A method and system for monitoring corrosion in a hydrogen-doped pipeline

Abstract

The application relates to a hydrogen-doped pipeline corrosion monitoring method and system, wherein a first corrosion parameter is acquired. The first corrosion parameter comprises a real-time monitoring-acquired corrosion parameter of the hydrogen-doped pipeline. First corrosion information of the hydrogen-doped pipeline is obtained based on the first corrosion parameter. The first corrosion information is predicted corrosion information of the hydrogen-doped pipeline. Second corrosion information is determined based on the first corrosion information and a risk factor identification model. The risk factor identification model is obtained based on at least one second corrosion parameter and third corrosion information corresponding to the at least one second corrosion parameter. The at least one second corrosion parameter comprises a historically-acquired corrosion parameter of the hydrogen-doped pipeline. The third corrosion information comprises detected corrosion information of the hydrogen-doped pipeline when the corresponding second corrosion parameter is historically acquired. The application can reduce the corrosion probability of the hydrogen-doped pipeline by monitoring the corrosion information of the hydrogen-doped pipeline.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy and hydrogen-doped transportation, and particularly relates to a corrosion monitoring method and system for a hydrogen-doped pipeline. BACKGROUND

[0002] The hydrogen-doped pipeline refers to a pipeline for transporting hydrogen obtained by modifying an original pipeline such as a natural gas pipeline network or an oil and gas gathering and transportation pipeline network. However, the hydrogen-doped pipeline obtained by modifying the original pipeline increases the risk of corrosion of the hydrogen-doped pipeline during the transportation of hydrogen, thereby causing hydrogen disaster accidents. Therefore, how to monitor the corrosion information of the hydrogen-doped pipeline is a problem to be solved.

[0003] At present, there is no formed hydrogen-doped transportation theory and supporting corrosion detection system, so the available corrosion information of the hydrogen-doped pipeline is very limited. Moreover, due to the large error of the existing corrosion-related algorithm and the low accuracy rate of sample prediction effect, it is difficult to effectively monitor the corrosion information of the hydrogen-doped pipeline, thereby increasing the probability of corrosion of the hydrogen-doped pipeline. SUMMARY

[0004] The present application provides a corrosion monitoring method and system for a hydrogen-doped pipeline, which can reduce the probability of corrosion of the hydrogen-doped pipeline by monitoring the corrosion information of the hydrogen-doped pipeline.

[0005] The technical solutions of the present application to solve the above technical problems are as follows:

[0006] On the one hand, the present application provides a corrosion monitoring method for a hydrogen-doped pipeline, comprising: obtaining a first corrosion parameter. The first corrosion parameter includes a real-time monitoring obtained corrosion parameter for the hydrogen-doped pipeline. Based on the first corrosion parameter, a first corrosion information is obtained, which is a predicted corrosion information of the hydrogen-doped pipeline. Based on the first corrosion information and a risk factor identification model, a second corrosion information is determined. The risk factor identification model is obtained based on at least one second corrosion parameter and third corrosion information corresponding to the at least one second corrosion parameter. The at least one second corrosion parameter includes a historically obtained corrosion parameter of the hydrogen-doped pipeline, and the third corrosion information includes a detected corrosion information of the hydrogen-doped pipeline when the corresponding second corrosion parameter is historically obtained.

[0007] The present application has the beneficial effect that by monitoring the corrosion information of the hydrogen-doped pipeline, the probability of corrosion of the hydrogen-doped pipeline can be reduced.

[0008] On the basis of the above technical solutions, the present application can also be improved as follows.

[0009] Further, the first corrosion information is determined as the second corrosion information based on that the similarity between the first corrosion parameter and the target second corrosion parameter satisfies a first preset condition, and the similarity between the first corrosion information and the target third corrosion information satisfies a second preset condition. The at least one second corrosion parameter includes the target second corrosion parameter, and the third corrosion information corresponding to the at least one second corrosion parameter includes the target third corrosion information.

[0010] The beneficial effect of the further scheme is that the predicted first corrosion information is verified based on the risk factor identification model. If the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information satisfies the second preset condition, the verification is passed. In this case, the first corrosion information is determined as the second corrosion information, which can reduce the error between the second corrosion information and the actual corrosion information of the hydrogen-added pipeline.

[0011] Further, the third corrosion parameter is obtained based on that the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information does not satisfy the second preset condition. The third corrosion parameter includes a corrosion parameter of the hydrogen-added pipeline obtained by real-time monitoring, and the third corrosion parameter is different from the first corrosion parameter. The first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter. The second corrosion information is determined based on the updated first corrosion information and the risk factor identification model.

[0012] The beneficial effect of the further scheme is that the predicted first corrosion information is verified based on the risk factor identification model. If the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information does not satisfy the second preset condition, the verification fails. In this case, the third corrosion parameter different from the first corrosion parameter is obtained, and the first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter. The second corrosion information is re-determined based on the updated first corrosion information and the risk factor identification model. This can reduce the error between the second corrosion information and the actual corrosion information of the hydrogen-added pipeline.

[0013] Further, the first preset condition includes that the similarity between the first corrosion parameter and the target second corrosion parameter is greater than a first threshold value.

