In-service pipeline residual life evaluation method and system, storage medium and equipment

Abstract

The invention relates to an in-service pipeline residual life evaluation method and system, a storage medium and equipment, and belongs to the technical field of non-metal in-service pipeline aging degree nondestructive testing and residual life quantitative evaluation. The method comprises the following steps: based on terahertz time-domain spectrum test data, Fourier transform infrared spectrum test data and tensile property test data of a nonmetal sample tube after accelerated aging test under different parameters; establishing a correlation model between the terahertz time-domain spectroscopy characteristic peak intensity and the carbonyl index and a correlation model between the carbonyl index and the yield strength; establishing a yield strength-residual life correlation model of the nonmetal pipeline; and based on the terahertz time-domain spectrum test data of the high-risk pipe section of the non-metal in-service pipeline and the three models, completing the evaluation of the residual life of the non-metal in-service pipeline. According to the invention, on-site quantitative evaluation of the residual life of the in-service pipeline can be realized only through the terahertz time-domain spectroscopy test.

Description

Technical Field

[0001] This invention belongs to the field of non-destructive testing of aging degree and quantitative assessment of remaining life of non-metallic in-service pipelines, and specifically relates to a method and system, storage medium and equipment for assessing the remaining life of in-service pipelines. Background Technology

[0002] Polyethylene (PE) pipes are widely used in urban gas supply, but their long-term service life makes them susceptible to aging due to environmental stress, chemical corrosion, and thermo-oxidative effects, leading to degradation of mechanical properties and potential leaks. Traditional assessment methods (such as destructive testing (OIT) and elongation at break) require cutting sections of the pipe, causing operational interruptions and damaging structural integrity. Conventional non-destructive technologies (such as ultrasonic and infrared detection) lack sufficient sensitivity to identify early oxidation and microcracks within PE and struggle to quantify molecular-level changes, necessitating high-precision in-situ detection methods. Terahertz waves (0.1-10 THz) combine microwave penetration with infrared spectral sensitivity, offering a new approach for PE aging detection: their non-ionizing nature, deep penetration, and sensitive response to polar groups demonstrate potential in polymer aging detection. Current technologies have not systematically explored the response mechanism of terahertz waves to the microstructural evolution of PE materials, particularly lacking in in-situ, quantitative assessment of aging degree and embrittlement state. Therefore, developing a dedicated detection method for in-service polyethylene pipelines based on terahertz analysis, and establishing a quantitative assessment model for the remaining life of pipelines by integrating time-domain signal processing and characteristic absorption peak identification technology, has significant engineering value for improving the safety operation and maintenance level and life prediction accuracy of urban gas pipelines. Summary of the Invention

[0003] To address the above problems, this invention provides a method and system for assessing the remaining service life of in-service pipelines, as well as a storage medium and equipment.

[0004] The first objective of this invention is to provide a method for assessing the remaining service life of in-service pipelines, comprising: Based on the terahertz time-domain spectral test data and Fourier transform infrared spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters, a correlation model between the intensity of characteristic peaks in the terahertz time-domain spectrum and the carbonyl index was established. Based on the tensile property test data and Fourier transform infrared spectroscopy test data of non-metallic tubes after accelerated aging tests under different parameters, a correlation model between carbonyl index and yield strength was established. Establish a yield strength-remaining life correlation model for non-metallic pipes; Based on the terahertz time-domain spectral test data of high-risk sections of non-metallic pipelines in service, the correlation models between the intensity of characteristic peaks in the terahertz time-domain spectral data and the carbonyl index, the correlation model between the carbonyl index and the yield strength, and the correlation model between the yield strength and the remaining life were established to complete the assessment of the remaining life of non-metallic pipelines in service.

[0005] In a specific embodiment of the present invention, the parameters in the accelerated aging test under different parameters include the temperature and time of the accelerated thermo-oxidative aging test.

[0006] In a specific embodiment of the present invention, the establishment of a correlation model between the intensity of terahertz time-domain spectral characteristic peaks and the carbonyl index based on the terahertz time-domain spectral test data and Fourier transform infrared spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters includes: Based on the terahertz time-domain spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters, the intensity data of terahertz characteristic peaks of non-metallic sample tubes after accelerated aging tests under different parameters were calculated. Based on the Fourier transform infrared spectral test data of non-metallic samples after accelerated aging tests under different parameters, the carbonyl index data of non-metallic samples after accelerated aging tests under different parameters were calculated. Based on the terahertz characteristic peak intensity data and carbonyl index data of non-metallic samples after accelerated aging tests under different parameters, a correlation model between the terahertz time-domain spectral characteristic peak intensity and the carbonyl index was fitted.

