Waveguide signal path optimization selection method based on signal difference coefficient and energy

Abstract

The present application relates to the technical field of ultrasonic guided wave path, and particularly provides a guided wave signal path optimization selection method based on signal difference coefficient and energy. The method comprises the following steps: building an ultrasonic guided wave structure defect detection system; grouping sensing paths according to the built system; collecting and grouping healthy signals and defect signals based on the sensing path grouping; and identifying effective sensing paths according to the collection and grouping of the healthy signals and the defect signals. The method eliminates invalid paths, highlights effective defect information, improves the accuracy of ultrasonic guided wave defect imaging, and effectively improves the optimization of guided wave signal paths.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ultrasonic guided wave path, and particularly relates to a guided wave signal path optimization selection method based on signal difference coefficient and energy. BACKGROUND

[0002] In the field of structural health monitoring, pipelines, as a key component of energy transportation, chemical production and urban infrastructure, their structural integrity is directly related to the operation safety and environmental protection, so it is of great significance to effectively detect pipeline defects. At present, the common detection methods of pipeline defects include internal detector (PIG), ray detection, penetration detection and conventional ultrasonic detection. However, these methods have certain limitations: the internal detector is limited in the application of pipe diameter and has high requirements for the cleanliness of the pipeline; the ray detection has safety protection problems and is difficult to identify small defects; the penetration detection is only suitable for surface defects; and the conventional ultrasonic detection is low in efficiency and difficult to achieve wide coverage.

[0003] The ultrasonic guided wave detection technology uses the reflection, scattering or mode conversion of high-frequency mechanical waves in the pipe wall when encountering defects to identify defects, and has the advantages of long propagation distance, small attenuation, wide detection range and high sensitivity, and is especially suitable for detecting hidden or inaccessible pipe sections. At present, the pipeline defect positioning method based on ultrasonic guided waves usually arranges a sensor array on the pipe wall, collects guided wave signals under all excitation-receiving paths, and constructs a defect probability image based on the full path data. However, this method has obvious problems in practical application: in all signal paths, a large number of paths are far away from the defect area, and the signal changes of these paths are mainly caused by environmental noise, temperature fluctuations or measurement errors, rather than real defects. Including these invalid paths (or useless paths) in imaging calculation will introduce significant noise interference and dilute real defect information, thereby reducing the positioning accuracy and reliability. SUMMARY

[0004] Therefore, the present application provides a guided wave signal path optimization selection method based on signal difference coefficient and energy, which can eliminate invalid paths and highlight effective defect information, and improve the accuracy of ultrasonic guided wave defect imaging, so as to effectively improve the guided wave signal path optimization.

[0005] In the first aspect, the present application provides a guided wave signal path optimization selection method based on signal difference coefficient and energy, which comprises the following steps:

[0006] Step 1, building an ultrasonic guided wave structure defect detection system;

[0007] Step 2, grouping the sensing paths according to the built system;

[0008] Step 3, collecting and grouping the health signals and defect signals based on the grouping of the sensing paths;

[0009] Step 4, according to the collection and grouping of health signals and defect signals, effective sensing path recognition is performed.

[0010] Optionally, the step 1 comprises:

[0011] An ultrasonic guided wave structure defect detection system is built by using a ring-shaped piezoelectric sensing array, an ultrasonic guided wave detector, a host computer and a pipeline structure to be detected.

[0012] a. The ring-shaped piezoelectric sensing array is composed of 2N piezoelectric sensors: N piezoelectric sensors are used to excite ultrasonic guided wave signals, which are defined as excitation sensors and marked as A1, A2, …, AN respectively; the other N piezoelectric sensors are used to receive ultrasonic guided wave signals, which are defined as receiving sensors and marked as R1, R2, …, RN respectively;

[0013] The excitation sensors A1, A2, …, AN are pasted on the outer surface of the pipeline structure at equal intervals around the circumferential direction of the pipeline structure, that is, if the outer radius of the pipeline structure is r, the arc length between the excitation sensor Ai1 and the excitation sensor Ai1+1 is 2πr / N, i1=1, 2, …, N-1; and the plane formed by A1, A2, …, AN is perpendicular to the central axis direction of the pipeline structure, and the sensing array formed by the excitation sensors A1, A2, …, AN is called the excitation sensing array;

[0014] The receiving sensors R1, R2, …, RN are pasted on the outer surface of the pipeline structure at equal intervals around the circumferential direction of the pipeline structure, that is, if the outer radius of the pipeline structure is r, the arc length between the receiving sensor Ri1 and the receiving sensor Ri1+1 is 2πr / N, i1=1, 2, …, N-1; and the plane formed by R1, R2, …, RN is perpendicular to the central axis direction of the pipeline structure, and the sensing array formed by the receiving sensors R1, R2, …, RN is called the receiving sensing array;

[0015] The line between the excitation sensor Ai' and the receiving sensor Ri' corresponding to the same number is parallel to the central axis of the pipeline structure, and the axial distance between the excitation sensing array and the receiving sensing array is d, i'=1, 2, …, N;

[0016] b. One end of the ultrasonic guided wave detector is connected with the piezoelectric sensor, and the other end is connected with the host computer, which is used for transmitting the excitation and collected guided wave signals;

[0017] c. The host computer is used for setting the excitation signal parameters and displaying and storing the collected signals;

[0018] d. The pipeline structure to be detected is a circular tubular structure made of steel or aluminum alloy material.

