage of the micro-bending of the optical fiber in the high-sensitivity Φ-OTDR distributed acoustic wave sensing system.

[0004] In view of the above technical problems, the present application provides a solution. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a distributed acoustic wave detection system for micro-bending damage of optical cable link and a method thereof.

[0006] In order to achieve the above-mentioned purpose, the technical scheme of the present application is as follows:

[0007] In the first aspect, the present application discloses a distributed acoustic wave detection method for micro-bending damage of optical cable link, comprising the following steps:

[0008] Obtaining the backscattering Rayleigh scattering signal sequence corresponding to the alternately emitted first wavelength and second wavelength probe light pulses to the optical fiber to be measured, wherein the first wavelength is less than the second wavelength;

[0009] Respectively performing phase demodulation on the backscattering Rayleigh scattering signal sequence to obtain the first wavelength phase change and the second wavelength phase change at each position point;

[0010] According to the first wavelength phase change and the second wavelength phase change, difference operation is performed to generate a difference bending characteristic signal;

[0011] Calculating the instantaneous amplitude of the difference bending characteristic signal at each position point, and judging whether the instantaneous amplitude is lower than the preset dynamic background noise threshold: if yes, marking as a background noise event, otherwise calculating the amplitude ratio of the first wavelength phase change and the second wavelength phase change at the position point;

[0012] judging whether the amplitude ratio falls into a preset theoretical wavelength response ratio range: if yes, marking as a candidate damage event, otherwise marking as a non-bending interference event;

[0013] performing spatial focus verification on the candidate damage event, judging whether the candidate damage event in the position point neighborhood exceeds a preset density threshold: if yes, marking as a microscopic bending damage event, otherwise marking as an isolated interference event.

[0014] In a second aspect, the present application discloses a distributed acoustic wave detection system for microscopic bending damage of an optical cable link, comprising:

[0015] a signal acquisition module, configured to alternately emit detection light pulses of a first wavelength and a second wavelength to a to-be-detected optical fiber, and acquire a corresponding backscattering Rayleigh signal sequence; the first wavelength is less than the second wavelength;

[0016] a phase demodulation module, configured to perform phase demodulation on the backscattering Rayleigh signal sequence, and obtain a first wavelength phase change amount and a second wavelength phase change amount of each position point respectively;

[0017] a difference operation module, configured to perform difference operation according to the first wavelength phase change amount and the second wavelength phase change amount, and generate a difference bending characteristic signal;

[0018] a first judgment module, configured to calculate an instantaneous amplitude of the difference bending characteristic signal at each position point, and judge whether the instantaneous amplitude is lower than a preset dynamic background noise threshold: if yes, marking as a background noise event;

[0019] a second judgment module, configured to calculate an amplitude ratio of the first wavelength phase change amount and the second wavelength phase change amount of the position point, and judge whether the amplitude ratio falls into a preset theoretical wavelength response ratio range: if yes, marking as a candidate damage event, otherwise marking as a non-bending interference event;

[0020] a damage verification module, configured to perform spatial focus verification on the candidate damage event, judging whether the candidate damage event in the position point neighborhood exceeds a preset density threshold: if yes, marking as a microscopic bending damage event, otherwise marking as an isolated interference event.

[0021] Compared with the prior art, the present application has the following beneficial effects:

[0022] 1. By introducing dual-wavelength alternating detection and difference operation technology, noise caused by random mode coupling in the optical fiber can be effectively suppressed, and the false positive rate can be significantly reduced; this method ensures accurate identification of microscopic bending damage through wavelength response ratio screening and spatial focus verification;

[0023] 2. By spatial focusing verification and multi-level interference event classification mechanism, such as temperature-related interference and periodic interference distinction, real damage signals and noise caused by environmental changes or equipment failure can be effectively distinguished, and the adaptability and stability of the system in complex environment are improved;

[0024] 3. A dynamic optimization calibration coefficient mechanism is proposed, which can maintain the sensitivity and stability of the system under different environments and fiber aging conditions through feedback of historical data and adjustment of deviation, thereby improving the accuracy of long-term monitoring;

[0025] 4. A temperature drift compensation step is introduced to avoid the interference of temperature fluctuations on the phase change amount, ensuring the stability and accuracy of the detection results. By automatically adjusting the temperature compensation strategy, false positives and false negatives caused by environmental temperature changes are effectively eliminated. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0027] Figure 1 The overall block diagram of the method of the first embodiment of the present application is shown in the figure.

[0028] Figure 2 The flowchart of the method of the first embodiment of the present application is shown in the figure.

[0029] Figure 3 The overall block diagram of the system of the second embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0030] The technical solutions of the present application will be described in detail below in conjunction with the embodiments. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0031] Summary of the application: In the traditional existing distributed acoustic sensing system based on phase-sensitive optical time domain reflectometry, the phase sensitivity of optical fiber backscattering Rayleigh scattering can detect the acoustic signal caused by microscopic bending damage, but the random mode coupling effect in single-mode fiber will introduce phase noise similar to the true damage characteristics. Such noise and the phase change of the real micro-bending damage have a high overlap in amplitude and time domain distribution, which makes the system unable to effectively distinguish between real damage and interference signals through single-wavelength phase demodulation results. Misjudgment events frequently trigger false alarms, reducing monitoring accuracy and reliability, while increasing the cost of manual verification.

[0032] For example, in the optical cable health monitoring scene of the cross-regional communication backbone network, there are various mechanical vibration sources and temperature gradient changes along the optical fiber. When the existing system uses single-wavelength phase demodulation, the random mode coupling caused by the thermal expansion and contraction of the metal bracket in the cable trench will generate phase fluctuation signals consistent with micro-bending damage. Such interference signals exhibit similar burst characteristics in time domain as real damage, and cover the typical frequency band range of micro-bending damage in frequency domain. The operation and maintenance system cannot filter interference based on a single criterion, resulting in frequent flickering of false alarm events on the monitoring interface, forcing the operation and maintenance personnel to conduct repetitive on-site verification at the same location, which seriously reduces monitoring efficiency.

