Pipeline elbow ultrasonic guided wave corrosion thinning imaging method and system

Abstract

The invention relates to a pipeline elbow ultrasonic guided wave corrosion thinning imaging method and system, and belongs to the technical field of ultrasonic guided wave nondestructive testing. The method comprises the following steps: establishing a two-dimensional planar non-uniform grid model of the pipeline elbow; determining the positions of the annular transduction arrays at the two ends of the to-be-detected area of the pipeline elbow; performing forward modeling based on the excitation signal; obtaining an objective function about sound velocity based on the simulation result and the observation result; judging whether the target function meets an iteration termination condition or not; according to a judgment result, whether iterative calculation of the target function is carried out is selected; obtaining sound velocity distribution information based on a judgment result and an iterative calculation result; and obtaining a pipeline elbow corrosion thinning image based on the relationship between the frequency thickness product and the sound velocity, the sound velocity distribution information and the two-dimensional plane non-uniform network model. According to the method, the two-dimensional planar non-uniform grid model conforming to the actual size of the pipeline elbow is constructed, and corrosion thinning imaging of the pipeline elbow is accurately achieved on the two-dimensional planar non-uniform grid model.

Description

Technical Field

[0001] The invention belongs to the technical field of ultrasonic guided wave nondestructive testing, and in particular relates to a pipeline elbow ultrasonic guided wave corrosion thinning imaging method and system. Background Art

[0002] Throughout the oil and gas industry, monitoring pipeline corrosion and thinning detection is an important means to ensure the safe and stable operation of upstream and downstream equipment.

[0003] Although various ultrasonic and electromagnetic thickness measurement devices are relatively mature, they require manual point-by-point scanning in the area to be inspected, which makes them unsuitable for long-distance pipeline monitoring and limits their applicability when physical obstacles prevent direct access to the pipeline. Another major limitation of current manual thickness measurement is that it relies on highly skilled operators, and inaccurate point selection can easily lead to missed inspections.

[0004] The detection method based on ultrasonic guided waves provides a detection solution for long distances and large coverage areas. The excitation sensor arranged at one point can propagate over a long distance on the structure to be tested. Guided waves are now used in defect detection of conventional pipelines. The current corrosion thinning imaging methods are mainly divided into travel-time tomography, diffraction tomography, and tomography based on full waveform inversion. The resolution of travel-time imaging is limited by the first Snell zone, and diffraction imaging needs to be based on multi-angle scattering field analysis, but in the pipeline structure, the incident and receiving angles of the guided wave signal are limited. Existing research on full-wave inversion focuses on imaging of straight pipe sections, and lacks research on elbows. In general, the current long-distance ultrasonic guided wave defect detection method cannot provide an accurate estimate of the defect depth, especially in the presence of complex shapes such as bends. Summary of the invention

[0005] In view of the above problems, the present invention provides a pipeline elbow ultrasonic guided wave corrosion thinning imaging method and system, which solves the problem of quantitative detection of elbow corrosion thinning in existing guided wave detection schemes.

[0006] The first object of the present invention is to provide a pipeline elbow ultrasonic guided wave corrosion thinning imaging method, the method comprising:

[0007] A two-dimensional plane non-uniform grid model of the pipe elbow is established according to the size information of the pipe elbow;

[0008] Determine the positions of the annular transducer arrays arranged at both ends of the pipeline elbow to be detected, wherein one side of the annular transducer array is used as an excitation source array, and the other side of the annular transducer array is used as a receiving array;

[0009] Based on the excitation signal of the excitation source, forward simulation is performed;

[0010] Based on the simulation results obtained from the forward simulation and the observation results at the receiving position, the objective function about the sound speed is obtained;

[0011] Determine whether the objective function meets the iteration termination condition;

[0012] According to the judgment result, choose whether to perform iterative calculation of the objective function;

[0013] Based on the judgment results and iterative calculation results, the sound velocity distribution information is obtained;

[0014] Based on the relationship between the frequency-thickness product and the sound velocity, the sound velocity distribution information and the two-dimensional plane non-uniform network model, the corrosion thinning image of the pipeline elbow is obtained.

[0015] In the embodiment of the present invention, the dimension information of the pipe elbow includes the inner bending radius, the outer bending radius, the bending angle of the elbow and the inner and outer diameters of the pipe.