[0019] Optionally, the step 2 comprises:

[0020] The signal used is the direct signal segment collected by the receiving sensor. When the structure is expanded, only half of the expansion plane needs to be expanded on each side;

[0021] Suppose there are an even number of unilateral sensors, when there are 8 unilateral sensors, the original plane of the pipe expansion structure, the 0th plane is denoted as Ω0; the 1st plane expanded to the left is denoted as Ω-1, and the 1st plane expanded to the right is denoted as Ω1; according to the different directions, there are a total of 9 sensor path groups. Since the type of path, which has the same path length of left-handed and right-handed waves in the pipe, only considers one direction, i.e. a total of 8 sensor path groups; similarly, suppose there are an odd number of unilateral sensors, when there are 7 unilateral sensors, there are a total of 7 sensor path groups;

[0022] According to the different propagation directions of the paths, all the sensor paths are divided into N groups, i.e. path group 1, path group 2, …, path group N; different path groups represent different propagation directions, i.e. direction 1, direction 2, …, direction N; use to represent the number of sensor paths in the kth group, then is the number of all sensor paths in the sensor array.

[0023] Optionally, the step 3 comprises:

[0024] Step 31, health signal acquisition and grouping;

[0025] Under the health state of the pipe structure to be tested, three groups of guided wave signals are collected using an ultrasonic guided wave detector, denoted as health signals HS, respectively HS1, HS2, and HS3, and combined with the grouping results of the sensor paths, HS1, HS2, and HS3 are divided into N signal sets, respectively {HS11}, {HS12}, …, {HS1 N}; {HS21}, {HS22}, …, {HS2 N}; {HS31}, {HS32}, …, {HS3 N}; N signal sets correspond to N path groups; if the number of sampling points is denoted as , represent the number of sensor paths in the kth group, then the dimension of each signal matrix in the kth signal set is ;

[0026] Step 32, defect signal acquisition and grouping;

[0027] Under the condition of defects in the pipeline structure, guided wave signals in the structure are collected using an ultrasonic guided wave detector, denoted as the original defect signal DS. Based on the sensor path grouping results, the defect signal DS is divided into N signal sets, namely {DS1}, {DS2}, ..., {DS...}. N The above N signal sets correspond to N path groups; signal set {DS} k The number of signals and data dimensions in} are related to the signal set {HS1}. k}、{HS2 k}、{HS3 k The number of signals and the data dimension are the same, k=1,2,…,N.

[0028] Optionally, step 4 includes:

[0029] Step 41: Effective sensing path identification based on signal difference coefficient SDC;

[0030] Threshold calculation based on health signals: The baseline SDC value is calculated using health signal HS1 and health signal HS2, and its expression is as follows:

[0031] ;

[0032] in, , The correlation coefficient represents the correlation between two health signals. Indicates the transmitter. Indicates the receiver; Represents covariance; Indicates standard deviation; and This represents the mean of two health signals; Indicates the length of the signal; Indicates the sampling time; and The health signal collected at different times between the transmitter and receiver is called the baseline signal;

[0033] After obtaining the baseline SDC, calculate its mean. and standard deviation Their expressions are as follows:

[0034] ;

[0035] ;

[0036] Where M represents all calculated baseline SDCs;

[0037] Get the mean and standard deviation Then, calculate the first threshold. , whose expression is:

[0038] ;

[0039] Based on the threshold calculation of the defect signal, the original defect signal DS and the healthy signal HS1 are used to calculate the defect SDC value, whose expression is:

[0040] ;

[0041] wherein, , represents the correlation coefficient of the healthy signal and the defect signal, represents the transmitter, represents the receiver; represents the defect signal; represents the mean value of the defect signal;

[0042] All path defect SDC values are compared with the first threshold , when SDC k > , it means that the signal collected by the path is different from the baseline signal collected when the structure is healthy, indicating that there is a high possibility of defects near the current sensing path, so as to select the path affected by the defect, k = 1, 2, …, N;

[0043] Step 42, effective sensing path identification based on windowed scattering signal energy WSE;

