Real-time leakage point early warning system with optical fiber embedded into intelligent pipeline

Abstract

The invention discloses a real-time leakage point early warning system for embedding an optical fiber into an intelligent pipeline, relates to the technical field of pipeline monitoring, solves the problem that an original light monitoring mode is easy to cause misjudgment signals, and judges whether discontinuous characteristic waves exist or not through waveform characteristic verification in a verification period. Distinguishing continuous leakage point oscillation from other short-term anomalies; the secondary verification center further identifies regular vibration and external random oscillation caused by a leakage point based on variance analysis of a fluctuation section time interval; the multi-level verification mechanism significantly reduces the probability of missed judgment and misjudgment, greatly improves the reliability and accuracy of leakage point early warning, and scientifically constructs an oscillation characteristic system based on an optical fiber signal oscillogram; the undetermined wave band is divided by using the fluctuation turning point, the characteristic value is calculated by combining the amplitude difference and the time interval, and the same characteristic wave band is clustered and divided according to the characteristic value, so that the characteristic interval is accurately determined, and a high-reliability reference model is provided for subsequent leakage point identification.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline monitoring, and specifically to a real-time leakage point warning system for optical fiber embedded intelligent pipelines. Background Art

[0002] In the fields of modern industry and people's livelihood, intelligent pipeline systems are widely used in key links such as oil and gas transportation, urban water supply, and heat transfer. The safe and stable operation of pipelines is of crucial importance; traditional pipeline leakage point detection methods, such as manual inspections and pressure monitoring, have problems such as low detection efficiency, poor real-time performance, and inability to accurately locate. With the development of optical fiber sensing technology, optical fiber-based pipeline leakage point monitoring systems have gradually become a research hotspot. By utilizing the characteristics of optical fibers being sensitive to changes in environmental physical quantities, real-time monitoring of the pipeline operation status can be achieved.

[0003] The application with the publication number CN112462657A discloses a smart pipeline big data collection, analysis, warning, and positioning system and method, including a cloud server, an above-ground detection device, and an underground detection device. The underground detection device includes a data detection optical fiber laid along the pipeline. Sensor groups are arranged on the data detection optical fiber at set positions. The data detection optical fiber is communicatively connected to the cloud server through an optical fiber monitoring and collection terminal, and the above-ground detection device is communicatively connected to the cloud server; the cloud server obtains and processes the detection data to achieve the detection, positioning, and warning of pipeline leakage points. By laying special optical fibers that can adapt to the pipeline network environment on the pipeline network, real-time data collection of the networked pipelines is carried out and big data analysis is performed to obtain the monitoring data of the pipeline network. For faults, they can be quickly identified and located, and real-time warnings can be issued, improving the intelligent monitoring of the pipeline network.

[0004] During the monitoring process of its intelligent pipeline, leakage point monitoring is generally based on corresponding sensors. However, in this monitoring method, the monitoring range is not comprehensive enough. When there is a leakage point in the pipeline section between some sensors, it will lead to incorrect monitoring. Currently, optical fibers are generally used for real-time monitoring of pipelines. During the actual monitoring process, when there are oscillations outside and inside the pipeline, the corresponding signal waveforms will be distorted, and the original monitoring method is prone to misjudging signals, resulting in inaccurate monitoring. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a real-time leakage point warning system for optical fiber embedded intelligent pipelines, which solves the problem that the original optical fiber monitoring method is prone to misjudging signals.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: A real-time leakage point warning system for optical fiber embedded intelligent pipelines, including:

[0007] Standard feature determination end, based on standard experimental data, for the oscillation characteristics associated with the intelligent pipeline under different liquid flow velocity states, the specific method is as follows:

[0008] Based on the optical fiber signal waveform diagram associated with the standard experimental data, calibrate the fluctuation turning points existing in the waveform diagram in sequence. The line trends on both sides of the waveband turning point are opposite;

