A pipeline corrosion condition monitoring system

Abstract

This invention discloses a pipeline corrosion monitoring system, belonging to the field of distributed acoustic sensing, comprising sensing optical fibers, communication optical fibers, and a distributed acoustic sensing host. This invention uses a distributed optical fiber sensing host to collect signals from normal pipeline operation. The sensing optical fibers are divided into multiple sensing intervals. Each sensing interval includes a first sensing optical fiber unit that spirals back and forth in a wave pattern covering the outer side of the pipe wall under test, and a second sensing optical fiber unit along the axis. Data augmentation algorithms are used to improve the perception of the encapsulation structure and train an initial machine learning model. When the model determines that the signal deviates from the normal range, it is identified as suspected corrosion. High-precision location of the suspected corrosion point is achieved based on the index of the suspected corrosion sensing structure. This invention can enhance sensing sensitivity, improve construction efficiency, and achieve high-precision, intelligent identification and location of pipeline corrosion status without prior information.

Description

Technical Field

[0001] This invention belongs to the field of pipeline monitoring using distributed fiber optic acoustic sensing, and more specifically, relates to a pipeline corrosion status monitoring system. Background Technology

[0002] Pipelines play a vital role in energy transportation, urban infrastructure, and industrial production, serving as essential infrastructure for daily life. my country's operational pipelines are distributed throughout the country, but with increasing years of operation, they are highly susceptible to corrosion from various media, environments, and electrochemical sources, leading to varying degrees and types of corrosion problems. Pipeline corrosion results in thinning of the pipe wall and decreased strength, and in severe cases, can cause leaks, ruptures, and other safety accidents, causing significant economic losses and adverse environmental impacts. Therefore, real-time and accurate monitoring of pipeline corrosion is crucial. Existing monitoring technologies typically include acoustic emission, ground-penetrating radar, thermal imaging, and inspection robots. However, these methods suffer from limitations such as small detection ranges, large blind spots, and difficulty in real-time monitoring of pipeline corrosion. Therefore, existing pipeline corrosion monitoring technologies generally have certain shortcomings.

[0003] Therefore, in response to the need for long-distance, large-scale, and real-time monitoring of pipeline corrosion, distributed optical fiber sensing technology stands out from many monitoring technologies due to its advantages such as high sensitivity, continuous large-scale coverage, and strong anti-interference ability. It can comprehensively and in real-time monitor pipeline corrosion and ensure pipeline safety.

[0004] However, in practical engineering applications of pipeline monitoring, distributed fiber optic sensing technology still faces many challenges. For example, in the selection of fiber optic deployment schemes, if a straight-line fiber optic deployment scheme is directly adopted, such as the structure proposed in patent CN220355187U, it will lead to a decrease in the sensitivity of pipeline circumferential monitoring and a tendency for missed detections. If a spiral fiber optic deployment scheme is adopted, such as the fiber optic deployment scheme mentioned in patent CN117705167A, although it can improve the sensing sensitivity, the construction efficiency is extremely low and the time cost is too high, making it particularly difficult to apply to long-distance scenarios such as pipelines. In addition, traditional monitoring methods still have certain limitations in the accuracy of identifying and locating pipeline corrosion. For example, as mentioned in patent CN117743765A, the use of a large peak value for positioning means that the propagation speed of sound waves in the pipeline is not constant, which can easily lead to large errors.

[0005] In summary, although distributed optical fiber sensing technology can meet the needs of pipeline corrosion monitoring well, there is still room for improvement in terms of optical fiber deployment, positioning, and intelligent judgment. In practical applications, a pipeline corrosion status monitoring, judgment, and positioning method with high construction efficiency and real-time intelligence is needed. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a pipeline corrosion status monitoring system, which aims to solve the problems of high construction difficulty, low efficiency and insufficient accuracy of identification and positioning in the existing pipeline corrosion status monitoring distributed fiber optic sensing technology.

