Ultrasonic signal space-time adaptive cross correlation measurement method for rough wall surface component

Abstract

The invention belongs to the field of ultrasonic detection, and particularly relates to a rough wall surface component ultrasonic signal space-time adaptive cross correlation measurement method, which comprises the following steps of: building an experiment system, and placing a rough wall surface pipeline, ultrasonic sensor equipment and a PC server for implementing a space-time adaptive cross correlation calculation method at a fixed detection position; the ultrasonic sensor equipment generates ultrasonic waves, and the ultrasonic waves are transmitted into the rough wall surface structure through the coupling agent and are reflected and transmitted back to the ultrasonic sensor when encountering an interface; an ultrasonic signal collected by the ultrasonic sensor device is transmitted to a PC server side for calculation, and an accurate pipeline wall thickness value is obtained. According to the invention, accurate calculation of the ultrasonic propagation time is realized through space-time adaptive cross correlation calculation, so that the change of the thickness of the rough wall surface is detected, the problem that the wall thickness cannot be detected due to echo waveform distortion caused by the fact that an ultrasonic sensor approaches the rough surface during movement in the traditional ultrasonic method is solved, and high-precision measurement of the wall thickness of the rough wall surface is realized.

Description

Technical Field

[0001] The present application belongs to the field of ultrasonic detection, and in particular to a method for measuring the time-space adaptive cross-correlation of ultrasonic signals of rough wall components. Background Art

[0002] Ultrasonic testing is the most commonly used non-destructive testing technology for wall thickness. The detection principle is to use an ultrasonic probe to generate and receive ultrasonic waves, and calculate the wall thickness of the pipeline by the time and speed of ultrasonic propagation in the pipeline. There are two main types. The first is to move the handheld ultrasonic probe on the surface of the pipeline to detect the wall thickness values ​​at different positions of the pipeline. The other is to fix the ultrasonic probe on the surface of a certain position of the pipeline to detect the change in the wall thickness of the pipeline at that position. It is a common method for pipeline wall thickness detection and corrosion monitoring. The most critical thing in the detection process is to calculate the propagation time of the ultrasound in the pipeline through the ultrasonic signal received by the probe. However, as the handheld ultrasonic probe gradually approaches the rough wall surface during the movement of the pipeline surface, or the wall surface where the fixed ultrasonic probe is installed changes over time due to corrosion and scouring, the ultrasonic signal scatters when it encounters a rough wall surface or corrosion defect, resulting in the inability of conventional methods to accurately obtain the propagation time of ultrasound in the pipeline, causing errors in wall thickness measurement and corrosion monitoring.

[0003] In previous studies, it is usually to find a peak of the ultrasonic wave and use the difference between the two peaks of the signal to calculate the ultrasonic propagation time. However, due to ultrasonic attenuation and distortion, there is a large error in the judgment of the wave peak. In response to the above problems, some scholars have proposed an autocorrelation algorithm, for example (doctoral dissertation: Research on key technologies for ultrasonic online monitoring of polymer blending state; Journal: Application of correlation matching in ultrasonic thickness measurement signal feature extraction), first set the ultrasonic signal standard wave, determine its length and shape, and continuously select the same length in the subsequent ultrasonic signal and calculate the correlation coefficient with the standard wave. When the correlation reaches a certain accuracy requirement, this signal is considered to be the next echo signal of the ultrasonic wave. The ultrasonic propagation time is obtained by dividing the time difference between the two signal segments by the number of returned ultrasonic waves. This method can greatly improve the accuracy of ultrasonic thickness measurement.

