Pipeline corrosion monitoring method and system based on phi-OTDR

Abstract

The invention discloses a pipeline corrosion monitoring method and system based on phi-OTDR, and relates to the technical field of engineering monitoring, and the method comprises the steps: installing an optical fiber; receiving the emitted optical signal by using an optical fiber, and transmitting back Rayleigh scattering light generated by the optical signal to a pipeline corrosion monitoring system for analysis; the received backward Rayleigh scattering light signal is processed; and performing early warning and real-time monitoring according to a processing result. The system comprises an optical fiber, a pipeline and a control host, wherein the control host monitors the corrosion condition of the pipeline through the optical fiber wound on the pipeline. According to the pipeline corrosion monitoring system based on the phi-OTDR technology, real-time, continuous and high-precision monitoring of pipeline corrosion can be achieved, so that potential pipeline leakage and fracture risks are found and prevented in time, the safety and reliability of the pipeline are remarkably improved, meanwhile, the maintenance cost is reduced, and the monitoring efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of engineering monitoring, and in particular to a pipeline corrosion monitoring method and system based on φ-OTDR. Background Art

[0002] At present, pipeline corrosion monitoring mainly relies on regular physical inspections or the use of electrochemical sensors and other methods. These methods have disadvantages such as discontinuous monitoring, high cost, and difficulty in real-time monitoring. In addition, these methods are difficult to implement for long-distance or difficult-to-reach pipelines, and there are limitations to pipeline monitoring. In addition, existing monitoring technologies usually cannot provide high-precision corrosion data, and it is difficult to detect small corrosion changes in a timely manner, thus affecting the safety and reliability of the pipeline.

[0003] Therefore, there is a need for a system and method that can monitor pipeline corrosion in real time, continuously and accurately to improve the safety and reliability of the pipeline. Summary of the invention

[0004] The present invention aims at solving the problems of discontinuous monitoring, high cost, difficulty in real-time monitoring and low monitoring accuracy in the pipeline corrosion monitoring methods in the prior art, and provides a pipeline corrosion monitoring method and system based on φ-OTDR.

[0005] To achieve the above purpose, the technical solution adopted by the present invention is as follows: A pipeline corrosion monitoring method based on φ-OTDR comprises the following steps: step S1, installing an optical fiber; step S2, using the optical fiber to receive a transmitted optical signal, and transmitting the back Rayleigh scattered light generated by the optical signal to a pipeline corrosion monitoring system for analysis; step S3, processing the received back Rayleigh scattered light signal; step S4, monitoring and comprehensively judging whether corrosion occurs according to the analysis result of step S2 and the processing result of step S3, and issuing an early warning.

[0006] Based on the above technical solution, further, in step S2, the back Rayleigh scattered light is analyzed from the perspectives of phase change, intensity change, spectrum characteristics, real-time alarm and positioning.

[0007] Based on the above technical solution, further, the analysis process from the perspective of spectral characteristics is: first emit a light pulse, and then collect backscattered Rayleigh light; wherein, during the collection, an analysis process involving phase information extraction, data analysis, and phase change analysis is involved; and the data analysis includes analysis of phase difference measurement, phase shift amplitude, and phase change rate.

[0008] Based on the above technical solution, further, in step S3, the received backscattered Rayleigh light signal is first amplified, filtered and digitized; then the characteristic information in the signal is extracted; wherein, when extracting the characteristic information in the signal, the time domain analysis method is first used to preliminarily screen out potential abnormal areas, and then the frequency domain analysis method is used to confirm whether there is a periodic vibration source, and finally the wavelet transform is used to accurately locate and characterize the spatial distribution characteristics of these vibrations; wherein, if the phase change in a certain area gradually increases, the area is set as a potential abnormal area where corrosion has occurred.

[0009] Based on the above technical solution, further, in step S3, φ-OTDR is used to monitor the change of amplitude parameters to determine whether corrosion occurs. The judgment process is as follows: the amplitude is the signal strength of the back Rayleigh scattered light, the reference interval is the initial measurement value of a newly built or well-maintained pipeline section as a benchmark, and the normal fluctuation range is within ±3dB. When the continuous change exceeds ±3dB, corrosion is considered to have occurred.

