A method for electromagnetic monitoring of the state of integrity of a pipeline and positioning of abnormal points

Abstract

The application discloses an electromagnetic monitoring and detecting method for buried pipe network state under complex environmental conditions, which comprises the following steps: establishing an electromagnetic system geoelectric model of a detection area containing a pipeline and external environmental conditions of the pipeline, including a reinforced concrete layer, gravel-soil landfill covering and an outer covering protective layer of the pipeline, pipeline and routing information; establishing an electromagnetic excitation, signal detection and data acquisition system for pipeline state monitoring; based on the collected electromagnetic field components, applying a time-frequency electromagnetic method to complete electromagnetic field inversion of the detection area, obtaining the resistivity and polarizability distribution, and realizing monitoring and detecting of the pipeline or pipe network integrity state. The application has the beneficial effects that different states of the pipeline can be distinguished, the leakage point position can be determined, and the method is still applicable under the complex environmental conditions containing the concrete covering; in addition, no manual participation is needed, and the method is suitable for complex pipe network scenes containing different pipe diameters and staggered laying, and needs real-time or regular or irregular monitoring and detecting.

Description

Technical Field

[0001] The present invention relates to the field of pipeline monitoring and detection, and in particular to a method for electromagnetic monitoring and detection of pipeline integrity status and abnormal point positioning. Background Art

[0002] Due to its many advantages such as high safety and efficiency, stable and reliable operation, low cost, and less impact from climatic conditions, pipeline transportation has always been widely regarded as the best choice for fuel transportation. Buried pipelines have also been widely used in fuel transportation on airport aprons.

[0003] However, with increasing service life or the influence of external environmental factors, pipelines can experience corrosion, aging, and even leaks, ultimately becoming risk factors for various pipeline accidents. Leaks in buried pipelines can lead to unpredictable risks, environmental pollution, and economic losses. Monitoring, testing, and leak location in complex environments like helipads are often even more complex and difficult.

[0004] Pipeline condition monitoring or inspection is a crucial component in maintaining safe pipeline operation. Pipeline monitoring and inspection can be broadly categorized into three types: internal inspection, external inspection, and real-time online monitoring and inspection. Current domestic and international internal inspection equipment, also known as internal inspection robots, requires the equipment to travel within the pipeline, inspecting the pipeline's integrity using various inspection techniques, such as magnetic flux leakage testing and ultrasonic testing. External inspection uses various patrol techniques, including audio, laser, and electromagnetic methods for buried pipeline inspection. Numerous methods have been developed for real-time online monitoring and inspection, including pressure gradient methods, acoustic wave methods, and simulation. However, all current inspection technologies have their limitations and are not well suited for monitoring and inspecting complex fuel pipelines laid beneath the reinforced concrete layer of airport aprons. Furthermore, they lack real-time online monitoring capabilities and still require significant human involvement during inspections. Summary of the Invention

[0005] To address the technical problem that pipeline integrity status monitoring and detection under complex environmental conditions cannot be performed in real time and requires human intervention, this application provides a time-frequency electromagnetic method that can achieve real-time online monitoring and detection and anomaly location. Based on electromagnetic detection technology, this method realizes real-time monitoring and detection of pipeline status under complex environmental conditions without the need for human on-site participation.

[0006] The present invention provides a pipeline integrity status electromagnetic monitoring detection and abnormal point location method comprising the following steps:

[0007] S1: Establish an electromagnetic field geoelectric model of the detection area containing the pipeline and the external environment condition of the pipeline, the electromagnetic field geoelectric model comprising a reinforced concrete layer, a gravel-soil landfill covering and an outer protective layer of the pipeline, a pipeline geometric model and routing information;

[0008] S2: Establish an electromagnetic monitoring and detection unit, the electromagnetic monitoring and detection unit comprising an electromagnetic excitation system, a signal detection system and an electromagnetic information acquisition system, the electromagnetic monitoring and detection unit being used for electromagnetic information verification and processing;

[0009] S3: The electromagnetic excitation system is used to generate an excitation signal, the excitation signal being coupled with the geoelectric system of the pipeline-external environment of the pipeline, being collected by the electromagnetic information acquisition system via the signal detection system; the electromagnetic excitation system and the electromagnetic information acquisition system are arranged in the monitoring and detection area, and the electromagnetic information acquisition system simultaneously collects an electric field component and a magnetic field component;

[0010] S4: Establish a signal processing system, the signal processing system performing signal preprocessing and signal correlation analysis denoising;

[0011] S5: Establish an inversion analysis system, the inversion analysis system providing a three-dimensional electromagnetic field distribution, a three-dimensional resistivity and a polarization rate distribution in the monitoring area by analyzing and processing the data provided by the electromagnetic information acquisition system; S6: A state discrimination system discriminates the integrity state of the buried pipeline through the electromagnetic information acquisition, signal processing and inversion analysis.

[0012] The application provides the beneficial effects that the technical problem of needing a large amount of manual participation in pipeline monitoring and detection under complex environmental conditions is solved, the pipeline detection efficiency is improved, and the cost is saved. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 is a method flowchart of the application;

[0014] Figure 2 is a two-dimensional metal pipeline model schematic diagram of the application;

[0015] Figure 3 is a principle schematic diagram of the electromagnetic monitoring and detection system;

[0016] Figure 4 is an electromagnetic excitation signal waveform schematic diagram;

[0017] Figure 5 is a calculation principle flowchart of COMSOL finite element simulation software;

[0018] Figure 6 is a working flowchart of a data processing device;

[0019] Figure 7is a schematic diagram of a frequency domain signal processing process;

[0020] Figure 8 is a schematic diagram of a time domain signal processing process;

[0021] Figure 9 is an electrical profile of a concrete layer model containing a substance;

[0022] Figure 10 is a time domain signal difference curve at a measuring point position of 0 meters of a concrete layer model containing a substance;

[0023] Figure 11 is an electrical profile of a reinforced concrete layer model;

[0024] Figure 12 is a time domain signal difference curve at a measuring point position of 0 meters of a reinforced concrete layer model. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and advantages of the present application clearer, the embodiments of the present application will be further described below with reference to the drawings.