[0014] The beneficial effect of the further scheme is that a possible implementation manner of the first preset condition is given.

[0015] Further, the second preset condition includes that the similarity between the first corrosion information and the target third corrosion information is greater than a second threshold value.

[0016] The beneficial effect of the further scheme is that a possible implementation of the second preset condition is provided.

[0017] Further, the corrosion information includes at least one of a corrosion degree, a corrosion type, a corrosion position, and a corrosion rate of the hydrogen-doped pipeline.

[0018] The beneficial effect of the further scheme is that the specific content of the corrosion information is provided, and by monitoring at least one of the corrosion degree, the corrosion type, the corrosion position, and the corrosion rate of the hydrogen-doped pipeline in real time, the probability of corrosion of the hydrogen-doped pipeline can be reduced.

[0019] Further, the corrosion parameter includes at least one of a first parameter, a second parameter, and a third parameter. The first parameter includes a corresponding relationship between a wall thickness of the hydrogen-doped pipeline and an electrode-to-electrode voltage acting on the hydrogen-doped pipeline. The second parameter includes a corresponding relationship between a pipe diameter of the hydrogen-doped pipeline and a size of a magnetic flux in the hydrogen-doped pipeline. The third parameter includes wavelength data and sound amplitude energy data of an acoustic wave echo in the hydrogen-doped pipeline.

[0020] The beneficial effect of the further scheme is that the specific content of the corrosion parameter is provided, and based on the corrosion parameter, the corrosion information of the hydrogen-doped pipeline can be determined, and the probability of corrosion of the hydrogen-doped pipeline can be reduced.

[0021] In another aspect, the present application provides a corrosion monitoring device for a hydrogen-doped pipeline, comprising:

[0022] The test module is configured to obtain a first corrosion parameter, wherein the first corrosion parameter includes a corrosion parameter of the hydrogen-doped pipeline obtained by real-time monitoring. The information interaction module is configured to obtain first corrosion information based on the first corrosion parameter, wherein the first corrosion information is predicted corrosion information of the hydrogen-doped pipeline. The information interaction module is further configured to determine second corrosion information based on the first corrosion information and a risk factor identification model. The risk factor identification model is obtained based on at least one second corrosion parameter and third corrosion information corresponding to the at least one second corrosion parameter. The at least one second corrosion parameter includes a corrosion parameter of the hydrogen-doped pipeline obtained in the past. The third corrosion information includes corrosion information of the hydrogen-doped pipeline detected when the corresponding second corrosion parameter is obtained in the past.

[0023] The beneficial effect of the present application is that by monitoring the corrosion information of the hydrogen-doped pipeline, the probability of corrosion of the hydrogen-doped pipeline can be reduced.

[0024] On the basis of the above technical scheme, the present application can be further improved as follows.

[0025] Further, the information interaction module is further configured to determine the first corrosion information as the second corrosion information based on that the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information satisfies the second preset condition. The at least one second corrosion parameter includes the target second corrosion parameter, and the third corrosion information corresponding to the at least one second corrosion parameter includes the target third corrosion information.

[0026] The beneficial effect of the above further scheme is that the information interaction module verifies the predicted first corrosion information based on the risk factor identification model. If the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information satisfies the second preset condition, the verification is passed. In this case, the first corrosion information is determined as the second corrosion information, which can reduce the error between the second corrosion information and the actual corrosion information of the hydrogen-doped pipeline.

[0027] Further, the information interaction module is further configured to obtain a third corrosion parameter based on that the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information does not satisfy the second preset condition. The third corrosion parameter includes a corrosion parameter of the hydrogen-doped pipeline obtained by real-time monitoring, and the third corrosion parameter is different from the first corrosion parameter. The first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter. The second corrosion information is determined based on the updated first corrosion information and the risk factor identification model.

[0028] The beneficial effect of the above further scheme is that the information interaction module verifies the predicted first corrosion information based on the risk factor identification model. If the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information does not satisfy the second preset condition, the verification fails. In this case, a third corrosion parameter different from the first corrosion parameter is obtained, and the first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter, so as to determine the second corrosion information based on the updated first corrosion information and the risk factor identification model. This can reduce the error between the second corrosion information and the actual corrosion information of the hydrogen-doped pipeline. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1 A flowchart of a corrosion monitoring method of a hydrogen-doped pipeline provided by the present application is shown in the figure;

[0030] Figure 2 A schematic diagram of a principle of performing an electric fingerprint corrosion test on a hydrogen-doped pipeline provided by the present application is shown in the figure;

[0031] Figure 3A schematic diagram of a method for determining third corrosion information provided by the present application is shown in the figure.

[0032] Figure 4 A structural schematic diagram of a corrosion monitoring system of a hydrogen-doped pipeline provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0033] The principles and features of the present application are described below, and the examples are only used to explain the present application and are not intended to limit the scope of the present application.

[0034] The hydrogen-doped pipeline refers to a pipeline for transporting hydrogen obtained by modifying an original pipeline such as a natural gas pipeline network or an oil and gas gathering and transportation pipeline network. However, the hydrogen-doped pipeline obtained by modifying the original pipeline increases the risk of corrosion of the hydrogen-doped pipeline during the transportation of hydrogen, thereby causing hydrogen disaster accidents. Therefore, how to monitor the corrosion information of the hydrogen-doped pipeline is a problem to be solved.