[0044] Defect energy calculation, using the defect signal DS and the healthy signal HS1 to calculate the scattering signal , combined with the sensing path grouping result, the scattering signal SS1 is divided into N signal sets {SS11}, {SS12}, …, {SS1 N} according to the path direction, and the above N signal sets correspond to N path groups respectively; then the envelope of the scattering signal SS1 is calculated by Hilbert transform, whose expression is:

[0045] ;

[0046] wherein, represents the Hilbert transform of the signal ; represents the Hilbert transform symbol; P.V. represents the Cauchy principal value integral;

[0047] The original signal is taken as the real part, and its Hilbert transform is taken as the imaginary part, to form a complex signal , and is called the analytic signal of , whose expression is:

[0048] ;

[0049] Parse the signal The module of the original signal The envelope of Its expression is:

[0050] After obtaining the envelope of the scattered signal SS1, integrate the envelope and select the integration time window; In order to avoid the influence of the spiral wave, the starting time of integration is the arrival time of the first direct wave of the healthy signal, and the ending time is the arrival time of the spiral wave;

[0051] , The time window is ;

[0052] Wherein, a is the axial distance between the pipeline excitation sensor array and the receiving sensor array, b is the distance between the sensors, d1 is the distance of the straight path Am-Rm+2, d2 is the distance of the spiral path Am-Rm+2 -1 , and v is the speed of the waveform;

[0053] Because of the different path directions and distances, the time window is selected for each of the N path groups of the healthy signal HS1, and is applied to the corresponding N path groups of the scattered signal SS1 for integration. After integration, the energy En of each path is calculated, and its expression is:

[0054] ;

[0055] Based on the threshold calculation of the healthy signal, the signals S12, S13 and S23 are obtained by subtracting two by two from the three groups of healthy signals HS1, HS2 and HS3; Then, the envelopes of the subtracted signals S12, S13 and S23 are calculated, and then the envelopes are integrated according to the steps in the above defect energy calculation to obtain three groups of reference energies E1, E2 and E3 containing each path signal; The average of all reference energies is calculated to obtain the average energy Eh;

[0056] According to the average energy Eh, the second threshold is calculated, and its expression is:

[0057] ;

[0058] Compare all path energies En with the second threshold When En k > Th2 , it means that the path is greatly affected by the defect, so the required path is selected, k=1, 2, …, N;

[0059] Step 43, obtaining an effective sensing path set;

[0060] The effective sensing path selected based on the signal difference coefficient SDC is fused with the effective sensing path selected based on the windowed scattered signal energy WES to obtain a final optimized total selection path.

[0061] In a second aspect, an embodiment of the present application provides a computer readable storage medium, the computer readable storage medium comprising a stored program, wherein the program, when executed, controls a device in which the computer readable storage medium is located to perform the guided wave signal path optimization selection method based on the signal difference coefficient and the energy in the first aspect or any possible implementation manner of the first aspect.

[0062] In a third aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs comprise instructions that, when executed by the device, cause the device to perform the guided wave signal path optimization selection method based on the signal difference coefficient and the energy in the first aspect or any possible implementation manner of the first aspect.

[0063] The technical scheme provided by the present application comprises the following steps: building an ultrasonic guided wave structure defect detection system; grouping sensing paths according to the built system; collecting and grouping healthy signals and defect signals based on the sensing path grouping; and identifying effective sensing paths according to the collection and grouping of the healthy signals and the defect signals. The method eliminates invalid paths, highlights effective defect information, improves the accuracy of ultrasonic guided wave defect imaging, and effectively improves the optimization of guided wave signal paths. BRIEF DESCRIPTION OF DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0065] Figure 1 The flowchart of the guided wave signal path optimization selection method based on the signal difference coefficient and the energy provided by the embodiment of the present application;

[0066] Figure 2 The pipeline expansion schematic diagram of 16 sensors provided by the embodiment of the present application;

[0067] Figure 3 The pipeline expansion schematic diagram of 14 sensors provided by the embodiment of the present application;

[0068] Figure 4 A schematic diagram of an Am-Rm+2 path provided for an embodiment of the present application;

[0069] Figure 5 A schematic diagram of an electronic device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0070] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0071] The terms used in the embodiments of the present application are merely for the purpose of describing specific embodiments and are not intended to limit the present application. The singular forms "a", "an" and "the" used in the embodiments of the present application are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0072] It should be understood that the term "and / or" used herein merely describes an association relationship of associated objects, and means that there can be three relationships, for example, A and / or B, which means that there are three cases of A alone, A and B together, and B alone. In addition, the character " / " herein generally represents an "or" relationship between the front and rear associated objects.

[0073] Depending on the context, the word "if" as used herein can be interpreted as meaning "when" or "upon" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if it is determined" or "if (a stated condition or event) is detected" can be interpreted as meaning "when it is determined" or "in response to determining" or "when (a stated condition or event) is detected" or "in response to detecting (a stated condition or event)".