[0007] In a specific embodiment of the present invention, before the step of "calculating the terahertz characteristic peak intensity data of the non-metallic sample tube after accelerated aging test under different parameters based on the terahertz time-domain spectral test data of the non-metallic sample tube after accelerated aging test under different parameters", the method further includes data reliability verification, which includes: The reliability correlation coefficient was calculated based on the terahertz time-domain spectral test data of the non-metallic sample tube after accelerated aging test. The reliability of terahertz time-domain spectroscopy test data can be determined based on the magnitude of the reliability correlation coefficient.

[0008] In a specific embodiment of the present invention, the reliability correlation coefficient is calculated using the following formula:

[0009] in, The correlation coefficient, The first scan time domain signal is the first... i The electric field intensity value at each time point The second scan time domain signal i The electric field intensity value at each time point This is the average value of the first scan signal. This is the average value of the second scan signal.

[0010] In a specific embodiment of the present invention, the establishment of a correlation model between the carbonyl index and yield strength based on the tensile property test data and Fourier transform infrared spectroscopy test data of the non-metallic sample tube after accelerated aging tests under different parameters includes: Based on the tensile property test data of non-metallic tubes after accelerated aging tests under different parameters, the yield strength data of non-metallic tubes after accelerated aging tests under different parameters were calculated. Based on the Fourier transform infrared spectroscopy test data of non-metallic samples after accelerated aging tests under different parameters, the carbonyl index data of non-metallic samples after accelerated aging tests under different parameters were calculated. Based on the yield strength and carbonyl index data of non-metallic samples after accelerated aging tests under different parameters, a correlation model between carbonyl index and yield strength was fitted.

[0011] In a specific embodiment of the present invention, the assessment of the remaining life of non-metallic in-service pipelines is completed using terahertz time-domain spectral test data of high-risk sections of non-metallic pipelines, including the correlation models between the intensity of terahertz time-domain spectral characteristic peaks and carbonyl index, the correlation model between carbonyl index and yield strength, and the yield strength-remaining life correlation model. The intensity of the characteristic peak of the terahertz time-domain spectrum of non-metallic in-service pipelines was calculated based on the terahertz time-domain spectral test data of high-risk sections of non-metallic in-service pipelines. The carbonyl index of the non-metallic in-service pipeline is obtained by inputting the intensity of the terahertz time-domain spectral characteristic peak of the Hertz time-domain spectral characteristic peak into the correlation model between the intensity of the terahertz time-domain spectral characteristic peak and the carbonyl index. By inputting the carbonyl index of the non-metallic in-service pipeline into the correlation model between the carbonyl index and the yield strength, the yield strength of the non-metallic in-service pipeline can be obtained. Input the yield strength of the non-metallic in-service pipeline into the yield strength-remaining life correlation model to obtain the remaining life of the non-metallic in-service pipeline. The remaining service life of non-metallic in-service pipelines is assessed based on their remaining service life.

[0012] In a specific embodiment of the present invention, the yield strength-remaining life correlation model of the non-metallic pipe is shown in the following formula:

[0013] in, σ y For yield strength, t res For remaining lifespan, For the circumferential stress of the pipeline, A , B , R For material constants, The oxidation activation energy of polyethylene material. For the operating temperature of the pipeline, Room temperature.

[0014] A second objective of this invention is to provide a system for assessing the remaining service life of in-service pipelines, comprising: Peak Intensity and Carbonyl Module: Used to establish a correlation model between the characteristic peak intensity of terahertz time-domain spectra and carbonyl index based on the terahertz time-domain spectral test data and Fourier transform infrared spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters; Carbonyl and Strength Module: Used to establish a correlation model between carbonyl index and yield strength based on the tensile property test data and Fourier transform infrared spectroscopy test data of non-metallic tubes after accelerated aging tests under different parameters; Strength and Life Module: Used to establish a yield strength-remaining life correlation model for non-metallic pipes; Evaluation module: Based on the terahertz time-domain spectral test data of high-risk sections of non-metallic pipelines in service, the correlation models between the intensity of characteristic peaks of terahertz time-domain spectroscopy and carbonyl index, the correlation model between carbonyl index and yield strength, and the correlation model between yield strength and remaining life are used to evaluate the remaining life of non-metallic pipelines in service.

[0015] In a specific embodiment of the present invention, the peak intensity and carbonyl module includes a calculation submodule and a simulation submodule; The calculation submodule is used to calculate the terahertz characteristic peak intensity data of the non-metallic sample tube after accelerated aging test under different parameters based on the terahertz time-domain spectral test data of the non-metallic sample tube after accelerated aging test under different parameters; it is also used to calculate the carbonyl index data of the non-metallic sample tube after accelerated aging test under different parameters based on the Fourier transform infrared spectral test data of the non-metallic sample tube after accelerated aging test under different parameters. The simulation submodule is used to simulate and obtain the correlation model between the intensity of the terahertz time-domain spectral characteristic peaks and the carbonyl index of the non-metallic sample tubes after accelerated aging tests under different parameters.

