Metal pipeline crack measurement method and system

Abstract

The present invention provides a metal pipeline crack measurement method and system, relating to the field of crack detection. The measurement method includes: obtaining detection impedance increments at multiple detection points on a target metal pipeline; the detection impedance increment is the impedance increment at each detection point when an excitation signal emitted by a detection probe is irradiated on each detection point; constructing an approximate analytical model based on crack parameters; the approximate analytical model is used to calculate the impedance increment based on the position of the detection point to obtain a calculated impedance increment; the crack parameters include crack depth and crack width; with the goal of minimizing the error sum between the detection impedance increment and the calculated impedance increment, an iterative algorithm is used to solve the approximate analytical model to obtain optimal crack parameters; the optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the error sum is minimized. The present invention can achieve high-precision measurement.

Description

Technical Field

[0001] The present invention relates to the field of crack detection, and in particular to a metal pipeline crack measurement method and system. Background Art

[0002] Nondestructive crack testing (NDT) is a method of detecting cracks in materials by utilizing the physical changes caused by cracks, without compromising the performance of the object being tested or damaging any internal or external structures. Common crack measurement methods for metal pipes include ultrasonic testing, radiographic testing, and eddy current testing.

[0003] Ultrasonic methods require smooth surfaces and good acoustic coupling, placing them under stringent conditions. X-ray methods present significant radiation hazards during the testing process, potentially causing radiation fatigue damage to the object being tested and potentially posing safety risks to the testers. The commonly used eddy current method focuses on detecting the presence of cracks, or it fixes the crack width parameter of the object being tested and only estimates the crack depth parameter. However, in actual testing, the depth and width of the crack being tested are often unknown, making these methods inaccurate and significantly limited. Summary of the Invention

[0004] The purpose of the present invention is to provide a metal pipeline crack measurement method and system to achieve high-precision measurement.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A method for measuring cracks in a metal pipeline, comprising:

[0007] Obtaining detection impedance increments at multiple detection points on the target metal pipe; the detection impedance increments are impedance increments at each detection point when an excitation signal emitted by the detection probe is irradiated on each detection point;

[0008] An approximate analytical model is constructed based on crack parameters; the approximate analytical model is used to calculate an impedance increment based on a position of a detection point to obtain a calculated impedance increment; the crack parameters include crack depth and crack width;

[0009] With the goal of minimizing the sum of the errors between the detected impedance increment and the calculated impedance increment, an iterative algorithm is used to solve the approximate analytical model to obtain optimal crack parameters; the optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the sum of the errors is minimized.

[0010] Optionally, the method of solving the approximate analytical model using an iterative algorithm with the goal of minimizing the sum of the errors between the detected impedance increment and the calculated impedance increment to obtain the optimal crack parameters specifically includes:

[0011] With the error sum as the minimum, the approximate analytical model is solved by using the least square method to obtain the optimal crack parameters.

[0012] Optionally, a calculation formula for the sum of errors between the detected impedance increment and the calculated impedance increment is:

[0013]

[0014] Where J(W,D) is the error sum; W is the crack width, D is the crack depth; i is the serial number of the detection point; n is the total number of detection points; y i is the imaginary part of the detection impedance increment corresponding to the i-th detection point; x i is the position of the i-th detection point; ΔZ(x i ,W,D) is the corresponding calculated impedance increment of the i-th detection point output of the approximate analytical model.