[0016] In an embodiment of the present invention, before the forward simulation, a sound absorbing layer is added to the boundary of the two-dimensional plane non-uniform grid model of the pipe elbow.

[0017] In the embodiment of the present invention, the excitation signal is a narrowband signal.

[0018] In the embodiment of the present invention, the specific process of the forward modeling is as follows:

[0019] Perform fast Fourier transform on the excitation signal to obtain the transformed excitation signal;

[0020] A frequency point whose amplitude is not zero is intercepted near the center frequency on the transformed excitation signal;

[0021] Based on the frequency domain wave equation and the non-uniform grid finite difference method, the matrix equation is established to perform forward simulation on each individual frequency point.

[0022] In the embodiment of the present invention, the objective function about the sound speed is obtained based on the simulation results obtained by the forward simulation and the observation results of the receiving position, including:

[0023] Based on the simulation results obtained by the forward simulation and the observation results at the receiving position, a residual between the simulation results obtained by the forward simulation and the observation results at the receiving position is calculated;

[0024] Based on the residuals of the simulation results obtained by the forward simulation and the observation results at the receiving position, the objective function with respect to the sound speed is calculated.

[0025] In an embodiment of the present invention, the iteration termination condition is that the current value of the objective function is less than a set threshold; or the iteration is stopped after reaching a target number of iterations.

[0026] In an embodiment of the present invention, the iterative calculation of the objective function includes:

[0027] Based on the simulation results obtained from the forward simulation and the observation results at the receiving position, the gradient of the objective function with respect to the sound speed is obtained;

[0028] Iterative calculation step size, where the step size is the increment of the objective function on the gradient;

[0029] Update the sound speed based on the gradient and step size;

[0030] Based on the updated sound velocity, iterative forward simulation is performed;

[0031] Based on the results of iterative forward simulation, the objective function is iteratively calculated;

[0032] Repeating the steps of “iterative calculation step size”, “updating sound velocity”, “iterative forward simulation” and “iterative calculation of objective function” until the objective function satisfies the iteration termination condition;

[0033] Determine the final step size as the step size of the last iterative calculation.

[0034] In the embodiment of the present invention, the step of selecting whether to perform iterative calculation of the objective function according to the judgment result includes:

[0035] The judgment result is:

[0036] Based on the simulation results obtained from the forward simulation corresponding to the objective function and the observation results at the receiving position, the gradient is obtained;

[0037] Obtain the step length according to the step length search algorithm;

[0038] Based on the gradient and step size, the speed of sound is obtained;

[0039] Output sound velocity;

[0040] or,

[0041] If the judgment result is no, iterative calculation of the objective function is performed.

[0042] The second object of the present invention is to provide a pipeline elbow ultrasonic guided wave corrosion thinning imaging system, the system comprising:

[0043] The model building module is used to build a two-dimensional plane non-uniform grid model of the pipeline elbow according to the size information of the pipeline elbow;

[0044] The determination module is used to determine the positions of the annular transducer arrays arranged at both ends of the pipeline elbow to be detected, wherein one side of the annular transducer array is used as an excitation source array, and the other side of the annular transducer array is used as a receiving array;

[0045] The forward simulation module is used to perform forward simulation based on the excitation signal of the excitation source;

[0046] The objective function module is used to obtain the objective function about the sound speed based on the simulation results obtained by the forward simulation and the observation results at the receiving position;

[0047] The iteration module is used to determine whether the objective function meets the iteration termination condition, and to select whether to perform iterative calculation of the objective function according to the determination result;

[0048] The sound velocity module is used to obtain the sound velocity distribution information based on the judgment results and iterative calculation results;

[0049] The imaging module is used to obtain the corrosion thinning image of the pipeline elbow based on the relationship between the frequency-thickness product and the sound speed, the sound speed distribution information and the two-dimensional plane non-uniform network model.

[0050] A third object of the present invention is to provide an electronic device, the electronic device comprising: a processor, the processor being coupled to a memory;

[0051] The memory is used to store computer programs;

[0052] The processor is used to execute the computer program stored in the memory so that the electronic device executes the method as described above.

[0053] A fourth object of the present invention is a computer-readable storage medium storing a program or instruction. When the program or instruction is executed on a computer, the computer executes the method as described above.