[0004] However, the above conventional adaptive algorithms have the problem of reduced accuracy or even failure to detect rough wall pipes. For example, when a handheld thickness measuring device is moving to measure the thickness of a pipe, if the thickness measuring device is close to the rough part of the pipe, the ultrasonic signal will be scattered, resulting in serious waveform distortion. The autocorrelation calculation of the first echo signal obtained with the initial manually selected position may fail to find an ultrasonic signal that meets the similarity coefficient condition, or find an erroneous secondary echo for wall thickness calculation, resulting in reduced wall thickness detection accuracy for rough walls. Similarly, for fixed ultrasonic wall thickness equipment monitoring, during long-term monitoring, the ultrasonic signal is more distorted after the wall thickness corrodes. The correlation algorithm of the first echo signal obtained with the initial manually selected position cannot accurately find the ultrasonic echo position or the secondary echo is found incorrectly, resulting in errors in the wall thickness monitoring results. Summary of the invention

[0005] In order to solve the problem in the prior art that the thickness measurement cannot correctly judge the second echo signal in time or space when a rough wall appears near the ultrasonic sensor, thereby causing an error in the calculation of the ultrasonic propagation time and resulting in an error in the wall thickness measurement, the present application proposes a time-space adaptive cross-correlation measurement method for ultrasonic signals of rough wall components that improves the calculation accuracy of the ultrasonic propagation time and realizes high-precision ultrasonic thickness measurement of rough walls with large gradients.

[0006] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is as follows: A temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of a rough wall component comprises the following steps: Step S1, building an experimental system, placing a rough wall pipe, an ultrasonic sensor device, and a PC server implementing a spatiotemporal adaptive cross-correlation calculation method at a fixed detection position; Step S2: The ultrasonic sensor device generates ultrasonic waves, which are transmitted to the interior of the rough wall structure through the coupling agent, and are reflected and transmitted back to the ultrasonic sensor when encountering an interface; Step S3: The ultrasonic signal collected by the ultrasonic sensor device is transmitted to the PC server for time-space adaptive cross-correlation calculation to obtain an accurate value of the pipe wall thickness.

[0007] Furthermore, step S1 specifically includes: Step S11, the ultrasonic sensor device is kept in contact with the pipeline, and the PC server is connected to the ultrasonic sensor through wireless communication to prepare for the experiment; The specific steps of step S2 include: Step S21, coupling between the ultrasonic sensor and the pipeline, the coupled ultrasonic echo signal has a large amplitude, is clear, and is symmetrical, and the echo delay and waveform are stable; Step S22, the ultrasonic sensor is connected to the PC server via wireless communication. The ultrasonic sensor wirelessly transmits the collected data to the LoRa gateway through the integrated LoRa module, and the LoRa gateway then sends the data to the PC server via the IP protocol.

[0008] The specific steps of spatiotemporal adaptive cross-correlation calculation in step S3 include: Step S31, preparation stage: processing ultrasonic data by cubic spline interpolation method, setting correlation coefficient threshold, and manually selecting the first echo signal position to provide a matching template for subsequent waveform matching and wall thickness calculation; Specifically, step S31 includes the following steps: Step S311: Select the cubic spline interpolation method to perform interpolation operation, and construct a cubic polynomial S for each pair of adjacent data points by means of piecewise cubic polynomials. i (x), whose general formula is: where a i 、b i 、c i and d i are the unknown coefficients, which are determined by the following constraints: each piecewise polynomial satisfies the interpolation points at both ends of the interval, that is, S i (x i )=y i and S i (x i +1)=y i+1 ; At each connection point x i The adjacent piecewise function S on i (x) and S i+1 The first and second order derivatives of (x) are continuous, that is, S ’ i (x i+1 )=S ’ i+1 (x i+1 ) and S ” i (x i+1 )=S ” i+1 (x i+1 ); at the same time, natural boundaries or fixed boundaries are used at the interval boundaries to determine the derivative values ​​of the first and last segments; The final piecewise function S of the cubic spline interpolation i (x) is expressed as: Among them, M i and M i+1 is the second-order derivative, h i =xi+1 -x i .

[0009] Furthermore, in each interval [x i ,x i+1 ], divide it into smaller equal intervals according to the required interpolation density, insert k points between every two original data points, that is, divide it into k+1 equal intervals, and then use S i (x) Calculate the y value of the interpolated point.