[0035] Since there is no existing hydrogen-doped transportation theory and supporting corrosion detection system, the available corrosion information of the hydrogen-doped pipeline is very limited. Moreover, since the existing corrosion-related algorithm has a large error and the sample prediction accuracy is low, it is difficult to effectively monitor the corrosion information of the hydrogen-doped pipeline, thereby increasing the probability of corrosion of the hydrogen-doped pipeline.

[0036] Based on the above problems, the present application provides a corrosion monitoring method for a hydrogen-doped pipeline, which can reduce the probability of corrosion of the hydrogen-doped pipeline by monitoring the corrosion information of the hydrogen-doped pipeline. Referring to Figure 1 The method includes steps S110-S130.

[0037] S110: Obtain a first corrosion parameter.

[0038] The first corrosion parameter includes a corrosion parameter of the hydrogen-doped pipeline obtained by real-time monitoring.

[0039] In some embodiments, the corrosion parameter includes at least one of a first parameter, a second parameter, and a third parameter. The first parameter includes a corresponding relationship between the wall thickness of the hydrogen-doped pipeline and the electrode-to-electrode voltage acting on the hydrogen-doped pipeline. The second parameter includes a corresponding relationship between the pipe diameter of the hydrogen-doped pipeline and the size of the magnetic flux in the hydrogen-doped pipeline. The third parameter includes wavelength data and sound amplitude energy data of the sound wave echo in the hydrogen-doped pipeline.

[0040] It should be noted that the present application does not limit the specific content of the corrosion parameter. In addition to including at least one of the first parameter, the second parameter, and the third parameter, the corrosion parameter can also include a fourth parameter, a fifth parameter, etc., which is not limited by the present application.

[0041] In some embodiments, the first parameter can be obtained based on performing a Field signature method test (FSM test) on the hydrogen-doped pipeline. The FSM test is essentially classified as a potential matrix method measurement type. The FSM test uses the measurement of the voltage between electrodes to obtain real-time pipeline wall corrosion data according to the correspondence between the voltage between electrodes and the thickness of the pipeline wall. The pipeline wall corrosion data is associated with the first parameter in the present application.

[0042] Referring to Figure 2 , a schematic diagram of performing an FSM test on a hydrogen-doped pipeline. The measurement electrodes can be arranged in an m x n matrix on the outer wall of the hydrogen-doped pipeline (which can also be referred to as a pipeline in the present application) in the axial and radial directions of the pipeline. A constant current is applied to both ends of the pipeline in the axial direction, and the voltage change between the electrodes is monitored in real time. If corrosion occurs in a certain area of the inner wall of the pipeline, the area will change the electric field distribution due to the increase in bulk resistance, causing a voltage change between the electrodes. Therefore, the signal of the change in the electrode matrix can be monitored. The first parameter can be obtained by performing data preprocessing on the signal of the change obtained by the monitoring electrode matrix.

[0043] In some embodiments, the resistivity of the pipeline wall changes with temperature, causing a slight fluctuation in the current, which interferes with the FSM test and affects the accuracy of the processing of the voltage change signal between the electrodes. Therefore, in order to eliminate the influence of temperature on the test accuracy, a reference plate can be arranged on the outer wall of the pipeline. Referring to Figure 2 , the reference plate is in close contact with the outer wall of the pipeline but is insulated from the pipeline and is connected to the measurement system through a cable; by measuring the reference voltage on the reference plate, the test error caused by temperature changes and current fluctuations can be compensated.

[0044] It should be noted that the first parameter can be obtained based on the FSM test, and the first parameter can also be obtained based on other methods. The present application does not limit the method of obtaining the first parameter.

[0045] In some embodiments, the second parameter can be obtained based on performing a magnetic flux leakage test on the hydrogen-doped pipeline. The magnetic flux leakage test can be performed on the hydrogen-doped pipeline by a magnetic flux leakage detection device. The magnetic flux leakage test device can include an electronic host and a scanning probe. The types of scanning probes can include fixed type, adjustable type, circumferential type, etc. The scanning probe coverage can be 50mm-2400mm.

[0046] In some embodiments, at least one set of scanning probes can be provided. According to the driving mode of the scanning probe, the push-pull speed is set, and the magnetic flux of the hydrogen-doped pipeline is obtained based on the set push-pull speed to determine the second parameter based on the obtained magnetic flux.

[0047] It should be noted that the second parameter can be obtained based on the magnetic flux leakage test, and the first parameter can be obtained based on other manners. The method for obtaining the first parameter is not limited in the present application.

[0048] In some embodiments, the third parameter can be obtained based on an acoustic wave test performed on the hydrogen-doped pipeline. The acoustic wave test performed on the hydrogen-doped pipeline includes taking an echo-echo ultrasonic thickness mode on the hydrogen-doped pipeline with a dry coupling material acoustic characteristic impedance test as a original control sample. The ideal transmission coefficient range is determined (for example, the ideal transmission coefficient range is determined to be 0.24-0.25), and the acoustic characteristic impedance data of the hydrogen-doped pipeline before and after filling the dry coupling agent is obtained. Considering the electrode test process, imitating the acoustic characteristic impedance physical effect of the piezoelectric wafer, the wavelength change and acoustic amplitude energy of the pipeline acoustic wave echo are studied and summarized; the acoustic wave test result is preprocessed, and the third parameter is determined.