[0033] In the face of the above problems, the present application first considers how to effectively distinguish the phase signals of random mode coupling noise and real micro-bending damage. Traditional single-wavelength phase demodulation cannot separate the characteristic differences of the two types of signals, and a multi-wavelength cooperative detection mechanism needs to be introduced. By analyzing the response characteristic differences of micro-bending damage and mode coupling at different wavelengths, it is found that the phase change of real damage and wavelength has a certain proportional relationship, while mode coupling interference shows wavelength independence. Based on this, the present application proposes to use dual-wavelength alternating detection, suppress common-mode noise through differential operation, and use wavelength response ratio to screen real damage. Further research shows that real damage events have an aggregation characteristic in spatial distribution, while interference events are randomly distributed, so a spatial focusing verification mechanism is introduced to enhance the reliability of discrimination.

[0034] Embodiment one:

[0035] As Figures 1-2As shown, the distributed acoustic wave detection method for micro-bending damage of optical cable link includes the following steps: acquiring the backscattering signal sequence corresponding to the first wavelength probe light pulse and the second wavelength probe light pulse alternately emitted to the optical fiber to be measured, the first wavelength being smaller than the second wavelength; phase demodulating the backscattering signal sequence respectively to obtain the first wavelength phase change and the second wavelength phase change at each position point; performing differential operation on the first wavelength phase change and the second wavelength phase change to generate a differential bending characteristic signal; calculating the instantaneous amplitude of the differential bending characteristic signal at each position point, and judging whether the instantaneous amplitude is lower than a preset dynamic background noise threshold; if yes, marking as a background noise event, otherwise calculating the amplitude ratio of the first wavelength phase change and the second wavelength phase change at the position point; judging whether the amplitude ratio falls within a preset theoretical wavelength response ratio range; if yes, marking as a candidate damage event, otherwise marking as a non-bending interference event; performing spatial focusing verification on the candidate damage event, and judging whether the candidate damage events in the neighborhood of the position point exceed a preset density threshold; if yes, marking as a micro-bending damage event, otherwise marking as an isolated interference event.

[0036] Acquiring the backscattering signal sequence corresponding to the first wavelength probe light pulse and the second wavelength probe light pulse alternately emitted to the optical fiber to be measured, the first wavelength being smaller than the second wavelength means that two different wavelength optical signals are used for alternate excitation, and the difference in sensitivity of different wavelengths to micro-bending in optical fiber transmission is utilized. Specifically, a tunable laser or a dual-wavelength laser source can be used in cooperation with an optical switch to realize alternate emission, and the response characteristics to micro-bending damage are enhanced through the wavelength difference. Phase demodulating the backscattering signal sequence respectively means extracting the phase information in the scattering signal through coherent detection technology, which can be realized by heterodyne detection or phase generation carrier demodulation algorithm, and is used for quantifying the phase change of the optical fiber caused by external disturbance. The differential bending characteristic signal means that the common mode interference is eliminated through the differential operation of the phase change of the two wavelengths, which can be realized by a subtracter or a digital signal processing algorithm, and effectively suppresses the influence of mode coupling noise on the detection result. The instantaneous amplitude means the amplitude change of the differential signal in the time domain, which can be calculated by Hilbert transform or envelope detection algorithm, and is used to represent the intensity of the local position disturbed by external disturbance. The dynamic background noise threshold is a judgment threshold adaptively adjusted according to the environmental noise level, which can be estimated in real time by sliding window statistical method or machine learning model, and is used to distinguish effective signals and random noises. The theoretical wavelength response ratio range is the ratio interval derived from the physical model based on the thermal-optical coefficient and the photoelastic effect of the optical fiber material, which can be determined by experimental calibration or theoretical calculation, and is used to verify the matching degree of the damage event and the wavelength characteristics. The spatial focusing verification means that the isolated interference is excluded through the neighborhood event density statistics, which can be realized by sliding window counting method or spatial clustering algorithm, and is used to confirm that the spatial distribution characteristics of the damage event are consistent with the focusing property of the real micro-bending damage.

[0037] Through the above scheme, the application can effectively distinguish the real microscopic bending damage in the optical fiber from the random mode coupling noise. The double-wavelength alternate detection and differential operation mechanism suppresses the common-mode noise and improves the signal-to-noise ratio. The wavelength response ratio accurately selects the events with microscopic bending characteristics, and the spatial focusing property further reduces the false positive rate. This multi-level judgment mechanism significantly improves the accuracy and reliability of microscopic bending damage detection, reduces false positive events, and reduces the workload of operation and maintenance personnel. At the same time, since the microscopic bending damage can be found early, the system can prevent the risk of fiber performance degradation and link interruption, and improve the operation stability and reliability of the cable link. This has important significance for scenarios with high reliability requirements such as communication backbone network and power communication network, and helps to ensure the safe operation of critical infrastructure.

[0038] The application further proposes a process for generating a differential bending characteristic signal, which includes obtaining an initial preset calibration coefficient, and the calibration coefficient represents a linear proportional relationship between the phase variation of the two wavelengths under mode coupling interference; subtracting the product of the calibration coefficient and the phase variation of the first wavelength from the phase variation of the second wavelength to obtain the differential bending characteristic signal.

[0039] The calibration coefficient is obtained through laboratory calibration or historical data statistics, and its value range is usually between 0.3 and 0.5. The differential operation adopts a vector subtraction form to eliminate the common-mode noise caused by mode coupling. The multiplication operation is realized by a digital signal processor, and the multiplication coefficient can be dynamically adjusted to adapt to different fiber types. The differential signal after subtraction operation retains the wavelength difference characteristics and suppresses non-bending interference.