[0074] Figure 1 A flowchart of a guided wave signal path optimization selection method based on signal difference coefficient and energy provided for an embodiment of the present application is shown as Figure 1 The method comprises the following steps:

[0075] Step 1, building an ultrasonic guided wave structure defect detection system.

[0076] In the embodiments of the present application, step 1 comprises:

[0077] An ultrasonic guided wave structure defect detection system is built by using a ring piezoelectric sensor array, an ultrasonic guided wave detector, a host computer and a pipeline structure to be detected.

[0078] a. The ring piezoelectric sensor array is composed of 2N piezoelectric sensors: N piezoelectric sensors are used to excite ultrasonic guided wave signals, which are defined as excitation sensors and marked as A1, A2, …, AN respectively; the other N piezoelectric sensors are used to receive ultrasonic guided wave signals, which are defined as receiving sensors and marked as R1, R2, …, RN respectively.

[0079] The excitation sensors A1, A2, …, AN are pasted on the outer surface of the pipeline structure at equal intervals around the circumferential direction of the pipeline structure, that is, if the outer radius of the pipeline structure is r, the arc length between the excitation sensor Ai1 and the excitation sensor Ai1+1 is 2πr / N, i1=1, 2, …, N-1; and the plane composed of A1, A2, …, AN is perpendicular to the central axis direction of the pipeline structure, which is called the excitation sensor array composed of A1, A2, …, AN.

[0080] The receiving sensors R1, R2, …, RN are pasted on the outer surface of the pipeline structure at equal intervals around the circumferential direction of the pipeline structure, that is, if the outer radius of the pipeline structure is r, the arc length between the receiving sensor Ri1 and the receiving sensor Ri1+1 is 2πr / N, i1=1, 2, …, N-1; and the plane composed of R1, R2, …, RN is perpendicular to the central axis direction of the pipeline structure, which is called the receiving sensor array composed of R1, R2, …, RN.

[0081] The line between the excitation sensor Ai' and the receiving sensor Ri' with the same number is parallel to the central axis of the pipeline structure, and the axial distance between the excitation sensor array and the receiving sensor array is d, i'=1, 2, …, N.

[0082] b. One end of the ultrasonic guided wave detector is connected to the piezoelectric sensor, and the other end is connected to the host computer, which is used to transmit the excitation and collected guided wave signals and has the functions of filtering and amplification.

[0083] c. The host computer is used for setting the excitation signal parameters and displaying and storing the collected signals.

[0084] d. The pipeline structure to be detected is a circular tubular structure made of steel or aluminum alloy.

[0085] Step 2: According to the built system, the sensor path is grouped.

[0086] In the research of helical waveguide propagation path, the pipe structure is usually unfolded into a plane. The analysis of high-order helical waveguide propagation path is realized by copying infinite extension planes on the left and right sides of the pipe unfolding plane, which converts the three-dimensional pipe problem into a two-dimensional plate problem.

[0087] In the embodiment of the present application, step 2 comprises:

[0088] The signals adopted are direct signal segments collected by the receiving sensors, and only half of the extension plane on each side needs to be extended when the structure is extended;

[0089] Suppose that the unilateral sensors are even, such as Figure 2 As shown in the figure, when the unilateral sensors are 8, as shown by the green area, the original plane of the pipe unfolding structure is marked as Ω0, wherein the excitation sensors are marked as A1, A2, …, A8; the receiving sensors are marked as R1, R2, …, R8; the 1st plane extended to the left is marked as Ω-1, wherein the excitation sensors are marked as A1 -1 , A2 -1 , …, A8 -1 ; the receiving sensors are marked as R1 -1 , R2 -1 , …, R8 -1 , and the 1st plane extended to the right is marked as Ω1, wherein the excitation sensors are marked as A11, A21, …, A81; the receiving sensors are marked as R11, R21, …, R81, as shown by the gray area; and the green dashed area represents the complete area adopted. Figure 2 As can be seen from the figure, according to the different directions, there are totally 9 sensor path groups, and since the path of the type is the same in length of the left-handed wave and the right-handed wave in the pipe, only one direction is considered, i.e., there are totally 8 sensor path groups; by analogy, suppose that the unilateral sensors are odd, such as Figure 3 As shown in the figure, when the unilateral sensors are 7, as shown by the green area, the original plane of the pipe unfolding structure is marked as Ω0, wherein the excitation sensors are marked as A1, A2, …, A7; the receiving sensors are marked as R1, R2, …, R7; the 1st plane extended to the left is marked as Ω-1, wherein the excitation sensors are marked as A1 -1 , A2 -1 , …, A7 -1 ; the receiving sensors are marked as R1 -1 , R2 -1 , …, R7 -1 , and the 1st plane extended to the right is marked as Ω1, wherein the excitation sensors are marked as A11, A21, …, A71; the receiving sensors are marked as R11, R21, …, R71, as shown by the gray area; and the green dashed area represents the complete area adopted, which has totally 7 sensor path groups.