[0007] To achieve the above objectives, the present invention provides a pipeline corrosion status monitoring system, comprising: a sensing optical fiber, a communication optical fiber, and a distributed acoustic wave sensor host; The sensing optical fiber is laid on the outside of the pipe wall under test and divided into multiple continuous sensing intervals to sense vibration information at different locations of the pipe and locate subsequent corrosion events. The two ends of the communication optical fiber are respectively connected to the sensing optical fiber and the distributed acoustic wave sensing host, and are used to transmit optical signals between the sensing optical fiber and the distributed acoustic wave sensing host. The distributed acoustic wave sensor host is used to emit probe light and receive reflected light. The probe light is transmitted through communication optical fiber and then enters sensing optical fiber. During the transmission process in the sensing optical fiber, Rayleigh scattering continuously generates scattered light in various directions. The reflected light is the light scattered back along the sensing optical fiber from the scattered light. The reflected light carries pipeline vibration information during the transmission process in the sensing optical fiber and is then received by the distributed acoustic wave sensor host through the communication optical fiber. The distributed acoustic wave sensor host is also used to recover pipeline vibration information from the reflected light and to identify pipeline corrosion status. Each sensing interval includes a first sensing optical fiber unit and a second sensing optical fiber unit that alternately follow the distribution direction of the sensing optical fiber. The first sensing optical fiber unit covers the outer side of the pipe wall under test in a wave-like pattern, and the second sensing optical fiber unit covers the outer side of the pipe wall under test along the axial direction of the pipe under test. The second sensing optical fiber unit includes... n Segment length is l The optical fiber, through the first n The sensing signal enhancement factor of the fiber segment is set to This is used to enhance the data of the pipeline vibration information carried by the reflected light.

[0008] Furthermore, each sensing zone also includes: a sensing fiber optic enhancement and encapsulation structure covering the first sensing fiber optic unit; n It is a positive integer greater than or equal to 2.

[0009] Furthermore, the sensing fiber optic enhancement packaging structure uses an elastic material; preferably, the elastic material is polyurethane, silicone rubber, or butyl rubber. The first sensing fiber unit is attached to the inner surface of the elastic material in a wavy, spiraling pattern, wherein the amplitude of the wave crests and troughs is equal to the perimeter of the pipe cross-section, ensuring that the fiber covers the circumferential range of the pipe and facilitating the installation of the elastic material. The elastic material covers the outer wall of the pipe to be tested, and the elastic material should be a polyurethane material with a low Young's modulus, so that the signal is enhanced after being transmitted from the outer wall of the pipe to the elastic material.

[0010] Furthermore, the distributed acoustic wave sensing host includes: The trained machine learning model is used to obtain the pipe state of each sensing interval based on the pipe vibration information at the current sampling time of each sensing interval, wherein the pipe state is normal or suspected corrosion. The positioning module is used to obtain the index of the encapsulation structure of the corresponding sensing area when the pipeline is suspected of being corroded, so as to locate the corrosion. The training of the machine learning model includes: At multiple sampling times, pipeline vibration information of a normal pipeline is collected, and the pipeline vibration information is augmented. The augmented pipeline vibration information is used as training data to train the original machine learning model, resulting in a trained model. After verifying and confirming the corrosion status (including corrosion type, degree, and cause), the relevant parameters are automatically updated to the database, improving the corrosion event branch of the machine learning model and continuously enhancing the accuracy of subsequent identification.

[0011] Furthermore, the training of the machine learning model also includes: The vibration information of the pipeline suspected of corrosion points is used as a new input to the machine learning model, and the machine learning model parameters are retrained and updated.

[0012] Furthermore, the pipeline vibration information is augmented, including: Will n Segment length is l Signal measured by optical fiber , The signal measured by the corresponding sensing fiber optic sensitization packaging structure By performing exponential superposition, an enhanced signal is obtained. : .

[0013] Further, in step S4, the index of the suspected corrosion encapsulation structure is obtained, and the suspected corrosion points in the pipeline are located based on the index, including: obtaining the sensing fiber optic sensitization encapsulation structure corresponding to the suspected corrosion. Therefore, the location area of ​​the suspected corrosion points in the pipeline is as follows:

[0014] in, L The length of the package structure, i This is an index showing a suspected corroded packaging structure.