[0049] In the present application, the dry coupling agent is mainly made of polydimethylsiloxane, and cross-linking agent, plasticizer, coupling agent, catalyst and the like are added and mixed, and then filled into the hydrogen-doped pipeline with high local corrosion risk. Under the preset temperature condition, the mixed paste-like semi-liquid dry coupling agent reacts with the water vapor in the pipeline, solidifies and adheres to the inner wall of the pipeline, expels the residual air in the corrosion groove, and finally uses a path device to remove the excess solidified material in the pipeline, and only the wall surface solidified material is reserved. The accuracy of the test result obtained by performing the acoustic wave test on the hydrogen-doped pipeline can be improved.

[0050] It should be noted that the third parameter can be obtained based on the acoustic wave test, and the first parameter can be obtained based on other manners. The method for obtaining the third parameter is not limited in the present application.

[0051] S120: obtaining first corrosion information based on the first corrosion parameter.

[0052] The first corrosion information is the predicted corrosion information of the hydrogen-doped pipeline.

[0053] In some embodiments, the influence of the first corrosion parameter on the pipeline corrosion can be quantitatively analyzed based on theoretical analysis, simulation, experiment and the like, so as to predict the first corrosion information.

[0054] In some embodiments, the corrosion information includes at least one of the corrosion degree, the corrosion type, the corrosion position and the corrosion rate of the hydrogen-doped pipeline.

[0055] S130: determining second corrosion information based on the first corrosion information and a risk factor identification model.

[0056] The risk factor identification model is obtained based on at least one second corrosion parameter and third corrosion information corresponding to the at least one second corrosion parameter. The at least one second corrosion parameter includes a corrosion parameter of the hydrogenated pipeline obtained in history. The third corrosion information includes corrosion information of the hydrogenated pipeline detected when the corresponding second corrosion parameter is obtained in history.

[0057] In some embodiments, the risk factor identification model is based on set pair analysis theory, and the core of the theory is connection number, which includes binary connection number to multi-connection number. To study the corrosion information of the hydrogenated pipeline under the influence of multiple factors, the first corrosion information can be verified according to the third corrosion information obtained in advance, so as to determine the second corrosion information.

[0058] In some embodiments, the first corrosion information is determined as the second corrosion information based on that the similarity between the first corrosion parameter and the target second corrosion parameter satisfies a first preset condition, and the similarity between the first corrosion information and the target third corrosion information satisfies a second preset condition. The at least one second corrosion parameter includes the target second corrosion parameter, and the third corrosion information corresponding to the at least one second corrosion parameter includes the target third corrosion information.

[0059] That is, the first corrosion information predicted can be verified based on the risk factor identification model. If the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information satisfies the second preset condition, the verification is passed. In this case, the first corrosion information is determined as the second corrosion information, which can reduce the error between the second corrosion information and the actual corrosion information of the hydrogenated pipeline.

[0060] In some embodiments, the third corrosion parameter is obtained based on that the similarity between the first corrosion parameter and the target second corrosion parameter satisfies the first preset condition, and the similarity between the first corrosion information and the target third corrosion information does not satisfy the second preset condition. The third corrosion parameter includes a corrosion parameter of the hydrogenated pipeline obtained by real-time monitoring, and the third corrosion parameter is different from the first corrosion parameter. The first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter. The second corrosion information is determined based on the updated first corrosion information and the risk factor identification model.

[0061] That is, the predicted first corrosion information can be verified based on the risk factor identification model, if the similarity between the first corrosion parameter and the target second corrosion parameter meets the first preset condition, and the similarity between the first corrosion information and the target third corrosion information does not meet the second preset condition, the verification fails. In this case, a third corrosion parameter different from the first corrosion parameter is obtained, and the first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter, so as to re-determine the second corrosion information based on the updated first corrosion information and the risk factor identification model. The error between the second corrosion information and the actual corrosion information of the hydrogen-doped pipeline can be reduced.

[0062] In some embodiments, the first preset condition includes that the similarity between the first corrosion parameter and the target second corrosion parameter is greater than a first threshold.

[0063] In some embodiments, the second preset condition includes that the similarity between the first corrosion information and the target third corrosion information is greater than a second threshold.

[0064] The method of constructing the risk factor identification model is specifically described below.

[0065] In system safety analysis, sample data is divided into three cases of same class, different class and opposite class according to definition, "same class" represents system safety, "opposite class" represents system insecurity, and "different class" represents good or medium system safety level. The certain component of multiple connection number is constant, and the "different class" uncertain component can be further divided. Therefore, the connection number relates to the three characteristics of same class, different class and opposite class of system safety state (same class is determined safety, opposite class is determined insecurity, and different class is uncertain safety), which can be expressed as:

[0066]

[0067] Wherein, a is the certain component; b is the uncertain component; c is also the certain component; i and j are uncertainty coefficients, representing the superposition of any system failure determination and uncertainty.