[0026] Please refer to Figure 1 , Figure 1 is a schematic diagram of a method flow of the present application; a pipeline integrity state electromagnetic monitoring and abnormal point positioning method, wherein the method comprises the following steps:

[0027] S1: establishing an electromagnetic field system geoelectric model of a pipeline and external environmental conditions in a detection area, the electromagnetic field system geoelectric model comprising a reinforced concrete layer, a gravel-soil landfill covering and a pipeline outer coating layer, a pipeline geometric model and routing information;

[0028] It should be noted that the establishment of the electromagnetic field system geoelectric model of the pipeline-net-coating layer-environmental condition system in the present application is established by COMSOL finite element simulation software.

[0029] As an embodiment, the outer layer of the electromagnetic field system geoelectric model is composed of a spherical boundary layer representing a finite distance electromagnetic field, which contains an inner boundary of the finite distance electromagnetic field boundary layer O , the electromagnetic field system geoelectric model is sequentially provided from outside to inside with: a spherical finite distance boundary layer, an upper air of the ground, a monitoring outer area below the ground O , a monitoring inner area M , a concrete layer and a gravel-soil landfill covering, a pipeline outer coating layer and a pipeline; the area O and M is a monitoring boundaryB ; A buried pipeline is provided in the pebble-soil landfill cover; the pipeline comprises: a pipe body and a covering layer outside the pipe body; the inside of the pipe body is fuel oil; the concrete comprises plain concrete and reinforced concrete.

[0030] Monitoring area M An electromagnetic excitation system is provided inside, which is composed of one or more groups of excitation electric dipoles A and B, wherein the electric dipole A is connected to the steel pipeline, and the other electric dipole B corresponding to the group of electromagnetic excitation is grounded.

[0031] It should be noted that the applicable conditions of the electromagnetic model described in the present invention include reinforced concrete layer, pebble-soil landfill coverage and outer protective layer wrapping of pipelines, pipeline intersections, and changes in pipeline diameter; monitoring area M There are also multiple appropriately distributed monitoring detection points, each of which is equipped with a set of electric field detection sensors and magnetic field detection sensors (S); monitoring area M The boundary 𝛤 B Outside the monitoring area O The geoelectric properties of the monitoring area M The impact of the boundary 𝛤 B impact.

[0032] Please refer to Figure 2 , Figure 2 It is a schematic diagram of the electromagnetic model of this application;

[0033] The model ignores the influence of axial pipe response signals other than those in the plane.

[0034] The entire model consists of a Circular composition of rice, external setting The meter-thick infinite domain ensures that there will be no interference caused by interface reflection.

[0035] The upper part of the interior is set to air attributes, and the lower part is set to soil attributes. Considering that there may be interference layers in the earth in actual situations, Set up a meter thick concrete layer.

[0036] The pipe body area consists of three parts: the coating layer, the pipe body and the oil. The inner diameter of the pipe body is set to Meter, outer diameter The pipeline is filled with oil and the outer coating thickness is 0.01 meters; the pipeline burial depth is set to rice.

[0037] The material property parameters are shown in Table 1. Among them, the oil conductivity is only the direct current conductivity, and the complex conductivity can be calculated by formula (13) below.

[0038] Table 1: Model material property parameter table

[0039]

[0040] By inputting the geometric parameters of the model and the above-mentioned material parameters into the COMSOL finite element simulation software, a corresponding electromagnetic model is generated.

[0041] It should be noted that, Figure 2 The material to be filled area is also included in the above-mentioned, which is used for setting different working conditions and will be further explained in the following.

[0042] Please refer to Figure 3 , Figure 3 is a schematic diagram of the principle of the electromagnetic monitoring and detection system;

[0043] S2: Establish an electromagnetic monitoring and detection unit, which includes an electromagnetic excitation system, a signal detection system and an electromagnetic information acquisition system, and is used for electromagnetic information verification and processing;

[0044] The electromagnetic excitation generated by the electromagnetic excitation system is composed of current or voltage signals with different frequencies, amplitudes and morphological characteristics;

[0045] The signal detection system or the electromagnetic information acquisition system detects or acquires electromagnetic signals at least containing horizontal electric field component , vertical magnetic field component .

[0046] S3: Use the electromagnetic excitation system to generate excitation signals, which are coupled with the ground system of the pipeline-pipeline external environment, and are collected by the electromagnetic information acquisition system after passing through the signal detection system; the electromagnetic excitation system and the electromagnetic information acquisition system are arranged in the monitoring and detection area, and the electromagnetic information acquisition system simultaneously collects electric field component and magnetic field component;

[0047] The excitation signal emitted by the electromagnetic excitation system is emitted in the form of voltage and propagates outward perpendicular to the ground by the pipeline; the electromagnetic excitation signal includes time domain signal and frequency domain signal; the time domain signal adopts zero-crossing square wave, and the frequency signal adopts non-zero-crossing square wave.

[0048] For details, please refer to Figure 4 , Figure 4 is a schematic diagram of the electromagnetic excitation signal waveform; Figure 4 In the above-mentioned, (a) is a zero-crossing square wave, and (b) is a non-zero-crossing square wave.