[0015] Optionally, the method of solving the approximate analytical model with the least square method with the goal of minimizing the sum of the errors to obtain the optimal crack parameters specifically includes:

[0016] Inputting the crack parameters at the current iteration number into the approximate analytical model to obtain the calculated impedance increment at the current iteration number;

[0017] Calculate the sum of the errors between the detection impedance increment at the current iteration number and the calculation impedance increment at the current iteration number to obtain the sum of the errors at the current iteration number;

[0018] Determine whether an iteration stop condition is met; the iteration stop condition is that the current number of iterations reaches a set number of times or the error at the current number of iterations is within a set error value range;

[0019] If the iteration stop condition is met, the crack parameters at the current iteration number are taken as the optimal crack parameters;

[0020] If the iteration stop condition is not met, the steepest gradient descent method is used to calculate the error and corresponding gradient information at the current iteration number, and the crack parameters at the current iteration number are updated according to the error and corresponding gradient information at the current iteration number, and the updated crack parameters are used as the crack parameters at the next iteration number, and the process returns to the step of "inputting the crack parameters at the current iteration number into the approximate analytical model to obtain the calculated impedance increment at the current iteration number".

[0021] Optionally, the updating of the crack parameters at the current iteration number according to the error sum at the current iteration number and the corresponding gradient information is specifically as follows:

[0022]

[0023] Where W is the crack width, D is the crack depth, α W is the iteration step of the width parameter, α D is the iteration step of the depth parameter, and ":=" is the parameter update indicator;

[0024] is the error and the gradient information corresponding to the crack width; is the error and the gradient information corresponding to the crack depth.

[0025] A metal pipeline crack measurement system, comprising:

[0026] A detection impedance increment acquisition module is used to obtain the detection impedance increment of multiple detection points on the target metal pipe; the detection impedance increment is the impedance increment at each detection point when the excitation signal emitted by the detection probe is irradiated on each detection point;

[0027] An approximate analytical model construction module is used to construct an approximate analytical model based on crack parameters; the approximate analytical model is used to calculate the impedance increment based on the position of the detection point to obtain the calculated impedance increment; the crack parameters include crack depth and crack width;

[0028] The optimal crack parameter acquisition module is used to solve the approximate analytical model using an iterative algorithm with the goal of minimizing the sum of the errors between the detected impedance increment and the calculated impedance increment to obtain the optimal crack parameters; the optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the sum of the errors is minimized.

[0029] Optionally, the optimal crack parameter acquisition module includes:

[0030] The crack parameter acquisition submodule is used to solve the approximate analytical model using the least square method with the goal of minimizing the error sum to obtain the optimal crack parameters.

[0031] Optionally, in the crack parameter acquisition submodule, the error sum is calculated as follows:

[0032]

[0033] Where J(W,D) is the error sum; W is the crack width, D is the crack depth; i is the serial number of the detection point; n is the total number of detection points; y i is the imaginary part of the detection impedance increment corresponding to the i-th detection point; x i is the position of the i-th detection point; ΔZ(x i ,W,D) is the corresponding calculated impedance increment of the i-th detection point output of the approximate analytical model.

[0034] Optionally, the crack parameter acquisition submodule includes:

[0035] Error and determination unit for:

[0036] Inputting the crack parameters at the current iteration number into the approximate analytical model to obtain the calculated impedance increment at the current iteration number;

[0037] Calculate the sum of the errors between the detection impedance increment at the current iteration number and the calculation impedance increment at the current iteration number to obtain the sum of the errors at the current iteration number;

[0038] A judgment unit, configured to judge whether an iteration stopping condition is satisfied; the iteration stopping condition being that the current number of iterations reaches a set number of iterations or the error at the current number of iterations is within a set error value range;

[0039] An optimal crack parameter determination unit, configured to take the crack parameter at the current number of iterations as the optimal crack parameter if an iteration stop condition is met;

[0040] The updating unit is used to calculate the error and corresponding gradient information at the current iteration number by using the steepest gradient descent method if the iteration stop condition is not met, and to update the crack parameters at the current iteration number according to the error sum and corresponding gradient information at the current iteration number, and use the updated crack parameters as the crack parameters at the next iteration number, and return to the "error and determination unit".

[0041] Optionally, in the updating unit, the crack parameter at the current iteration number is updated according to the error sum at the current iteration number and the corresponding gradient information, specifically as follows:

[0042]

[0043] Where W is the crack width, D is the crack depth, α W is the iteration step of the width parameter, α D is the iteration step of the depth parameter, and ":=" is the parameter update indicator;

[0044] is the error and the gradient information corresponding to the crack width; is the error and the gradient information corresponding to the crack depth.