[0010] Step S312: Determine the threshold of the correlation coefficient. The threshold of the correlation coefficient includes the maximum threshold of the correlation coefficient and the minimum threshold of the correlation coefficient, which are represented by variables max_threshold and min_threshold, respectively. The max_threshold is set to 0.95, and the min_threshold is set to 0.75.

[0011] Step S313, select the first echo position of the pipe wall ultrasonic signal, select the waveform at the position as a template to match the subsequent waveform signal and then calculate the wall thickness. The first echo, the range only includes the echo signal.

[0012] Step S32, defining the correlation coefficient threshold and traversal range, and explaining the change rule of the current correlation coefficient threshold; Specifically: define variables i, N and correlation_threshold; where i represents the serial number of the first data point of the waveform segment that will be matched to calculate the correlation coefficient, and I represents the serial number of the first data point of the manually selected first echo signal segment, then i=I at the initial time; N represents the number of data points of the manually selected first echo signal segment, and M represents the serial number of the last data point of the entire interpolated waveform, then Z=MN, Z represents the end point of the manually selected first echo signal segment as the template waveform for backward traversal to calculate the correlation coefficient value; correlation_threshold is the current correlation coefficient threshold, and the value of correlation_threshold is initially equal to the value of the maximum threshold max_threshold. If the template waveform does not find a second echo with a correlation coefficient value greater than or equal to the current correlation coefficient threshold, i.e., correlation_threshold, during this backward traversal, the value of correlation_threshold will gradually decrease, and the traversal will be performed again until the value of correlation_threshold is equal to the value of the minimum threshold min_threshold.

[0013] Step S33, by gradually increasing the matching starting point i and calculating the correlation coefficient between the template waveform and the target waveform, find the second echo that meets the threshold value for subsequent wall thickness calculation; if the secondary echo with a correlation coefficient value greater than the current correlation coefficient threshold value is not found, then decrease the current correlation coefficient threshold value and traverse again; Specifically, the first data point sequence number of the target waveform segment that matches the manually selected first echo signal segment is traversed backwards as the template waveform to calculate the correlation coefficient value; the value range of i is (I, Z], and it is determined whether the value of i is greater than Z. If not, the correlation coefficient value of the template waveform and the target waveform is calculated; x(n) is used to represent the first manually selected echo signal, the first echo signal is the template signal, y represents the original ultrasound signal, and y is used to represent the first echo signal. i (n) represents the target signal segment with which the template signal will traverse the target signal segment with which the correlation coefficient value is to be calculated. The calculation formula of the correlation coefficient value is as follows: where y i (n)=y(i+n), i≤n≤N+i-1, n represents the index of the ultrasonic signal segment sample point, is the average value of the signal segment x(n), is the signal segment y i The average value of (n), y i (n) The new signal generated as the value of i changes during the traversal process of searching for the secondary echo is a signal consisting of N consecutive points selected from the original signal y; If the value of a certain r(i) is greater than or equal to the current correlation_threshold value, all data points between the current i-th data point and the i+N-th data point are taken as the second echo found and directly enter the wall thickness value calculation stage; if the value of i is greater than the Z value in the process of continuously adding one, it means that no secondary echo with a correlation coefficient value greater than or equal to the current correlation coefficient threshold correlation_threshold is obtained, then the value of correlation_threshold is decremented by 0.01, and then the value of i is reset to I, and the above-mentioned traversal and correlation coefficient calculation process is performed again. If the secondary echo is still not found under the current correlation_threshold value, the value of correlation_threshold is decremented by 0.01 again until the value of correlation_threshold is less than the minimum threshold min_threshold; if the value of correlation_threshold is less than min_threshold and the second echo is still not found, it means that there is a problem with the waveform itself or the first waveform selection is incorrect, and it is necessary to return to the preparation stage for readjustment and retest.