[0068] By coupling the identification decision process of set pair analysis result and space fault tree, a pipeline corrosion risk fault tree can be established. The pipeline corrosion risk fault tree T is as follows:

[0069]

[0070] Wherein, η S is used to represent the first corrosion information set. n S1 , n S2 ,... n Sm are respectively used to represent different first corrosion information. M is used to represent the number of first corrosion information. η is used to represent the third corrosion information set, n1, n2,... nz respectively represent different third corrosion information, and Z represents the number of the third corrosion information. F represents a set of direct corrosion parameters in the corrosion parameters, f1, f2,... f q represent different direct corrosion parameters, and Q represents the number of the direct corrosion parameters. X represents a set of background corrosion parameters in the corrosion parameters, X1, X2,... X l represent different background corrosion parameters, and L represents the number of the background corrosion parameters. represent a set of background corrosion parameters associated with any direct corrosion parameter; W represents a set of weights of any direct corrosion parameter, W1, W2,... W Q represent risk weights corresponding to different direct corrosion parameters.

[0071] wherein the direct risk parameters refer to independent variables that affect corrosion, and the background risk parameters refer to quantities that affect corrosion but do not change themselves. For example, the corrosion resistance of a hydrogen-containing pipeline, the gas concentration in the hydrogen-containing pipeline, the pressure difference allowance, the gas flow rate, the corrosion prevention measures of the hydrogen-containing pipeline, and the like. The properties, structure, surface state, deformation and stress, environmental factors (medium composition, temperature, pH), and pipeline anticorrosion layer state of the hydrogen-containing pipeline, and the like.

[0072] In some embodiments, only a single direct corrosion parameter F is considered, and the relationship between the third corrosion information η and the first corrosion information η S is analyzed.

[0073]

[0074] In the fault space, the same, different and opposite states are set according to the distance, wherein the distance less than 30% is the same state, the distance between 30% and 70% is the different state, and the distance greater than 70% is the opposite state. The average distance of the corrosion information switching is used to determine Z a , Z b , and Z c . Figure 3 .

[0075] After Z a , Z b , and Z c are determined, a, b, and c can be determined, and thus the contact degree calculation process of μ(η→η S ) can be determined. In the set of background corrosion parameters X, according to the weights of the influence factors in the set F, the recognition degrees of the first corrosion information and the third corrosion information in the fault space are obtained (the greater the recognition degree, the more correct the corresponding relationship of the recognition), and the multi-factor pattern recognition calculation process expression involved is as follows:

[0076]

[0077] In some embodiments, the risk categories of pipeline corrosion damage can be determined by an intelligent algorithm of multi-factor pattern recognition, a numerical model of risk factors can be quantitatively established, and the weights of the risk factors can be determined by statistical fitting. In addition, considering that the increase of the content of corrosive impurities in the pipeline increases the corrosion risk of the pipeline, the types and contents of corrosive media in the pipeline environment are determined by experiments, the chemical composition is analyzed, the metallographic structure of the pipeline material is observed, the electron microscopic analysis and micro-area EDX analysis of the corrosion perforation prone position are performed, the flow state of the fluid in the pipeline is simulated and calculated, and the corrosion failure reasons of different parts of the hydrogen-doped pipeline are determined.

[0078] In some embodiments, the corrosion points in the pipeline can be measured. The measurement of the corrosion points in the pipeline includes the measurement of the corrosion pit parameters, the measurement of the corrosion points and the wall thickness of the pipeline near the corrosion points. In addition, the metallographic specimens can be prepared from the corrosion pits, the metallographic structure observation can be performed by using an SCT-147 metallographic microscope, and the analysis of the pipeline condensate and scale in the corrosion area can be performed.

[0079] In some embodiments, the second corrosion information of the hydrogen-doped pipeline can be determined based on the results of the above analysis process in view of the safety operation risk of hydrogen-doped transportation. Based on the second corrosion information, the main risk factors affecting the hydrogen-doped transportation operation can be determined. After the hierarchical division of the safety risk factors, the influence degree of different risk factors needs to be optimized, the analytic hierarchy process method is used to realize the transformation of the risk factors from qualitative to quantitative.

[0080] The calculation process of quantitatively establishing the numerical model of the risk factors and determining the weights of the risk factors is as follows:

[0081] ① The risk factors of the safety risk in the transportation process are grouped to form different levels;

[0082] ② The judgment matrix is further constructed to calculate the weights of the risk factors: the importance of different factors under the same subordinate relationship is compared, and the weight is determined by the ratio method; usually, a "1-9" proportional scale is used for assignment to form a judgment matrix, where a ij represents the risk proportional scale. When A meets the consistency requirement, the maximum eigenvalue λ max (A) corresponding to the characteristic vector is normalized and recorded as the weight vector to represent the weight division in the criterion.

[0083] ③To ensure the rationality of the judgment matrix, consistency test should also be carried out. If it does not meet the requirements, the judgment matrix needs to be restructured to ensure the rationality of the weight division. After obtaining the consistency index CI, match the average random consistency index RI corresponding to different orders. When the calculation result CR is less than 0.1, the judgment matrix is reasonable; otherwise, the judgment matrix is not reasonable and does not have consistency, and the judgment matrix needs to be restructured.