[0010] Based on the above technical solution, further, in step S3, φ-OTDR is used to monitor the change of frequency parameters to determine whether corrosion occurs. The judgment process is: frequency is the repetition rate of vibration or stress wave, and the reference range is the natural vibration frequency of the undamaged pipeline. The specific value depends on the pipeline design and environmental conditions. When a deviation of more than ±5% occurs relative to the baseline value, it is considered to be an abnormal sign.

[0011] Based on the above technical solution, further, in step S3, φ-OTDR is used to monitor the change of phase parameters to determine whether corrosion occurs. The judgment process is as follows: the phase is the relative time difference between two waveforms of the same frequency. The initial phase reading of the optical fiber installation is used as the standard, which is smooth, stable and unchanged. When the phase difference of a certain section of the pipeline suddenly increases by more than 0.1 radians or periodic fluctuations occur, an early warning is issued.

[0012] Based on the above technical solution, further, in step S4, it is necessary to determine whether the signal characteristics are similar and then determine whether to issue an alarm, wherein the similarity judgment process is judged from amplitude fluctuation, frequency distribution and phase stability.

[0013] A pipeline corrosion monitoring system based on φ-OTDR comprises an optical fiber, a pipeline and a control host. The control host monitors the pipeline corrosion through the optical fiber wound around the pipeline.

[0014] Based on the above technical solution, further, the control host includes a receiver, a transmitter, a signal feature library, a data acquisition and processing unit, and an early warning monitoring unit; the transmitter is used to emit a light source; the receiver is used to receive the backscattered Rayleigh light generated by the optical fiber; the signal feature library is used to store signal feature data as a reference for signal judgment; the data acquisition and processing unit is used to amplify, filter and digitize the signal; the early warning monitoring unit is used to monitor the pipeline corrosion in real time and issue early warning reminders.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention adopts a pipeline corrosion monitoring system based on φ-OTDR technology, which can realize real-time, continuous and high-precision monitoring of pipeline corrosion, so as to timely discover and prevent potential pipeline leakage and rupture risks, significantly improve the safety and reliability of the pipeline, and at the same time reduce maintenance costs and improve monitoring efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of the monitoring method of the present invention; Figure 2 A simplified diagram of the monitoring system of the present invention; Figure numerals: 1. optical fiber; 2. pipeline; 3. control host. DETAILED DESCRIPTION

[0017] The present invention is further described and illustrated below in conjunction with the accompanying drawings and specific embodiments. The technical features of each embodiment of the present invention can be combined accordingly without conflicting with each other.

[0018] In order to make the above-mentioned purpose, features and advantages of the present invention more obvious and easy to understand, the specific implementation mode of the present invention is described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below. The technical features in each embodiment of the present invention can be combined accordingly without conflicting with each other.

[0019] In the description of the present invention, it is to be understood that when an element is considered to be "connected" to another element, it may be directly connected to the other element or indirectly connected, that is, there are intermediate elements. On the contrary, when an element is said to be "directly" connected to another element, there are no intermediate elements.

[0020] Example 1 The phase-sensitive optical time-domain reflectometer (φ-OTDR) adopts a distributed optical fiber sensing technology based on Rayleigh scattering. When light propagates in the optical fiber 1, Rayleigh scattering will occur due to the uneven refractive index in the optical fiber 1. The φ-OTDR can sense the changes in the external environment by detecting the phase change of the back-scattered Rayleigh light.

[0021] This embodiment provides a pipeline corrosion monitoring method based on φ-OTDR. The pipeline corrosion monitoring system based on φ-OTDR uses optical fiber sensing technology to detect the tiny deformation of the pipeline with high sensitivity, thereby inferring the corrosion situation. This monitoring method can not only provide real-time data, but also has high monitoring accuracy and low maintenance cost, and is particularly suitable for monitoring long-distance or difficult-to-reach pipelines.