[0015] Compared with the prior art, the above-described technical solutions conceived in this invention can achieve the following beneficial effects: 1. This invention provides a pipeline corrosion monitoring system that employs distributed optical fiber sensing technology. By laying sensing optical fibers on the pipe wall under test, it senses pipeline vibration information. Different regions of the sensing interval have different sensitivities. The first sensing optical fiber unit is a curved segment sensing optical fiber, which is wavy and coiled on the surface of an elastic material. This design significantly improves the circumferential monitoring sensitivity of the pipeline, avoiding the low circumferential sensitivity problem of straight-line deployment schemes, and can capture weak corrosion signals. The second sensing optical fiber unit is a straight segment sensing optical fiber. While the straight segment sensing optical fiber has lower sensitivity, its signal attenuation law is clear, providing reference information for spatial continuity. By utilizing this preset difference in sensing intensity during signal recovery, the system can fuse and enhance reflected light signals from different intervals. Because different sensing intervals are set, the collected pipeline vibration information can be matched with the corresponding pipe segment intervals, obtaining the pipeline location information corresponding to the pipeline vibration information while avoiding crosstalk caused by data transmission from different locations, improving the data signal-to-noise ratio, and resulting in higher recognition accuracy in subsequent pipeline corrosion status identification.

[0016] 2. This invention designs a sensitivity-enhancing encapsulation structure specifically for pipeline monitoring. The sensing fiber optic sensitivity-enhancing encapsulation structure uses polyurethane, silicone rubber, or butyl rubber, which have low Young's modulus characteristics (typically in the range of several...). MPa Up to dozens MPa The elastic material (within a certain range) has good flexibility, aging resistance, and strong adhesion to the pipe surface, and can enhance the vibration transmission effect.

[0017] 3. The method for monitoring pipeline corrosion status using the above-mentioned pipeline corrosion status monitoring system provided by the present invention enhances the pipeline vibration information data, improves the sensing capability of the encapsulation structure, and the continuously updated machine learning model training library ensures that the system can identify pipeline corrosion status efficiently over a long period of time. This achieves the beneficial effect of improving construction efficiency and identification accuracy while ensuring sensing sensitivity, and realizes high-precision, intelligent identification and location of pipeline corrosion. Attached Figure Description

[0018] Figure 1 A structural diagram of a pipeline corrosion status monitoring system provided by the present invention; Figure 2 A schematic diagram of the sensing fiber optic enhancement packaging structure provided by the present invention; Figure 3 A flowchart of the automatic update method for machine learning models provided by the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0020] This invention provides a pipeline corrosion status monitoring system, such as... Figure 1 As shown, it includes: sensing optical fiber, communication optical fiber, and distributed acoustic wave sensing host; The sensing optical fiber is laid on the outside of the pipe wall under test and divided into multiple continuous sensing intervals to sense vibration information at different locations of the pipe and locate subsequent corrosion events. The two ends of the communication optical fiber are respectively connected to the sensing optical fiber and the distributed acoustic wave sensing host, and are used to transmit optical signals between the sensing optical fiber and the distributed acoustic wave sensing host. The distributed acoustic wave sensor host is used to emit probe light and receive reflected light. The probe light is transmitted through communication optical fiber and then enters sensing optical fiber. During the transmission process in the sensing optical fiber, Rayleigh scattering continuously generates scattered light in various directions. The reflected light is the light scattered back along the sensing optical fiber from the scattered light. The reflected light carries pipeline vibration information during the transmission process in the sensing optical fiber and is then received by the distributed acoustic wave sensor host through the communication optical fiber. The distributed acoustic wave sensor host is also used to recover pipeline vibration information from the reflected light and to identify pipeline corrosion status. Each sensing interval includes a first sensing optical fiber unit and a second sensing optical fiber unit that alternately follow the distribution direction of the sensing optical fiber. The first sensing optical fiber unit covers the outer side of the pipe wall under test in a wave-like pattern, and the second sensing optical fiber unit covers the outer side of the pipe wall under test along the axial direction of the pipe under test. The second sensing optical fiber unit includes... n Segment length is l The optical fiber, through the first n The sensing signal enhancement factor of the fiber segment is set to This is used to enhance the data of the pipeline vibration information carried by the reflected light.

[0021] Furthermore, each sensing interval also includes: a sensing fiber optic enhancement and encapsulation structure covering the first sensing fiber optic unit, wherein... nIt is a positive integer greater than or equal to 2. In this embodiment, 2 is preferred, but in practical applications it can be adjusted according to factors such as pipe diameter and monitoring accuracy requirements. n The value of can be adjusted. For example, when the pipe diameter is large or a higher spatial resolution is required, it can be appropriately increased. n Value or decrease l Value; conversely, it can be reduced. n Value or increase l The alternating arrangement of "encapsulation + bare fiber" not only utilizes the high sensitivity of the encapsulation structure to capture weak corrosion signals, but also achieves spatial continuity of the signal through the bare fiber segments, providing multi-dimensional information for subsequent data enhancement.