[0090] All sensing paths are divided into N groups, i.e. path group 1, path group 2, …, path group N, according to different propagation directions of the paths, and different path groups represent different propagation directions, i.e. direction 1, direction 2, …, direction N, and the number of sensing paths in the kth group is represented by , which is the number of all sensing paths in the sensing array.

[0091] Step 3, collecting and grouping the health signals and defect signals based on the sensing path grouping.

[0092] In the embodiment of the present application, step 3 comprises:

[0093] Step 31, collecting and grouping the health signals;

[0094] Under the health state of the to-be-tested pipeline structure, three groups of guided wave signals are collected by using an ultrasonic guided wave detector, denoted as health signals (HS), which are HS1, HS2 and HS3 respectively, and combined with the sensing path grouping result, HS1, HS2 and HS3 are divided into N signal sets, i.e. {HS11}, {HS12}, …, {HS1 N}, {HS21}, {HS22}, …, {HS2 N}, {HS31}, {HS32}, …, {HS3 N}, respectively, and the N signal sets correspond to the N path groups respectively; if the number of sampling points is represented by , and the number of sensing paths in the kth group is represented by , then the dimension of each signal matrix in the kth signal set is

[0095] Step 32, collecting and grouping the defect signals;

[0096] Under the defect state of the to-be-tested pipeline structure, guided wave signals in the structure are collected by using an ultrasonic guided wave detector, denoted as original defect signals (DS); combined with the sensing path grouping result, the defect signals DS are divided into N signal sets, i.e. {DS1}, {DS2}, …, {DS N}, and the N signal sets correspond to the N path groups respectively; the number of signals and the data dimension in the signal set {DS k} are the same as those of the signal sets {HS1 k}, {HS2 k} and {HS3 k}, and k=1, 2, …, N.

[0097] Step 4, identifying effective sensing paths according to the collection and grouping of the health signals and the defect signals.​​

[0098] In the embodiment of the present application, step 4 comprises:

[0099] Step 41, effective sensing path identification based on signal difference coefficient (SDC);

[0100] Based on the threshold calculation of the health signal, the baseline SDC value is calculated by using the health signal HS1 and the health signal HS2, and the expression is:

[0101]

[0102] wherein, , represents the correlation coefficient of the two health signals, represents the transmitter, represents the receiver; represents the covariance; represents the standard deviation; and represent the mean of the two health signals; represents the length of the signal; represents the sampling time; and represent the health signals collected at different times between the transmitter and the receiver, which are called baseline signals;

[0103] After obtaining the baseline SDC, the mean and the standard deviation are calculated, and the expressions are respectively:

[0104]

[0105]

[0106] wherein, M represents all the baseline SDCs calculated;

[0107] After obtaining the mean and the standard deviation , the first threshold is calculated, and the expression is:

[0108]

[0109] Based on the threshold calculation of the defect signal, the defect SDC value is calculated by using the original defect signal DS and the health signal HS1, and the expression is:

[0110]

[0111] wherein, ,​​​​​ correlation coefficient representing health signals and defect signals, represents a transmitter, represents a receiver; represents a defect signal; represents a mean value of a defect signal;

[0112] compare all path defect SDC values with a first threshold When SDC k > is greater than a baseline signal collected when the structure is healthy, indicating that there is a high possibility of defects near the current sensing path, so as to select a path that is greatly affected by defects, k = 1, 2, …, N;

[0113] Step 42, effective sensing path identification based on windowed scattered signal energy (WSE);

[0114] Defect energy calculation, using defect signal DS and health signal HS1 to calculate scattered signal , combined with the sensing path grouping result, the scattered signal (Scatter Signal, SS1) is divided into N signal sets {SS11}, {SS12}, …, {SS1 N} according to the path direction, and the above N signal sets correspond to N path groups respectively; then the envelope of the scattered signal SS1 is obtained by Hilbert transform, and the expression is:

[0115] ;

[0116] wherein, represents the Hilbert transform of the signal ; represents the Hilbert transform symbol; P.V. represents the Cauchy principal value integral;

[0117] The original signal is taken as the real part, and the Hilbert transform of the original signal is taken as the imaginary part to form a complex signal , and is called the analytic signal of , and the expression is:

[0118] ;

[0119] The modulus (amplitude) of the analytic signal is the envelope of the original signal , and the expression is:

[0120] ​ After obtaining the envelope of the scattered signal SS1, the envelope is integrated, and an integration time window is selected. In order to avoid the influence of the spiral wave, the integration start time is the arrival time of the first direct wave of the healthy signal, and the end time is the arrival time of the spiral wave.