[0016] A third objective of this invention is to provide an electronic device comprising: a processor coupled to a memory; The memory is used to store computer programs; The processor is configured to execute the computer program stored in the memory, so that the electronic device performs the method as described.

[0017] A fourth objective of this invention is to provide a computer-readable storage medium storing a program or instructions that, when executed on a computer, cause the computer to perform the method as described.

[0018] The beneficial effects of this invention are: This invention discloses a method, system, storage medium, and device for assessing the remaining life of in-service pipelines. By utilizing terahertz time-domain spectral data, Fourier transform infrared spectral data, and tensile test data of sample tubes after accelerated aging tests, it constructs correlation models between the intensity of characteristic peaks in the terahertz time-domain spectrum and the carbonyl index, the correlation model between the carbonyl index and the yield strength, and the correlation model between the yield strength and the remaining life. This enables on-site quantitative assessment of the remaining life of in-service pipelines solely through terahertz time-domain spectral testing, solving the problem of in-situ, non-destructive, and quantitative assessment of the aging degree and remaining life of in-service pipelines.

[0019] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart of a method for assessing the remaining service life of an in-service pipeline according to an embodiment of the present invention is shown; Figure 2 A detailed flowchart of a method for assessing the remaining service life of in-service polyethylene pipelines according to an embodiment of the present invention is shown; Figure 3 A tensile test sample of a polyethylene sample pipe according to an embodiment of the present invention is shown; Figure 4 The following is a terahertz time-domain spectral analysis of an in-service polyethylene pipeline according to an embodiment of the present invention; Figure 5 A thermal map of the remaining life of a pipeline obtained after a quantitative evaluation of the remaining life of a polyethylene pipeline in service according to an embodiment of the present invention is shown. Figure 6 A framework diagram of an in-service pipeline remaining life assessment system according to an embodiment of the present invention is shown; Figure 7 A frame diagram of an electronic device according to an embodiment of the present invention is shown; In the figure: Peak intensity and carbonyl module 10; carbonyl and intensity module 20; intensity and lifetime module 30; evaluation module 40. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] like Figure 1 As shown, a method for assessing the remaining service life of an in-service pipeline according to certain embodiments of the present invention includes: S1. Based on the terahertz time-domain spectral test data and Fourier transform infrared spectral test data of non-metallic sample tubes after accelerated aging test under different parameters, a correlation model between the intensity of characteristic peaks of terahertz time-domain spectroscopy and carbonyl index is established. S2. Based on the tensile property test data and Fourier transform infrared spectroscopy test data of non-metallic tubes after accelerated aging tests under different parameters, a correlation model between carbonyl index and yield strength is established. S3. Establish a yield strength-remaining life correlation model for non-metallic pipes; S4. Based on the terahertz time-domain spectral test data of high-risk sections of non-metallic in-service pipelines, establish correlation models between the intensity of characteristic peaks in the terahertz time-domain spectrum and the carbonyl index, correlation models between the carbonyl index and the yield strength, and correlation models between the yield strength and the remaining life, and complete the assessment of the remaining life of non-metallic in-service pipelines.

[0024] In some embodiments of the present invention, in step S1, the non-metallic sample tube is a new non-metallic tube, that is, a new tube made of the same material as the non-metallic in-service pipeline of the evaluation object.

[0025] In some embodiments of the present invention, in step S1, the parameters in the accelerated aging test under different parameters include the temperature and time of the accelerated thermo-oxidative aging test. In accelerated aging tests under different parameters, the controlled variable method was used to control the temperature and time variables of the thermo-oxidative aging accelerated test to obtain polyethylene sample tubes with different aging degrees, thereby providing sufficient experimental data for subsequent correlation model parameter fitting. For example, set 3 to 4 test temperatures within the temperature range of 60℃ to 120℃, and set 4 to 6 test holding times within the time range of 0 to 2000h, for a total of 12 to 24 experimental groups, and set up a control group at the same time.

[0026] In some embodiments of the present invention, in step S1, when performing terahertz time-domain spectroscopy on the non-metallic sample tube after the accelerated aging test, the aged sample tube needs to be removed from the oven and placed in the test environment for 2 to 8 hours, and the test surface should be cleaned with reagents such as isopropanol to avoid interference from oxidized dust. The terahertz detection parameters were set as follows: scanning time window ≥ 80 ps, ​​spectral range between 0.4 and 2.6 THz, so as to obtain high-quality terahertz time-domain signals.

[0027] In some embodiments of the present invention, step S1 includes: S1-1. Based on the terahertz time-domain spectral test data of the non-metallic sample tube after accelerated aging test under different parameters, calculate the terahertz characteristic peak intensity data of the non-metallic sample tube after accelerated aging test under different parameters. S1-2. Based on the Fourier transform infrared spectral test data of the non-metallic sample tubes after accelerated aging tests under different parameters, the carbonyl index data of the non-metallic sample tubes after accelerated aging tests under different parameters are calculated. S1-3. Based on the terahertz characteristic peak intensity data and carbonyl index data of non-metallic sample tubes after accelerated aging tests under different parameters, a correlation model between the terahertz time-domain spectral characteristic peak intensity and the carbonyl index is fitted.