[0040] Specifically, when there is random mode coupling in the optical fiber, the phase variation of the first wavelength and the second wavelength presents a fixed proportional relationship. By introducing the calibration coefficient, the interference component linearly related to the first wavelength in the phase variation of the second wavelength is offset. For example, when the calibration coefficient is 0.4, 40% of the first wavelength interference component in the phase variation of the second wavelength is removed. This process uses matrix operation to realize, and the phase variation of each position point is used as an independent vector to participate in the calculation. After differential processing, the signal-to-noise ratio of the bending characteristic signal is improved by about 8dB, effectively distinguishing the mode coupling noise from the real damage signal. The calibration coefficient can be dynamically optimized according to the aging degree of the optical fiber link, and the coefficient accuracy is adjusted to two decimal places through a feedback mechanism.

[0041] By the technical solution, the application can effectively eliminate the influence of mode coupling interference on micro-bending detection. By introducing a calibration coefficient, the linear relationship between the phase change of different wavelengths under mode coupling interference can be accurately characterized. The differential operation further eliminates the influence of such interference, so that the generated differential bending feature signal can more accurately reflect the real micro-bending situation. This method improves the accuracy and reliability of micro-bending detection, and reduces the probability of false positives and false negatives.

[0042] The application further proposes that the spatial focusing verification includes calculating the number of candidate damage events within a preset radius of the position point, judging whether the number of candidate damage events is lower than a preset first density threshold, and if so, marking it as an isolated interference event, otherwise further counting the number of times that the position point is marked as a candidate damage event within a preset past time range, judging whether the number of times exceeds a preset second density threshold, and if so, marking it as a micro-bending damage event, otherwise marking it as a transient interference event.

[0043] The preset radius is used to define the neighborhood spatial range, the value of which is set according to the physical diffusion range of the fiber micro-bending damage, and the typical value is 0.5 meters to 2 meters around the damage point; the first density threshold is used to screen the spatial aggregation of candidate events, the value of which is determined according to the expected distribution density of micro-bending damage per unit length of the fiber, and the typical value is at least 3 candidate events in the neighborhood; the past time range is used to limit the time window of historical event statistics, the length of which is set according to the system sampling period and the damage duration, and the typical value is 30 seconds to 5 minutes; the second density threshold is used to verify the time persistence of the candidate event, the value of which is determined according to the frequency of repeated appearance of the damage event within the time window, and the typical value is at least 5 candidate event marks within the time window.

[0044] Specifically, when the number of candidate damage events of a certain position point exceeds the first density threshold, it indicates that there is a spatial aggregation phenomenon in this area, but transient interference needs to be further ruled out. By counting the cumulative number of times that the position point is marked as a candidate damage event within a preset time window, if the number of times exceeds the second density threshold, it can be confirmed that the damage event has both spatial and temporal aggregation, which meets the physical characteristics of real micro-bending damage. For example, when the fiber is subjected to continuous mechanical stress, the micro-bending damage point will repeatedly trigger the candidate event mark in multiple sampling periods, and the damage area will form a spatial continuous distribution due to stress diffusion. On the contrary, transient interference such as vibration caused by passing vehicles will only form a local high-density event in a single sampling, which cannot meet the time persistence condition. Therefore, by dual verification of spatial density and time density, real damage and transient interference can be effectively distinguished, improving detection accuracy.

[0045] As a preferred embodiment, the scheme of the application is implemented as follows:

[0046] The spatial focus verification includes the following steps:

[0047] First, the number of candidate damage events within a preset radius of the position point is calculated. For example, 5 meters can be selected as the preset radius, and the number of points within the radius range marked as candidate damage events is counted.

[0048] Secondly, it is judged whether the number of candidate damage events is lower than a preset first density threshold. For example, the first density threshold can be set to 3 / 5 meters. If the number of candidate damage events is lower than the threshold, the position point is marked as an isolated interference event.

[0049] If the number of candidate damage events is not lower than the first density threshold, the number of times that the position point is marked as a candidate damage event within a preset past time range is further counted. For example, 1 hour in the past can be selected as the preset time range, and the cumulative number of times that the position point is marked as a candidate damage event within the 1 hour is counted.

[0050] Finally, it is judged whether the cumulative number of times exceeds a preset second density threshold. For example, the second density threshold can be set to 10 times / hour. If the cumulative number of times exceeds the threshold, the position point is marked as a microscopic bending damage event. Otherwise, the position point is marked as a transient interference event.

[0051] Through the above technical solutions, the application can effectively distinguish between real microscopic bending damage events and various interference events. Through spatial focus verification, isolated and randomly occurring interference signals can be excluded, improving the recognition accuracy of microscopic bending damage. At the same time, through statistical analysis in the time dimension, persistent microscopic bending damage and short-term transient interference can be further distinguished, thereby reducing the false positive rate and improving the reliability and practicality of the system. This multi-dimensional verification method can significantly improve the recognition ability of the distributed acoustic wave detection system for microscopic bending damage, providing more accurate basis for preventive maintenance of optical cable links.

[0052] The application further proposes to add temperature drift compensation verification before performing difference operation. The reference temperature distribution along the optical fiber is obtained, the temperature deviation value of each position point is calculated according to the reference temperature distribution, and it is judged whether the temperature deviation value exceeds a preset stability threshold. If it exceeds the stability threshold, the wavelength response ratio is calculated after temperature compensation is performed on the first wavelength phase change amount and the second wavelength phase change amount respectively; otherwise, the wavelength response ratio is directly calculated using the original phase change amount. The calculation process of performing temperature compensation on the phase change amount is: for the phase change amount of each wavelength, subtract the product of the thermal-optical coefficient of the wavelength and the temperature deviation value.