[0022] Reference Figure 1 As shown, the monitoring method specifically includes the following steps: Step S1, installing the optical fiber 1. Specifically, the optical fiber 1 is laid along the pipeline, and can be directly attached to the surface of the pipeline 2, embedded in the pipeline protective layer, etc. When the environment around the pipeline changes, the optical fiber 1 will also be affected accordingly. Ensure that the optical fiber 1 is firmly installed and has good contact with the pipeline 2 so that the changes around the pipeline can be accurately sensed.

[0023] Step S2, using optical fiber 1 to receive the emitted optical signal, and transmitting the back-Rayleigh scattered light generated by the optical signal to the pipeline corrosion monitoring system for analysis. Specifically, the light source in the pipeline corrosion monitoring system in Example 2 emits a beam of light pulses into optical fiber 1. When the light pulse propagates in optical fiber 1, it will continuously generate back-Rayleigh scattered light; and the receiver in the pipeline corrosion monitoring system receives these back-Rayleigh scattered lights, and mainly analyzes the phase information carried by the back-Rayleigh scattering. Since φ-OTDR is very sensitive to the phase change of light, even a small phase change can be detected.

[0024] In this embodiment, the pipeline corrosion monitoring system can analyze the phase information carried in Rayleigh Scattering. When analyzing the back Rayleigh scattered light, it includes at least the following analysis angles: Angle 1. Phase change: φ-OTDR uses the phase change caused by the interaction between the light pulse and the surrounding environment when it propagates in the optical fiber 1. When the pipeline is corroded, the material properties around the optical fiber 1 change, causing the phase information to change.

[0025] Angle 2: Intensity change: In addition to monitoring phase changes, φ-OTDR can also perform comprehensive analysis based on intensity changes (such as the intensity of backscattered light) to improve detection accuracy.

[0026] Angle 3: Spectral characteristics: In some cases, the pipeline corrosion monitoring system will also analyze the spectral characteristics of backscattered light, especially Brillouin scattering or Raman scattering. These scattering phenomena can provide information about environmental parameters such as temperature and stress, and indirectly reflect the corrosion situation.

[0027] In this embodiment, from angle 1 to angle 3, the specific process of using φ-OTDR to monitor and numerically analyze the back Rayleigh scattered light is as follows: First, a light pulse is emitted. The pipeline corrosion monitoring system is provided with a control host 3 , in which a light source module is integrated. The light source module emits a laser pulse with a narrow line width and enters the single-mode communication optical fiber 1 .

[0028] Then, the backscattered Rayleigh light is collected; during the collection, the analysis process involves phase information extraction, data analysis, phase change analysis, etc. Among them, the data analysis includes the analysis process of phase difference measurement, phase change amplitude, and phase change rate. The details are as follows: (1) Phase change analysis is to analyze the amplitude and rate of phase change, and then calculate the corrosion rate. Specifically, the corrosion of pipeline 2 causes the refractive index of the optical signal passing through this area to change, or the geometric structure around optical fiber 1 changes, which affects the phase response.

[0029] Calculate the phase change: ; In the formula, represents the phase difference between time t and the initial time; Indicates at time The phase value of Represents the phase value at the initial moment.

[0030] Determine the proportionality constant: ; In the formula, Δt represents the time difference between two moments; Calculate the corrosion rate: .

[0031] (2) Phase difference measurement: φ-OTDR is used to extract phase information by transmitting optical pulses and receiving the returned backscattered Rayleigh light signals using interference phenomena. Assume that the phase at a certain point in the optical fiber is , then the phase difference It can be expressed as the phase difference between two adjacent points in time or space: ; In this formula, Indicated in The phase of the moment and The phase difference between the phases of the moments; Indicates at time The phase value of Indicates at time The phase value of .

[0032] (3) Phase change amplitude: The phase change amplitude reflects the degree of phase change at a certain position. It is usually measured by calculating the maximum phase change over a period of time or a certain distance; ; In the formula, Indicates the phase change amplitude; Indicates the phase difference.

[0033] (4) Phase change rate: The phase change rate refers to the speed at which the phase changes per unit time, which can be used to evaluate the rate of influence of corrosion or other environmental factors. Assuming that the phase changes with time t, the phase change rate It can be obtained by taking the derivative: ; represents the rate of phase change; Represents the function of phase changing with time t.