[0028] In some embodiments of the present invention, prior to step S1-1, a data reliability verification is further included, wherein the data reliability verification includes: i. Calculate the reliability correlation coefficient based on the terahertz time-domain spectral test data of the non-metallic sample tubes after accelerated aging test; ii. Based on the magnitude of the reliability correlation coefficient, determine whether the terahertz time-domain spectral test data is reliable. Specifically, if the reliability correlation coefficient is greater than or equal to the preset value, the terahertz time-domain spectral test data passes the reliability verification, and the calculation of step S1-1 is performed; if the reliability correlation coefficient is less than the preset value, the terahertz time-domain spectral test data fails the reliability verification, and it is necessary to rescan or readjust the terahertz detection parameters and re-detect until the terahertz time-domain spectral test data passes the reliability verification.

[0029] In some embodiments of the present invention, the reliability correlation coefficient is calculated using the following formula (1): (1) In equation (1), The correlation coefficient, The first scan time domain signal is the first... i The electric field intensity value at each time point The second scan time domain signal i The electric field intensity value at each time point This is the average value of the first scan signal. This is the average value of the second scan signal.

[0030] In some embodiments of the present invention, the intensity of the terahertz characteristic peak The calculation formulas are shown in equations (2)-(4): (2) (3) (4) In equations (2)-(4), and These represent the time-domain and frequency-domain signal strengths of the terahertz signal, respectively. and These represent the frequency domain intensity signals of the sample and the reference (air), respectively. For frequency The absorption coefficient at that location, For sample thickness, , The start and end frequencies of the characteristic peak.

[0031] In some embodiments of the present invention, the carbonyl index The calculation formula is shown in equation (5): (5) In equation (5), The area of ​​the carbonyl peak. This represents the area of ​​the methylene peak (internal standard peak).

[0032] In some embodiments of the present invention, in steps S1-3, a correlation model between the intensity of the terahertz time-domain spectral characteristic peak and the carbonyl index is established through data fitting. The correlation model between the intensity of the terahertz time-domain spectral characteristic peak and the carbonyl index is shown in equation (6): (6) In equation (6), , These are the parameters for the associated model.

[0033] In some embodiments of the present invention, step S2 includes: S2-1. Based on the tensile property test data of non-metallic tubes after accelerated aging tests under different parameters, calculate the yield strength data of non-metallic tubes after accelerated aging tests under different parameters. S2-2. Based on the Fourier transform infrared spectral test data of the non-metallic sample tube after accelerated aging test under different parameters, the carbonyl index data of the non-metallic sample tube after accelerated aging test under different parameters is calculated. It can be seen that step S1-2 and step S2-2 are the same. The carbonyl index data of the non-metallic sample tube only needs to be obtained once. That is, the carbonyl index data of the non-metallic sample tube has been calculated in step S1-2, so step S2-2 can be omitted. S2-3. Based on the yield strength data and carbonyl index data of non-metallic sample tubes after accelerated aging tests under different parameters, a correlation model between carbonyl index and yield strength is simulated.

[0034] In some embodiments of the present invention, in steps S2-3, a correlation model between the carbonyl index and the yield strength is established through data fitting, and the correlation model between the carbonyl index and the yield strength is shown in equation (7): (7) In equation (7), σ y For yield strength, For initial strength, This represents the aging sensitivity coefficient.

[0035] In some embodiments of the present invention, step S3 includes: S3-1. The tensile property test data of the non-metallic sample tube after accelerated aging test under different parameters is used as the yield strength data of the non-metallic sample tube after accelerated aging test under different parameters. It can be seen that step S3-1 is the same as step S2-1. The tensile property test data of the non-metallic sample tube only needs to be obtained once. That is, the tensile property test data of the non-metallic sample tube has been calculated in step S2-1, so step S3-1 can be omitted. S3-2. Based on the standard power law formula and the actual operating temperature and pressure of in-service pipelines, a correlation model between the yield strength and remaining life of in-service polyethylene pipelines is established.

[0036] In some embodiments of the present invention, the standard power law formula is shown in equation (8): (8) In equation (8), The circumferential stress borne by the pipe material. t For stress Time required for destruction under the influence of the action a is a material constant, and b is the stress exponent.