[0049] The electromagnetic information acquisition system is set in the second layer of soil; in the embodiment of the present invention, the receiving source is set at a depth of 0.5 meters below the surface, which is conducive to the coupling of the receiving device and the soil and helps to effectively detect the signal.

[0050] S4: establishing a signal processing system, wherein the signal processing system performs signal preprocessing and signal correlation analysis and denoising;

[0051] S5: establishing an inversion analysis system, wherein the inversion analysis system analyzes and processes the data provided by the electromagnetic information acquisition system to provide a three-dimensional electromagnetic field distribution, a three-dimensional resistivity distribution, and a polarizability distribution within the monitoring area;

[0052] In step S5, the monitoring area is generated by inversion in the time domain and frequency domain using the electromagnetic information processing system. M The three-dimensional electromagnetic field distribution, three-dimensional resistivity and polarizability distribution within are as follows:

[0053] S51: In the monitoring area M The boundary 𝛤 B On, monitor the outer area O The geoelectric properties of the monitoring area M The influence of the boundary 𝛤 B and areas outside monitoring O The geoelectric system is determined by the corresponding boundary element method: L B U B = C O ,Right now U B = L B -1 C O ;in, U B is the geoelectric parameter on the boundary, L B 、 C O The monitoring area O The geoelectric system matrix and parameter vector;

[0054] S52: Establish monitoring area under normal circumstances M The discrete electromagnetic field equations in the monitoring area are solved to generate the M the electric field information and the magnetic field information inside the monitoring area;

[0055] S53: establishing a discrete electromagnetic field equation group in the monitoring area that meets the electromagnetic field information of the detection point, and inversely generating a monitoring area that meets the measured conditions when the excitation is applied M the electric field information and the magnetic field information inside the monitoring area; M the electric field information and the magnetic field information inside the monitoring area;

[0056] S54: inversely generating the three-dimensional electromagnetic field distribution, the three-dimensional resistivity and the polarization rate distribution inside the monitoring area.

[0057] S6: a state discrimination system that discriminates the integrity state of the buried pipeline through the above-mentioned electromagnetic information collection, signal processing and inversion analysis.

[0058] The excitation signal emitted by the electromagnetic excitation system is emitted in the form of voltage and is propagated outwardly from the pipeline perpendicular to the ground; the electromagnetic excitation signal includes a time domain signal and a frequency domain signal; the time domain signal adopts a zero-crossing square wave, and the frequency signal adopts a non-zero-crossing square wave.

[0059] The specific process of the signal processing system for processing the frequency domain electromagnetic field signal is as follows:

[0060] In the normal working condition, Fourier transform is performed on different frequency signals to obtain different frequency signal spectra; the normal working condition specifically refers to that the pipeline has no leakage and damage;

[0061] The different frequency signal spectra are superimposed to obtain a frequency curve; the frequency curve is corrected to obtain a corrected curve;

[0062] In the detection working condition, the detection working condition corrected curve is obtained;

[0063] The difference between the normal working condition corrected curve and the detection working condition corrected curve is processed to obtain a frequency signal difference curve;

[0064] The pipeline detection state is analyzed according to the frequency signal difference curve.

[0065] The specific process of the signal processing system for processing the time domain electromagnetic field signal is as follows:

[0066] In the normal working condition, the first period signal in the time domain signal is discarded, and the second period signal thereof is obtained;

[0067] The response signal of the time domain signal zero-crossing period is obtained;

[0068] The second period signal and the response signal are normalized to obtain a normalized signal;

[0069] The reverse superposition signal is obtained by reverse superposition processing on the normalized signal;

[0070] In the detection condition, the reverse superposition signal in the detection condition is obtained;

[0071] The reverse superposition signal in the normal condition is processed by difference with the reverse superposition signal in the detection condition, to obtain a time domain difference curve;

[0072] The pipeline detection state is obtained according to the time domain difference curve analysis.

[0073] The processing system determines whether the buried pipeline appears integrity state abnormality by comparing the measured electric field and magnetic field signals with the change characteristics of the normal state based on the time-frequency detection data processing method;

[0074] If the integrity state abnormality appears, it is determined whether the coating is damaged or the pipeline leaks based on the state change characteristics obtained by the time-frequency detection data processing method.

[0075] Here, the entire pipeline state detection is briefly described as follows.

[0076] Please refer to Figure 5 , Figure 5 is the calculation principle flowchart of COMSOL finite element simulation software;

[0077] Through COMSOL simulation, only a two-dimensional metal pipeline model can be established, meshed, matrix solved and results output. To meet the calculation requirements of the time-frequency electromagnetic method in the point model, the AC / DC module is selected, and the matrix solution is calculated by using the magnetic field solver.

[0078] In this process, there are two parts that COMSOL simulation software cannot accurately perform, namely the method of applying the field source and the reprocessing of the output data.

[0079] In this application, the signal excitation module of the electromagnetic monitoring and detection system is used to apply the field source (electric field, magnetic field), and the data processing module is used to reprocess the output data.

[0080] The entire forward process of the pipeline state detection is as follows:

[0081] First, the predetermined electromagnetic excitation signal is added in the electromagnetic excitation system, and the electromagnetic excitation signal is added as an initial condition in the electromagnetic model of the pipeline-coating-environmental condition system by the electromagnetic excitation system, and the electromagnetic field distribution in the model is obtained by solving the magnetic field solver;

[0082] Then, the signal at the receiving position is captured by the electromagnetic information acquisition system.

[0083] And the signal is screened, get with time-frequency electromagnetic method theoretical model in the corresponding And .