[0022] Furthermore, such as Figure 2 As shown, the sensing fiber optic enhancement packaging structure is made of elastic material; the first sensing fiber unit is attached to the inner surface of the elastic material in a wave-like spiral pattern.

[0023] The wave-shaped peaks and troughs are designed with amplitudes equal to the perimeter of the cross-section of the pipe being measured. This design significantly improves the monitoring sensitivity in the circumferential direction of the pipe, avoiding the problem of low circumferential sensitivity in straight-line layout schemes. Furthermore, compared to traditional spiral layouts, wave-shaped layouts are more convenient and efficient to construct, requiring only the application of elastic material to the pipe surface, eliminating the need for complex fiber optic winding operations on-site, making it particularly suitable for rapid deployment of long-distance pipelines.

[0024] The elastic material of the sensing fiber optic enhancement packaging structure should possess low Young's modulus characteristics to enhance vibration transmission. In this embodiment, polyurethane is preferred because of its low Young's modulus (typically in the range of several milliseconds). MPa Up to dozens MPa It has good flexibility, aging resistance, and strong adhesion to the pipe surface. In practical applications, other elastic materials with similar properties, such as silicone rubber and butyl rubber, can also be selected, as long as the signal is effectively enhanced after being transmitted from the outer wall of the pipe to the elastic material.

[0025] Furthermore, such as Figure 3 As shown, the distributed acoustic wave sensing host includes: The trained machine learning model is used to obtain the pipe state of each sensing interval based on the pipe vibration information at the current sampling time of each sensing interval. In this embodiment, the pipe state is divided into two categories: "normal" and "suspected corrosion". However, the model can also be extended to multi-classification (such as distinguishing corrosion types). The positioning module is used to obtain the index of the encapsulation structure of the corresponding sensing area when the pipeline is suspected of being corroded, so as to locate the corrosion. The training of the machine learning model includes: At multiple sampling times, pipeline vibration information of a normal pipeline is collected, and the pipeline vibration information is augmented. The data-enhanced pipeline vibration information is used as training data to train the original machine learning model. During training, all normal samples are labeled as "normal", and the categories can be balanced by synthetic minority class oversampling technology to obtain a well-trained machine learning model.

[0026] Furthermore, the training of the machine learning model also includes: By using pipeline vibration information from suspected corrosion sites as new input to the machine learning model for incremental updates, the model gradually improves its ability to distinguish various corrosion events, continuously enhancing the accuracy of subsequent identifications. This self-learning mechanism enables the system to adapt to changes in corrosion characteristics in different pipelines and environments, maintaining high accuracy over the long term.

[0027] Furthermore, the pipeline vibration information is augmented, including: Will n Segment length is l Signal measured by optical fiber , The signal measured by the corresponding sensing fiber optic sensitization packaging structure By performing exponential superposition, an enhanced signal is obtained. : .

[0028] in i Indicates the first i Each sensing range, the enhanced signal In the first sensing fiber, the signal will gradually attenuate as the transmission distance increases, so an attenuation coefficient needs to be assigned; secondly, the greater the distance between the second sensing fiber and the first sensing unit, the smaller the impact, so the weight assigned to the attenuation coefficient is lower.

[0029] Further, in step S4, the index of the suspected corrosion encapsulation structure is obtained, and the suspected corrosion points in the pipeline are located based on the index, including: obtaining the sensing fiber optic sensitization encapsulation index corresponding to the suspected corrosion. j Therefore, the area of ​​the pipe where suspected corrosion occurred is:

[0030] in, L This represents the length of the encapsulation structure.

[0031] The workflow of this system is as follows: 1. Deployment phase: The encapsulation structure and fiber optic segments are alternately laid on the surface of the pipe, and the communication fiber optic cable is connected to the distributed acoustic wave sensor host; 2. Initial training phase: Vibration signals during normal pipeline operation are collected and trained using data augmentation to create an initial machine learning model; 3. Real-time monitoring phase: The host continuously collects signals, amplifies them in real time, and inputs them into the model to determine the status of each interval; 4. Alarm and location: Once a certain section is identified as potentially corroded, an alarm will be issued immediately, and the corresponding pipeline location area will be output; 5. Model Update: After on-site verification and confirmation of corrosion information, the new data is fed back to the host computer to update the model parameters.