[0037] Assuming the long-term strength behavior of the polyethylene pipeline (i.e., the circumferential stress of the pipeline under operating conditions) σ op and short-term strength behavior (i.e., yield strength obtained from tensile properties) and short-term strength behavior. σ y Both follow the classical power-law equation, assuming that long-term strength and short-term strength lie on the same stress-life curve. The short-term point ( t y , σ y ) and long-term point ( t op , σ op Substituting all of them into the power law formula (8), we can obtain equations (9) and (10): (9) (10) Dividing formula (9) by formula (10) yields: (11) Taking the natural logarithm of both sides and simplifying, we get formula (12): (12) Since the time required for material failure during short-term strength testing is much shorter than that required for material failure during long-term strength testing, formula (12) can be further simplified to obtain: (13) In equation (13), A and B are both material constants, which are constants determined by the material properties.

[0038] Based on formula (13), the influence of pipeline operating temperature on its lifespan is further considered, and the Arrhenius equation is used to modify the pipeline lifespan. The modified formula is shown in formula (14): (14) In equation (14), t OP This is the equivalent time (i.e., equivalent life) for pipeline failure when converted to the actual operating temperature of the pipeline. t res Let R be the remaining life of the pipeline, and R be a material constant. The oxidation activation energy of polyethylene material. For the operating temperature of the pipeline, Room temperature.

[0039] After the above processing, the yield strength-remaining life correlation model is obtained, as shown in equation (15): (15) In equation (8), For the circumferential stress of the pipeline, σ y For yield strength, A , B , R For material constants, The oxidation activation energy of polyethylene material. For the operating temperature of the pipeline, Room temperature.

[0040] In some embodiments of the present invention, step S4 includes: S4-1. Based on the terahertz time-domain spectral test data of high-risk sections of non-metallic in-service pipelines, calculate the intensity of the characteristic peaks of the terahertz time-domain spectrum of non-metallic in-service pipelines. S4-2. Input the intensity of the terahertz time-domain spectral characteristic peak of the non-metallic in-service pipeline into the correlation model between the intensity of the terahertz time-domain spectral characteristic peak and the carbonyl index to obtain the carbonyl index of the non-metallic in-service pipeline. S4-3. Input the carbonyl index of the non-metallic in-service pipeline into the correlation model between the carbonyl index and the yield strength to obtain the yield strength of the non-metallic in-service pipeline. S4-4. Input the yield strength of the non-metallic in-service pipeline into the yield strength-remaining life correlation model to obtain the remaining life of the non-metallic in-service pipeline. S4-5. Based on the remaining service life of non-metallic pipelines in service, conduct an assessment of the remaining service life of non-metallic pipelines in service.

[0041] In some embodiments of the present invention, the high-risk pipe section of the non-metallic in-service pipeline is obtained through risk analysis of the non-metallic in-service pipeline, wherein the risk analysis includes: A systematic survey and analysis is conducted on the pipeline attributes (material, diameter, wall thickness, working pressure, service life, burial depth, etc.), operating history (leakage records, third-party damage incidents, maintenance records, inspection reports, etc.), environmental information (soil corrosivity, surrounding geology, etc.), and management data (design documents, installation quality records, welding process qualification, completeness of safety management system, etc.) of non-metallic in-service pipelines to screen out typical high-risk pipeline sections. The specific analysis process is a routine operation in this technical field, and the embodiments of this invention will not be described in detail here.

[0042] In some embodiments of the present invention, before conducting terahertz time-domain spectroscopy testing on high-risk sections of non-metallic in-service pipelines, the process includes on-site excavation of the high-risk sections and pretreatment of the pipe surface. The pretreatment of the pipe surface after excavation mainly includes: removal of attachments, polishing of the testing area, and cleaning of dust / oil.

[0043] Remove attachments: Use a plastic scraper to gently scrape away hard attachments such as soil / asphalt; Polishing of the inspection area: Use #600-#2000 grit sandpaper in sequence for polishing under water lubrication conditions; Dust / oil cleaning: Wipe with a non-woven cloth soaked in isopropyl alcohol in one direction, repeat until no residue remains, and then blow the surface with a high-pressure air gun.

[0044] The following is a specific application example of the above-mentioned method for assessing the remaining service life of in-service pipelines. The non-metallic in-service pipeline is a polyethylene in-service pipeline. The detailed flowchart is as follows: Figure 2 As shown, it specifically includes: Thermo-oxidative aging test: The test plan is set in advance: The thermo-oxidative aging test temperatures are 80℃, 100℃ and 120℃, and the test times are 0h, 48h, 168h and 336h, respectively. Three parallel samples are prepared for each aging condition. After setting the target temperature and ventilation rate (air exchange rate of 10 times / hour) according to the experimental plan, place the sample to start the thermo-oxidative accelerated aging test, mark it and record the experimental data; After the thermo-oxidative accelerated aging test, the sample was removed from the oven and placed in the test environment for 2 hours. The test surface was then cleaned with isopropanol to avoid interference from oxidative dust.