[0009] Starting from the initial point of the optical fiber signal waveform diagram, calibrate the wavebands associated between adjacent fluctuation turning points as undetermined wavebands, and classify the characteristics of the undetermined wavebands in sequence from front to back: confirm the highest amplitude point and the lowest amplitude point of the undetermined waveband, and confirm the difference amplitude CZ between the highest amplitude point and the lowest amplitude point, where CZ > 0. Then confirm the time interval between the highest amplitude point and the lowest amplitude point, and record the time length of the time interval as TC. Use: Tz = CZ × C1 + TC × C2 to confirm the characteristic value Tz associated with this undetermined waveband, where C1 and C2 are both preset fixed coefficient factors;

[0010] Arrange the associated undetermined wavebands from front to back, and calibrate the characteristic values associated with different undetermined wavebands as Tz k , where k = 1, 2,..., n, and n represents the total number of undetermined wavebands. Those that satisfy: |Tz j - Tz j+1 | ≤ Y1 are calibrated as the same characteristic wavebands. Y1 is a preset value, and j ∈ [1, n - 1]. By analogy, confirm the several undetermined wavebands belonging to the same characteristic waveband in sequence from front to back, and select the highest amplitude and the lowest amplitude from the several undetermined wavebands to confirm the characteristic interval belonging to the same characteristic waveband;

[0011] Then confirm the characteristic intervals associated with other same characteristic wavebands in sequence, and store the several confirmed characteristic intervals;

[0012] Spectrum verification analysis end, obtain the waveform spectrum monitoring data generated by the optical fiber in real time, perform spectrum verification on the optical fiber waveform, and confirm the characteristic interval associated with the corresponding waveband. If there is no associated characteristic interval in the corresponding waveband, generate an abnormal signal. The specific method is as follows:

[0013] Based on the optical fiber waveform generated in real time, confirm the fluctuation turning points existing in this optical fiber waveform, and confirm the fluctuation segments between adjacent fluctuation turning points in sequence from front to back, and confirm the highest amplitude and the lowest amplitude associated with each fluctuation segment, and lock the fluctuation amplitude interval associated with this fluctuation segment;

[0014] Identify whether there is a corresponding characteristic interval within this fluctuation amplitude interval. If not, continue to confirm backward. If there is no corresponding characteristic interval in the next three consecutive fluctuation segments, generate an abnormal signal and transmit the generated abnormal signal to the abnormal verification center. If so, continue to confirm backward;

[0015] Based on the generated abnormal signal, the abnormal verification center determines a set of inspection periods, conducts characteristic verification and analysis on the associated waveforms generated within the inspection periods, and determines whether there are discontinuous characteristic waves within the associated waveforms. The specific method is as follows:

[0016] Based on the generated abnormal signal, starting from the generation moment of the abnormal signal, confirm a set of inspection periods backward, confirm some of the optical fiber waveforms generated within the inspection periods, and mark them as associated waveforms;

[0017] Successively confirm several fluctuation segments existing within the associated waveforms. Starting from the initial point of the associated waveform, successively confirm the fluctuation characteristics associated with different fluctuation segments backward: confirm the highest amplitude and the lowest amplitude associated with the corresponding fluctuation segment, and use fluctuation characteristic = highest amplitude - lowest amplitude;

[0018] Determine whether the fluctuation characteristics associated with adjacent fluctuation segments meet the preset threshold: respectively mark the two sets of fluctuation characteristics associated with adjacent fluctuation segments as B1 and B2. If B1 and B2 satisfy: |B1 - B2| ≤ preset threshold, no processing is required. If not, mark the subsequent fluctuation segment among the adjacent fluctuation segments as a discontinuous characteristic wave;

[0019] For each set of marked discontinuous characteristic waves, extract this discontinuous characteristic wave from the original arrangement of fluctuation segments, and then conduct forward and backward characteristic verification on the remaining fluctuation segments to identify whether there are discontinuous characteristic waves. By analogy, successively confirm several discontinuous characteristic waves existing within the associated waveforms;