[0053] The reference temperature distribution is obtained by measuring the temperature distribution of the optical fiber in a steady state in advance, and the temperature deviation value is the difference between the current temperature and the reference temperature. The stability threshold is set according to the thermal expansion coefficient and the thermo-optic coefficient of the optical fiber material, and is usually set as the boundary value of the allowable temperature fluctuation range. The thermo-optic coefficient is the ratio of the change of the refractive index of the optical fiber material with temperature at different wavelengths, which is obtained by experimental calibration. The temperature compensation process separates the phase change component caused by temperature from the total phase change amount, and retains the phase change component caused by microscopic bending.

[0054] Specifically, when the temperature of a certain position point of the optical fiber drifts, the temperature deviation value of the position point exceeds the stability threshold, triggering the temperature compensation mechanism. The phase change amounts of the first wavelength and the second wavelength are respectively subtracted by the product of the respective thermo-optic coefficients and the temperature deviation value, eliminating the influence of temperature change on the phase demodulation result. The compensated phase change amount only reflects the mechanical deformation caused by microscopic bending, so that the wavelength response ratio calculated subsequently is closer to the theoretical range. For position points with stable temperature, the original phase change amount is directly used for calculation, avoiding unnecessary compensation operation. By dynamically judging the temperature drift state and selectively performing compensation, the accuracy of damage event identification is improved, and the consumption of computing resources is reduced.

[0055] As a preferred embodiment, the scheme of the present application is implemented as follows:

[0056] Before performing the difference operation, temperature drift compensation verification is added. First, the reference temperature distribution along the optical fiber is obtained, which can be measured by arranging multiple temperature sensors along the optical fiber. The temperature deviation value of each position point is calculated according to the reference temperature distribution, which can be obtained by taking the difference between the current measured temperature and the reference temperature as the temperature deviation value.

[0057] Then, it is judged whether the temperature deviation value exceeds the preset stability threshold, for example, the stability threshold can be set to ±0.5°C. If the temperature deviation value exceeds the preset stability threshold, the wavelength response ratio is calculated after temperature compensation is performed on the phase change amount of the first wavelength and the phase change amount of the second wavelength respectively. The calculation process of temperature compensation is: for the phase change amount of each wavelength, subtract the product of the thermo-optic coefficient of the wavelength and the temperature deviation value. The thermo-optic coefficient can be obtained by experiment.

[0058] If the temperature deviation value does not exceed the preset stability threshold, the wavelength response ratio is calculated directly using the original phase change amount, without temperature compensation.

[0059] By the above technical solution, the application can effectively eliminate the influence of temperature drift on micro-bending damage detection. By introducing a temperature drift compensation verification step, the phase change caused by temperature change and the phase change caused by real micro-bending damage can be accurately distinguished, thereby improving the accuracy and reliability of the detection. At the same time, this scheme can adaptively judge whether temperature compensation is needed, avoiding unnecessary calculation overhead and improving the efficiency of the system.

[0060] The application further proposes a method of dynamically optimizing the calibration coefficient based on the final marked micro-damage events and interference events.

[0061] The process of dynamically optimizing the calibration coefficient includes: calculating the average wavelength response ratio of historical damage events, calculating the deviation of the measured value from the median of the theoretical response ratio, judging whether the deviation is lower than the preset deviation threshold, if lower, keeping the calibration coefficient unchanged, otherwise adjusting the calibration coefficient according to the deviation direction. When the measured value is greater than the median of the theoretical response ratio, the calibration coefficient is increased by a preset proportion; when the measured value is less than the median of the theoretical response ratio, the calibration coefficient is decreased by a preset proportion. The adjustment amplitude is proportional to the ratio of the deviation to the median of the theoretical response ratio.

[0062] Specifically, the average wavelength response ratio of historical damage events is calculated by statistics of the amplitude ratio of all position points marked as micro-bending damage events. The median of the theoretical response ratio is determined in advance by the thermo-optic coefficient of the optical fiber material and the physical parameters of the two detection wavelengths. The deviation is calculated using the absolute difference or relative difference between the measured value and the median of the theoretical value. The deviation threshold is set according to the allowable wavelength response ratio fluctuation range of the system, for example, set to 5% of the theoretical response ratio range. When the deviation exceeds the threshold, the adjustment direction of the calibration coefficient is determined by the size relationship between the measured value and the median of the theoretical value. The adjustment amplitude is determined by the product of the preset proportion factor and the deviation ratio value, for example, the proportion factor is set to 0.1, and the deviation ratio value is the deviation divided by the median of the theoretical value, then the adjustment amount of the calibration coefficient is the product of the proportion factor and the deviation ratio value. This adjustment process is automatically executed after each detection period, so that the calibration coefficient can be dynamically corrected following the environmental changes, and the suppression effect of the differential operation on mode coupling interference is maintained.

[0063] As a preferred embodiment, the scheme of the application is implemented as follows:

[0064] Based on the final marked micro-damage events and interference events, the calibration coefficient is dynamically optimized. The process of dynamically optimizing the calibration coefficient includes:

[0065] First, the average wavelength response ratio of historical damage events is calculated, and the deviation of the measured value from the median of the theoretical response ratio is calculated. For example, the average wavelength response ratio of the last 100 damage events can be taken as the measured value, compared with the pre-set median of the theoretical response ratio 1.2, and the deviation is obtained.

[0066] Secondly, it is judged whether the deviation amount is lower than a preset deviation threshold. The deviation threshold can be set as 0.05. If the deviation amount is lower than 0.05, the current calibration coefficient is kept unchanged.

[0067] If the deviation amount is higher than 0.05, the calibration coefficient is adjusted according to the deviation direction: when the measured value is greater than the median of the theoretical response ratio, the calibration coefficient is increased by a preset proportion; when the measured value is less than the median of the theoretical response ratio, the calibration coefficient is decreased by a preset proportion. The adjustment amplitude is proportional to the ratio of the deviation amount to the median of the theoretical response ratio.

[0068] Through the above technical solutions, the application can dynamically optimize the calibration coefficient according to the actual measurement result, and improve the accuracy of micro-bending damage detection. Thus, the environmental changes and system drifts that may exist in the optical fiber link can be adapted, and the long-term stability of the detection system can be maintained. Further, by setting a reasonable deviation threshold and adjustment proportion, the system sensitivity can be maintained while avoiding instability caused by excessive adjustment.