[0045] Terahertz time-domain spectroscopy testing: The terahertz time-domain spectroscopy system was used to scan and detect the samples after accelerated aging tests under different parameters to obtain the time-domain spectral data of the polyethylene sample tubes. The terahertz scanning frequency range is set to 0.4~2.6 THz, and the scanning time window is ≥80 ps; First, the same point on the sample is scanned three times repeatedly, and the reliability of the terahertz time-domain data is verified according to equation (1): Substituting the scan data into formula (1), the correlation coefficient of the terahertz time-domain waveform is >0.99, indicating that the terahertz scan data is reliable and can be used for subsequent modeling.

[0046] Fourier transform infrared spectroscopy test: Fourier transform infrared spectrometer was used to test the sample tubes after accelerated aging test under different parameters.

[0047] Tensile testing: Samples were taken from the tubes after accelerated aging tests under different parameters for tensile property testing to obtain the tensile strength of tubes at different aging degrees. The samples for tensile testing are as follows: Figure 3 As shown.

[0048] Step S1: Based on the terahertz time-domain spectroscopy test data, and according to formulas (2) to (4), the carbonyl characteristic peaks at 1.6-1.8 THz are analyzed, and the time-domain signal is converted into a digital signal. Convert to frequency domain signal And calculate the intensity of the terahertz characteristic peak. ; In this embodiment, =10 cm, =1.6 THz, =1.8 THz, substituting into formulas (2)~(4) to calculate the terahertz characteristic peak intensity of samples with different aging degrees. See Table 1 (characteristic peak intensities of samples after different thermo-oxidative accelerated aging tests). and carbonyl index ).

[0049] Table 1

[0050] Step S2: Based on the Fourier transform infrared spectroscopy test data, and according to formula (5), the carbonyl index of the sample tubes with different aging degrees is determined. The calculations were performed, and the results are shown in Table 1.

[0051] The characteristic peak intensities calculated based on Table 1 carbonyl index of polyethylene sample tube The relationship between the two is fitted to establish the characteristic peak intensity of the terahertz time-domain spectrum. carbonyl index of polyethylene sample tube The relationship model between them is shown in equation (16): (16) Step S3: Establish the carbonyl index of the polyethylene sample tube With yield strength The relationship model between them is shown in Equation (17): (17) Risk analysis of in-service polyethylene pipelines: Conduct risk analysis of in-service polyethylene pipelines, systematically investigate and analyze the material, diameter, wall thickness, working pressure, service life, burial depth, leakage records, third-party damage incidents, maintenance records, inspection reports, soil corrosivity, surrounding geology, design documents, installation quality records, welding process qualification, and completeness of safety management system of polyethylene pipelines, and screen out typical high-risk pipeline sections.

[0052] On-site excavation: High-risk pipe sections are excavated on-site, and the pipe surface is pre-treated. First, use a plastic scraper to lightly scrape away hard deposits such as soil / asphalt on the surface of the area to be inspected. Then, use #600, #1000, #1500, and #2000 grit sandpaper in sequence under water lubrication to polish the surface of the area to be inspected; use a non-woven cloth soaked in isopropyl alcohol to wipe in one direction, repeat until there is no residue, and then blow the surface with a high-pressure air gun.

[0053] Terahertz time-domain spectroscopy was performed on the high-risk section of the in-service ethylene pipeline obtained from the on-site excavation. The on-site test results were as follows: Figure 4 The pretreated polyethylene pipe was scanned on-site using a terahertz time-domain spectroscopy system. The terahertz scanning frequency range was set to 0.4~2.6 THz, and the scanning time window was ≥80 ps. The intensity of the terahertz characteristic peaks was calculated using formulas (2)~(4) in conjunction with terahertz signal processing. Approximately 19.8 cm -1 ·THz.

[0054] Step S4: Substitute the characteristic peak intensity value into the pre-established terahertz characteristic peak intensity -Carbonyl index The correlation model (Formula (16)) is used to calculate the carbonyl index of polyethylene pipes. It is approximately 2.80.

[0055] Substitute the carbonyl index into the pre-established carbonyl index. - Yield strength σ y The correlation model (Formula (17)) is used to calculate the yield strength of polyethylene pipes. σ y It is approximately 23.36 MPa.

[0056] Substituting the yield strength value into equation (15), the remaining service life of polyethylene pipelines in service is calculated. t res In this embodiment, a quantitative assessment is performed. σ y =23.36 MPa =2.2 MPa, A=0.00002, B=5.8125, =90 kJ / mol, R=8.314J / (mol·K), =313K, =293K, the remaining life of the polyethylene pipe is calculated. t res Approximately 18 years.

[0057] Based on the above assessment method, the remaining life of other pipe sections was calculated. The remaining life was then divided into segments of 5 years each, and a heat map of the pipeline's remaining life was drawn to provide a reference for subsequent pipeline operation and management after the assessment. Figure 5 As shown.