[0054] Beneficial effects of the present invention:

[0055] The present invention provides a pipeline elbow ultrasonic guided wave corrosion thinning imaging method and system, which constructs a two-dimensional plane non-uniform grid model that conforms to the actual size of the pipeline elbow, and based on the non-uniform grid finite difference method in full waveform inversion and the frequency domain acoustic wave equation in the form of a discretized matrix, forward simulation is performed to achieve accurate corrosion thinning imaging of the pipeline elbow on the two-dimensional plane non-uniform grid model, solving the problem that the traditional diffraction imaging cannot achieve corrosion thinning imaging of the pipeline elbow due to the limited incident and receiving angles of the guided wave signal in the pipeline structure detection;

[0056] In addition, in order to avoid the influence of boundary echoes, the present invention adds a PML sound absorbing layer at the boundary of the two-dimensional plane non-uniform grid model of the pipeline elbow, which further improves the accuracy of corrosion thinning imaging obtained by forward simulation.

[0057] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0059] Figure 1 A flow chart of a pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to an embodiment of the present invention is shown;

[0060] Figure 2 A schematic diagram of the arrangement of transducer arrays at both ends of a pipe elbow according to an embodiment of the present invention is shown;

[0061] Figure 3 A schematic diagram of a two-dimensional non-uniform grid expansion of a pipeline elbow according to an embodiment of the present invention is shown;

[0062] Figure 4 A schematic diagram showing the positions of m points in a non-uniform grid model according to an embodiment of the present invention;

[0063] Figure 5 shows a dispersion curve diagram according to an embodiment of the present invention;

[0064] Figure 6 A framework diagram of a pipeline elbow ultrasonic guided wave corrosion thinning imaging system according to an embodiment of the present invention is shown;

[0065] Figure 7 A framework diagram of an electronic device according to an embodiment of the present invention is shown;

[0066] In the figure:

[0067] Model building module 1; detection module 2; forward simulation module 3; objective function module 4; iteration module 5; sound speed module 6; imaging module 7; electronic device 300; processor 301; memory 302. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] like Figure 1 As shown, a pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to an embodiment of the present invention includes:

[0070] Step S1, establishing a two-dimensional plane non-uniform grid model of the pipeline elbow according to the size information of the pipeline elbow;

[0071] Step S2, determining the positions of the annular transducer arrays arranged at both ends of the pipeline elbow to be detected, wherein one side of the annular transducer array is used as an excitation source array, and the other side of the annular transducer array is used as a receiving array;

[0072] Step S3, performing forward modeling based on the excitation signal of the excitation source;

[0073] Step S4, obtaining an objective function related to the sound speed based on the simulation results obtained by the forward simulation and the observation results at the receiving position;

[0074] Step S5, judging whether the objective function satisfies the iteration termination condition;

[0075] Step S6: According to the judgment result, whether to perform iterative calculation of the objective function is selected;

[0076] Step S7, obtaining sound velocity distribution information based on the judgment result and the iterative calculation result;

[0077] Step S8: Based on the relationship between the frequency-thickness product and the sound velocity, the sound velocity distribution information and the two-dimensional plane non-uniform network model, a corrosion thinning image of the pipeline elbow is obtained.

[0078] In step S1, the dimension information of the pipe elbow includes the inner bending radius r, the outer bending radius R, the bending angle α and the inner and outer diameters of the pipe;

[0079] In step S1, in order to accurately reflect the corrosion thinning imaging of the pipeline elbow, a two-dimensional plane non-uniform network model that conforms to the elbow structure is established according to the size of the pipeline elbow. Specifically, the two-dimensional plane non-uniform network model is discretized into non-uniform grids according to the actual size of the elbow. Taking the expansion along the inside of the elbow as an example, the length of the left and right boundaries of the grid is 2πr×(α / 2π), and the length of the outer side of the elbow is 2πR×(α / 2π). The length of each grid in the middle area is determined by the linear difference method; wherein, when the grid is divided, a non-uniform grid is established for the change of the length size of the inner and outer sides in the Y direction; after the non-uniform grid is established, each node represents the sound velocity parameter at the node, see specifically Figure 2 ;

[0080] In step S2, the specific operations are:

[0081] Annular transducer arrays are arranged at both ends of the pipeline elbow area to be detected. One side of the annular transducer array is used as the excitation source array, and the other side of the annular transducer array is used as the receiving array. After the array is fixed, the position of each excitation and receiving array element is recorded. The specific transducer array arrangement diagram is shown in the figure. Figure 3 As shown;

[0082] In step S3, before the forward simulation, a PML (Perfectly Matched Layer) sound absorbing layer is added at the boundary of the two-dimensional plane non-uniform grid model of the pipe elbow to avoid the influence of boundary echoes. The best matching layer acoustic wave equation is shown in formula (1).