[0034] Angle 4: Real-time alarm and positioning: Once a significant phase change is detected, indicating that there may be a corrosion point, the pipeline corrosion monitoring system immediately triggers an alarm and accurately locates the corrosion position through the phase change, facilitating rapid maintenance. In some embodiments, the significant phase change conditions are defined as: amplitude change greater than ±3db; frequency change greater than ±5%; phase change greater than 0.1 radian.

[0035] Step S3, processing the received backscattered Rayleigh light signal. Specifically, the received backscattered Rayleigh light signal is processed by a data acquisition and processing unit. The data acquisition and processing unit includes at least an amplifier, a filter, an analog-to-digital converter and other devices, which are used to amplify, filter and digitize the backscattered Rayleigh light signal. Then, a specific method such as time domain analysis, frequency domain analysis, wavelet analysis, etc. is used to extract characteristic information from the signal.

[0036] In this embodiment, the specific process of extracting characteristic information from the signal by using the time domain analysis method is as follows: denoising and smoothing the original signal. Then calculating the mean μ and variance of the signal To evaluate the overall level of the signal and its fluctuation. The autocorrelation function (ACF) is used to understand the internal structure and periodic characteristics of the signal.

[0037] ; Where R(k) represents the autocorrelation coefficient of lag k; x trepresents the signal intensity at time t; μ represents the mean value of the signal; finally, the local maximum or minimum points in the signal are identified for peak detection to indicate where corrosion may occur. For a one-dimensional signal x(t), if x(t0) satisfies x(t0)>x(t0-Δt)x(t0) and x(t0)>x(t0+Δt)x(t0), then x(t0) is a peak point.

[0038] By performing time domain analysis on the time series data collected by φ-OTDR, the phase change pattern over time can be found, and potential corrosion activities can be inferred. For example, if the phase change in a certain area gradually increases, it may be that corrosion has occurred there, that is, the area is identified as a potential abnormal area.

[0039] In this embodiment, the specific process of extracting characteristic information from a signal using a frequency domain analysis method is as follows: converting a time domain signal into a frequency domain signal using Fourier transform (FFT): ; where X(f) represents the spectral density of the signal; x(t) represents the time domain signal; f represents the frequency variable; and j represents the imaginary unit. For discrete-time signals, the discrete Fourier transform (DFT) is used to approximate the continuous Fourier transform. The power spectral density (PSD) estimate is used to calculate the energy distribution of each frequency component: ; Where Pxx(f) represents the power spectrum density; |X(f)| represents the mode of the frequency domain signal. When studying the weak vibration caused by corrosion inside the pipeline, frequency domain analysis can effectively separate these small but important frequency components, thereby assisting in determining the presence and severity of corrosion. In addition, frequency domain information can also be used for fault diagnosis, such as distinguishing between background noise under normal operating conditions and abnormal vibration caused by corrosion, and then determining the source of vibration.

[0040] In this embodiment, the specific process of extracting characteristic information from a signal using the wavelet analysis method is as follows: In order to improve accuracy, this monitoring system uses wavelet analysis, which is more flexible than traditional Fourier transform. It has the advantages of multi-resolution decomposition, which not only retains the position information in the time domain but also shows the characteristics of the frequency domain, and uses discrete wavelet transform (DWT); ; In the formula, c j [k] represents the wavelet coefficient at the jth scale; x[n] represents the discrete time signal; ψ j,k [n] represents discrete wavelet basis function.

[0041] Since DWT can analyze signals in both time and frequency dimensions, it can effectively identify the exact location where the vibration occurs. In the pipeline corrosion monitoring system, by performing wavelet transform on the reflected light signal, the point where the vibration occurs can be accurately located along the length of the optical fiber 1. In addition to spatial positioning, wavelet analysis can also reveal the time-frequency characteristics of vibration. This is very important for distinguishing different types of vibration sources, such as distinguishing normal vibration caused by natural environmental factors from abnormal vibration caused by corrosion or other damage.