[0058] like Figure 6 As shown, a system for assessing the remaining service life of an in-service pipeline according to certain embodiments of the present invention includes: Peak Intensity and Carbonyl Module 10: Used to establish a correlation model between the characteristic peak intensity of terahertz time-domain spectra and carbonyl index based on the terahertz time-domain spectral test data and Fourier transform infrared spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters; Carbonyl and Strength Module 20: Used to establish a correlation model between carbonyl index and yield strength based on the tensile property test data and Fourier transform infrared spectroscopy test data of non-metallic tubes after accelerated aging tests under different parameters; Strength and Life Module 30: Used to establish a yield strength-remaining life correlation model for non-metallic pipes; Evaluation Module 40: Based on the terahertz time-domain spectral test data of high-risk sections of non-metallic in-service pipelines, the correlation models between the intensity of terahertz time-domain spectral characteristic peaks and carbonyl index, the correlation model between carbonyl index and yield strength, and the correlation model between yield strength and remaining life are used to evaluate the remaining life of non-metallic in-service pipelines.

[0059] In some embodiments of the present invention, the peak intensity and carbonyl module 10 includes a calculation submodule and a simulation submodule; The calculation submodule is used to calculate the terahertz characteristic peak intensity data of the non-metallic sample tube after accelerated aging test under different parameters based on the terahertz time-domain spectral test data of the non-metallic sample tube after accelerated aging test under different parameters; it is also used to calculate the carbonyl index data of the non-metallic sample tube after accelerated aging test under different parameters based on the Fourier transform infrared spectral test data of the non-metallic sample tube after accelerated aging test under different parameters. The simulation submodule is used to simulate and obtain the correlation model between the intensity of the terahertz time-domain spectral characteristic peaks and the carbonyl index of the non-metallic sample tubes after accelerated aging tests under different parameters.

[0060] like Figure 7 As shown, in some embodiments of the present invention, an electronic device is provided, the electronic device 300 including: a processor 301 coupled to a memory 302; The memory 302 is used to store computer programs; The processor 301 is configured to execute the computer program stored in the memory 302, so that the electronic device performs the method described in the above embodiments.

[0061] In some embodiments of the present invention, a computer-readable storage medium is provided that stores a program or instructions that, when executed on a computer, cause the computer to perform the methods described in the above embodiments.

[0062] According to embodiments of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, electronic device, or apparatus.

[0063] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for assessing the remaining service life of in-service pipelines, characterized in that, include: Based on the terahertz time-domain spectral test data and Fourier transform infrared spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters, a correlation model between the intensity of characteristic peaks in the terahertz time-domain spectrum and the carbonyl index was established. Based on the tensile property test data and Fourier transform infrared spectroscopy test data of non-metallic tubes after accelerated aging tests under different parameters, a correlation model between carbonyl index and yield strength was established. Establish a yield strength-remaining life correlation model for non-metallic pipes; Based on the terahertz time-domain spectral test data of high-risk sections of non-metallic pipelines in service, the correlation models between the intensity of characteristic peaks in the terahertz time-domain spectral data and the carbonyl index, the correlation model between the carbonyl index and the yield strength, and the correlation model between the yield strength and the remaining life were established to complete the assessment of the remaining life of non-metallic pipelines in service.

2. The method for assessing the remaining service life of in-service pipelines according to claim 1, characterized in that, The parameters in the accelerated aging test under different parameters include the temperature and time of the accelerated thermo-oxidative aging test.

3. The method for assessing the remaining service life of an in-service pipeline according to claim 1, characterized in that, Based on the terahertz time-domain spectral data and Fourier transform infrared spectral data of non-metallic sample tubes after accelerated aging tests under different parameters, a correlation model between the intensity of characteristic peaks in the terahertz time-domain spectrum and the carbonyl index is established, including: Based on the terahertz time-domain spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters, the intensity data of terahertz characteristic peaks of non-metallic sample tubes after accelerated aging tests under different parameters were calculated. Based on the Fourier transform infrared spectral test data of non-metallic samples after accelerated aging tests under different parameters, the carbonyl index data of non-metallic samples after accelerated aging tests under different parameters were calculated. Based on the terahertz characteristic peak intensity data and carbonyl index data of non-metallic samples after accelerated aging tests under different parameters, a correlation model between the terahertz time-domain spectral characteristic peak intensity and the carbonyl index was fitted.

4. The method for assessing the remaining service life of an in-service pipeline according to claim 3, characterized in that, Before the step of "calculating the terahertz characteristic peak intensity data of non-metallic sample tubes after accelerated aging tests under different parameters based on the terahertz time-domain spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters", the reliability verification of the data is also included, which includes: The reliability correlation coefficient was calculated based on the terahertz time-domain spectral test data of the non-metallic sample tube after accelerated aging test. The reliability of terahertz time-domain spectroscopy test data can be determined based on the magnitude of the reliability correlation coefficient.