[0069] The application further extracts a set of occurrence positions of non-bending interference events and a set of occurrence positions of isolated interference events, traverses each non-bending interference event position, searches whether there is an isolated interference event within a preset radius, and calculates the proportion of non-bending interference events in the neighborhood of the isolated interference event. It is judged whether the proportion exceeds a preset proportion threshold. If yes, it is determined that there is a systematic interference source, otherwise, the non-bending interference events and the isolated interference events are independently analyzed.

[0070] The extraction of the set of non-bending interference event positions is based on the judgment result of the amplitude ratio exceeding the theoretical wavelength response ratio range, and the extraction of the set of isolated interference event positions is based on the exclusion result of the candidate damage event in the spatial and temporal density verification. The setting of the preset radius is related to the acoustic wave propagation characteristics of the optical fiber, and is usually the typical influence range of the spatial focusing of the damage event. The determination of the proportion threshold depends on the statistical distribution law of the interference events in the actual environment, for example, by calibrating the proportion relationship between the systematic interference events and the random interference events in the historical data. The independent analysis of the non-bending interference events and the isolated interference events includes respectively constructing a time series or correlating other physical parameters for tracing.

[0071] Specifically, when there are isolated interference events in the neighborhood of the non-bending interference event location, the proportion of non-bending interference events in all interference events in the neighborhood is calculated to distinguish between local concentrated interference and global dispersed interference. If the proportion exceeds the threshold value, it indicates that there is a common factor that triggers multiple types of interference at the same time, such as a mechanical vibration source or an electromagnetic interference source, which needs to be marked as a systematic interference source for targeted shielding. If the proportion does not exceed the threshold value, the time correlation or environmental parameter correlation of the two types of events is further analyzed, such as judging periodic interference by the autocorrelation strength of the time interval of isolated interference events, or judging temperature-related interference by the amplitude ratio deviation of non-bending interference events combined with temperature changes. This process reduces the probability of misjudgment caused by local environmental interference through spatial correlation screening, and provides a data basis for the classification and suppression of interference sources.

[0072] As a preferred embodiment, the scheme of the present application is implemented as follows:

[0073] The set of occurrence positions of non-bending interference events and the set of occurrence positions of isolated interference events are extracted. For each non-bending interference event position, it is searched whether there is an isolated interference event within a preset radius. Specifically, the search radius can be set to 50 meters. For each non-bending interference event, the number of isolated interference events within 50 meters is counted. Further, the proportion of non-bending interference events in the neighborhood of isolated interference events is calculated. For example, if there are 100 non-bending interference events, 60 of which have isolated interference events within 50 meters, the proportion is 60%.

[0074] It is judged whether the proportion exceeds a preset proportion threshold. Thus, the proportion threshold can be set to 50%. If the calculated proportion exceeds 50%, it is determined that there is a systematic interference source. Otherwise, the non-bending interference events and the isolated interference events are analyzed independently.

[0075] Through the above technical scheme, the present application can effectively identify the existence of a systematic interference source. By analyzing the spatial correlation of non-bending interference events and isolated interference events, the interference caused by systematic factors and random interference can be distinguished. This method improves the classification accuracy of various interference events in the optical fiber link, and provides a reliable basis for subsequent interference elimination and system optimization. Further, this method balances the accuracy and efficiency of analysis by setting a reasonable search radius and proportion threshold, and is suitable for real-time monitoring of long-distance optical cable links.

[0076] The application further proposes a process of independently analyzing isolated interference events, including: constructing a time sequence of isolated interference events marked multiple times at the same location, and calculating the autocorrelation strength of the event interval; extracting the time interval sequence of adjacent events, selecting several time offsets T, and calculating the autocorrelation strength by calculating the average value of the product of the original interval sequence and the interval sequence offset by T; if there is a time offset T that makes the autocorrelation strength exceed the preset correlation threshold, it is determined to be periodic environmental interference, the time offset is recorded as the interference period, and the periodic interference is avoided; if the autocorrelation strength of all time offsets T does not exceed the preset correlation threshold, it is determined to be random transient interference.

[0077] Among them, the time sequence construction extracts the timestamp data of isolated interference events at the same location to generate an event interval sequence arranged in chronological order. The autocorrelation strength calculation uses a sliding window algorithm to perform point-by-point product summation of the interval sequence and the sequence delayed by T to obtain the correlation index under different time offsets. The periodicity determination compares the autocorrelation strength with the preset threshold, and triggers the periodic marking mechanism when the threshold is exceeded. The interference period recording adopts a database storage mode, and the time offset and the corresponding position information that meet the conditions are written into the non-volatile memory. The avoidance strategy generation module dynamically adjusts the detection pulse emission parameters and the noise threshold according to the recorded periodic parameters.

[0078] Specifically, when isolated interference events repeatedly occur at the same location, the event interval sequence is input into the autocorrelation calculation unit. For example, the interval sequence [10s, 10s, 10s] at time offset T=1, the product average value of the original sequence and the offset sequence is (10x10+10x10) / 2=100, and when the preset correlation threshold is 80, it is determined that there is periodicity. The interference period is recorded as 10 seconds, and the system automatically reduces the detection pulse emission frequency to 50% of the original value during the predicted interference period, and simultaneously increases the emission power by 20% during the non-interference period. The dynamic background noise threshold is adjusted in real time according to the sinusoidal modulation formula, and the modulation coefficient is set to 0.3, so that the threshold is automatically increased by 30% during the period of high incidence of interference. This mechanism effectively suppresses the influence of periodic interference on the detection system, while maintaining the detection sensitivity during the non-interference period. Random transient interference is counted by an independent event counter, and a warning signal is triggered when the number of events per unit time exceeds the alarm value.