[0121] In embodiments of the present invention, such as Figure 4 As shown, the green area represents the original plane of the pipe development structure. The 0th-order plane is denoted as Ω0, and Am-Rm+2 in the 0th-order plane is a straight path. The excitation sensors are denoted as A1, ..., Am, Am+1, Am+2, ..., AN; the receiving sensors are denoted as R1, ..., Rm, Rm+1, Rm+2, ..., RN. The 1st-order plane extending to the left is denoted as Ω-1, and the 1st-order plane Am-Rm+2... -1 The path is a spiral, where the excitation sensor is denoted as A1. -1 ..., Am+1 -1 Am+2 -1 , ..., AN -1 The receiving sensor is denoted as R1. -1 ..., Rm+1 -1 Rm+2 -1 ..., RN -1 The first-order plane extending to the right is denoted as Ω1, where the excitation sensors are denoted as A11, ..., Am+11, Am+21, ..., AN1; and the receiving sensors are denoted as R11, ..., Rm+11, Rm+21, ..., RN1, as shown in the gray area.

[0122] , The time window is ;

[0123] Where a is the axial distance between the pipe excitation sensor array and the receiving sensor array, b is the spacing between the sensors, d1 is the distance of the straight path Am-Rm+2, and d2 is the distance of the spiral path Am-Rm+2. -1 The distance, v is the velocity of the waveform;

[0124] Since the path directions and distances differ, time windows are selected for each of the N path groups of the health signal HS1, and these are applied to the N path groups corresponding to the scattered signal SS1 for integration. The energy En of each path is calculated through integration, and its expression is as follows:

[0125] ;

[0126] Based on the threshold value calculation of the health signal, the signals S12, S13 and S23 are obtained by subtracting two from each other among the three groups of health signals HS1, HS2 and HS3; then the envelopes of the subtracted signals S12, S13 and S23 are calculated, and then the integral of the envelope is calculated according to the steps in the above defect energy calculation, to obtain three groups of reference energies E1, E2 and E3 containing each path signal; the mean value of all reference energies is calculated to obtain the mean value energy Eh;

[0127] According to the mean value energy Eh, the second threshold value , and its expression is:

[0128] ;

[0129] Compare all path energies En with the second threshold value , when En k > , it means that the path is greatly affected by the defect, and the required path is selected, k=1, 2, …, N;

[0130] Step 43, obtaining an effective sensing path set;

[0131] The effective sensing path selected based on the signal difference coefficient SDC is fused with the effective sensing path selected based on the windowed scattered signal energy WES to obtain the final optimized total selected path.

[0132] Compared with the prior art, the present application has the following beneficial effects:

[0133] (1) The method of the present application greatly improves the analysis efficiency: its core advantage lies in significantly reducing the computational complexity and time cost. It quickly filters out a few key paths that are most significantly affected by the defect from all sensor paths through simple signal difference coefficient and envelope area calculation, thereby avoiding complex full waveform analysis on all paths. This realizes the change from comprehensive net casting to key fishing, making the defect positioning process more efficient and fast, and is particularly suitable for engineering applications that require real-time or near real-time monitoring.

[0134] (2) The method of the present application effectively enhances the positioning reliability: it can actively focus on the sensitive signal of the defect, thereby improving the accuracy and anti-interference ability of positioning. Since the defect has the greatest impact on the path signal passing through its vicinity, the high-value path selected itself clearly indicates the possible area of the defect. This not only narrows the search range of the fine algorithm and improves the positioning accuracy, but also performs a signal filtering, effectively suppressing the interference of irrelevant factors such as environmental noise, making the final positioning result clearer and more reliable.

[0135] The technical scheme provided by the application comprises the following steps: building an ultrasonic guided wave structure defect detection system; grouping sensing paths according to the built system; collecting and grouping healthy signals and defect signals based on the grouping of the sensing paths; and identifying effective sensing paths according to the collection and grouping of the healthy signals and the defect signals.

[0136] The various steps of the embodiment of the application can be executed by an electronic device, which includes but is not limited to a tablet computer, a portable PC, a desktop computer, etc.

[0137] The embodiment of the application provides a computer readable storage medium, which comprises a stored program, wherein when the program is running, the electronic device where the computer readable storage medium is located executes the embodiment of the guided wave signal path optimization selection method based on the signal difference coefficient and the energy.

[0138] Figure 5 An electronic device provided by the embodiment of the application is shown in a schematic diagram as shown in the figure, Figure 5 The electronic device 21 comprises a processor 211, a memory 212, and a computer program 213 stored in the memory 212 and executable on the processor 211, and the computer program 213 is executed by the processor 211 to implement the guided wave signal path optimization selection method based on the signal difference coefficient and the energy in the embodiment, and thus the detailed description is not repeated here.

[0139] The electronic device 21 comprises but is not limited to the processor 211 and the memory 212. Figure 5 The electronic device 21 is merely an example and does not constitute a limitation on the electronic device 21, and can comprise more or fewer components than those shown in the figure, or combine certain components or different components, for example, the electronic device can further comprise an input / output device, a network access device, a bus, etc.