[0084] Again in electromagnetic information processing system electromagnetic excitation signal and received signal correlation processing, from this time-frequency electromagnetic method in the application of buried pipeline simulation analog calculation results.

[0085] The following is about the theoretical basis of time-frequency electromagnetic method, the invention made certain elaboration:

[0086] In the buried metal pipeline model, it can be assumed that the electromagnetic wave conducted to the ground by the pipeline is a plane wave, and its propagation process satisfies Maxwell's equations, as follows:

[0087]

[0088] The constitutive equation is:

[0089]

[0090] Among them, , is the dielectric constant, is the electrical conductivity; is the electric field intensity, is the magnetic field intensity, is the magnetic induction intensity, is the electric flux density, is the current density.

[0091] From the field theory formula and Lorentz condition, the wave equation of vector potential and scalar potential in electromagnetic field can be derived as follows:

[0092]

[0093]

[0094] Among them is the vector potential function, is the scalar potential function.

[0095] In the application of time-frequency electromagnetic method, the excitation signal has the nature of simple harmonic vibration, that is, contains time factor .

[0096] So you can get the frequency domain Maxwell's equations, as follows:

[0097]

[0098]

[0099]

[0100]

[0101] Taking the curl of both sides of equation (5) and substituting equation (6) into it, we get

[0102]

[0103] where , to consider the effect of the induced polarization effect, to ensure that the buried metal pipeline model material is polarizable, the frequency has an impact on the conductivity, here Take , , to consider the Cole-Cole model represented by the complex resistivity, as follows:

[0104]

[0105] where, is the direct current resistivity, is the polarization rate, is the time constant, is the frequency coefficient.

[0106] The reason for using the Cole-Cole model to represent the equivalent resistivity is that the double-layer of the two-phase medium will produce charging and discharging effect under the condition of external electric field, that is, excitation polarization effect, especially after the pipeline is damaged, the solid-liquid two-phase interface will be formed at the contact between the pipeline and the surrounding rock, and the excitation polarization effect will be produced under the excitation of the external electric field. In order to more accurately describe the resistivity of the stratum rock, the Cole-Cole model needs to be introduced to represent the equivalent resistivity of the earth.

[0107] In addition, the determination of the equivalent resistivity of the main medium in the foregoing model is as follows.

[0108] The main medium is soil, concrete, oil and metal pipeline. Since oil, concrete and metal pipeline themselves will not produce excitation polarization effect, only when the pipeline is damaged and the oil leaks into the soil, the Cole-Cole model needs to be introduced.

[0109] Therefore, the resistivity of oil, concrete and metal pipeline itself still adopts the known parameters, and the resistivity of soil without damage also adopts the normal value. Only when the soil is contaminated, the equivalent resistivity model is adopted.

[0110] Regarding the determination of the equivalent resistivity model parameters. The parameters in the equivalent resistivity model after the soil is contaminated include ρ 0, m , c , τ , collect the contaminated soil samples, and conduct resistivity dispersion test to obtain ρ 0,m , c , etc.

[0111] Thus, the complex resistivity represented by Cole-Cole model can be obtained by Helmholtz equation:

[0112]

[0113] By expanding formula (5), we can obtain:

[0114]

[0115] By expanding formula (6), we can obtain:

[0116]

[0117] In this study, the excitation signal is propagated outward by the pipe perpendicular to the ground, so , ; thus, in the homogeneous layered medium, there are only , and two mode polarized waves;

[0118] In this theoretical model, we need to solve mode electromagnetic wave propagation.

[0119] According to Helmholtz equation, we can solve :

[0120]

[0121] where the receiving source and the excitation source are not in the same position, at the same time, the outer boundary of the model is set to be infinite, and considering the small thickness of the interference layer and the small amplitude of the secondary reflection, the reflection term of the electromagnetic wave in the propagation process can be ignored.

[0122] Assuming the initial position , the solution of the above equation is:

[0123]

[0124] Thus, according to formula (13), we can obtain the amplitude of , and combined with the wave equation containing time variation, we can obtain the distribution of electromagnetic wave amplitude in time and space.

[0125] Regarding the inversion process, the theoretical basis is as follows:

[0126] How to improve the time-frequency electromagnetic identification pipeline running state, the inversion method is the key. Here to use known data modeling constraints part of the known model to improve the accuracy of the sequential constraint inversion method. General time-frequency joint inversion of resistivity model, is not enough to achieve the desired accuracy. Here to use time-frequency joint inversion of resistivity model as the initial model, on this basis will be known pipeline interface, with known oil, metal pipe, concrete interface and its resistivity change range of data to further refine the model, get used for inversion of the constraint model.

[0127] Geoelectric model includes geometric model M G and electrical model, electrical model includes M R (resistivity model), M η (polarization rate model, for soil layer), that is:

[0128] (16)

[0129] In the above formula:

[0130]

[0131]

[0132]

[0133] Using least squares for resistivity, polarization rate of the sequential inversion.

[0134] Resistivity inversion: geometric model M G The depth or thickness of the model is given by the known data; in the inversion of resistivity, we do not consider the polarization effect of soil, therefore, formula (16) only the first two, and, since the model geometric parameters do not need to be inverted, therefore, in the inversion equation model M G does not participate in the inversion, only for resistivity model M R inversion, resistivity model M R by time-frequency joint inversion of resistivity results and pipeline known data to give, according to the known data statistics model of part of the resistivity change, give the model resistivity change range , such as soil without known data is given by the test data of the soil resistivity of the exploration area. From the one-dimensional inversion can be calculated, the model geometric parameters do not participate in the inversion, the unknown number is reduced from 2 n +1 to n+1, the two-dimensional inversion reduces more; and the search range of resistivity model is reduced from more than 3 orders to within 1 order, which accelerates the convergence and inversion speed, especially can make the inversion converge to the reasonable range of stratum electrical property change, and finally obtain the model conforming to the geological law.