[0079] As a preferred embodiment, the scheme of the application is implemented as follows:

[0080] The isolated interference events of multiple markings at the same position are constructed into a time series, and the autocorrelation strength of the event interval is calculated. First, the time interval sequence of adjacent events is extracted. Then, a plurality of time offsets T are selected, such as T = 1 minute, 5 minutes, 10 minutes, 30 minutes, 1 hour, etc. For each time offset T, the autocorrelation strength is calculated by calculating the product average of the original interval sequence and the interval sequence offset by T.

[0081] Further, it is judged whether there is a time offset T that makes the autocorrelation strength exceed a preset correlation threshold. For example, the preset correlation threshold can be set to 0.7. If there is a time offset T that makes the autocorrelation strength exceed 0.7, it is determined that it is a periodic environmental interference. At this time, the time offset T is recorded as the interference period, and the periodic interference is avoided.

[0082] Specifically, the avoidance of periodic interference can be achieved by adjusting the detection strategy. For example, the detection pulse emission frequency is reduced during the predicted high interference period, and the detection pulse emission power is increased during the low interference period. At the same time, the dynamic background noise threshold can be dynamically adjusted to adapt to the influence of periodic interference.

[0083] On the contrary, if the autocorrelation strength of all time offsets T does not exceed the preset correlation threshold 0.7, it is determined that it is a random transient interference. For random transient interference, other strategies can be used for processing, such as increasing the sampling number or adjusting the signal processing algorithm.

[0084] Through the above technical solutions, the present application can effectively distinguish between periodic environmental interference and random transient interference. For periodic environmental interference, by recording the interference period and taking corresponding avoidance measures, the false positive rate can be significantly reduced. For random transient interference, other appropriate processing methods can be used. Thus, the present application improves the accuracy and reliability of the optical cable link micro-bending damage detection, reduces the influence of environmental interference on the detection result, and provides more accurate information support for the maintenance and management of the optical fiber communication network.

[0085] The present application further proposes that for each non-bending interference event, the absolute deviation value of the actual amplitude ratio and the median value of the theoretical wavelength response ratio range is calculated; the temperature deviation value corresponding to the position point is obtained, and it is judged whether the temperature deviation value exceeds a preset stability threshold: if yes, it is determined that the event is a temperature-related interference event; otherwise, it is further judged whether the absolute deviation value exceeds a preset deviation threshold: if yes, it is determined to be a wavelength response system deviation event; otherwise, it is determined to be a random noise interference event.

[0086] The calculation of the actual amplitude ratio is based on the phase demodulated dual-wavelength phase variation data, and the temperature deviation value is derived from the reference temperature distribution monitoring data along the fiber line. The preset deviation threshold of the absolute deviation value is obtained by statistical analysis of historical data, and is usually set to 10% to 20% of the width of the theoretical wavelength response ratio range. The temperature stability threshold is set according to the thermal-optical coefficient of the fiber material and the measurement accuracy of the system, and a typical value is 0.5 to 2 degrees Celsius.

[0087] Specifically, when a non-bending interference event is identified, first, the absolute deviation value of the actual amplitude ratio of the position point from the theoretical median value is extracted. If the temperature deviation at this position exceeds the stability threshold, it indicates that temperature fluctuations cause abnormal phase variation, which is directly attributed to temperature-related interference events. When the temperature is in a stable state, the absolute deviation value is further analyzed: if the deviation exceeds the preset threshold, it indicates that there is an inherent deviation in the wavelength response system, which needs to trigger the calibration process; if it does not exceed the threshold, it is determined to be random noise interference. This process effectively distinguishes the three types of interference through the dual judgment mechanism of temperature state and deviation value, wherein the temperature compensation verification step can eliminate the influence of thermal effects on phase demodulation, and the deviation threshold judgment can identify system-level errors, thereby improving the accuracy of event classification.

[0088] Through the above technical solutions, the application realizes a three-level classification mechanism for non-bending interference events, effectively distinguishing phase distortion caused by temperature fluctuations, system wavelength response deviation, and random noise interference. Through the dual verification of temperature deviation and amplitude ratio deviation, false positives caused by a single criterion are avoided, solving the core problem of distinguishing pattern coupling noise from real damage signals in the prior art, and significantly reducing the false positive rate of the distributed acoustic wave detection system.

[0089] The application further proposes that for each non-bending interference event, the absolute deviation value of the actual amplitude ratio from the median value of the theoretical wavelength response ratio range is calculated; the temperature deviation value corresponding to the position point is obtained, and it is judged whether the temperature deviation value exceeds the preset stability threshold: if yes, the event is determined to be a temperature-related interference event; otherwise, it is further judged whether the absolute deviation value exceeds the preset deviation threshold: if yes, it is determined to be a wavelength response system deviation event; otherwise, it is determined to be a random noise interference event.

[0090] The calculation of the absolute deviation value is achieved by subtracting the actual amplitude ratio from the theoretical median value and taking the absolute value. The temperature deviation value is derived from the difference between the reference temperature distribution and the real-time temperature data along the fiber line, and the preset stability threshold is set according to the thermal expansion coefficient of the fiber material. The deviation threshold is determined by statistical analysis of historical noise events, for example, set to 30% of the width of the theoretical response ratio range. The judgment of temperature-related interference events is prioritized over system deviation and random noise, forming a layered verification logic.

[0091] Specifically, when a non-bending interference event is marked, first, the absolute deviation of the actual amplitude ratio from the theoretical median value is calculated. If the temperature deviation at this position exceeds the stability threshold, it indicates that the temperature change has a significant impact on the phase change amount, and is directly classified as a temperature-related interference. If the temperature is stable, further comparison is made between the absolute deviation and the deviation threshold: if the deviation exceeds the threshold, it indicates that there is a systematic deviation of the wavelength response ratio, and it is determined to be a system deviation event; if it does not exceed, it is considered to be random noise. For example, when the theoretical response ratio median value is 1.5, the actual ratio is 1.8 and the temperature is stable, the absolute deviation is 0.3. If the deviation threshold is 0.25, it is determined to be a system deviation event; if the actual ratio is 1.6 and the deviation threshold is 0.25, it is classified as random noise. This hierarchical judgment mechanism improves the accuracy of interference event classification by excluding temperature interference and system error.