[0042] In the pipeline corrosion monitoring scenario, wavelet analysis is very suitable for analyzing signals with complex dynamic characteristics, such as sudden stress changes. It can accurately locate the specific time and location of these events and provide guidance for subsequent maintenance work.

[0043] In order to obtain the most accurate results, this method combines the above three methods for comprehensive analysis. The specific process is: first use time domain analysis to preliminarily screen out potential abnormal areas, which can quickly identify areas where problems may exist; then use frequency domain analysis to further confirm whether there are periodic vibration sources, which is used for in-depth research to confirm whether there are potential corrosion phenomena; finally, wavelet transform analysis is used to accurately locate and characterize the spatial distribution characteristics of these vibration sources, which is used for precise positioning and provides detailed time and space distribution information. Further explanation: use time domain analysis to determine potential abnormal areas, and use frequency domain analysis to analyze potential abnormal areas. If the frequency domain analysis determines that it is not corrosion, no subsequent operations will be performed; if the frequency domain analysis determines that it is corrosion, the results and related information will be passed down for wavelet transform analysis to finally determine the corrosion location.

[0044] Specifically, first use optical fiber 1 to wrap around a section of pipe 2 that is guaranteed not to be corroded, and test the relevant parameters; then use optical fiber 1 to wrap around the pipe 2 to be tested, compare the amplitude, phase and other parameters, and analyze through time domain, frequency domain, wavelet transform and other methods. If the tested parameters are similar, no corrosion has occurred, and if the difference is large, corrosion has occurred. Furthermore, under the comparison conditions of a newly built or undamaged pipe section with the same material, environmental conditions and service life, the signal at this time is recorded and compared with the signal of the test pipe, so as to determine whether the pipe has been corroded and the degree of corrosion. For example, using φ-OTDR, the changes in parameters such as amplitude, frequency, and phase can be monitored to determine whether corrosion has occurred. When the detected signal amplitude, frequency, phase and other parameters have changed significantly or obviously in a short period of time, it can be inferred that the pipe may have been corroded.

[0045] In this embodiment, as long as one of the analysis results of amplitude, frequency, phase, etc. meets the conditions, time domain, frequency domain and wavelet transform analysis will be performed. When the final result predicts that corrosion has occurred, it will be determined that corrosion has occurred. The specific analysis process from three angles is as follows: From the perspective of amplitude analysis, in this embodiment, the amplitude is the signal intensity of the backscattered Rayleigh light, the reference interval is based on the initial measurement value of a newly built or well-maintained pipeline section, the normal fluctuation range is within ±3dB, and the obvious change is a continuous change beyond ±3dB, which may indicate corrosion or other damage.

[0046] From the perspective of frequency analysis, in this embodiment, the frequency is the repetition rate of the vibration or stress wave, and the reference interval is the natural vibration frequency of the undamaged pipeline. The specific value depends on the pipeline design and environmental conditions. An obvious change is a deviation of more than ±5% relative to the baseline value, which may be a sign of abnormality.

[0047] From the perspective of phase analysis, in this embodiment, the phase is the relative time difference between two waveforms of the same frequency. The initial phase reading of the optical fiber 1 installation is used as the standard. It is smooth and stable. The obvious change is when the phase difference of a certain section of the pipeline suddenly increases by more than 0.1 radians, or periodic fluctuations occur, which is an early warning. Among them, the optical fiber 1 surrounding the pipeline 2 can be used as a sensor. By surrounding the optical fiber 1 around the pipeline 2 to monitor corrosion, the light source shines into the optical fiber 1, and the returned optical signal will carry relevant information, which is first analyzed by φ-OTDR, and then further analyzed in combination with algorithms such as wavelet analysis, and finally outputs the prediction result.

[0048] Step S4, monitor and comprehensively judge whether corrosion occurs according to the analysis results of step S2 and the processing results of step S3, and issue an early warning. When the analysis results show that the corrosion degree of the pipeline exceeds the set threshold, the early warning system issues an alarm. Further, when setting the threshold, this needs to be determined according to the design, environmental conditions and service life of the pipeline to be tested. In this embodiment, the amplitude fluctuation range is within ±3dB, the frequency offset is below ±5%, and the phase difference is less than 0.1 radians. As long as one of the corresponding conditions is met, further analysis will be performed to determine whether an alarm needs to be issued based on the analysis results. The alarm can be notified to relevant personnel through sound and light alarms, text messages, emails, etc. At the same time, the system can continuously monitor the pipeline and update the corrosion assessment results in real time so that relevant personnel can take timely measures to repair or replace the pipeline.