[0083]

[0084] In formula (1), L PML is the thickness of the matching layer, A is the attenuation coefficient,

[0085] make We can get equations (2)-(4);

[0086]

[0087]

[0088]

[0089] In formula (4), P represents the wave field in the frequency domain, ω represents the angular frequency, c represents the sound velocity, and F(ω) represents the earthquake source;

[0090] The processing methods at the boundaries and corners of the grid model are somewhat different. The attenuation of the wave field in the corner area is a superposition of the attenuation in the x-direction and the z-direction.

[0091] In step S3, the excitation signal is a narrowband signal, taking a sine wave modulated by a Hanning window as an example, the Hanning window function is shown in formula (5), and the waveguide information at the receiving sensor array is obtained through the acquisition circuit connected to the receiving transducer;

[0092]

[0093] In formula (5), α = 0.53836;

[0094] In step S3, the specific process of the forward modeling is as follows:

[0095] Step A1, performing fast Fourier transform on the excitation signal to obtain a transformed excitation signal;

[0096] Step A2, intercepting a frequency segment (i.e., the target frequency) near the center frequency and with a non-zero amplitude on the transformed excitation signal;

[0097] Step A3: Establish a matrix equation based on the frequency domain wave equation and the non-uniform grid finite difference method, and perform forward simulation on each individual frequency point.

[0098] Specifically, in step A3, the frequency domain wave equation is a frequency domain acoustic wave equation in a discretized matrix form, as shown in formula (6);

[0099] A a (c,ω)Y a (ω)=F a (ω) (6)

[0100] In formula (6), the number of grids in the area to be calculated is N = Nx × Ny, then Aa is an N × N impedance matrix, Ya is the wave field value to be solved, Fa represents the excitation source, ω is the angular frequency, and c represents the sound speed;

[0101] In step A3, the non-uniform grid finite difference method is established for the two-dimensional plane non-uniform grid model established in step S1;

[0102] The forward simulation of the present invention is based on the finite difference method used in the forward and inverse calculations in the full waveform inversion calculations, using the difference approximation to realize the partial differential calculations in the partial differential equations, and the difference equations approximate the differential equations in the frequency domain finite difference;

[0103] Conventional finite difference is a finite difference method based on uniform grids, which is difficult to solve the problem of pipe bending. Because in actual situations, the size of the inner side of the pipe bending is significantly smaller than the outer side of the pipe bending. Using the general uniform grid difference method to establish the forward model will inevitably cause positioning errors and errors in the quantitative measurement of defects, and even lead to difficult-to-compensate deviations between the forward model and the design structure. Therefore, for the pipe bending, a discretization method of non-uniform grids for the pipe bending is proposed in step 1. According to the size constraints in the actual physical model, a non-uniform grid of the actual shape of the composite elbow is established.

[0104] When dividing the grid, a non-uniform grid is established according to the change of the length size on the inside and outside of the Y direction. The Y-axis size of each grid is determined by using linear difference, and the forward model is established.

[0105] Based on this, the embodiment of the present invention selects the non-uniform grid finite difference method and performs forward simulation on the frequency domain acoustic wave equation in discretized matrix form, wherein the formulas specifically involved in the non-uniform grid finite difference method are shown in equations (7)-(9);

[0106]

[0107]

[0108] and

[0109]

[0110] Equations (7)-(9) represent the analytical equations for a point (m, n) in a non-uniform grid, and in Equations (7)-(9), α1, α2, β1, β2, and c ij is the weight coefficient, P m,n represents the wave field at any point, and point (m, n) is any point in the non-uniform grid. For details, see Figure 4 ,The non-uniform grid can be regarded as a splicing of nine-point grids with different grid spacing ratios.