[0084]

[0085] In the formula: CI is the consistency judgment index; n is the order of the judgment matrix; λ max (A) is the maximum eigenvalue of the judgment matrix; RI is a constant that changes with n.

[0086] In some embodiments, based on the existing natural gas pipeline network and gathering pipeline equipment and technology, a hydrogen-doped mixed transportation pipeline corrosion prediction model can be established through finite element simulation, and indoor or local field application statistical results can be used to optimize the algorithm and correct the model.

[0087] In some embodiments, the flow conditions of the fluid in the pipeline not only affect the medium mixing heat transfer, condensation and evaporation, but also affect the shear stress on the inner wall of the pipeline, thereby affecting the erosion of the pipe wall. Therefore, finite element simulation is carried out to calculate the fluid velocity distribution and temperature distribution, which is helpful for medium corrosion analysis.

[0088] For example, for a certain tee pipe, the finite element simulation boundary conditions are as follows: the main pipe inlet flow rate is 8.82 m / s, the temperature is 200℃, the main pipe outlet flow rate is 10.53 m / s, the temperature is 183℃, the branch pipe inlet flow rate is 2.41 m / s, and the temperature is 78℃. The grid is divided from the tee end surface for 500 mm, and the tee corrosion morphology and finite element simulation results can be obtained. Among them, there is a mixing zone downstream of the branch pipe fluid entering, and the local temperature and flow rate of the tee in this area are relatively low, and the liquid droplets in the pipeline are easy to settle and deposit at the bottom of the pipe wall. The corrosion is likely to occur in the above-mentioned area, and the serious parts will be corroded and perforated. The corrosion product analysis results show that the corrosion product is mainly iron oxide, and there are some chlorides and a small amount of sulfides. From the corrosion influence range, the hydrogen-doped pipeline corrosion is not only affected by the chemical corrosion of the medium, but also affected by the flow of hydrogen-containing fluid and temperature difference.

[0089] In some embodiments, based on the aforementioned hydrogen-doped transportation pipeline corrosion risk factor weight data, a hydrogen-doped mixed transportation pipeline corrosion rate prediction model can be established, and indoor or local field application statistical results can be used to optimize the algorithm and correct the model.

[0090] The hydrogen-doped mixed transportation pipeline corrosion rate prediction calculation formula is established as follows:

[0091]

[0092] Wherein, θ is the corrosion rate, mm / h; Ω(t) represents the state of hydrogen-doped pipeline at any time, in terms of average wall thickness, mm, Ω0 is the initial degradation state of the equipment; σ is the material corrosion diffusion coefficient, dimensionless; B(t) represents the molecular thermal motion potential function of the pipeline material at any time, dimensionless.

[0093] In some embodiments, there can be CO2 and H2S corrosion for hydrogen-doped mixed transportation of pipelines, considering the temperature effect, the temperature function is introduced into the corrosion rate calculation formula of hydrogen-doped mixed transportation pipeline based on the above formula, and a preliminary correction model is established, which is specifically:

[0094]

[0095] Wherein, θ c is the corrected pipeline corrosion rate, mm / h; t represents time, h; k1, k2, k3 are corrosion calculation auxiliary parameters, which are given by finite element simulation results, dimensionless; P1 represents the CO2 partial pressure in the hydrogen-doped mixed transportation fluid in the pipeline, MPa; P2 represents the H2S partial pressure in the hydrogen-doped mixed transportation fluid in the pipeline.

[0096] In some embodiments, the indoor or local field application statistical results can be used to optimize the algorithm and the correction model, and the specific method includes:

[0097] Considering that the dimensionless differences of different influencing factors in the sample set are large, the extreme value method is used for data preprocessing. The preprocessed data set is introduced into the KPCA algorithm, and the dimensionality reduction effects of different kernel functions are compared. The IGOA model is constructed, the related parameters are initialized, the root mean square error is used as the fitness function, and the trial method is used to determine the number of hidden layer nodes and the type of excitation function of the ELM model. The model is trained, the training data is imported into the IGOA-ELM model, the minimum fitness value is taken as the goal, and the optimal prediction model is obtained. The prediction set is regressed and predicted, and the prediction effect is evaluated by using three statistical indexes of E RMS , E MAP and TIC, and the comparison curve of different corrosion rate prediction results is obtained, which is fed back into the hydrogen-doped pipeline corrosion monitoring system.

[0098] Wherein, the expression of the above optimization algorithm process is:

[0099]

[0100] Wherein, E RMS is the root mean square error; θ c * is the measured corrosion rate; E MAP is the mean absolute percentage error; TIC is the Hill inequality coefficient.