[0014] Furthermore, the adjustment includes two types of situations. The first type is that if the second echo cannot be found due to an error in selecting the first waveform, it is necessary to return to the preparation stage and reselect the first waveform position; if the ultrasonic waveform effect is poor, the min_threshold value is lowered in the preparation stage. If the min_threshold is less than 0.5 and the second echo still cannot be found, it means that there is a problem with the ultrasonic sensor equipment and needs to be checked; the second type is that the wall thickness values ​​measured in the past are normal, and the second echo cannot be found in a subsequent measurement, which means that serious corrosion defects have occurred near the ultrasonic probe, causing the ultrasonic waveform to be distorted. The first echo obtained at the originally manually selected position is no longer suitable as a template, and time-space adaptive cross-correlation calculation is required.

[0015] Step S34, after finding the second echo, calculate the wall thickness value according to the time difference between the second echo and the template waveform, the sampling frequency, and the interpolation multiple, and compare the calculated result with the reference value to verify its rationality and save it; Specifically, if the value of r(i) is greater than or equal to the current correlation coefficient threshold correlation_threshold, the wall thickness value is calculated; The Num variable is used to represent the difference between the first data point index of the second echo found and the first data point index of the first echo manually selected. The variables B and V are used to represent the sampling frequency and the interpolation multiple of the cubic spline interpolation method respectively. The unit of the material sound velocity v is m / s. Then the formula for calculating the wall thickness is: ; If the calculated wall thickness value differs from the wall thickness reference value or the previously calculated wall thickness universal value within the range of ±10%, the wall thickness value calculated in this test and the secondary echo data point information found will be stored; the wall thickness reference value is the wall thickness marked when the pipeline is produced and shipped; the calculated wall thickness universal value is the wall thickness value calculated using the ordinary correlation coefficient algorithm when there is no severe corrosion and roughness around the ultrasonic probe.

[0016] Step S35: If the calculated wall thickness value is abnormal, since the signal is affected by defects, it is necessary to adjust the template waveform for time-space adaptive cross-correlation measurement algorithm for calculation; Specifically, if the calculated wall thickness value differs from the wall thickness reference value or the previously calculated wall thickness universal value by more than ±10%, it means that the wall thickness value result is abnormal, and the first echo obtained at the manually selected position is no longer suitable as a template.

[0017] Step S36, use the secondary echo found in the process of wall thickness calculation at the last farther distance or last time within the normal range of the wall thickness calculation result as a new waveform matching template to replace the first echo obtained by manually selecting the position when the initial overall waveform is less affected by corrosion defects; the normal range means that the calculated wall thickness value differs from the wall thickness reference value or the common wall thickness value calculated previously within ±10%.

[0018] Compared with the prior art, the advantages of the present invention are: 1. The present invention can realize ultrasonic detection of wall thickness of rough wall pipes and improve the measurement accuracy of wall thickness. The ultrasonic propagation time can be accurately calculated through the time-space adaptive cross-correlation algorithm, so as to detect the change of the thickness of the rough wall. The problem that the traditional ultrasonic cannot detect the wall thickness due to the distortion of the echo waveform when the ultrasonic sensor moves close to the rough surface is overcome, and the high-precision measurement of the wall thickness of the rough wall is realized.

[0019] 2. The present invention can monitor the wall thickness of a wall pipe that corrodes over time. When the pipeline forms an uneven surface due to corrosion, the echo waveform can be accurately found through the time-space adaptive cross-correlation algorithm to achieve accurate monitoring of the wall thickness change.

[0020] 3. When the method of the present invention is used to measure the wall thickness of a rough wall, the wall thickness of a rough wall with a large gradient can be measured. The calculation is simple and fast, and the data can be processed in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of the spatiotemporal adaptive cross-correlation calculation method of this application.

[0022] Figure 2 This is a schematic diagram of the electromagnetic ultrasonic sensor being attached to a defective pipe and continuously performing ultrasonic thickness measurement in Example 3.