[0020] Then confirm the fluctuation amplitude intervals of the several confirmed discontinuous characteristic waves, and identify whether all the confirmed sets of fluctuation amplitude intervals belong to the confirmed characteristic intervals. If all belong, generate an external oscillation signal through the signal display end. Otherwise, execute the secondary verification center;

[0021] The secondary verification center determines the time intervals associated with different fluctuation segments within the associated waveforms, and based on the clustering characteristics associated with the time intervals, evaluates whether to generate and display a missing point signal. The specific method is as follows:

[0022] Mark the successively appearing fluctuation segments within the associated waveforms, and determine the time intervals associated with the fluctuation segments from the marked fluctuation segments;

[0023] Variance confirmation is performed on a number of time intervals associated with a number of fluctuation segments to lock the characteristic variance, and the characteristic variance is verified against a preset value Y2. If the characteristic variance < Y2, a leakage point signal is generated and displayed through the signal display end. If the characteristic variance ≥ Y2, other oscillation signals are generated and displayed through the signal display end.

[0024] The present invention provides a real-time leakage point early warning system for optical fiber embedded intelligent pipelines. Compared with the prior art, it has the following beneficial effects:

[0025] The present invention scientifically constructs an oscillation feature system based on the optical fiber signal waveform diagram; uses the fluctuation turning points to divide the undetermined wave bands, combines the amplitude difference and time interval to calculate the characteristic values, and divides the same characteristic wave bands according to the clustering of the characteristic values, so as to accurately determine the characteristic interval, providing a highly reliable benchmark model for subsequent leakage point identification, and greatly improving the accuracy and standardization of feature analysis;

[0026] Through the waveform feature verification within the inspection period, it is judged whether there are discontinuous characteristic waves to distinguish continuous leakage point oscillations from other short-term anomalies; the secondary verification center is based on the variance analysis of the time intervals of the fluctuation segments to further identify the regular vibrations caused by leakage points and external random oscillations; this multi-level verification mechanism significantly reduces the probability of missed judgment and misjudgment, and greatly improves the reliability and accuracy of leakage point early warning;

[0027] Through the signal display end, targeted signal prompts are output, including external oscillation signals, leakage point signals, etc., providing clear and intuitive decision-making basis for operation and maintenance personnel, helping them quickly locate the nature of the problem, and taking measures such as maintenance and troubleshooting in a timely manner, effectively improving the pipeline operation and maintenance efficiency, and reducing safety risks and economic losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a schematic diagram of the principle framework of the present invention;

[0029] Figure 2 is a schematic diagram of the leakage point determination process of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0031] The First Embodiment

[0032] Please refer to Figure 1, this application provides a real-time leak point warning system for optical fiber embedded in an intelligent pipeline, including a standard feature determination end, a spectrum verification and analysis end, an anomaly verification center, a secondary verification center, and a signal display end. Among them, the standard feature determination end, the spectrum verification and analysis end, and the anomaly verification center are electrically connected in sequence from the output node to the input node, and the anomaly verification center is electrically connected to the input node of the signal display end or the secondary verification center respectively, and the secondary verification center is electrically connected to the input node of the signal display end;

[0033] Among them, the standard feature determination end, based on the standard experimental data generated during the data experiment stage of the intelligent pipeline, determines and stores the oscillation characteristics associated with the intelligent pipeline under different liquid flow velocity states. Specifically, during the experimental stage, the corresponding personnel operate to gradually adjust the liquid flow velocity inside the corresponding intelligent pipeline, and determine the oscillation spectrogram associated with each different adjustment process. Such processes belong to normal flow velocity processes, and there is no leakage in the pipeline. Therefore, the corresponding data generated during the experimental stage are all standard data, and the confirmed oscillation characteristics are all standard characteristics, which is convenient for subsequent feature verification to identify whether there is a leak point. The specific method for confirming the oscillation characteristics is as follows:

[0034] Based on the optical fiber signal waveform diagram associated with the standard experimental data, mark the fluctuation turning points existing in the waveform diagram in sequence. The line segments on both sides of the wave band turning point have opposite trends, that is, when the front line segment of the corresponding fluctuation turning point climbs upward, the subsequent line segment descends, and vice versa, when the front line segment of the subsequent corresponding fluctuation turning point descends, the subsequent line segment climbs upward;

[0035] Starting from the initial point of the optical fiber signal waveform diagram, mark the wave bands associated with adjacent fluctuation turning points as undetermined wave bands, and classify the characteristics of the undetermined wave bands in sequence from front to back: confirm the highest amplitude point and the lowest amplitude point of the undetermined wave band, and confirm the difference amplitude CZ between the highest amplitude point and the lowest amplitude point. Assume the amplitude associated with the highest amplitude point is F1, and the amplitude associated with the lowest amplitude point is F2. The difference amplitude = |F1 - F2|, and CZ > 0. Then confirm the time interval between the highest amplitude point and the lowest amplitude point, and record the time length of the time interval as TC. Use: Tz = CZ × C1 + TC × C2 to confirm the characteristic value Tz associated with this undetermined wave band. Both C1 and C2 are preset fixed coefficient factors, and their specific values are determined by the operator according to experience. Generally, C1 takes a value of 0.454, and C2 takes a value of 0.546;

[0036] Arrange the associated undetermined wave bands from front to back, and mark the characteristic values associated with different undetermined wave bands as Tz k , where k = 1, 2,..., n, and n represents the total number of undetermined wave bands, satisfying: |Tz j-Tz j+1 The adjacent undetermined bands with |≤Y1 are calibrated as the same characteristic bands, where Y1 is a preset value, and its specific value is determined by the operator according to experience. For j ∈ [1, n - 1], and so on. Several undetermined bands belonging to the same characteristic band are confirmed in sequence from front to back, and the highest amplitude and the lowest amplitude are selected from several undetermined bands to confirm the characteristic interval belonging to the same characteristic band (representing an oscillation characteristic);

[0037] Then, the characteristic intervals associated with other same - characteristic bands are confirmed in sequence, and several confirmed characteristic intervals are stored;

[0038] Specifically, different oscillation characteristics are associated with different undetermined bands, and there are same - characteristic representations between different undetermined bands. Then, based on the corresponding characteristic representations, the specific calibration of the same - characteristic bands can be carried out. From front to back, the specific division of the same - characteristic bands can be carried out in sequence to confirm the specific division of the characteristic intervals corresponding to different characteristics. Subsequently, based on the characteristic waveform diagram of real - time monitoring, the abnormality is confirmed;

[0039] Among them, for the spectrum calibration analysis terminal, the optical fiber is placed outside the intelligent pipeline, which can monitor the intelligent pipeline in real time, obtain the waveform spectrum monitoring data generated by the optical fiber in real time, calibrate the spectrum of the optical fiber waveform generated in real time, and confirm the characteristic interval associated with the corresponding band. If there is no associated characteristic interval in the corresponding band, an abnormal signal is generated and the abnormal calibration center is executed. Specifically, when the corresponding intelligent pipeline is operating normally and there is no leakage point in the water flow state, the associated waveforms are all in a normal state, and the numerical characteristics shown belong to the corresponding characteristic interval. In the subsequent calibration process, such characteristics can be used;

[0040] Among them, the specific method for spectrum calibration is as follows:

[0041] Based on the optical fiber waveform generated in real time, the fluctuation turning points existing in this optical fiber waveform are confirmed, and the fluctuation segments between adjacent fluctuation turning points are confirmed in sequence from front to back. The highest amplitude and the lowest amplitude associated with each fluctuation segment are confirmed, and the fluctuation amplitude interval associated with this fluctuation segment is locked;