[0135] The polarization inversion: after the inversion determines the resistivity model, the inversion of the soil polarization effect is carried out again, because in the mathematical model describing the stratum complex frequency characteristics, such as the Cole-Cole model, the resistivity and the polarization are generally in the product relationship:

[0136] (17)

[0137] The inversion is difficult to fit and determine any unknown number at the same time, since the resistivity has a greater impact, generally, the direct current resistivity is inverted first, and after the resistivity model is obtained, the resistivity of the Cole-Cole model is fixed to invert the polarization, and other parameters τ 、 c can also be fixed and inverted one by one.

[0138] In this way, the resistivity model result reflects the electrical characteristics of the basic geological model, and the polarization inversion model result is the remaining electromagnetic anomaly in addition to the basic electrical characteristics. Similarly, the polarization model of the pipeline soil changes The range is given by the soil test.

[0139] After the theoretical model is described, the present application further describes from the set electromagnetic excitation signal.

[0140] In the frequency domain, the frequency of the transmitted signal will affect the distance of signal propagation, therefore, the transmitted signal frequency is calculated and determined by means of the effective skin depth formula.

[0141] It should be noted that since a disturbance layer-concrete layer is added in the model, its electrical parameters are quite different from those of the soil, and if the interference of the signal in the propagation process is ignored, the determination of the transmitted signal frequency range will be inaccurate;

[0142] Therefore, in order to improve the detection accuracy, the conductivity in formula (18) is modified, and the effective conductivity of the multi-layer medium is considered by formula derivation and brought into the calculation, and the specific form is shown in formula (19).

[0143] In order to obtain the response of the buried metal pipeline model in the frequency domain, the number of excitation signal frequencies is determined as 15, which is increased to , the calculation time of each model is kept at , and the step is .

[0144] In the time domain, the determination of the frequency in the reference frequency domain signal, the selection As the excitation period, the calculation time of each model is kept at three periods, i.e. , with a step size of .

[0145]

[0146]

[0147] wherein, is the effective skin depth, is the resistivity of the medium, is the effective conductivity, is the frequency of the transmitted signal, denotes the resistivity of the layer, denotes the thickness of the layer.

[0148] After obtaining the original signal by means of simulation calculation, the magnetic field signal and the electric field signal in the time domain and the frequency domain are reprocessed respectively, so as to help obtain better detection effect.

[0149] Please refer to Figure 6 , Figure 6 is a schematic diagram of the working process of the data processing device.

[0150] The working conditions will be discussed below. As for the working conditions, the present application is described as follows:

[0151] There are four working conditions in the present application, which are achieved by changing the properties of the material at the lower part of the pipeline.

[0152] Working condition one (normal working condition, which can be understood as a control group): the pipeline is in a normal and healthy state, and the coating layer is complete and has no leakage; Figure 2 Region 1 is filled with coating layer material, and region 2 is filled with soil.

[0153] Working condition two (detection working condition, which can be understood as experimental group 1): the oil in the pipeline leaks outward and penetrates into the soil layer, which is simplified as the lower part of the pipeline being wrapped by oil, and the coating layer being between the pipeline and the leaked oil; region 1 is filled with coating layer material, and region 2 is filled with oil.

[0154] Working condition three (detection working condition, which can be understood as experimental group 2): the outer coating layer of the pipeline is damaged, and the lower half of the original coating layer is missing, so that the pipeline is wrapped by the soil layer; region 1 and region 2 are both filled with soil.

[0155] Working condition four (detection working condition, which can be understood as experimental group 3): the outer wrapping layer of the pipeline is damaged, resulting in oil leakage and penetration into the soil layer, which is simplified as the pipeline being completely wrapped by the leaked oil; region 1 and region 2 are both filled with oil.

[0156] The specific process of the electromagnetic information processing system processing frequency domain electromagnetic field signals is as follows:

[0157] In normal working conditions, Fourier transform is performed on different frequency domain signals to obtain different frequency signal spectra; the normal working conditions specifically refer to no leakage and damage of the pipeline;

[0158] The different frequency signal spectra are superimposed to obtain a frequency curve;

[0159] The frequency curve is corrected to obtain a corrected curve;

[0160] In the detection working condition, the detection working condition corrected curve is obtained;

[0161] The difference between the normal working condition corrected curve and the detection working condition corrected curve is processed to obtain a frequency domain signal difference curve;

[0162] The pipeline detection state is analyzed according to the frequency signal difference curve.

[0163] Please refer to Figure 7 , Figure 7 is a schematic diagram of the frequency domain signal processing process (taking a 3000 Hz signal as an example) (a) original signal, (b) Fourier transform spectrum, (c) superimposed spectrum of each frequency spectrum, (d) simplified spectrum.

[0164] In the frequency domain, the original signal is first Fourier transformed to obtain the spectrum of each frequency signal, and then The spectrum of each frequency is superimposed to obtain a frequency curve containing frequencies under a working condition, and through simplification and correction, a trend line with obvious peak changes is obtained (as shown in Figure 7 ). By making a difference between different working conditions, the signal difference is amplified to obtain the final frequency domain signal difference curve.