[0111] In step S4, the objective function on the sound speed is obtained based on the simulation results obtained by the forward simulation and the observation results of the receiving position, including:

[0112] Step B1, based on the simulation results obtained by the forward simulation and the observation results at the receiving position, calculating the residual of the simulation results obtained by the forward simulation and the observation results at the receiving position;

[0113] Step B2: Calculate the objective function regarding the speed of sound based on the simulation results obtained by the forward simulation and the residual of the observation results at the receiving position.

[0114] Specifically, in step B1, the residual of the simulation result obtained by the forward simulation and the observation result at the receiving position, the residual s δ The expression is shown in formula (10);

[0115] s δ =s cal -s obs (10)

[0116] In formula (10), s cal is the simulation result obtained by forward simulation, s obs is the observation result of the receiving position.

[0117] In step B2, the expression of the objective function of the speed of sound is as described in formula (11);

[0118]

[0119] In formula (11), the superscript T represents matrix transposition, the superscript * represents complex conjugate, E(c) is the objective function about the sound speed, and c is the sound speed.

[0120] In step S5, the iteration termination condition is that the current value of the objective function is less than a set threshold (a set value, 0.1 is selected empirically); or the iteration is stopped after reaching a target number of iterations (the target number of iterations is a set value).

[0121] In step S6, the iterative calculation of the objective function includes:

[0122] Step C1, based on the simulation results obtained by the back propagation forward simulation and the observation results at the receiving position, the gradient of the objective function with respect to the sound speed is obtained;

[0123] Step C2, iteratively calculating the step length, where the step length is the increment of the objective function on the gradient;

[0124] Step C3, updating the sound speed based on the gradient and the step size;

[0125] Step C4: performing iterative forward modeling based on the updated sound velocity;

[0126] Step C5, iteratively calculating the objective function based on the result of the iterative forward simulation;

[0127] Step C6, repeating the steps of "iterative calculation step size", "updating sound speed", "iterative forward simulation" and "iterative calculation objective function" until the objective function meets the iteration termination condition;

[0128] Step C7: Determine the final step size as the step size of the last iterative calculation.

[0129] In step C1, first, the residual is obtained according to the simulation results obtained by the back propagation forward simulation and the observation results of the receiving position, as shown in formula (10);

[0130] Then, the residual is back-propagated to obtain the companion wave field, and the gradient of the objective function with respect to the sound velocity is calculated using the companion wave field, which is expressed as shown in formula (12);

[0131]

[0132] By transforming equation (12), we can obtain the relationship between the gradient and the accompanying wave field (13), which is specifically derived as follows:

[0133] make have to Substituting it into equation (12), we get the relationship between the gradient and the accompanying wave field (13);

[0134]

[0135] In formula (13), let the accompanying wave field but This is equivalent to the back propagation of the residual wave field. By back propagating the conjugate of the residual wave field, we can calculate Thus, the gradient is obtained, which is the calculation process of the above step C1.

[0136] In step C2 to step C6, the iterative calculation step length in step C2 refers to assigning values ​​to the step length and calculating iteratively by different methods, and repeating the iterative calculation of step C3, step C4, and step C5 (i.e., step C6);

[0137] In the present invention, a simple calculation method is exemplified as an example, an initial step length is set to 1, and the sound speed under the step length 1 is obtained using the calculated gradient and step length (i.e., step C3), wherein the step length is the increment of the objective function on the gradient;

[0138] Re-perform forward modeling (forward modeling and simulation result calculation) to obtain the objective function under the velocity model (i.e., step C4 and step C5), that is, update the objective function under the step length l;

[0139] And determine whether the updated objective function meets the iteration termination condition:

[0140] When the updated objective function meets the iteration termination condition, it means that the objective function is optimized under the step length d, and the step length is taken as the final step length;

[0141] When the updated objective function does not meet the iteration termination condition, it means that the objective function is not optimized, and half of the step length d is taken as the step length after iteration, and step C6 is performed until the iteration obtains that the objective function meets the iteration termination condition, and the last iteration step length is determined as the final step length;

[0142] In step S6, the step of selecting whether to perform iterative calculation of the objective function according to the judgment result includes:

[0143] If the result is yes, do the following:

[0144] Step D1, based on the simulation results obtained by the forward simulation corresponding to the objective function and the observation results at the receiving position, the gradient of the objective function with respect to the sound velocity is obtained, which is the same as the above step C1;

[0145] Step D2, obtaining a step length according to a step length search algorithm, wherein the step length search condition is obtained by formula (14);

[0146]

[0147] In formula (14), m0 represents the initial model parameters, r1 represents the step size of the first iteration (here the first iteration is taken as an example);

[0148] Step D3, based on the gradient and the step length, obtain the sound velocity, which is the same as step C3;

[0149] Step D4, output the sound velocity;

[0150] or,

[0151] When the judgment result is no, iterative calculation of the objective function is performed, that is, the above-mentioned steps C1 to C6 are performed.