[0045] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0046] The present invention provides a metal pipeline crack measurement method and system. This measurement method aims to minimize the error sum between the detected impedance increment and the calculated impedance increment. It employs an iterative algorithm to solve an approximate analytical model to obtain optimal crack parameters. The approximate analytical model is used to calculate the impedance increment based on the location of the detection point, resulting in a calculated impedance increment. Crack parameters include crack depth and crack width. With the goal of minimizing the error sum, the present invention employs an iterative algorithm to continuously search, iterate, and update the crack parameters, achieving optimal matching values. This eliminates the need for detection accuracy to rely on the initial values of the crack parameters, ensuring measurement stability and high-precision detection. Consequently, the present invention is capable of achieving high-precision measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] 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. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 A flow chart of a metal pipe crack measurement method provided by an embodiment of the present invention;

[0049] Figure 2 A structural diagram of a metal pipe crack measurement system provided by an embodiment of the present invention;

[0050] Figure 3 A schematic diagram of a metal pipe crack measurement method provided by an embodiment of the present invention;

[0051] Figure 4 A schematic diagram showing how the detection impedance increment varies with the position of the detection point according to an embodiment of the present invention;

[0052] Figure 5 A flowchart of a crack parameter iteration process provided by an embodiment of the present invention;

[0053] Figure 6 A schematic diagram of crack depth parameter results during the iterative process provided by an embodiment of the present invention;

[0054] Figure 7 A schematic diagram of crack width parameter results during the iterative process provided by an embodiment of the present invention;

[0055] Figure 8 A schematic diagram of error results during the iterative process provided by an embodiment of the present invention.

[0056] Explanation of symbols:

[0057] Detection impedance increment acquisition module-1, approximate analytical model construction module-2, optimal crack parameter acquisition module-3. DETAILED DESCRIPTION

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only 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 making creative efforts are within the scope of protection of the present invention.

[0059] The object of the present invention is to provide a metal pipeline crack measurement method and system, which obtains the detection impedance increment of multiple detection points on the target metal pipeline; the detection impedance increment is the impedance increment at each detection point when the excitation signal emitted by the detection probe is irradiated on each detection point; then an approximate analytical model is constructed according to the crack parameters; the approximate analytical model is used to calculate the impedance increment according to the position of the detection point to obtain the calculated impedance increment; the crack parameters include crack depth and crack width; then, with the goal of minimizing the error sum of the detection impedance increment and the calculated impedance increment, an iterative algorithm is used to solve the approximate analytical model to obtain the optimal crack parameters; the optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the error sum is minimized; due to the continuous search, iteration and update of the crack parameters, the error sum parameters can be optimally matched, thereby obtaining the optimal matching value, so that the detection accuracy no longer depends on the setting of the initial value of the crack parameter, and the stability of the measurement and high-precision detection can be guaranteed. Therefore, the present invention can achieve high-precision measurement.

[0060] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0061] Example 1

[0062] like Figure 1 The embodiment of the present invention provides a method for measuring cracks in a metal pipeline, the method comprising:

[0063] Step 100: Obtain the detection impedance increments at multiple detection points on the target metal pipe. The detection impedance increments are the impedance increments at each detection point when the excitation signal emitted by the detection probe is irradiated on the detection point. The detection probe uses a sinusoidal signal as the excitation signal.

[0064] Step 200: construct an approximate analytical model based on crack parameters; the approximate analytical model is used to calculate the impedance increment according to the position of the detection point to obtain the calculated impedance increment; the crack parameters include crack depth and crack width.

[0065] Step 300: With the goal of minimizing the sum of errors between the detected impedance increment and the calculated impedance increment, an iterative algorithm is used to solve the approximate analytical model to obtain optimal crack parameters; the optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the sum of errors is minimized.