[0165] The specific process of the electromagnetic information processing system processing time domain electromagnetic field signals is as follows:

[0166] In normal working conditions, the first periodic signal in the time domain signal is discarded, and the second periodic signal is obtained;

[0167] The response signal of the zero-crossing period of the time domain signal is obtained;

[0168] The second periodic signal and the response signal are normalized to obtain a normalized signal;

[0169] The normalized signal is inversely superimposed to obtain an inverse superimposed signal;

[0170] In the detection condition, the reverse superimposed signal in the detection condition is obtained;

[0171] The reverse superimposed signal in the normal condition is subtracted from the reverse superimposed signal in the detection condition, to obtain a time-domain difference curve;

[0172] The pipeline detection state is analyzed according to the time-domain difference curve.

[0173] Please refer to Figure 8 , Figure 8 is a schematic diagram of a time-domain signal processing process. (a) original signal, (b) second period signal, (c) falling segment signal, (d) rising segment signal, (e) normalized rising segment signal, (f) normalized falling segment signal, (g) curve after reverse superimposition;

[0174] In the time domain, the interference of the transmission module on the signal in the signal transmission and end phase needs to be eliminated, and the decay curve of the signal is obtained. First, the original whole segment signal is intercepted, which is divided into two steps, the first step obtains the signal of the second period, and the second step obtains the response signal of the transmission signal zero crossing period; then the two signals are normalized, and reverse superposition processing (as shown in Figure 8 ) is performed to enhance the signal-to-noise ratio of the signal.

[0175] Finally, the response signal curves of the four conditions are compared, and the difference is amplified by difference processing.

[0176] Finally, the present application describes how to identify abnormal pipelines.

[0177] As an embodiment, according to the change of the electromagnetic signal of the 15 measuring points with frequency, a model electrical section profile can be drawn, as shown in Figure 9 . Figure 9 is a model electrical section profile of a concrete layer containing elements.

[0178] Figure 9 In the figure, (a) is an electric field detection signal, (b) is a signal change of a damage layer in the electric field relative to a normal state, (c) is a signal change of a leakage in the electric field relative to a normal state, (d) is a magnetic field detection signal, (e) is a signal change of a damage in the magnetic field relative to a normal state, and (f) is a signal change of a leakage in the magnetic field relative to a normal state.

[0179] Figure 9 (a) is an electric field original signal of a pipeline in a normal condition, and it can be easily observed that the peak value appears at a frequency of .

[0180] Since the pipeline is the excitation source, the signal intensity should be the highest, so the frequency range of the peak value of the signal can be used to determine the depth range of the pipeline, or as a reference for pipeline detection and positioning.

[0181] Secondly, considering the change (difference) of signals in the broken and leakage conditions compared with the normal condition, the figures (b), (c) can be obtained. Figure (b) shows that between the two peak positions of the original signal, the maximum value of the difference amplitude appears, which accounts for , and the maximum proportion can reach . The reason for this difference or change is the damage of the pipeline coating. In figure (c), the frequency position corresponding to the highest detection signal strength also has a significant peak, and the maximum difference proportion can reach . This change is similar to the effect of the broken condition, which is the difference caused by pipeline leakage. The difference is that when the pipeline leaks, the difference amplitude and proportion increase. Because the distribution of electric field and magnetic field in the earth is different, the peak of the detection signal in the magnetic field appears at the lowest frequency Hz, which is much lower than the frequency position where the peak appears in the electric field. After comparing with the normal condition, the existence of the change can be clearly observed. The position of the difference peak in the broken coating condition is similar to the electric field, and the maximum abnormal proportion is . While the position of the difference peak in the leakage condition is similar to the detection signal, and both the amplitude and proportion are significantly larger than the broken condition, reaching .

[0182] Overall, when the pipeline state changes from the coating damage or leakage, the change can be observed from both the electric field and the magnetic field, and can be distinguished according to the different characteristics of the change and the difference of the signal change. In addition, the model also shows that the magnetic field signal is more sensitive to the change of the pipeline state.

[0183] Please refer to Figure 10 , Figure 10 for the difference curve of the time domain signal at the 0-meter point of the plain concrete layer model Figure 10 (a) electric field signal, (b) magnetic field signal.

[0184] In the electric field, whether it is a broken coating condition or a leakage condition, the difference with the normal condition increases first and then decreases with time, reaching a peak at , but the peak of the broken condition appears earlier than that of the leakage condition. In the magnetic field, the maximum peak of the signal difference appears at . Secondly, whether it is a magnetic field signal or an electric field signal, the absolute value of the change caused by the leakage condition is significantly larger than that of the broken coating condition. Based on the range of amplitude difference caused by the change of the pipeline state, different pipeline abnormal states can be distinguished.

[0185] To explore the influence of concrete on electromagnetic signals, the distribution of steel bars in the concrete layer also needs to be considered and compared with the detection signal under plain concrete.

[0186] Please refer to Figure 11 , Figure 11 It is the electrical cross-section diagram of the model including reinforced concrete layer.

[0187] Figure 11 (a) Electric field detection signal, (b) Signal difference between the coating damage and normal state in the electric field, (c) Signal difference between the leakage and normal state in the electric field, (d) Magnetic field detection signal, (e) Signal difference between the coating damage and normal state in the magnetic field, (f) Signal difference between the leakage and normal state in the magnetic field.

[0188] In the frequency domain, according to Figure 11 (a) and 11(b), it can be clearly observed that the electromagnetic shielding effect of the signal in the middle area of ​​the two steel-concrete boundaries due to the distribution of steel bars greatly weakens the strength of the detection signal. Since the signal can still bypass the reinforced concrete layer and propagate upwards through both sides to the measuring point on the surface, peaks can be observed on both sides of the steel-concrete boundary; and in the longitudinal direction, they correspond to the signal on the center line below the plain concrete. Secondly, according to Figure 11 (b), 11(c), 11(e) and 11(f) Figure 9 By comparing the corresponding figures in Figure 2, it can be found that the presence of steel bars also weakens the difference between the cover damage condition and the leakage condition and the normal condition. In particular, the maximum difference of the damage condition is reduced to the original This indicates that the distribution of steel bars will also lead to a decrease in the sensitivity of electric field signals to the identification of pipeline abnormalities, resulting in a worse effect.