[0023] Figure 3 This is a schematic diagram of the positions of the first echo manually selected when the sensor probe is 12 mm away from the defect center in Example 3 and the second echo found by the algorithm.

[0024] Figure 4 This is a schematic diagram showing a large deviation in the wall thickness value directly calculated at a distance of 4.7 mm in Example 3.

[0025] Figure 5 This is a diagram showing the effect of waveform processing at 4.8 mm in Example 3.

[0026] Figure 6 This is the secondary echo waveform found by the algorithm at 4.8 mm in Example 3.

[0027] Figure 7 This is a waveform effect diagram of the second waveform found by the algorithm at 4.8 mm in Example 3, which is used as a template to match the data at 4.7 mm away from the defect center.

[0028] Figure 8 This is a schematic diagram showing that the wall thickness calculated by directly using the ordinary correlation algorithm to calculate the waveform at a distance of 3.9 mm from the defect center in Example 3 is 35.343 mm.

[0029] Fig. 9 This is a schematic diagram of the waveform at 3.9 mm from the defect center in Example 3 using the cross-correlation wall thickness calculation value of 22.176 mm.

[0030] Fig.10 This is a schematic diagram showing that the wall thickness calculated by directly using the ordinary correlation algorithm for the waveform at a distance of 2.9 mm from the defect center in Example 3 is 22.6226 mm.

[0031] Fig.11 This is a schematic diagram showing that the cross-correlation wall thickness calculation value of the waveform at 2.9 mm from the defect center in Example 3 is 22.068 mm.

[0032] Fig.12This is a schematic diagram showing that the wall thickness calculated by directly using the ordinary correlation algorithm for the waveform at a distance of 2.4 mm from the defect center in Example 3 is 12.5664 mm.

[0033] Fig.13 This is a schematic diagram showing that the cross-correlation wall thickness calculation value of the waveform at 2.4 mm from the defect center in Example 3 is 22.053 mm.

[0034] Fig.14 This is a schematic diagram showing that the wall thickness calculated by directly using the ordinary correlation algorithm for the waveform at a distance of 1.9 mm from the defect center in Example 3 is 34.0186 mm.

[0035] Fig.15 This is a schematic diagram showing that the cross-correlation wall thickness calculation value of the waveform at 1.9 mm from the defect center in Example 3 is 22.068 mm. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0037] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0038] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0039] In the description of the present application, it should be noted that the terms "upper", "vertical", "inner", "outer", etc. indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the product of the application is usually placed when in use, or the orientation or position relationship commonly understood by those skilled in the art. They are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0040] In the description of this application, it should also be noted that, unless otherwise clearly specified and limited, the terms "set", "install", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0041] Example 1 A temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of a rough wall component comprises the following steps: Step S1, building an experimental system, placing a rough wall pipe, an ultrasonic sensor device, and a PC server implementing a spatiotemporal adaptive cross-correlation calculation method at a fixed detection position; In step S1, the experimental system includes: a pipeline with a rough wall or defects, an ultrasonic sensor device and a PC server. The ultrasonic sensor device is kept in contact with the pipeline, and the PC server is connected to the ultrasonic sensor through wireless communication to prepare for the experiment.

[0042] Step S2: The ultrasonic sensor device generates ultrasonic waves, which are transmitted to the interior of the rough wall structure through the coupling agent, and are reflected and transmitted back to the ultrasonic sensor when encountering an interface; Step S21: The ultrasonic sensor and the pipeline should be well coupled. The coupled ultrasonic echo signal has a large amplitude, is clear, and is symmetrical, and the echo delay and waveform are stable, which is conducive to more accurate measurement and defect detection and ensures effective detection data collection. Step S22, the ultrasonic sensor is connected to the PC server via wireless communication to ensure the stability of the data transmission process. The ultrasonic sensor integrates the LoRa module to wirelessly transmit the collected data to the LoRa gateway, and the LoRa gateway then sends the data to the PC server via the IP protocol for processing and analysis.