[0066] Specifically, with the goal of minimizing the sum of errors, the least squares method is used to solve the approximate analytical model to obtain the optimal crack parameters.

[0067] Furthermore, the formula for calculating the sum of the errors between the detected impedance increment and the calculated impedance increment is:

[0068]

[0069] n detection points are set on the target metal tube, and the positions of the detection points are represented by x:

[0070] x=[x1...x n ] T ∈R n ;

[0071] The imaginary part of the detection impedance increment corresponding to each detection point is represented by y:

[0072] y=[y1 ... y n ] T ∈R n ;

[0073] Where J(W,D) is the error sum; W is the crack width, D is the crack depth; i is the serial number of the detection point; n is the total number of detection points; y i is the imaginary part of the detection impedance increment corresponding to the i-th detection point; x i is the position of the i-th detection point; ΔZ(x i ,W,D) is the calculated impedance increment corresponding to the i-th detection point output of the approximate analytical model; T is represented by the transpose; R n is an n-dimensional column vector.

[0074] Specifically, with the goal of minimizing the error sum, the least squares method is used to solve the approximate analytical model to obtain the optimal crack parameters, including:

[0075] The crack parameters at the current iteration number are input into the approximate analytical model to obtain the calculated impedance increment at the current iteration number.

[0076] The sum of errors between the detection impedance increment at the current iteration number and the calculation impedance increment at the current iteration number is calculated to obtain the sum of errors at the current iteration number.

[0077] Determine whether the iteration stopping condition is met; the iteration stopping condition is that the current number of iterations reaches the set number of times or the error sum at the current number of iterations is within the set error value range.

[0078] If the iteration stop condition is met, the crack parameters at the current iteration number are taken as the optimal crack parameters;

[0079] If the iteration stop condition is not met, the steepest gradient descent method is used to calculate the error and corresponding gradient information at the current iteration number, and the crack parameters at the current iteration number are updated according to the error sum and corresponding gradient information at the current iteration number. The updated crack parameters are used as the crack parameters at the next iteration number, and the process returns to the step of "inputting the crack parameters at the current iteration number into the approximate analytical model to obtain the calculated impedance increment at the current iteration number".

[0080] Furthermore, the crack parameters at the current iteration number are updated according to the error sum at the current iteration number and the corresponding gradient information, specifically including:

[0081]

[0082] Where W is the crack width, D is the crack depth, α W is the iteration step of the width parameter, α D is the iteration step of the depth parameter, and ":=" is the parameter update indicator;

[0083] is the error and the gradient information corresponding to the crack width; is the error and the gradient information corresponding to the crack depth.

[0084] The metal pipe crack measurement method provided in an embodiment of the present invention is an optimized metal pipe crack detection method based on an eddy current field approximate analytical model, wherein the detection signal, i.e., the detection impedance increment, is obtained by eddy current non-destructive testing technology, and the eddy current field approximate analytical model is obtained by computational electromagnetic field theory.

[0085] This measurement method is based on the variation in the impedance increment of the solenoid coil when it is excited at different positions on the pipeline. It detects crack parameters using an approximate analytical model and optimization methods. This embodiment of the present invention calculates the impedance increment of the detection probe by varying its detection position. Then, using the least squares method, it calculates the sum of the errors between the approximate analytical model and the detection signal. By minimizing the sum of squared errors, it finds the optimal model parameter matching value for the detection data. This matching value can be used to obtain the crack parameters.

[0086] Figure 3 A schematic diagram of a metal pipe crack measurement method provided by an embodiment of the present invention is shown in FIG. Figure 3As shown in the figure, by using a sinusoidal signal as the excitation signal of the detection probe, crack detection is performed on the actual detection object, that is, the target metal pipe, to obtain the detection impedance increment. Then, by setting the initial value of the detection parameter of the cracked cylindrical conductor calculation model (that is, the approximate analytical model), the impedance increment is calculated according to the position of the detection point to obtain the calculated impedance increment. Then, the error information between the detection impedance increment and the calculated impedance increment, that is, the error sum, is calculated. With the goal of minimizing the error sum, an iterative algorithm is used to solve the approximate analytical model, and finally the optimal crack parameter is obtained. α in the figure D is the iterative step size of the depth parameter; α W is the iteration step size of the width parameter.