[0049] In this embodiment, if the corrosion of a section of pipeline 2 is monitored for a long time, the pipeline will generate an alarm signal due to non-corrosion, but this signal changes greatly in a short time, so it is an interference signal and needs to be recorded separately. If this signal is generated, no alarm is issued, and a signal feature library needs to be established in the monitoring system and a calibration operation is performed. Specifically, a signal feature library under normal operating conditions is established, and this signal feature library will serve as a reference for subsequent judgment of whether it is a false alarm. Among them, the signal feature library includes but is not limited to signal amplitude, frequency, phase, etc., and can also be combined with data such as pressure sensors and flow sensors as a basis for judgment to exclude interference signals. For example, by comparing the corrosion signal characteristics with the normal interference signal characteristics, if the change characteristics are similar to the signal characteristics caused by normal oil flow or external pressure, the preliminary judgment may be a false alarm; specifically, whether corrosion occurs is mainly based on the three signal characteristics of amplitude fluctuation, frequency distribution and phase stability, but sometimes a certain parameter will cause a corrosion alarm, and it is also necessary to combine other parameters; sometimes the three parameters are similar to the corrosion characteristics, then it is necessary to look at the historical records and compare whether it has ever occurred. If it has not occurred, corrosion may have occurred.

[0050] In this embodiment, the understanding of the corrosion signal characteristics is that corrosion is a local material loss, and the amplitude of the reflected light signal will gradually decrease; the corroded area will change the mechanical properties of the pipeline, affecting the natural vibration frequency or transfer function, usually increasing the low-frequency component; the phase will cause periodic or nonlinear changes.

[0051] The understanding of the characteristics of normal interference signals is that liquid flow usually vibrates in a specific frequency range, and external pressure waves can cause instantaneous stress release or absorption, usually manifested as rapid and short-term amplitude fluctuations or frequency shifts at specific time points.

[0052] In this embodiment, in the process of determining the similarity of signal characteristics, when the monitored signal exhibits the following characteristics, it can be considered to be similar to the signal caused by normal oil flow or external pressure: 1) Amplitude fluctuations: If rapid, short-term, large amplitude changes are observed rather than a gradually decreasing trend, this is more likely to be caused by oil flow or external pressure changes rather than corrosion.

[0053] 2) Frequency distribution: The frequency changes caused by corrosion are often slow and concentrated in the lower frequency band, while the frequency changes caused by fluid flow or pressure fluctuations may involve a wider frequency band, especially the high frequency part.

[0054] 3) Phase stability: Phase changes caused by corrosion are usually irregular and persistent, while phase changes caused by oil flow or external pressure changes are often temporary and can return to their original state after a period of time.

[0055] In this embodiment, the process of determining similarity is as follows: the current main method is to combine multiple parameters and analyze the experience summarized from historical data. Relying on one parameter alone to make a judgment may lead to erroneous conclusions. Therefore, information from multiple aspects such as amplitude, frequency and phase should be considered at the same time to find the correlation and consistency between them. Considering that environmental variables such as temperature and humidity may also affect the signal, the influence of these interference sources must be excluded during the analysis process to ensure that the observed changes are indeed caused by changes in the internal structure. Compare the current signal with the data recorded under the same conditions in the past to see if there is a similar pattern. If the difference between the new and old data is not large, it is likely to be the result under normal operating conditions. At this time, although the signal characteristics are similar to the corrosion signal characteristics, no corrosion has occurred. It is also necessary to compare historical corrosion records. If the signal characteristics under this mode are recorded in history and no corrosion has occurred; if it is a new feature, corrosion may have occurred.