[0152] In step S7, based on the judgment result and the iterative calculation result, that is, according to the sound velocity distribution information corresponding to some frequency points output by step D4 in step S6 (the judgment result is no result),

[0153] and

[0154] According to the final step size determined by step C7 (iterative calculation result) in step S6, in combination with the gradient, the corresponding sound velocity distribution information at other frequency points is updated;

[0155] That is, the sound speed distribution information at the target frequency is obtained.

[0156] In step S8, based on the relationship between the frequency-thickness product and the sound velocity, the sound velocity distribution information and the two-dimensional plane non-uniform grid model, the corrosion thinning image of the pipeline elbow is obtained, wherein the relationship between the frequency-thickness product and the sound velocity is expressed as a dispersion curve relationship, see Figure 5 , Figure 5(a) is the phase velocity dispersion curve, Figure 5 (b) is the group velocity dispersion curve;

[0157] According to the relationship between the frequency-thickness product and the guided wave velocity, and the sound velocity distribution information at the target frequency obtained through the above steps, substitute it into formula (15) to obtain the thickness distribution information;

[0158] c(r)=c ph {f·d[r]} (15)

[0159] In formula (15), C' represents the sound velocity at the node, r represents the position information (the position of all points in each calculation during the forward and inversion process), and C ph represents the phase velocity, f and d represent the frequency and thickness, respectively;

[0160] The thickness distribution information obtained above and the corresponding position information are plotted on a two-dimensional plane non-uniform grid model to obtain a corrosion thinning image of the pipeline elbow.

[0161] like Figure 6 As shown, a pipeline elbow ultrasonic guided wave corrosion thinning imaging system according to an embodiment of the present invention includes:

[0162] The model building module 1 is used to build a two-dimensional plane non-uniform grid model of the pipeline elbow according to the size information of the pipeline elbow;

[0163] The detection module 2 is used to arrange an annular transducer array at both ends of the pipeline elbow area to be detected, one side is used as an excitation source, and the other side is used as a receiver;

[0164] The forward simulation module 3 is used to perform forward simulation based on the excitation signal of the excitation source;

[0165] The objective function module 4 is used to obtain an objective function about the sound speed based on the simulation results obtained by the forward simulation and the observation results of the receiving position;

[0166] The iteration module 5 is used to determine whether the objective function meets the iteration termination condition, and to select whether to perform iterative calculation of the objective function according to the determination result;

[0167] The sound speed module 6 is used to obtain the sound speed distribution information based on the judgment result and the iterative calculation result;

[0168] The imaging module 7 is used to obtain the corrosion thinning image of the pipeline elbow based on the relationship between the frequency-thickness product and the sound speed, the sound speed distribution information and the two-dimensional plane non-uniform network model.

[0169] like Figure 7 As shown, some embodiments of the present invention provide an electronic device, the electronic device 300, comprising: a processor 301, the processor 301 is coupled to a memory 302;

[0170] The memory 302 is used to store computer programs;

[0171] The processor 301 is configured to execute the computer program stored in the memory 302 so that the electronic device executes the method described in the above embodiment.

[0172] In certain embodiments of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a program or instruction. When the program or instruction is executed on a computer, the computer executes the method described in the above embodiments.

[0173] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an electronic device or a device.

[0174] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A pipeline elbow ultrasonic guided wave corrosion thinning imaging method, characterized in that: include: A two-dimensional plane non-uniform grid model of the pipe elbow is established according to the size information of the pipe elbow; Determine the positions of the annular transducer arrays arranged at both ends of the pipeline elbow to be detected, wherein one side of the annular transducer array is used as an excitation source array, and the other side of the annular transducer array is used as a receiving array; Based on the excitation signal of the excitation source, forward simulation is performed; Based on the simulation results obtained from the forward simulation and the observation results at the receiving position, the objective function about the sound speed is obtained; Determine whether the objective function meets the iteration termination condition; According to the judgment result, choose whether to perform iterative calculation of the objective function; Based on the judgment results and iterative calculation results, the sound velocity distribution information is obtained; Based on the relationship between the frequency-thickness product and the sound velocity, the sound velocity distribution information and the two-dimensional plane non-uniform network model, the corrosion thinning image of the pipeline elbow is obtained.