[0043] Step S3: The ultrasonic signal collected by the ultrasonic sensor device is transmitted to the PC server for time-space adaptive cross-correlation calculation to obtain an accurate value of the pipe wall thickness.

[0044] Step S3 is mainly completed by the program deployed on the server. The specific steps of spatiotemporal adaptive cross-correlation calculation include: Step S31, preparation stage: ultrasonic data is processed by cubic spline interpolation method to ensure data smoothness and continuity, and correlation coefficient thresholds (max_threshold and min_threshold) are set, and the first echo signal position is manually selected to provide a matching template for subsequent waveform matching and wall thickness calculation; Step S32, defining the correlation coefficient threshold and traversal range, and explaining the change rule of the current correlation coefficient threshold; Step S33, by gradually increasing the matching starting point i and calculating the correlation coefficient between the template waveform and the target waveform, find the second echo that meets the threshold value for subsequent wall thickness calculation; if the secondary echo with a correlation coefficient value greater than the current correlation coefficient threshold value is not found, then decrease the current correlation coefficient threshold value and traverse again; Step S34, after successfully finding the second echo, calculate the wall thickness value according to the time difference between the second echo and the template waveform, the sampling frequency, the interpolation multiple, etc., and compare the calculated result with the reference value to verify its rationality and save it; Step S35: If the calculated wall thickness value is abnormal, it is very likely that the signal is affected by defects, and it is necessary to adjust the template waveform by using a spatiotemporal adaptive cross-correlation measurement algorithm for calculation; Step S36, for this situation, the present invention proposes a spatiotemporal adaptive cross-correlation measurement algorithm. That is, if the corrosion and roughness of the pipe wall near the ultrasonic sensor gradually affect the overall waveform of the ultrasonic signal due to changes in space or time, and the first echo obtained at the manually selected position when the initial overall waveform is less affected by the corrosion defect is no longer suitable as a template for traversal detection of the secondary echo, then the secondary echo found in the process of wall thickness calculation at the last farther distance or last time within the normal range of the wall thickness value calculation result is used as a new waveform matching template to replace the first echo obtained at the manually selected position when the initial overall waveform is less affected by the corrosion defect; the normal range means that the calculated wall thickness value is within ±10% of the wall thickness reference value or the wall thickness universal value calculated previously.

[0045] Example 2 A temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of a rough wall component comprises the following steps: Step S1, building an experimental system, placing a rough wall pipe, an ultrasonic sensor device, and a PC server implementing a spatiotemporal adaptive cross-correlation calculation method at a fixed detection position; Step S2: The ultrasonic sensor device generates ultrasonic waves, which are transmitted to the interior of the rough wall structure through the coupling agent, and are reflected and transmitted back to the ultrasonic sensor when encountering an interface; Step S3: The ultrasonic signal collected by the ultrasonic sensor device is transmitted to the PC server for time-space adaptive cross-correlation calculation to obtain an accurate value of the pipe wall thickness.

[0046] Furthermore, step S1 specifically includes: Step S11: The experimental system in step S1 includes: a pipe with a rough wall or defects, an ultrasonic sensor device and a PC server. The ultrasonic sensor device is kept in contact with the pipe, and the PC server is connected to the ultrasonic sensor via wireless communication to prepare for the experiment; The specific steps of step S2 include: Step S21: The ultrasonic sensor and the pipeline should be well coupled. The coupled ultrasonic echo signal has a large amplitude, is clear, and is symmetrical, and the echo delay and waveform are stable, which is conducive to more accurate measurement and defect detection and ensures effective detection data collection. Step S22, the ultrasonic sensor is connected to the PC server via wireless communication to ensure the stability of the data transmission process. The ultrasonic sensor integrates the LoRa module to wirelessly transmit the collected data to the LoRa gateway, and the LoRa gateway then sends the data to the PC server via the IP protocol for processing and analysis.