[0042] And identify whether there is a corresponding characteristic interval for this fluctuation amplitude interval (that is, the case where the fluctuation amplitude interval belongs to the corresponding characteristic interval). If so, continue to confirm backward. If not, continue to confirm backward. If there is no corresponding characteristic interval for three consecutive fluctuation segments that appear subsequently, an abnormal signal is generated and transmitted to the abnormal verification center. When there is abnormal vibration, there will be a relatively regular waveform of continuous oscillation. Then, the three consecutive wave segments generated subsequently also do not belong to the corresponding confirmed standard interval. Therefore, abnormal verification is required, and comprehensive analysis is carried out to evaluate whether there is a leak point in this pipeline;

[0043] Specifically, when the waveform vibrates, the generated vibration amplitude far exceeds the corresponding confirmed characteristic interval. Then, abnormal confirmation is required, and the corresponding abnormal signal is locked. The situation where the corresponding amplitude change does not belong to the corresponding characteristic interval means that the vibration situation of the corresponding optical fiber signal far exceeds the originally determined standard range.

[0044] Among them, the abnormal verification center, based on the generated abnormal signal, confirms a set of inspection periods, conducts characteristic verification and analysis on the associated waveforms generated within the inspection period, and confirms whether there are discontinuous characteristic waves within the associated waveforms. And based on different confirmation results, different subsequent processing terminals (signal display terminal or secondary verification center) are executed. Specifically, when there is a leak point, the liquid flows outwards, generating continuous and uninterrupted oscillation waves. Then, there is no discontinuous situation for such oscillation waves, unless the liquid inflow in the corresponding channel stops, but this situation generally does not occur. The specific method for confirmation is as follows:

[0045] Based on the generated abnormal signal, starting from the generation moment of the abnormal signal, confirm a set of inspection periods backward. The inspection period is a preset period, which is determined in advance by relevant operators according to experience, generally taking a value of 2 - 3 minutes. Confirm some of the optical fiber waveforms generated within the inspection period and label them as associated waveforms;

[0046] Successively confirm several fluctuation segments existing in the associated waveforms (based on the specific confirmation of the corresponding fluctuation turning points, the fluctuation segments between adjacent fluctuation turning points can be locked). Starting from the initial point of the associated waveform, successively confirm the fluctuation characteristics associated with different fluctuation segments backward: confirm the highest amplitude and the lowest amplitude associated with the corresponding fluctuation segment, and use the fluctuation characteristic = highest amplitude - lowest amplitude;

[0047] Confirm whether the fluctuation characteristics associated with adjacent fluctuation segments meet the preset threshold: respectively label the two groups of fluctuation characteristics associated with adjacent fluctuation segments as B1 and B2. If B1 and B2 satisfy: |B1 - B2| ≤ preset threshold, no processing is required. If not, mark the subsequent fluctuation segment among the adjacent fluctuation segments as a discontinuous characteristic wave;

[0048] For each calibrated set of discontinuous characteristic waves, extract this discontinuous characteristic wave from the original wave segment arrangement, and then perform front and back characteristic verification on the remaining wave segments to identify whether there are discontinuous characteristic waves. And so on, confirm the several discontinuous characteristic waves existing in the associated waveform in sequence. For example, assume that the wave segments associated with a set of associated waveforms are {D1, D2, D3, D4, D5, D6, D7, D8}. Start from the front and confirm backward. First, identify that D3 belongs to the discontinuous characteristic wave. Then extract D3, and perform front and back characteristic verification on D2 and D4 to identify whether D4 belongs to the discontinuous characteristic wave. And so on, confirm the discontinuous characteristic waves existing in this associated waveform in sequence;

[0049] Then confirm the fluctuation amplitude intervals of the several confirmed discontinuous characteristic waves (the confirmation method is the same as the fluctuation amplitude interval associated with the wave segment, and confirm the associated amplitude interval through the highest amplitude and the lowest amplitude), and identify whether the several groups of confirmed fluctuation amplitude intervals all belong to the confirmed characteristic intervals. If they all belong, generate an external oscillation signal through the signal display end. If not, execute the secondary verification center. The reason for performing secondary verification processing here is that during the corresponding fluctuation oscillation process, if there are discontinuous waves with different characteristics and these discontinuous waves do not belong to the previously confirmed characteristic intervals, then these discontinuous waves may also be caused by other oscillations. Therefore, secondary verification analysis is still required. If it belongs to the corresponding characteristics, it means that the external oscillation is obvious and does not belong to the corresponding leakage point situation, then directly perform signal display.