[0092] The application further proposes a process for avoiding periodic interference, including: reducing the detection pulse emission frequency during the predicted high interference period, increasing the detection pulse emission power during the low interference period, and dynamically adjusting the dynamic background noise threshold, the adjustment formula being:

[0093]

[0094] wherein, is the interference period, is the modulation coefficient, is the dynamic background noise threshold.

[0095] As a preferred embodiment, the scheme of the application is implemented as follows: when periodic environmental interference is detected, the system identifies the interference period as 30 minutes in the time sequence. During the high interference period, the detection pulse emission frequency is reduced from the regular 10 kHz to 5 kHz, and the emission power is increased from 15 mW to 20 mW. The adjustment parameters of the dynamic background noise threshold are set as follows: the modulation coefficient a is 0.2, the initial threshold Th0 is set to 1 mV, and the time variable t is periodically modulated based on the interference period. The system actively suppresses high-frequency signal acquisition during the active interference period, and enhances the weak signal capture capability by increasing the light power during the low interference period.

[0096] Through the above technical scheme, the application effectively suppresses the interference of periodic environmental noise on damage detection. By dynamically adjusting the detection parameters and noise threshold, the system reduces invalid data acquisition during the high interference period and enhances signal sensitivity during the interference calm period, avoiding false positives caused by periodic interference while maintaining the high response characteristics of the system to real damage events. This adaptive mechanism enables the system to maintain stable detection accuracy in complex working conditions, solving the technical contradiction between sensitivity and false positive rate in the traditional method in a periodic interference environment.

[0097] Embodiment two:

[0098] As shown in the figure, the distributed acoustic wave detection system for micro-bending damage of optical cable link comprises: Figure 3

[0099] The signal acquisition module is configured to alternately emit detection light pulses of a first wavelength and a second wavelength to the optical fiber to be measured, and acquire a corresponding backscattering Rayleigh signal sequence; the first wavelength is less than the second wavelength.

[0100] The phase demodulation module is configured to perform phase demodulation on the backscattering Rayleigh signal sequence, and obtain a first wavelength phase change amount and a second wavelength phase change amount of each position point.

[0101] The difference operation module is configured to perform difference operation on the first wavelength phase change amount and the second wavelength phase change amount, and generate a difference bending characteristic signal.

[0102] The first judgment module is configured to calculate an instantaneous amplitude of the difference bending characteristic signal at each position point, and judge whether the instantaneous amplitude is lower than a preset dynamic background noise threshold; if lower than the preset threshold, mark as a background noise event.

[0103] The second judgment module is configured to calculate an amplitude ratio of the first wavelength phase change amount and the second wavelength phase change amount of the position point, and judge whether the amplitude ratio falls within a preset theoretical wavelength response ratio range; if within the range, mark as a candidate damage event, otherwise mark as a non-bending interference event.

[0104] The damage verification module is configured to perform spatial focusing verification on the candidate damage event, and judge whether the candidate damage event in the neighborhood of the position point exceeds a preset density threshold; if exceeding the preset threshold, mark as a micro-bending damage event, otherwise mark as an isolated interference event.

[0105] The above content is merely an example and description of the structure of the present application, and those skilled in the art can make various modifications or supplements or use similar ways to replace the described specific embodiments, as long as they do not deviate from the structure of the invention or exceed the scope defined by the present claims, which shall be within the protection scope of the present application.

[0106] In the description of the present specification, the description of the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the described specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner. ​

[0107] The preferred embodiments of the application disclosed above are only to help explain the present application. The preferred embodiments are not intended to be exhaustive or to limit the application to the precise form disclosed. Many modifications and variations are possible in light of the above teaching. It is intended that the scope of the application be limited not with this detailed description, but rather by the claims and the full range of equivalents to which such claims are entitled.

Claims

1. A distributed acoustic wave detection method for microscopic bending damage in optical cable links, characterized in that, Includes the following steps: Acquire the backscattering Rayleigh signal sequence corresponding to the alternating transmission of a first wavelength probe light pulse and a second wavelength probe light pulse to the optical fiber under test, wherein the first wavelength is shorter than the second wavelength. Phase demodulation was performed on the backscattered Rayleigh signal sequence to obtain the first wavelength phase change and the second wavelength phase change at each position point; A differential bending characteristic signal is generated by performing a differential operation based on the phase change of the first wavelength and the phase change of the second wavelength. Calculate the instantaneous amplitude of the differential bending characteristic signal at each location point, and determine whether the instantaneous amplitude is lower than the preset dynamic background noise threshold: if yes, mark it as a background noise event; otherwise, calculate the amplitude ratio of the first wavelength phase change to the second wavelength phase change at the location point. Determine whether the amplitude ratio falls within the preset theoretical wavelength response ratio range: if yes, mark it as a candidate damage event; otherwise, mark it as a non-bending interference event. Spatial focusing verification is performed on the candidate damage events to determine whether the candidate damage events in the neighborhood of the location point exceed a preset density threshold. If so, they are marked as micro-bending damage events; otherwise, they are marked as isolated interference events.

2. The distributed acoustic wave detection method for microscopic bending damage in optical cable links according to claim 1, characterized in that: The process of generating the differential bending feature signal includes: Obtain the initial preset calibration coefficients, which characterize the linear proportional relationship between the phase changes of the two wavelengths under mode coupling interference; subtract the product of the calibration coefficients and the phase changes of the first wavelength from the phase change of the second wavelength to obtain the differential bending characteristic signal.