5. The method for assessing the remaining service life of an in-service pipeline according to claim 4, characterized in that, The reliability correlation coefficient is calculated using the following formula: in, The correlation coefficient is... The first scan time domain signal is the first... i The electric field intensity value at each time point The second scan time domain signal i The electric field intensity value at each time point The average value of the first scan signal. This is the average value of the second scan signal.

6. The method for assessing the remaining service life of an in-service pipeline according to claim 1, characterized in that, Based on the tensile property test data and Fourier transform infrared spectroscopy test data of non-metallic sample tubes after accelerated aging tests under different parameters, a correlation model between carbonyl index and yield strength is established, including: Based on the tensile property test data of non-metallic tubes after accelerated aging tests under different parameters, the yield strength data of non-metallic tubes after accelerated aging tests under different parameters were calculated. Based on the Fourier transform infrared spectroscopy test data of non-metallic samples after accelerated aging tests under different parameters, the carbonyl index data of non-metallic samples after accelerated aging tests under different parameters were calculated. Based on the yield strength and carbonyl index data of non-metallic samples after accelerated aging tests under different parameters, a correlation model between carbonyl index and yield strength was fitted.

7. The method for assessing the remaining service life of an in-service pipeline according to claim 1, characterized in that, The remaining life of non-metallic in-service pipelines is assessed using terahertz time-domain spectral test data of high-risk sections of the pipeline, including correlation models between terahertz time-domain spectral characteristic peak intensity and carbonyl index, correlation models between carbonyl index and yield strength, and yield strength-remaining life correlation models. This assessment includes: The intensity of the characteristic peak of the terahertz time-domain spectrum of non-metallic in-service pipelines was calculated based on the terahertz time-domain spectral test data of high-risk sections of non-metallic in-service pipelines. The carbonyl index of the non-metallic in-service pipeline is obtained by inputting the intensity of the terahertz time-domain spectral characteristic peak of the Hertz time-domain spectral characteristic peak into the correlation model between the intensity of the terahertz time-domain spectral characteristic peak and the carbonyl index. By inputting the carbonyl index of the non-metallic in-service pipeline into the correlation model between the carbonyl index and the yield strength, the yield strength of the non-metallic in-service pipeline can be obtained. Input the yield strength of the non-metallic in-service pipeline into the yield strength-remaining life correlation model to obtain the remaining life of the non-metallic in-service pipeline. The remaining service life of non-metallic in-service pipelines is assessed based on their remaining service life.

8. The method for assessing the remaining service life of an in-service pipeline according to claim 1, characterized in that, The yield strength-remaining life correlation model for the non-metallic pipe is shown in the following equation: in, σ y For yield strength, t res For remaining lifespan, For the circumferential stress of the pipeline, A , B , R For material constants, The oxidation activation energy of polyethylene material. The operating temperature of the pipeline. Room temperature.

9. A system for assessing the remaining service life of in-service pipelines, characterized in that, include: Peak Intensity and Carbonyl Module: Used to establish a correlation model between the characteristic peak intensity of terahertz time-domain spectra and carbonyl index based on the terahertz time-domain spectral test data and Fourier transform infrared spectral test data of non-metallic sample tubes after accelerated aging tests under different parameters; Carbonyl and Strength Module: Used to establish a correlation model between carbonyl index and yield strength based on the tensile property test data and Fourier transform infrared spectroscopy test data of non-metallic tubes after accelerated aging tests under different parameters; Strength and Life Module: Used to establish a yield strength-remaining life correlation model for non-metallic pipes; Evaluation module: Based on the terahertz time-domain spectral test data of high-risk sections of non-metallic pipelines in service, the correlation models between the intensity of characteristic peaks of terahertz time-domain spectroscopy and carbonyl index, the correlation model between carbonyl index and yield strength, and the correlation model between yield strength and remaining life are used to evaluate the remaining life of non-metallic pipelines in service.

10. A system for assessing the remaining service life of in-service pipelines according to claim 9, characterized in that, The peak intensity and carbonyl module includes a calculation submodule and a simulation submodule; The calculation submodule is used to calculate the terahertz characteristic peak intensity data of the non-metallic sample tube after accelerated aging test under different parameters based on the terahertz time-domain spectral test data of the non-metallic sample tube after accelerated aging test under different parameters; it is also used to calculate the carbonyl index data of the non-metallic sample tube after accelerated aging test under different parameters based on the Fourier transform infrared spectral test data of the non-metallic sample tube after accelerated aging test under different parameters. The simulation submodule is used to simulate and obtain the correlation model between the intensity of the terahertz time-domain spectral characteristic peaks and the carbonyl index of the non-metallic sample tubes after accelerated aging tests under different parameters.

11. An electronic device, characterized in that, include: Processor, the processor being coupled to memory; The memory is used to store computer programs; The processor is configured to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 8.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program or instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 8.

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