[0087] As the manufacturing industry develops informatization, industrial production places higher demands on cost control and detection accuracy in detection technology. Therefore, low-cost and accurate detection of cracks in industrial metal pipes is particularly necessary. The measurement method provided by the embodiments of the present invention can achieve low-cost and high-precision parameter detection of cracks in metal pipes.

[0088] This method uses eddy current nondestructive testing technology to measure metal pipes. A sinusoidal signal is used as the excitation signal for the detection probe. By varying the detection position of the detection probe, a detection signal is obtained for the corresponding position and the impedance increment of the detection probe at that position. The impedance increment signal obtained by varying the detection coil's detection position is compared with the results of an approximate analytical solution model using the least squares method to calculate the error. The steepest gradient descent method is then used to search for the optimal model depth and width parameter matching value that achieves the minimum sum of squared errors, thereby enabling crack parameter detection. Experimental results demonstrate that this method can perform nondestructive, low-cost, and high-precision detection of crack depth and width in metal pipes.

[0089] In practical applications, the specific implementation steps of the measurement method provided by the embodiment of the invention are as follows:

[0090] Step 1. Perform impedance increment detection on the pipeline to be detected. Set several detection points on the surface of the conductor to be detected (5-10 is better for both efficiency and accuracy), detect the detection probe one by one according to the designed detection point position, record the detection probe position and the impedance increment signal at that position, because the real part signal value of the impedance increment is small and easily affected by the probe temperature, the imaginary part of the impedance increment is selected as the detection signal to quantitatively detect the crack width and depth. The imaginary part of the impedance increment can be expressed by ΔX. Through this step, the curve of the detection signal changing with the detection position can be obtained, such as Figure 4 shown.

[0091] Step 2. Use the least squares method to calculate the error sum between the approximate analytical model and the detection signal. Set the depth and width parameter values of the object to be detected, and use the least squares method to obtain the error sum between the approximate analytical model and the detection signal. If n detection points are set, the position of the detection point is represented by x, that is,

[0092] x=[x1 ... x n ] T ∈R n

[0093] The imaginary part of the impedance increment corresponding to each detection point is represented by y, that is,

[0094] y=[y1 ... y n ] T ∈R n

[0095] The approximate analytical model is expressed as

[0096] ΔZ(x i ,W,D)

[0097] Where W is the crack width and D is the crack depth.

[0098] The error is calculated using the least squares method and is expressed as:

[0099]

[0100] Step 3. Use the steepest gradient descent algorithm to search for the parameter value that optimizes the error sum J(W,D). Set the search iteration step, set the maximum search iteration number and error value interval for the stop condition, set the parameter search range, calculate the gradient information of the corresponding position error sum, and then update the initial parameter value. The update method is:

[0101]

[0102] Where W is the crack width, D is the crack depth, α W and α D is the iteration step size, and “:=” is the parameter update indicator.

[0103] Use the updated parameters to execute the process shown in step 2 to obtain the error and information. The stopping condition is:

[0104] 1. When the error sum meets the set range, stop the parameter update iteration and output the parameter results.

[0105] 2. When the maximum search iteration number is reached, stop parameter updating and output the parameter results.