[0101] See also Figure 4 , a corrosion monitoring system for a hydrogen-doped pipeline provided by the present invention includes a test module and an information interaction module. The test module is used to obtain a first corrosion parameter, and the first corrosion parameter includes a corrosion parameter for the hydrogen-doped pipeline obtained through real-time monitoring. The information interaction module is used to obtain first corrosion information based on the first corrosion parameter, and the first corrosion information is the predicted corrosion information of the hydrogen-doped pipeline. The information interaction module is also used to determine second corrosion information based on the first corrosion information and a risk factor identification model. The risk factor identification model is obtained based on at least one second corrosion parameter and third corrosion information corresponding to the at least one second corrosion parameter. The at least one second corrosion parameter includes a corrosion parameter of the hydrogen-doped pipeline obtained historically. The third corrosion information includes the corrosion information of the hydrogen-doped pipeline detected when the corresponding second corrosion parameter was obtained historically.

[0102] In some embodiments, the testing module may include a preparation module, a data acquisition module, and a data preprocessing module.

[0103] Among them, the preparation module is used as the sample data collection terminal for on-site testing in the hydrogen blending and transportation stage to prepare for on-site layout for data extraction and preprocessing. The data acquisition module is used to acquire data during the test process. The data preprocessing module is used to perform data preprocessing based on the data acquired by the data acquisition module, establish a labeling matrix, and carry out the following preliminary theoretical analysis work: 1. Matrix eigenvalue selection (labeling matrix linearization processing), 2. Intelligent screening (key test parameters or test parameters with great influence), 3. Classification decision-making (unified integration of the change trend and feedback information of a single test parameter during the test process to lay a mathematical foundation for multi-factor pattern recognition).

[0104] In some embodiments, see Figure 4 The hydrogen-doped pipeline corrosion monitoring system provided by the present invention also includes a communication module for enabling communication between the testing module and the information exchange module. The communication module may include at least one of a radio wave receiving device, a synchronous satellite phone, TCP / IP network protocol dialing, and a dedicated fixed-line communication.

[0105] In some embodiments, during data transmission by the communication module, if there is an error in the data transmission or the signal is lost, the communication module can actively feed back information to the test module, which will then resend the data or issue an early warning to on-site technicians for handling.

[0106] In some embodiments, the information interaction module is further configured to determine the first corrosion information as the second corrosion information based on that the similarity between the first corrosion parameter and the target second corrosion parameter meets a first preset condition, and the similarity between the first corrosion information and the target third corrosion information meets a second preset condition. The at least one second corrosion parameter includes the target second corrosion parameter, and the third corrosion information corresponding to the at least one second corrosion parameter includes the target third corrosion information.

[0107] That is, the information interaction module verifies the predicted first corrosion information based on the risk factor identification model. If the similarity between the first corrosion parameter and the target second corrosion parameter meets the first preset condition, and the similarity between the first corrosion information and the target third corrosion information meets the second preset condition, the verification is passed. In this case, the first corrosion information is determined as the second corrosion information, which can reduce the error between the second corrosion information and the actual corrosion information of the hydrogen-doped pipeline.

[0108] In some embodiments, the information interaction module is further configured to obtain a third corrosion parameter based on that the similarity between the first corrosion parameter and the target second corrosion parameter meets the first preset condition, and the similarity between the first corrosion information and the target third corrosion information does not meet the second preset condition. The third corrosion parameter includes a corrosion parameter of the hydrogen-doped pipeline obtained by real-time monitoring, and the third corrosion parameter is different from the first corrosion parameter. The first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter. The second corrosion information is determined based on the updated first corrosion information and the risk factor identification model.

[0109] That is, the information interaction module can verify the predicted first corrosion information based on the risk factor identification model. If the similarity between the first corrosion parameter and the target second corrosion parameter meets the first preset condition, and the similarity between the first corrosion information and the target third corrosion information does not meet the second preset condition, the verification fails. In this case, a third corrosion parameter different from the first corrosion parameter is obtained, and the first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter, so as to determine the second corrosion information based on the updated first corrosion information and the risk factor identification model. This can reduce the error between the second corrosion information and the actual corrosion information of the hydrogen-doped pipeline.

[0110] It should be noted that in the corrosion monitoring system of the hydrogen-doped pipeline provided by the present application, the descriptions of the first preset condition, the second preset condition, the corrosion information, and the corrosion parameter can refer to the descriptions in the corrosion monitoring method of the hydrogen-doped pipeline provided in the foregoing embodiments, which will not be repeated here.

[0111] In some embodiments, after receiving the data sent by the communication module, the information interaction module analyzes the data. The information interaction module classifies the returned data based on multi-factor pattern recognition through a classifier such as TensorFlow, completes data analysis and working condition warning, and finally pushes the corrosion condition analysis result of the pipeline system to the customer end of each type and each region such as the field and sub-base for user reference and decision-making. The probability of hydrogen-doped pipeline corrosion can be reduced.

[0112] Based on the above embodiments, the present application provides a corrosion monitoring method and system for hydrogen-doped pipelines. The system adopts a modular, componentized, and open design concept, and has good maintainability and scalability. From the system deployment, the system modules form a closed loop processing mechanism, and based on the dynamic monitoring results of the entire system, technical guidance is provided for the operation and regulation of hydrogen-doped pipeline networks, thereby reducing the probability of pipeline corrosion accidents.

[0113] In the description of the present application, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0114] In addition, the terms "first", "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, such as two, three, etc., unless otherwise specifically limited.