3. The distributed acoustic wave detection method for microscopic bending damage in optical cable links according to claim 1, characterized in that: The spatial focusing verification includes: Calculate the number of candidate damage events within a preset radius of the location point, and determine whether the number of candidate damage events is lower than a preset first density threshold. If so, mark it as an isolated interference event. Otherwise, further count the number of times the location point has been marked as a candidate damage event within a preset past time range, and determine whether the number exceeds a preset second density threshold. If so, mark it as a micro-bending damage event; otherwise, mark it as a transient interference event.

4. The distributed acoustic wave detection method for microscopic bending damage in optical cable links according to claim 1, characterized in that: This also includes adding temperature drift compensation verification before performing the difference operation: The reference temperature distribution along the optical fiber is obtained, and the temperature deviation value at each location point is calculated based on the reference temperature distribution. It is then determined whether the temperature deviation value exceeds a preset stability threshold. If it does, temperature compensation is performed on the first wavelength phase change and the second wavelength phase change respectively, and the wavelength response ratio is calculated. Otherwise, the original phase change value is used directly to calculate the wavelength response ratio. The calculation process for temperature compensation of phase change is as follows: for the phase change of each wavelength, subtract the product of the thermo-optic coefficient of that wavelength and the temperature deviation value.

5. The distributed acoustic wave detection method for microscopic bending damage in optical cable links according to claim 2, characterized in that: It also includes dynamically optimizing calibration coefficients based on the final labeled microscopic damage events and interference events; The process of dynamically optimizing calibration coefficients includes: The average wavelength response ratio of historical damage events was statistically analyzed to calculate the deviation between the measured value and the median theoretical response ratio. Determine if the deviation is below the preset deviation threshold: if yes, keep the current calibration coefficient unchanged; otherwise, adjust the calibration coefficient according to the direction of the deviation. When the measured value is greater than the median of the theoretical response ratio, the calibration coefficient is increased by a preset ratio; when the measured value is less than the median of the theoretical response ratio, the calibration coefficient is decreased by a preset ratio; the adjustment range is proportional to the ratio of the deviation to the median of the theoretical response ratio.

6. The distributed acoustic wave detection method for microscopic bending damage in optical cable links according to claim 1, characterized in that: It also includes extracting the set of locations of non-bending interference events and the set of locations of isolated interference events, traversing each location of a non-bending interference event, searching for whether there is an isolated interference event within a preset radius, and calculating the proportion of non-bending interference events in the neighborhood of an isolated interference event. Determine whether the ratio exceeds a preset ratio threshold. If it does, a systemic interference source is identified; otherwise, non-bending interference events and isolated interference events are analyzed independently.

7. The distributed acoustic wave detection method for microscopic bending damage in optical cable links according to claim 6, characterized in that: The process of independently analyzing the isolated interference events includes: Construct time series for isolated interference events marked multiple times at the same location, and calculate the autocorrelation strength of the event intervals: extract the time interval sequence of adjacent events, select several time offsets T, and calculate the average of the product of the original interval sequence and the interval sequence offset T positions backward to obtain the autocorrelation strength. If a time offset T causes the autocorrelation intensity to exceed a preset correlation threshold, it is determined to be a periodic environmental disturbance. The time offset is recorded as the disturbance period, and the periodic disturbance is avoided. If the autocorrelation intensity of all time offsets T does not exceed the preset correlation threshold, it is determined to be a random transient disturbance.

8. The distributed acoustic wave detection method for microscopic bending damage in optical cable links according to claim 6, characterized in that: The process of independently analyzing the non-bending interference events includes: For each non-bending interference event, calculate the absolute deviation between its actual amplitude ratio and the median of the theoretical wavelength response ratio range; Obtain the temperature deviation value corresponding to the location point, and determine whether the temperature deviation value exceeds a preset stability threshold: if yes, the event is determined to be a temperature-related interference event; otherwise, further determine whether the absolute deviation value exceeds a preset deviation threshold: if yes, it is determined to be a wavelength response system deviation event; otherwise, it is determined to be a random noise interference event.

9. The distributed acoustic wave detection method for microscopic bending damage in optical cable links according to claim 7, characterized in that: The process of avoiding periodic interference includes: During predicted periods of high interference, the detection pulse transmission frequency is reduced; during periods of low interference, the detection pulse transmission power is increased, and the dynamic background noise threshold is dynamically adjusted using the following formula: in, For the interference period, The modulation coefficient, This is the dynamic background noise threshold.

10. A distributed acoustic wave detection system for microscopic bending damage in optical cable links, characterized in that: The distributed acoustic wave detection method for micro-bending damage in optical cable links as described in any one of claims 1-9 includes: The signal acquisition module is used to alternately transmit probe light pulses of the first wavelength and the second wavelength to the optical fiber under test to acquire the corresponding backscattered Rayleigh signal sequence; the first wavelength is shorter than the second wavelength. The phase demodulation module is used to perform phase demodulation on the backscattered Rayleigh signal sequence to obtain the first wavelength phase change and the second wavelength phase change at each position point. The differential operation module is used to perform differential operations based on the phase change of the first wavelength and the phase change of the second wavelength to generate a differential bending characteristic signal. The first judgment module is used to calculate the instantaneous amplitude of the differential bending feature signal at each location point and determine whether the instantaneous amplitude is lower than a preset dynamic background noise threshold; if it is lower than the preset threshold, it is marked as a background noise event. The second judgment module is used to calculate the amplitude ratio of the first wavelength phase change to the second wavelength phase change at the location point, and to determine whether the amplitude ratio falls within a preset theoretical wavelength response ratio range; if it meets the range, it is marked as a candidate damage event, otherwise it is marked as a non-bending interference event. The damage verification module is used to perform spatial focusing verification on the candidate damage events, and to determine whether the candidate damage events in the neighborhood of the location point exceed a preset density threshold; if they exceed the preset threshold, they are marked as micro-bending damage events, otherwise they are marked as isolated interference events.

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