[0050] Among them, combined with Figure 2 , the secondary verification center, confirm the time intervals associated with different wave segments in the associated waveform, and based on the clustering characteristics associated with the time intervals, evaluate whether to generate a leakage point signal and display it. The specific method for evaluation is as follows:

[0051] Calibrate the wave segments that appear in sequence from the associated waveform, and determine the time intervals associated with the wave segments from the calibrated wave segments;

[0052] And perform variance confirmation on the several time intervals associated with the several wave segments, lock the characteristic variance, and verify the characteristic variance with the preset value Y2. If the characteristic variance < Y2, generate a leakage point signal and display it through the signal display end, indicating that there is an influence of water flow leakage and actual inspection and analysis are required to evaluate whether there is a corresponding water leakage situation in the corresponding pipeline;

[0053] On the contrary, generate other oscillation signals and display them through the signal display end. This situation may be that the pipeline itself is pushed or pulled by other objects, and such irregular oscillation fluctuations will occur.

[0054] For some of the data in the above formula, dimensional quantities are removed for numerical calculations. At the same time, the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0055] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A real-time leak point warning system for optical fiber embedded in an intelligent pipeline, characterized in that, Including: A standard feature determination end, based on standard experimental data, for the oscillation features associated with the intelligent pipeline under different liquid flow velocity states; A spectrum verification analysis end, which obtains in real time the waveform spectrum monitoring data generated by the optical fiber, verifies the spectrum of the optical fiber waveform, confirms the characteristic interval associated with the corresponding wavelength band, and if there is no associated characteristic interval in the corresponding wavelength band, generates an abnormal signal; An abnormal verification center, based on the generated abnormal signal, confirms a set of inspection periods, conducts characteristic verification analysis on the associated waveforms generated within the inspection periods, and confirms whether there are discontinuous characteristic waves in the associated waveforms; A secondary verification center, confirms the time intervals associated with different fluctuation segments in the associated waveforms, and based on the clustering characteristics associated with the time intervals, determines whether to generate a leakage point signal and display it.

2. The real-time leak point warning system for an optical fiber embedded intelligent pipeline according to claim 1, wherein The specific method for the standard feature determination end to confirm the oscillation features is as follows: Based on the optical fiber signal waveform diagram associated with the standard experimental data, the fluctuation turning points existing in the waveform diagram are sequentially calibrated, and the line trends on both sides of the wavelength band turning points are opposite; Starting from the initial point of the optical fiber signal waveform diagram, the wavelength bands associated with adjacent fluctuation turning points are calibrated as undetermined wavelength bands, and the features of the undetermined wavelength bands are classified sequentially from front to back: confirm the highest amplitude point and the lowest amplitude point of the undetermined wavelength band, and confirm the difference amplitude CZ between the highest amplitude point and the lowest amplitude point, where CZ>0, then confirm the time interval between the highest amplitude point and the lowest amplitude point, record the time length of the time interval as TC, and use: Tz = CZ×C1 + TC×C2 to confirm the characteristic value Tz associated with this undetermined wavelength band, where C1 and C2 are both preset fixed coefficient factors; Arrange the associated pending bands from front to back, and calibrate the eigenvalue associated with different pending bands as Tz k , where k = 1, 2, ……, n, and n represents the total number of pending bands, and it will satisfy: |Tz j - Tz j+1 | ≤ Y1 of adjacent pending bands are calibrated as the same characteristic bands, where Y1 is a preset value, and j ∈ [1, n - 1], and so on. Confirm several pending bands belonging to the same characteristic band in sequence from front to back, and select the highest amplitude and the lowest amplitude from several pending bands, and confirm the characteristic interval belonging to the same characteristic band; Then, the characteristic intervals associated with other same-feature wavelength bands are sequentially confirmed, and the confirmed several characteristic intervals are stored.