[0115] In the present application, unless otherwise specifically defined and limited, the terms "mounting", "connection", "connection", "fixing" and the like should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication or interaction relationship of two elements, unless otherwise specifically limited. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0116] In the present application, unless otherwise explicitly specified and limited, a first feature is "on" or "under" a second feature can mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, the first feature is "over", "above" and "on top of" the second feature can mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is horizontally higher than the second feature. The first feature is "under", "below" and "underneath" the second feature can mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is horizontally lower than the second feature.

[0117] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present application and the features of the different embodiments or examples without contradiction.

[0118] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary and are not to be construed as limiting the present application, and the person skilled in the art can make changes, modifications, replacements and variations to the above-described embodiments within the scope of the present application.

Claims

1. A method of monitoring corrosion of a hydrogen-dosed pipeline, characterized by, The method comprises: obtaining a first corrosion parameter; the first corrosion parameter comprises a corrosion parameter of the hydrogen-doped pipeline obtained through real-time monitoring; obtaining first corrosion information based on the first corrosion parameter; the first corrosion information is predicted corrosion information of the hydrogen-doped pipeline; determining second corrosion information based on the first corrosion information and a risk factor identification model; the risk factor identification model is obtained based on at least one second corrosion parameter and third corrosion information corresponding to the at least one second corrosion parameter; the at least one second corrosion parameter comprises a historical corrosion parameter of the hydrogen-doped pipeline; and the third corrosion information comprises corrosion information of the hydrogen-doped pipeline detected when the corresponding second corrosion parameter is obtained historically; the determination of the second corrosion information based on the first corrosion information and the risk factor identification model comprises: when a similarity between the first corrosion parameter and a target second corrosion parameter satisfies a first preset condition, and a similarity between the first corrosion information and target third corrosion information satisfies a second preset condition, the first corrosion information is determined as the second corrosion information; wherein the at least one second corrosion parameter comprises the target second corrosion parameter, and the third corrosion information corresponding to the at least one second corrosion parameter comprises the target third corrosion information; the corrosion information comprises at least one of a corrosion degree, a corrosion type, a corrosion position, and a corrosion rate of the hydrogen-doped pipeline; the corrosion parameter comprises at least one of a first parameter, a second parameter, and a third parameter; the first parameter comprises a corresponding relationship between a wall thickness of the hydrogen-doped pipeline and an electrode-to-electrode voltage acting on the hydrogen-doped pipeline; the second parameter comprises a corresponding relationship between a pipe diameter of the hydrogen-doped pipeline and a size of a magnetic flux in the hydrogen-doped pipeline; the third parameter comprises wavelength data and sound amplitude energy data of an acoustic wave echo in the hydrogen-doped pipeline.

2. The method of claim 1, wherein, the determination of the second corrosion information based on the first corrosion information and the risk factor identification model comprises: when a similarity between the first corrosion parameter and a target second corrosion parameter satisfies a first preset condition, and a similarity between the first corrosion information and target third corrosion information does not satisfy a second preset condition, a third corrosion parameter is obtained, the third corrosion parameter comprises a corrosion parameter of the hydrogen-doped pipeline obtained through real-time monitoring, and the third corrosion parameter is different from the first corrosion parameter; the first corrosion information is updated based on the first corrosion parameter and the third corrosion parameter; the second corrosion information is determined based on the updated first corrosion information and the risk factor identification model.

3. The method of claim 2, wherein, the first preset condition comprises that the similarity between the first corrosion parameter and the target second corrosion parameter is greater than a first threshold value.

4. The method of claim 3, wherein, the second preset condition comprises that the similarity between the first corrosion information and the target third corrosion information is greater than a second threshold value.

5. A corrosion monitoring system for a hydrogen-blended pipeline according to claim 1, wherein The method comprises: a test module configured to obtain a first corrosion parameter; the first corrosion parameter comprises a corrosion parameter of the hydrogen-doped pipeline obtained through real-time monitoring; The information interaction module is configured to obtain first corrosion information based on the first corrosion parameter, the first corrosion information being predicted corrosion information of the hydrogen-doped pipeline; The information interaction module is further configured to determine second corrosion information based on the first corrosion information and a risk factor identification model, the risk factor identification model being obtained based on at least one second corrosion parameter and third corrosion information corresponding to the at least one second corrosion parameter, the at least one second corrosion parameter including a corrosion parameter of the hydrogen-doped pipeline obtained in the past, and the third corrosion information including corrosion information of the hydrogen-doped pipeline detected when the corresponding second corrosion parameter is obtained in the past.

6. The system of claim 5, wherein, The information interaction module is further configured to obtain a third corrosion parameter based on the similarity between the first corrosion parameter and a target second corrosion parameter satisfying a first preset condition and the similarity between the first corrosion information and target third corrosion information not satisfying a second preset condition, the third corrosion parameter including a corrosion parameter of the hydrogen-doped pipeline obtained by real-time monitoring, the third corrosion parameter being different from the first corrosion parameter. The information interaction module is further configured to update the first corrosion information based on the first corrosion parameter and the third corrosion parameter. The information interaction module is further configured to determine the second corrosion information based on the updated first corrosion information and the risk factor identification model.

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