[0189] According to the comparison of the degree of reduction of the electric field signal and the magnetic field signal in the figure, it can be found that the reduction effect of the difference amplitude between the working conditions of the steel bars in the magnetic field is significantly smaller, which also reflects that the magnetic field signal has a stronger anti-interference ability to the steel bars.

[0190] In the time domain, after comparing the normalized electromagnetic field signals under different working conditions, the signal difference curves that change with time are obtained, such as Figure 12 shown. Figure 12 is the time domain signal difference curve at the 0-meter position of the measurement point of the reinforced concrete layer model, where Figure 12 (a) Electric field signal, Figure 12 (b) Magnetic field signal.

[0191] By comparison Figure 12 and Figure 10 , it can be found that the change trend of the signal attenuation curve is similar, with no obvious difference; but the peak time of the electric field signal is delayed. ,exist On the left and right, the peak of the coating damage condition still appears earlier than the peak of the leakage condition; while the peak position of the magnetic field signal is delayed. At , the two working condition peak occurrence times are basically the same; secondly, the difference amplitude of the electric field signal has no obvious change, and the difference amplitude of the magnetic field signal is reduced to about of the original difference amplitude. This shows that the electric field signal has stronger anti-interference performance in the time domain.

[0192] The application applies the time-frequency electromagnetic method to the state monitoring and detection of complex pipe networks, uses a numerical method to complete simulation and simulation of changes of the buried metal pipeline under different working conditions, and also compares and analyzes the response differences of signals under different pipeline conditions, and the conclusions are as follows:

[0193] (1) The time-frequency electromagnetic method can be applied to the monitoring and detection of buried pipelines under the complex environment conditions of the parking apron, including the monitoring and detection of buried pipelines under the reinforced concrete cover layer. By comparing the differences of electromagnetic signals under different pipeline conditions, i.e., pipeline leakage, pipeline coating layer damage and pipeline normal conditions, it is shown that the detection signals under different pipeline conditions can be distinguished, and can also be one-to-one corresponding to different pipeline conditions. That is, the abnormal state of the pipeline can be recognized by inversion of the measured electromagnetic signals, and it is feasible to apply the time-frequency electromagnetic method to the monitoring and detection of buried pipelines.

[0194] (2) By comparing the changes of the detection signals, reliable monitoring and detection of pipeline state abnormalities can be realized:

[0195] a. The change of the detection signal of the pipeline when the leakage occurs is significantly abnormal, and can be easily identified;

[0196] b. The change of the detection signal when the coating layer is damaged is smaller than that when the leakage occurs, but it is also sufficient to be identified.

[0197] (3) The steel bars in the reinforced concrete layer have a significant shielding effect on the electromagnetic detection signal. By comparing the time-frequency signals under the setting of the plain concrete layer, the steel bars can cause a significant reduction in the amplitude of the signal collected by the measuring point directly above the pipeline, but the abnormal information of the pipeline state can still be obtained by processing the signals outside the concrete boundary, and if necessary, the sensor can be buried under the reinforced concrete layer.

[0198] The application has the beneficial effects that the technical problem of requiring a large amount of manual participation in pipeline monitoring and detection under complex environmental conditions is solved, the pipeline detection efficiency is improved, and the cost is saved.

[0199] The above only describes the preferred embodiments of the application, and is not used to limit the application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A pipeline integrity status electromagnetic monitoring detection and abnormal point location method, characterized in that: The following steps are involved: S1: Establishing a geoelectric model of the electromagnetic field system containing the pipeline and the external environmental conditions of the pipeline in the detection area, wherein the geoelectric model of the electromagnetic field system includes the reinforced concrete layer, the pebble-soil landfill cover and the outer protective layer of the pipeline, the pipeline geometry model and routing information; S2: Establishing an electromagnetic monitoring and detection unit, which includes an electromagnetic excitation system, a signal detection system, and an electromagnetic information acquisition system. The electromagnetic monitoring and detection unit is used for electromagnetic information verification and processing; S3: generating an excitation signal using the electromagnetic excitation system, coupling the excitation signal with the geoelectric system between the pipeline and the external environment of the pipeline, passing through the signal detection system, and then being collected by the electromagnetic information collection system; the electromagnetic excitation system and the electromagnetic information collection system are arranged in the monitoring and detection area, and the electromagnetic information collection system simultaneously collects the electric field component and the magnetic field component; S4: establishing a signal processing system, wherein the signal processing system performs signal preprocessing and signal correlation analysis and denoising; S5: establishing an inversion analysis system, wherein the inversion analysis system analyzes and processes the data provided by the electromagnetic information acquisition system to provide a three-dimensional electromagnetic field distribution, a three-dimensional resistivity distribution, and a polarizability distribution within the monitoring area; S6: Status identification system, which determines the integrity status of the buried pipeline through the above-mentioned electromagnetic information collection, signal processing and inversion analysis; The outer layer of the geoelectric model of the electromagnetic field system is composed of a spherical boundary layer representing the finite electromagnetic field, which contains the inner boundary Γ of the finite electromagnetic field boundary layer. O The geoelectric model of the electromagnetic field system is sequentially provided with: a spherical finite-distance boundary layer, air above the ground, and an outer monitoring area Ω below the ground. O , monitor the inner area Ω M , concrete layer and pebble-soil landfill cover, pipeline outer covering layer and pipeline; the area Ω O and Ω M The monitoring boundary Γ B The pebble-soil landfill is covered with an underground pipeline; the pipeline includes: a pipe body and a coating layer outside the pipe body; the inside of the pipe body is fuel oil; the concrete includes plain concrete and reinforced concrete; In step S5, the electromagnetic information processing system is used to generate the monitoring area Ω in the time domain and frequency domain respectively. M The three-dimensional electromagnetic field distribution, three-dimensional resistivity and polarizability distribution within are as follows: S51: In the monitoring area Ω M The boundary Γ B On, monitor the outer area Ω O The geoelectric properties of the monitoring area Ω M The influence of the boundary Γ B and monitor the outer area Ω O The geoelectric system is determined by the corresponding boundary element method: L B U B =C O , that is U B =L B -1 C O Among them, U B is the geoelectric parameter on the boundary, L B 、C O They are respectively monitoring the outer area Ω O The geoelectric system matrix and parameter vector; S52: Establish monitoring area Ω under normal circumstances M The discrete electromagnetic field equations in the monitoring area Ω are solved to generate the M Electric field information and magnetic field information within; S53: Establishing a monitoring area Ω based on the electromagnetic field information of the detection point M The discrete electromagnetic field equations in the inverse are used to generate the monitoring area Ω that meets the measured conditions when the excitation is applied. M Electric field information and magnetic field information within; S54: Inversion generates three-dimensional electromagnetic field distribution, three-dimensional resistivity and polarizability distribution in the monitoring area.