[0056] In summary, the similarity judgment process is judged by eliminating the interference of time domain analysis, frequency domain analysis and wavelet analysis, but these three analyses are based on amplitude fluctuation, frequency distribution and phase stability. Among them, in step S3, whether corrosion occurs has been judged by time domain analysis, frequency domain analysis and wavelet analysis. Step S4 eliminates similar interference again and decides whether to alarm.

[0057] Specifically, time domain analysis eliminates interference: short-term fluctuations and periodic changes, observing whether they are short-lived and recover quickly, or whether there is obvious periodicity, to determine whether they are caused by corrosion.

[0058] Frequency domain analysis eliminates interference: Distinguishes between broadband noise and fixed frequency pulses, eliminating interference caused by fluid flow or pumping.

[0059] Wavelet analysis eliminates interference: identifies transient events and periodic fluctuations, and distinguishes whether corrosion occurs through the characteristics of detail coefficients after wavelet transformation.

[0060] In some embodiments, chemical substances may suddenly appear due to pipeline corrosion, which will affect the soil conditions around the optical cable. At this time, the signal parameters will change, and a corrosion alarm will occur. This situation is not a false alarm. It is also possible that due to slight corrosion of pipeline 2, chemical substances are produced, but the chemical substances cause the system to issue a corrosion alarm in advance. Perhaps the pipeline has not been obviously corroded, but there will be a corrosion alarm. This situation is a false alarm. Specifically, pipeline corrosion is detected by detecting changes in soil composition. When the pipeline corrodes, it will cause a series of changes in the surrounding environment. For example, corrosion may cause the pipeline wall to become thinner, thereby affecting the structural strength of the pipeline. In this case, pipeline 2 may produce tiny vibrations, and these vibration sources will be transmitted to the surrounding soil, thereby affecting the optical fiber 1 laid nearby. Some chemical substances may be produced during the corrosion process, which may change the refractive index around the optical fiber, thereby affecting the propagation of light in the optical fiber. These changes will cause the optical phase in the optical fiber to change. φ-OTDR can detect this phase change and convert it into an electrical signal for processing.

[0061] Example 2 Combination Figure 2 As shown, this embodiment also provides a pipeline corrosion monitoring system based on φ-OTDR, which includes an optical fiber 1, a pipeline 2 and a control host 3. The control host 3 monitors the corrosion of the pipeline 2 through the optical fiber 1 wound around the pipeline 2.

[0062] Specifically, the control host 3 includes a receiver, a transmitter, a signal feature library, a data acquisition and processing unit, and an early warning monitoring unit. Further, the receiver is used to receive the backscattered Rayleigh light generated by the optical fiber 1; the transmitter is used as a light source module to emit light; the signal feature library is used to store signal feature data as a reference for signal judgment; the data acquisition and processing unit includes but is not limited to amplifiers, filters, analog-to-digital converters and other devices, which are used to amplify, filter and digitally process the signal; the early warning monitoring unit is used to monitor the corrosion of the pipeline 2 in real time and can provide early warning reminders.

[0063] In this embodiment, the control host information transmission process is as follows: The light pulse enters the optical fiber 1, and the optical fiber 1 is wound around the corrosion monitoring pipeline 2. The light pulse signal propagates in the optical fiber 1. The optical fiber 1 acts as a sensor, and all signal information is brought back to the receiver of the control host 3 by the light pulse; after receiving the light signal, the receiver transmits it to the data acquisition and processing unit, and the data acquisition and processing unit calculates parameters such as amplitude and phase, and analyzes them through time domain, spectrum and wavelet transform; after analyzing these result parameters, the analyzed results are compared with the reference parameters of the signal feature library, and finally a comprehensive prediction value of the probability of corrosion is given; the comprehensive prediction value is compared with the threshold set by the early warning monitoring unit, and an early warning is issued when the comprehensive prediction value is larger than the threshold.

[0064] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A pipeline corrosion monitoring method based on φ-OTDR, characterized in that: The following steps are involved: Step S1, installing optical fiber; Step S2, using an optical fiber to receive the emitted optical signal, and transmitting the backscattered Rayleigh light generated by the optical signal to the pipeline corrosion monitoring system for analysis; Step S3, processing the received backscattered Rayleigh light signal; Step S4: monitor and comprehensively judge whether corrosion occurs based on the analysis result of step S2 and the processing result of step S3, and issue an early warning.