[0047] Step S3 is mainly completed by the program deployed on the server. The specific steps of spatiotemporal adaptive cross-correlation calculation include: Step S31, preparation stage: ultrasonic data is processed by cubic spline interpolation method to ensure data smoothness and continuity, and correlation coefficient thresholds (max_threshold and min_threshold) are set, and the first echo signal position is manually selected to provide a matching template for subsequent waveform matching and wall thickness calculation; Specifically, step S31 includes the following steps: Step S311: First, since the original pipe wall ultrasonic echo data points are relatively sparse, direct calculation will lead to large errors. In this embodiment of the present invention, a cubic spline interpolation method is selected for interpolation operation. A cubic polynomial S is constructed for each pair of adjacent data points by means of piecewise cubic polynomials. i (x), whose general formula is: ; where a i 、b i 、c i and d i are the unknown coefficients, which are determined by the following constraints: each piecewise polynomial satisfies the interpolation points at both ends of the interval, that is, S i (x i )=y i and S i (x i +1)=y i+1 ; At each connection point x i The adjacent piecewise function S on i (x) and S i+1 The first and second order derivatives of (x) are continuous, that is, S ’i (x i+1 )=S ’ i+1 (x i+1 ) and S ” i (x i+1 )=S ” i+1 (x i+1 ); At the same time, natural boundaries (i.e., the second-order derivative is zero) or fixed boundaries (the first-order derivative is a specified value) are used at the interval boundaries to determine the derivative values ​​of the first and last segments; The final piecewise function S of the cubic spline interpolation i (x) is expressed as: ; Among them, M i and M i+1 is the second-order derivative, h i =x i+1 -x i Cubic spline interpolation can ensure the continuity of the interpolation result and the continuity of the first-order and second-order derivatives, avoid unnecessary oscillations, and provide better smoothness when processing data with more complex shapes.

[0048] Furthermore, in order to meet the requirements of different resolutions and the computing power conditions of different platforms, the algorithm can flexibly adjust the number of interpolation points in each interval. i ,x i+1 ], divide it into smaller equal intervals according to the required interpolation density, such as inserting k points between every two original data points, that is, dividing it into k+1 equal intervals, and then using S on each point i (x) Calculate the y value of the interpolation point; Since the original ultrasonic waveform itself has a certain degree of continuity, cubic spline interpolation reduces the risk of overfitting by using piecewise low-order polynomials to fit the data compared to high-order polynomial interpolation, and can more truly reflect the trend of the data.

[0049] Step S312, then it is necessary to determine the threshold of the correlation coefficient, and the threshold of the correlation coefficient includes the maximum threshold of the correlation coefficient and the minimum threshold of the correlation coefficient. The function of the threshold of the correlation coefficient itself is to ensure that the matched target waveform has sufficient similarity with the template waveform, thereby improving the reliability of the match. By setting the maximum threshold of the correlation coefficient and the minimum threshold of the correlation coefficient, the algorithm is allowed to dynamically adjust the matching requirements according to the actual situation of the signal quality, while ensuring accuracy and enhancing robustness. In order to facilitate subsequent descriptions, they are represented by variables max_threshold and min_threshold respectively; these two values ​​need to be determined according to the specific working conditions of ultrasonic wall thickness detection. In general, when the ambient temperature is not extreme and the equipment processes the ultrasonic signal well, the variables max_threshold and min_threshold can be set higher. When the environment in which the pipeline is located is relatively harsh and the ultrasonic signal quality is poor, the variables max_threshold and min_threshold can be appropriately lowered. In general, max_threshold is set to 0.95 and min_threshold is set to 0.75.

[0050] Step S313: The waveform visualization tool can be used in the ultrasonic thickness measurement data processing software program on the PC to manually select the first echo position of the pipe wall ultrasonic signal. Since the waveform at the selected position will be used as a template to match subsequent waveform signals and then calculate the wall thickness, it is necessary to select a clean waveform that is not mixed with the excitation signal as the first echo, and the range needs to include only the echo signal, otherwise it is easy to include irrelevant waveforms and affect the subsequent matching effect.