2. A pipeline integrity status electromagnetic monitoring and abnormal point location method according to claim 1, characterized in that: Monitoring areaΩ M An electromagnetic excitation system is provided inside, which is composed of one or more groups of excitation electric dipoles A and B, wherein the electric dipole A is connected to the steel pipeline, and the other electric dipole B corresponding to the group of electromagnetic excitation systems is grounded.

3. The method for electromagnetic monitoring and detection of pipeline integrity and abnormal point location according to claim 2, characterized in that: Monitoring areaΩ M There are also multiple appropriately distributed monitoring detection points, each of which is provided with a group of electric field detection sensors and magnetic field detection sensors (S); monitoring area Ω M The boundary Γ B Outside the monitoring areaΩ O The geoelectric properties of the monitoring area Ω M The influence of the boundary Γ B impact.

4. A pipeline integrity status electromagnetic monitoring and detection and abnormal point location method according to any one of claims 1 to 3, characterized in that: The electromagnetic excitation generated by the electromagnetic excitation system is composed of current or voltage signals with different frequencies, amplitudes, and morphological characteristics; The electromagnetic signal detected or collected by the signal detection system or electromagnetic information acquisition system at least includes a horizontal electric field component E x , vertical magnetic field component H z .

5. The method for electromagnetic monitoring and detection of pipeline integrity and abnormal point location according to claim 1, characterized in that: Based on the three-dimensional electromagnetic field distribution, three-dimensional resistivity and polarizability distribution inverted and calculated in step S5, it is further determined whether an abnormality occurs and the abnormal point is located, and the abnormality category is determined according to the characteristics of the abnormality; the abnormality categories include: the pipeline coating is damaged, but the pipeline has no leakage; the pipeline coating is damaged, and the pipeline leaks; there is no abnormality, and the pipeline integrity is intact.

6. The method for electromagnetic monitoring and detection of pipeline integrity and abnormal point location according to claim 1, characterized in that: The excitation signal emitted by the electromagnetic excitation system is emitted in the form of voltage and propagates outward from the pipeline perpendicular to the ground; the electromagnetic excitation signal includes a time domain signal and a frequency domain signal; the time domain signal adopts a zero-crossing square wave, and the frequency signal adopts a non-zero-crossing square wave.

7. The method for electromagnetic monitoring and detection of pipeline integrity and abnormal point location according to claim 6, characterized in that: The specific process of the signal processing system processing the frequency domain electromagnetic field signal is as follows: Under normal operating conditions, Fourier transform is performed on different frequency domain signals to obtain different frequency signal spectra; the normal operating conditions specifically refer to: no leakage or damage in the pipeline; Superimposing the spectra of signals of different frequencies to obtain a frequency curve; correcting the frequency curve to obtain a corrected curve; Under the test working condition, obtain the corrected curve under the test working condition; Perform difference processing on the corrected curve under normal working conditions and the corrected curve under test conditions to obtain the frequency domain signal difference curve; The pipeline detection status is obtained based on the frequency signal difference curve analysis.

8. The method for electromagnetic monitoring and detection of pipeline integrity and abnormal point location according to claim 7, characterized in that: The specific process of the signal processing system processing the time domain electromagnetic field signal is as follows: Under normal working conditions, the first periodic signal in the time domain signal is discarded and the second periodic signal is obtained; Obtaining a response signal during a zero-crossing period of the time domain signal; Normalizing the second periodic signal and the response signal to obtain a normalized signal; Performing reverse superposition processing on the normalized signal to obtain a reverse superposition signal; Under the detection working condition, a reverse superposition signal under the detection working condition is obtained; Perform difference processing on the reverse superposition signal under normal working conditions and the reverse superposition signal under detection working conditions to obtain a time domain difference curve; The pipeline detection status is obtained based on the time domain difference curve analysis; The processing system uses a data processing method based on time-frequency detection to compare the change characteristics of the measured electric and magnetic field signals with the normal state to determine whether the buried pipeline has any abnormal integrity status; If an abnormal integrity state occurs, the state change characteristics obtained by the data processing method of time-frequency detection are further determined to determine whether it is damage to the coating or leakage in the pipeline.

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