[0106] The implementation flow chart, that is, the flow chart of the crack parameter iteration process is as follows Figure 5As shown. First, the impedance increment signal of the detected object, i.e., the target metal tube, is detected, i.e., the impedance increment is detected. Then, the initial value of the calculation model is set to calculate the impedance increment, i.e., an approximate analytical model is constructed according to the crack parameters. The approximate analytical model calculates the impedance increment according to the position of the detection point to obtain the calculated impedance increment. Then, the measured value and the model calculated value are compared, i.e., the error sum between the detected impedance increment and the calculated impedance increment is calculated. Furthermore, with the minimum error sum as the goal, the approximate analytical model is solved using an iterative algorithm to obtain the optimal crack parameters. The optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the error sum is minimized. In short, a judgment is made as to whether the error meets the set requirements, which include the iteration step size, iteration number, and error value interval. If the set requirements are met, the iterative result is output; if the set requirements are not met, the initial value is updated and it is iterated until the requirements are met, and then the iterative process is stopped.

[0107] The iterative process and results are shown as follows: Figure 6-Figure 8 As shown. Among them, Figure 6 A schematic diagram of crack depth parameter results during the iterative process provided for this embodiment; Figure 7 A schematic diagram of crack width parameter results during the iterative process provided for this embodiment; Figure 8 A schematic diagram of error results during the iterative process provided for this embodiment.

[0108] Based on the approximate analytical solution of the eddy current field in metal pipelines, the present invention analyzes the change in the coil impedance increment when the excitation solenoid coil is at different positions in the cracked pipeline. The least squares method is used to calculate the sum of the errors between the approximate analytical solution and the detection signal. Then, the steepest gradient descent method is used to search for the best model depth and width parameter matching value that achieves the minimum sum of squared errors, thereby obtaining the optimal matching value of the parameters and realizing the detection of pipeline crack parameters.

[0109] Example 2

[0110] An embodiment of the present invention provides a metal pipeline crack measurement system, which includes: a detection impedance increment acquisition module 1, an approximate analytical model construction module 2, and an optimal crack parameter acquisition module 3.

[0111] The detection impedance increment acquisition module 1 is used to obtain the detection impedance increment of multiple detection points on the target metal pipeline; the detection impedance increment is the impedance increment at each detection point when the excitation signal emitted by the detection probe is irradiated on each detection point.

[0112] The approximate analytical model construction module 2 is used to construct an approximate analytical model based on crack parameters; the approximate analytical model is used to calculate the impedance increment based on the position of the detection point to obtain the calculated impedance increment; the crack parameters include crack depth and crack width.

[0113] The optimal crack parameter acquisition module 3 is used to solve the approximate analytical model using an iterative algorithm with the goal of minimizing the sum of the errors between the detected impedance increment and the calculated impedance increment to obtain the optimal crack parameters; the optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the sum of the errors is minimized.

[0114] Specifically, the optimal crack parameter acquisition module 3 includes: a crack parameter acquisition submodule.

[0115] The crack parameter acquisition submodule is used to solve the approximate analytical model using the least squares method with the goal of minimizing the error sum to obtain the optimal crack parameters.

[0116] In the crack parameter acquisition submodule, the error sum calculation formula is:

[0117]

[0118] Where J(W,D) is the error sum; W is the crack width, D is the crack depth; i is the serial number of the detection point; n is the total number of detection points; y i is the imaginary part of the detection impedance increment corresponding to the i-th detection point; x i is the position of the i-th detection point; ΔZ(x i ,W,D) is the corresponding calculated impedance increment of the i-th detection point output of the approximate analytical model.

[0119] Furthermore, the crack parameter acquisition submodule includes: an error sum determination unit, a judgment unit, an optimal crack parameter determination unit and an update unit.

[0120] The error and determination unit is used to input the crack parameters at the current iteration number into the approximate analytical model to obtain the calculated impedance increment at the current iteration number.

[0121] The error sum determination unit is further used to calculate the error sum between the detection impedance increment at the current iteration number and the calculation impedance increment at the current iteration number, to obtain the error sum at the current iteration number.

[0122] The judgment unit is used to judge whether the iteration stopping condition is met; the iteration stopping condition is that the current number of iterations reaches the set number of times or the error at the current number of iterations is within the set error value range.

[0123] The optimal crack parameter determination unit is used to take the crack parameter at the current iteration number as the optimal crack parameter if the iteration stop condition is met.