2. The pipeline corrosion monitoring method based on φ-OTDR according to claim 1 is characterized in that: In step S2, the back Rayleigh scattered light is analyzed from the perspectives of phase change, intensity change, spectrum characteristics, real-time alarm and positioning.

3. The pipeline corrosion monitoring method based on φ-OTDR according to claim 2 is characterized in that: The analysis process from the perspective of spectral characteristics is: first emit a light pulse, and then collect the backscattered Rayleigh light; wherein, during the collection, the analysis process involves phase information extraction, data analysis, and phase change analysis; and the data analysis includes analysis of phase difference measurement, phase shift amplitude, and phase change rate.

4. The pipeline corrosion monitoring method based on φ-OTDR according to claim 1 is characterized in that: In step S3, the received backscattered Rayleigh light signal is first amplified, filtered and digitized; then the characteristic information in the signal is extracted; wherein, when extracting the characteristic information in the signal, the time domain analysis method is first used to preliminarily screen out potential abnormal areas, and then the frequency domain analysis method is used to confirm whether there is a periodic vibration source, and finally the wavelet transform is used to accurately locate and characterize the spatial distribution characteristics of the vibration source; wherein, if the phase change in a certain area gradually increases, the area is set as a potential abnormal area where corrosion has occurred.

5. The pipeline corrosion monitoring method based on φ-OTDR according to claim 4 is characterized in that: In step S3, φ-OTDR is used to monitor the change of amplitude parameters to determine whether corrosion has occurred. The judgment process is as follows: the amplitude is the signal strength of the back Rayleigh scattered light, the reference interval is the initial measurement value of the newly built or maintained pipeline section as the benchmark, the normal fluctuation range is within ±3dB, and when the continuous change exceeds ±3dB, corrosion is considered to have occurred.

6. The pipeline corrosion monitoring method based on φ-OTDR according to claim 5 is characterized in that: In step S3, φ-OTDR is used to monitor the changes in frequency parameters to determine whether corrosion occurs. The judgment process is as follows: frequency is the repetition rate of vibration or stress waves, and the reference range is the natural vibration frequency of the undamaged pipeline. The specific value depends on the pipeline design and environmental conditions. When a deviation of more than ±5% occurs relative to the reference value, it is considered to be an abnormal sign.

7. The pipeline corrosion monitoring method based on φ-OTDR according to claim 6 is characterized in that: In step S3, φ-OTDR is used to monitor the change of phase parameters to determine whether corrosion occurs. The judgment process is as follows: phase is the relative time difference between two waveforms of the same frequency. The initial phase reading of the optical fiber installation is used as the standard. When the phase difference of a certain section of the pipeline suddenly increases by more than 0.1 radians or periodic fluctuations occur, an early warning is issued.

8. The pipeline corrosion monitoring method based on φ-OTDR according to claim 1 is characterized in that: In step S4, it is necessary to determine whether the signal characteristics are similar and then determine whether to issue an alarm, wherein the similarity determination process is performed based on amplitude fluctuation, frequency distribution and phase stability.

9. A pipeline corrosion monitoring system based on φ-OTDR, characterized in that: A pipeline corrosion monitoring method based on φ-OTDR is implemented as described in any one of claims 1 to 8, wherein the pipeline corrosion monitoring system includes an optical fiber, a pipeline and a control host, and the control host monitors the pipeline corrosion through the optical fiber wound around the pipeline.

10. The pipeline corrosion monitoring system based on φ-OTDR according to claim 9, characterized in that: The control host includes a receiver, a transmitter, a signal feature library, a data acquisition and processing unit, and an early warning monitoring unit; The emitter is used to emit light; The receiver is used to receive the back-scattered Rayleigh light generated by the optical fiber; The signal feature library is used to store signal feature data as a reference for signal judgment; The data acquisition and processing unit is used to amplify, filter and digitize the signal; The early warning monitoring unit is used to monitor pipeline corrosion in real time and provide early warning reminders.

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