[0140] The processor 211 can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0141] The memory 212 can be an internal storage unit of the electronic device 21, such as a hard disk or a memory of the electronic device 21. The memory 212 can also be an external storage device of the electronic device 21, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like. Further, the memory 212 can include both the internal storage unit and the external storage device of the electronic device 21. The memory 212 is used to store computer programs and other programs and data required by the network device. The memory 212 can also be used to temporarily store data that has been output or will be output.

[0142] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described herein.

[0143] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for optimizing the selection of guided signal paths based on signal difference coefficient and energy, characterized in that, The method includes: Step 1: Build an ultrasonic guided wave structure defect detection system; Step 2: Group the sensor paths according to the system being built; Step 3: Based on sensor path grouping, collect and group health signals and defect signals; Step 4: Based on the collection and grouping of health and defect signals, identify effective sensing paths; Step 4 includes: Step 41: Effective sensing path identification based on signal difference coefficient SDC; Threshold calculation based on health signals: The baseline SDC value is calculated using health signal HS1 and health signal HS2, and its expression is as follows: ； in, , The correlation coefficient represents the correlation between two health signals. Indicates the transmitter. Indicates the receiver; Represents covariance; Indicates standard deviation; and This represents the mean of two health signals; Indicates the length of the signal; Indicates the sampling time; and The health signal collected at different times between the transmitter and receiver is called the baseline signal; After obtaining the baseline SDC, calculate its mean. and standard deviation Their expressions are as follows: ； ； Where M represents all calculated baseline SDCs; Get the mean and standard deviation Then, calculate the first threshold. Its expression is: ； Threshold calculation based on defect signals uses the original defect signal DS and the healthy signal HS1 to calculate the defect SDC value, and its expression is as follows: ； in, , The correlation coefficient represents the correlation between health signals and defect signals. Indicates the transmitter. Indicates the receiver; Indicates a defect signal; This represents the mean of the defect signal; Compare all path defect SDC values ​​with the first threshold When comparing, when SDC k > When the signal obtained from the path differs significantly from the baseline signal obtained when the structure is healthy, it indicates that there is a high probability of a defect near the current sensing path, so as to select the path that is most affected by the defect, k=1,2,…,N; Step 42: Effective sensing path identification based on windowed scattering signal energy (WSE); Defect energy calculation uses the defect signal DS and the healthy signal HS1 to calculate the scattered signal. Based on the sensing path grouping results, the scattered signal SS1 is divided into N signal sets {SS11}, {SS12}, ..., {SS1...} according to the path direction. N The above N signal sets correspond to N path groups; then, the envelope of the scattered signal SS1 is obtained through Hilbert transform, and its expression is: ； in, Indicates signal Hilbert transform; The symbol for Hilbert transform is represented; PV represents Cauchy principal value integral. The original signal Its Hilbert transform is the real part. As the imaginary part, it constitutes a complex signal. ,Will Called The analytic signal is expressed as follows: ； Analyzing signals The modulus is the original signal envelope Its expression is: After obtaining the envelope of the scattered signal SS1, the envelope is integrated, and an integration time window is selected. In order to avoid the influence of the spiral wave, the integration start time is the arrival time of the first direct wave of the healthy signal, and the end time is the arrival time of the spiral wave. , The time window is ; Where a is the axial distance between the pipe excitation sensor array and the receiving sensor array, b is the spacing between the sensors, d1 is the distance of the straight path Am-Rm+2, and d2 is the distance of the spiral path Am-Rm+2. -1 The distance, v is the velocity of the waveform; Since the path directions and distances differ, time windows are selected for each of the N path groups of the health signal HS1, and these are applied to the N path groups corresponding to the scattered signal SS1 for integration. The energy En of each path is calculated through integration, and its expression is as follows: ； Based on the threshold calculation of the health signals, signals S12, S13, and S23 are obtained by subtracting each pair of the three sets of health signals HS1, HS2, and HS3. Then, the envelopes of the subtracted signals S12, S13, and S23 are calculated respectively. Then, the envelopes are integrated according to the steps in the above defect energy calculation to obtain three sets of reference energies E1, E2, and E3 containing the signals of each path. The mean energy Eh is obtained by averaging all the reference energies. Calculate the second threshold based on the mean energy Eh. Its expression is: ； Compare all path energy En values ​​with the second threshold Comparison, when En k > If the path is significantly affected by the defect, then the required path is selected, k=1, 2, ..., N; Step 43: Obtain the set of valid sensor paths; The effective sensing path selected based on the signal difference coefficient (SDC) is fused with the effective sensing path selected based on the windowed scattering signal energy (WES) to obtain the final optimized overall selection path.