3. The real-time leak point warning system for optical fiber embedded intelligent pipeline according to claim 1, characterized in that, The specific method for the spectrum verification analysis end to generate an abnormal signal is as follows: Based on the optical fiber waveform generated in real time, confirm the fluctuation turning points existing in this optical fiber waveform, and sequentially confirm the fluctuation segments between adjacent fluctuation turning points from front to back, and confirm the highest amplitude and the lowest amplitude associated with each fluctuation segment, and lock the fluctuation amplitude interval associated with this fluctuation segment; And identify whether there is a corresponding characteristic interval in this fluctuation amplitude interval. If not, continue to confirm backward. If there are no corresponding characteristic intervals in the three consecutive fluctuation segments that appear subsequently, generate an abnormal signal and transmit the generated abnormal signal to the abnormal verification center.

4. The real-time leakage point warning system for optical fiber embedded intelligent pipeline according to claim 3, characterized in that, If there is a corresponding characteristic interval in this fluctuation amplitude interval, continue to confirm backward.

5. The real-time leakage point warning system for optical fiber embedded intelligent pipeline according to claim 1, characterized in that, The specific method for the abnormal verification center to confirm whether there are discontinuous characteristic waves in the associated waveforms is as follows: Based on the generated abnormal signal, starting from the generation moment of the abnormal signal, confirm a set of inspection periods backward, confirm a part of the optical fiber waveforms generated within the inspection periods, and calibrate them as associated waveforms; Confirm the several fluctuation segments in the associated waveform in turn, starting from the initial point of the associated waveform, and confirm the fluctuation characteristics associated with different fluctuation segments in turn: confirm the highest amplitude and the lowest amplitude associated with the corresponding fluctuation segment, and use the fluctuation characteristic = highest amplitude - lowest amplitude; Confirm whether the fluctuation characteristics associated with adjacent fluctuation segments meet the preset threshold: mark the two sets of fluctuation characteristics associated with adjacent fluctuation segments as B1 and B2 respectively. If B1 and B2 satisfy: |B1-B2|≤preset threshold, no processing is required. If not, the subsequent fluctuation segments in the adjacent fluctuation segments are recorded as discontinuous characteristic waves. Each time a group of intermittent characteristic waves is calibrated, the intermittent characteristic waves are extracted from the original wave segment arrangement, and the remaining wave segments are checked for front and back characteristics to identify whether there are intermittent characteristic waves. Similarly, several intermittent characteristic waves existing in the associated waveform are confirmed in turn. Then the fluctuation amplitude intervals of the confirmed several intermittent characteristic waves are confirmed, and it is identified whether the confirmed several groups of fluctuation amplitude intervals all belong to the confirmed characteristic intervals. If they all belong, an external oscillation signal is generated through the signal display terminal.

6. The real-time leak point warning system for an optical fiber embedded intelligent pipeline according to claim 5, wherein, If the confirmed groups of fluctuation amplitude intervals do not all belong to the confirmed characteristic intervals, a secondary verification center is performed.

7. The real-time leak point warning system for optical fiber embedded intelligent pipeline according to claim 1, characterized in that, The specific method of the secondary verification center to assess whether a leakage signal is generated is: Demarcating the fluctuation segments that appear in sequence in the associated waveform, and determining the time intervals associated with the fluctuation segments from the demarcated fluctuation segments; The variance of several time intervals associated with several fluctuation segments is confirmed, the characteristic variance is locked, and the characteristic variance is verified with the preset value Y2. If the characteristic variance is less than Y2, a leakage signal is generated and displayed through the signal display terminal.

8. The real-time leakage point warning system for optical fiber embedded intelligent pipeline according to claim 7, characterized in that, If the characteristic variance is ≥ Y2, other oscillation signals are generated and displayed through the signal display terminal.

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