[0124] The updating unit is used to calculate the error and corresponding gradient information at the current iteration number by using the steepest gradient descent method if the iteration stop condition is not met, and to update the crack parameters at the current iteration number according to the error sum and corresponding gradient information at the current iteration number, and use the updated crack parameters as the crack parameters at the next iteration number, and return to the "error and determination unit".

[0125] In the update unit, the crack parameters at the current iteration number are updated according to the error sum at the current iteration number and the corresponding gradient information, specifically:

[0126]

[0127] Where W is the crack width, D is the crack depth, α W is the iteration step of the width parameter, α D is the iteration step of the depth parameter, and “:=” is the parameter update indicator.

[0128] is the error and the gradient information corresponding to the crack width; is the error and the gradient information corresponding to the crack depth.

[0129] The advantages of the present invention are:

[0130] 1. This method uses an approximate analytical model and optimization ideas to more realistically detect the depth and width parameters of metal pipe cracks at the same time, without being restricted to using the control variable method to control the crack width parameter to detect the depth parameter or to control the crack depth parameter to detect the width parameter.

[0131] 2. The detection signal of this method is the impedance increment. Parameter detection can be achieved using only the original detection signal. There is no need to select detection features based on the detection signal or obtain the signal change curve through experiments in advance. This method has better convenience and lower detection cost.

[0132] 3. The detection accuracy of this method does not depend on the initial value of the parameter setting, has good detection stability, and avoids the complex parameter adjustment process in actual detection.

[0133] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0134] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for measuring cracks in a metal pipeline, characterized in that: The measuring method comprises: Obtaining detection impedance increments at multiple detection points on the target metal pipe; the detection impedance increments are impedance increments at each detection point when an excitation signal emitted by the detection probe is irradiated on each detection point; An approximate analytical model is constructed based on crack parameters; the approximate analytical model is used to calculate an impedance increment based on a position of a detection point to obtain a calculated impedance increment; the crack parameters include crack depth and crack width; With the goal of minimizing the sum of the errors between the detected impedance increment and the calculated impedance increment, an iterative algorithm is used to solve the approximate analytical model to obtain optimal crack parameters; the optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the sum of the errors is minimized.

2. The metal pipe crack measurement method according to claim 1, characterized in that: The method of solving the approximate analytical model using an iterative algorithm with the goal of minimizing the sum of the errors between the detected impedance increment and the calculated impedance increment to obtain the optimal crack parameters specifically includes: With the error sum as the minimum, the approximate analytical model is solved by using the least square method to obtain the optimal crack parameters.

3. The metal pipe crack measurement method according to claim 2, characterized in that: The calculation formula for the sum of the errors of the detected impedance increment and the calculated impedance increment is: Where J(W,D) is the error sum; W is the crack width, D is the crack depth; i is the serial number of the detection point; n is the total number of detection points; y i is the imaginary part of the detection impedance increment corresponding to the i-th detection point; x i is the position of the i-th detection point; ΔZ(x i ,W,D) is the corresponding calculated impedance increment of the i-th detection point output of the approximate analytical model.

4. The metal pipe crack measurement method according to claim 2, characterized in that: The method of solving the approximate analytical model with the least square method with the goal of minimizing the error sum to obtain the optimal crack parameters specifically includes: Inputting the crack parameters at the current iteration number into the approximate analytical model to obtain the calculated impedance increment at the current iteration number; Calculate the sum of the errors between the detection impedance increment at the current iteration number and the calculation impedance increment at the current iteration number to obtain the sum of the errors at the current iteration number; Determine whether an iteration stop condition is met; the iteration stop condition is that the current number of iterations reaches a set number of times or the error at the current number of iterations is within a set error value range; If the iteration stop condition is met, the crack parameters at the current iteration number are taken as the optimal crack parameters; If the iteration stop condition is not met, the steepest gradient descent method is used to calculate the error and corresponding gradient information at the current iteration number, and the crack parameters at the current iteration number are updated according to the error sum and corresponding gradient information at the current iteration number. The updated crack parameters are used as the crack parameters at the next iteration number, and the process returns to the step of "inputting the crack parameters at the current iteration number into the approximate analytical model to obtain the calculated impedance increment at the current iteration number".