2. The method according to claim 1, characterized in that, Step 1 includes: An ultrasonic guided wave structural defect detection system was built using a ring piezoelectric sensor array, an ultrasonic guided wave detector, a host computer, and the pipe structure under test. a. The ring piezoelectric sensing array consists of 2N piezoelectric sensors: N piezoelectric sensors are used to excite ultrasonic guided wave signals, and these N piezoelectric sensors are defined as excitation sensors, labeled A1, A2, ..., AN respectively; the other N piezoelectric sensors are used to receive ultrasonic guided wave signals, and these N piezoelectric sensors are defined as receiving sensors, labeled R1, R2, ..., RN respectively. Excitation sensors A1, A2, ..., AN are attached at equal intervals to the outer surface of the pipe structure along the circumference. That is, if the outer radius of the pipe structure is r, the arc length between excitation sensors Ai1 and Ai1+1 is 2πr / N, i1=1,2,...,N-1; and the plane formed by A1, A2, ..., AN is perpendicular to the central axis of the pipe structure. The sensor array formed by excitation sensors A1, A2, ..., AN is called the excitation sensor array. Receiving sensors R1, R2, ..., RN are attached at equal intervals around the circumference of the pipe structure on the outer surface of the pipe. That is, if the outer radius of the pipe structure is r, the arc length between receiving sensors Ri1 and Ri1+1 is 2πr / N, i1=1,2,...,N-1; and the plane formed by R1, R2, ..., RN is perpendicular to the central axis of the pipe structure. The sensing array formed by receiving sensors R1, R2, ..., RN is called the receiving sensor array. The line connecting the excitation sensor Ai' and the corresponding numbered receiving sensor Ri' is parallel to the central axis of the pipe structure. The axial distance between the excitation sensor array and the receiving sensor array is d, and i' = 1, 2, ..., N. b. One end of the ultrasonic guided wave detector is connected to the piezoelectric sensor, and the other end is connected to the host computer to transmit the guided wave signals for excitation and acquisition. c. The host computer is used for setting excitation signal parameters and displaying and storing acquired signals; d. The pipe structure to be tested is a circular tube made of steel or aluminum alloy.

3. The method according to claim 2, characterized in that, Step 2 includes: The signal used is the direct signal segment collected by the receiving sensor. When expanding the structure, only half of the unfolded plane needs to be expanded on each side. Assuming there are an even number of sensors on one side, when there are 8 sensors on one side, the original plane of the pipe development structure, the 0th order plane, is denoted as Ω0; the 1st order plane extending to the left is denoted as Ω-1, and the 1st order plane extending to the right is denoted as Ω1; depending on the direction, there are a total of 9 sensor path groups. For a path of this type, the left-handed and right-handed wave paths in the pipe have the same length. Only one direction is considered, meaning there are a total of 8 sensor path groups. Similarly, assuming an odd number of sensors on one side, when there are 7 sensors on one side, there are a total of 7 sensor path groups. Based on the different propagation directions of the paths, all sensing paths are divided into N groups, namely path group 1, path group 2, ..., path group N; different path groups represent different propagation directions, namely direction 1, direction 2, ..., direction N; using Let represent the number of sensor paths within the k-th group. This represents the number of all sensing paths within the sensor array.

4. The method according to claim 3, characterized in that, Step 3 includes: Step 31: Health signal acquisition and grouping; Under the condition of a healthy pipeline structure, three sets of guided wave signals, denoted as health signals HS1, HS2, and HS3, are collected using an ultrasonic guided wave detector. Based on the sensor path grouping results, HS1, HS2, and HS3 are further divided into N signal sets, namely {HS11}, {HS12}, ..., {HS1...}. N };{HS21},{HS22},…,{HS2 N }; {HS31}, {HS32},…, {HS3 N }; N signal sets correspond to N path groups; if the number of sampling points is used express, Let represent the number of sensing paths within the k-th group. Then, the dimension of each signal matrix in the k-th signal set is... ; Step 32: Defect signal acquisition and grouping; Under the condition of defects in the pipeline structure under test, guided wave signals in the structure are collected using an ultrasonic guided wave detector, denoted as the original defect signal DS. Based on the sensor path grouping results, the defect signal DS is divided into N signal sets, namely {DS1}, {DS2}, ..., {DS... N The above N signal sets correspond to N path groups; signal set {DS} k The number of signals and data dimensions in} are related to the signal set {HS1}. k }、{HS2 k }、{HS3 k The number of signals and the data dimension are the same, k=1,2,…,N.

5. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the guided wave signal path optimization selection method based on signal difference coefficient and energy as described in any one of claims 1 to 4.

6. An electronic device, characterized in that, include: One or more processors; Memory; And one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs including instructions that, when executed by the device, cause the device to perform the guided wave signal path optimization selection method based on signal difference coefficient and energy as described in any one of claims 1 to 4.

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