2. The pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to claim 1 is characterized in that: The dimension information of the pipe elbow includes the inner bending radius, the outer bending radius, the bending angle and the inner and outer diameters of the pipe.

3. The pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to claim 1 is characterized in that: Before the forward modeling, a sound absorbing layer is added at the boundary of the two-dimensional plane non-uniform grid model of the pipe elbow.

4. The pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to claim 1 is characterized in that: The excitation signal is a narrowband signal.

5. The pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to claim 1 is characterized in that: The specific process of the forward modeling is as follows: Perform fast Fourier transform on the excitation signal to obtain the transformed excitation signal; A frequency point whose amplitude is not zero is intercepted near the center frequency on the transformed excitation signal; Based on the frequency domain wave equation and the non-uniform grid finite difference method, the matrix equation is established to perform forward simulation on each individual frequency point.

6. The pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to claim 1 is characterized in that: The objective function about the sound speed is obtained based on the simulation results obtained by the forward simulation and the observation results of the receiving position, including: Based on the simulation results obtained by the forward simulation and the observation results at the receiving position, a residual between the simulation results obtained by the forward simulation and the observation results at the receiving position is calculated; Based on the residuals of the simulation results obtained by the forward simulation and the observation results at the receiving position, the objective function with respect to the sound speed is calculated.

7. The pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to claim 1 is characterized in that: The iteration termination condition is that the current value of the objective function is less than a set threshold; or the iteration is stopped after reaching the target number of iterations.

8. The pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to claim 1 is characterized in that: The iterative calculation of the objective function includes: Based on the simulation results obtained from the forward simulation and the observation results at the receiving position, the gradient of the objective function with respect to the sound speed is obtained; Iterative calculation step size, where the step size is the increment of the objective function on the gradient; Update the sound speed based on the gradient and step size; Based on the updated sound velocity, iterative forward simulation is performed; Based on the results of iterative forward simulation, the objective function is iteratively calculated; Repeat the steps of "iterative calculation step size", "update sound velocity", "iterative forward simulation" and "iterative calculation objective function" until the objective function meets the iteration termination condition; Determine the final step size as the step size of the last iterative calculation.

9. The pipeline elbow ultrasonic guided wave corrosion thinning imaging method according to claim 1 is characterized in that: The step of selecting whether to perform iterative calculation of the objective function according to the judgment result includes: The judgment result is: Based on the simulation results obtained from the forward simulation corresponding to the objective function and the observation results at the receiving position, the gradient is obtained; Obtain the step length according to the step length search algorithm; Based on the gradient and step size, the speed of sound is obtained; Output sound velocity; or, If the judgment result is no, iterative calculation of the objective function is performed.

10. A pipeline elbow ultrasonic guided wave corrosion thinning imaging system, characterized in that: include: The model building module is used to build a two-dimensional plane non-uniform grid model of the pipeline elbow according to the size information of the pipeline elbow; The determination module is used to determine the positions of the annular transducer arrays arranged at both ends of the pipeline elbow to be detected, wherein one side of the annular transducer array is used as an excitation source array, and the other side of the annular transducer array is used as a receiving array; The forward simulation module is used to perform forward simulation based on the excitation signal of the excitation source; The objective function module is used to obtain the objective function about the sound speed based on the simulation results obtained by the forward simulation and the observation results at the receiving position; The iteration module is used to determine whether the objective function meets the iteration termination condition, and to select whether to perform iterative calculation of the objective function according to the determination result; The sound velocity module is used to obtain the sound velocity distribution information based on the judgment results and iterative calculation results; The imaging module is used to obtain the corrosion thinning image of the pipeline elbow based on the relationship between the frequency-thickness product and the sound speed, the sound speed distribution information and the two-dimensional plane non-uniform network model.

11. An electronic device, characterized in that: include: a processor coupled to the 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 executes the method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program or an instruction. When the program or the instruction is executed on a computer, the computer is caused to perform the method according to any one of claims 1 to 9.

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