5. The metal pipe crack measurement method according to claim 4, characterized in that: The crack parameters at the current number of iterations are updated according to the error sum at the current number of iterations and the corresponding gradient information, specifically: Where W is the crack width, D is the crack depth, α W is the iteration step of the width parameter, α D is the iteration step of the depth parameter, ":=" is the parameter update indicator; is the error and the gradient information corresponding to the crack width; is the error and the gradient information corresponding to the crack depth.

6. A metal pipeline crack measurement system, characterized in that: The measurement system comprises: A detection impedance increment acquisition module is used to obtain the detection impedance increment of multiple detection points on the target metal pipe; the detection impedance increment is the impedance increment at each detection point when the excitation signal emitted by the detection probe is irradiated on each detection point; An approximate analytical model construction module is used to construct an approximate analytical model based on crack parameters; the approximate analytical model is used to calculate the impedance increment based on the position of the detection point to obtain the calculated impedance increment; the crack parameters include crack depth and crack width; The optimal crack parameter acquisition module is used to solve the approximate analytical model using an iterative algorithm with the goal of minimizing the sum of the errors between the detected impedance increment and the calculated impedance increment to obtain the optimal crack parameters; the optimal crack parameters are the crack parameters corresponding to the approximate analytical model when the sum of the errors is minimized.

7. The metal pipe crack measurement system according to claim 6, characterized in that: The optimal crack parameter acquisition module includes: The crack parameter acquisition submodule is used to solve the approximate analytical model using the least square method with the goal of minimizing the error sum to obtain the optimal crack parameters.

8. The metal pipe crack measurement system according to claim 7, characterized in that: In the crack parameter acquisition submodule, the error sum is calculated as follows: Where J(W,D) is the error sum; W is the crack width, D is the crack depth; i is the serial number of the detection point; n is the total number of detection points; y i is the imaginary part of the detection impedance increment corresponding to the i-th detection point; x i is the position of the i-th detection point; ΔZ(x i ,W,D) is the corresponding calculated impedance increment of the i-th detection point output of the approximate analytical model.

9. The metal pipe crack measurement system according to claim 7, characterized in that: The crack parameter acquisition submodule includes: Error and determination unit for: Inputting the crack parameters at the current iteration number into the approximate analytical model to obtain the calculated impedance increment at the current iteration number; Calculate the sum of the errors between the detection impedance increment at the current iteration number and the calculation impedance increment at the current iteration number to obtain the sum of the errors at the current iteration number; A judgment unit, configured to judge whether an iteration stopping condition is satisfied; the iteration stopping condition being that the current number of iterations reaches a set number of iterations or the error at the current number of iterations is within a set error value range; An optimal crack parameter determination unit, configured to take the crack parameter at the current number of iterations as the optimal crack parameter if an iteration stop condition is met; The updating unit is used to calculate the error and corresponding gradient information at the current iteration number using the steepest gradient descent method if the iteration stopping condition is not met, and to update the crack parameters at the current iteration number based on the error sum and corresponding gradient information at the current iteration number, and use the updated crack parameters as the crack parameters at the next iteration number, and return to the "error and determination unit".

10. The metal pipeline crack measurement system according to claim 9, characterized in that: In the updating unit, the crack parameters at the current iteration number are updated according to the error sum at the current iteration number and the corresponding gradient information, specifically: Where W is the crack width, D is the crack depth, α W is the iteration step of the width parameter, α D is the iteration step of the depth parameter, ":=" is the parameter update indicator; is the error and the gradient information corresponding to the crack width; is the error and the gradient information corresponding to the crack depth.

Images