[0032] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A pipeline corrosion status monitoring system, characterized in that, include: Sensor fiber optics, communication fiber optics, and distributed acoustic wave sensor main unit; The sensing optical fiber is laid on the outside of the pipe wall under test and divided into multiple continuous sensing intervals to sense vibration information at different locations of the pipe and locate subsequent corrosion events. The two ends of the communication optical fiber are respectively connected to the sensing optical fiber and the distributed acoustic wave sensing host, and are used to transmit optical signals between the sensing optical fiber and the distributed acoustic wave sensing host. The distributed acoustic wave sensor host is used to emit probe light and receive reflected light. The probe light is transmitted through the communication optical fiber and then enters the sensing optical fiber. During the transmission process in the sensing optical fiber, Rayleigh scattering continuously generates scattered light in various directions. The reflected light is the light that is backscattered along the sensing optical fiber from the scattered light. The reflected light carries the pipeline vibration information during the transmission process in the sensing optical fiber and is then received by the distributed acoustic wave sensor host through the communication optical fiber. The distributed acoustic wave sensor host is also used to recover the pipeline vibration information from the reflected light and to identify the pipeline corrosion status. Each sensing interval includes a first sensing fiber unit and a second sensing fiber unit that alternately follow the distribution direction of the sensing fiber. The first sensing fiber unit covers the outer side of the pipe wall under test in a wavy, back-and-forth pattern, while the second sensing fiber unit covers the outer side of the pipe wall under test along the axial direction of the pipe. The second sensing fiber unit includes... n Segment length is l The optical fiber, through the first n The sensing signal enhancement factor of the fiber segment is set to This is used to enhance the data of the pipeline vibration information carried by the reflected light.

2. The pipeline corrosion status monitoring system according to claim 1, characterized in that, Each sensing interval further includes: a sensing fiber optic enhancement and encapsulation structure covering the first sensing fiber optic unit; the sensing fiber optic enhancement and encapsulation structure is made of an elastic material.

3. The pipeline corrosion status monitoring system according to claim 2, characterized in that, The elastic material is polyurethane, silicone rubber, or butyl rubber.

4. The pipeline corrosion status monitoring system according to claim 2, characterized in that, The distributed acoustic wave sensing host includes: The trained machine learning model is used to obtain the pipe state of each sensing interval based on the pipe vibration information at the current sampling time of each sensing interval, wherein the pipe state is normal or suspected corrosion. The positioning module is used to obtain the index of the encapsulation structure of the corresponding sensing area when the pipeline is suspected of being corroded, so as to locate it. The training of the machine learning model includes: At multiple sampling times, pipeline vibration information is collected, and the pipeline vibration information is augmented. The data-enhanced pipeline vibration information is used as training data to train a machine learning model, resulting in a well-trained machine learning model.

5. The pipeline corrosion status monitoring system according to claim 4, characterized in that, The training of the machine learning model also includes: The vibration information of the pipeline suspected of corrosion points is used as a new input to the machine learning model, and the parameters of the machine learning model are retrained and updated.

6. The pipeline corrosion status monitoring system according to claim 4, characterized in that, The second sensing fiber optic unit includes n Segment length is l optical fibers, of which n For positive integers greater than or equal to 2, data augmentation is performed on the pipeline vibration information, including: Will n Segment length is l Signal measured by optical fiber , The signal measured by the corresponding first sensing fiber unit By performing exponential superposition, we obtain the first... i Enhanced signal for each sensing zone : in i Indicates the first i One sensing range.

7. The pipeline corrosion status monitoring system according to claim 6, characterized in that, Obtain the index of the suspected corrosion encapsulation structure, and locate the suspected corrosion points in the pipeline based on the index, including: obtaining the index of the sensing fiber optic sensitization encapsulation structure corresponding to the suspected corrosion. j The location area of ​​suspected corrosion points in the pipeline is as follows: in, L This represents the length of the encapsulation structure.

8. The pipeline corrosion status monitoring system according to claim 3, characterized in that, The amplitude of the wave crests and troughs is equal to the perimeter of the pipe cross-section.

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