[0051] Step S32, defining the correlation coefficient threshold and traversal range, and explaining the change rule of the current correlation coefficient threshold; Specifically: define variables i, N and correlation_threshold; where i represents the serial number of the first data point of the waveform segment that will be matched to calculate the correlation coefficient, and I represents the serial number of the first data point of the manually selected first echo signal segment, then i=I at the initial time; N represents the number of data points of the manually selected first echo signal segment, and M represents the serial number of the last data point of the entire interpolated waveform, then Z=MN, Z represents the end point of the manually selected first echo signal segment as the template waveform for backward traversal to calculate the correlation coefficient value; correlation_threshold is the current correlation coefficient threshold, and the value of correlation_threshold is initially equal to the value of the maximum threshold max_threshold. If the template waveform does not find a second echo with a correlation coefficient value greater than or equal to the current correlation coefficient threshold, i.e., correlation_threshold, during this backward traversal, the value of correlation_threshold will gradually decrease, and the traversal will be performed again until the value of correlation_threshold is equal to the value of the minimum threshold min_threshold.

[0052] S33, by gradually increasing the matching starting point i and calculating the correlation coefficient between the template waveform and the target waveform, find the second echo that meets the threshold value for subsequent wall thickness calculation; if the secondary echo with a correlation coefficient value greater than the current correlation coefficient threshold value is not found, then decrease the current correlation coefficient threshold value and traverse again; Specifically: perform a self-increment operation on i to simulate the first echo signal segment manually selected as the template waveform to traverse backward to calculate the first data point sequence number of the matching target waveform segment with the correlation coefficient value; for example, if the range of the manually selected first echo signal segment is from the 3000th data point to the 5000th data point, then the first waveform segment to be used as the template waveform data point to calculate the correlation coefficient is the data segment composed of the 3001th data point to the 5001th data point, and the second is the data segment composed of the 3002th data point to the 5002th data point, and so on. It can be seen that the value range of i is (I, Z], and it is determined whether the value of i is greater than Z. If not, the correlation coefficient value of the template waveform and the target waveform is calculated; x(n) is used to represent the manually selected first echo signal, the first echo signal is the template signal, y represents the original ultrasonic signal, and y is used. i (n) represents the target signal segment with which the template signal will traverse the target signal segment with which the correlation coefficient value is to be calculated. The calculation formula of the correlation coefficient value is as follows: ; where y i(n)=y(i+n), i≤n≤N+i-1, n represents the index of the ultrasonic signal segment sample point, is the average value of the signal segment x(n), is the signal segment y i The average value of (n), y i (n) The new signal generated as the value of i changes during the traversal process of searching for the secondary echo is a signal consisting of N consecutive points selected from the original signal y; If the value of a certain r(i) is greater than or equal to the current correlation_threshold value, all data points between the current i-th data point and the i+N-th data point are taken as the second echo found to directly enter the wall thickness value calculation stage; the reason why the waveform corresponding to the i-th value with the largest correlation coefficient result is not used as the second echo is because the waveform corresponding to the i-th value with the largest correlation coefficient result is not necessarily the real second echo on the waveform image. In some cases, the subsequent third or fourth echo may have a correlation coefficient value calculated with the template signal segment that is slightly larger than the correlation coefficient value calculated between the real second echo and the template waveform. If the third or fourth echo signal is mistakenly used as the second echo signal to calculate the wall thickness, the wall thickness value will suddenly change to twice or even three times the original wall thickness. If the value of i is greater than the Z value during the process of continuous self-increment, it means that no secondary echo with a correlation coefficient value greater than or equal to the current correlation coefficient threshold correlation_threshold is obtained, then the value of correlation_threshold is decremented by 0.01 (the specific reduction step can be customized according to the situation), and then the value of i is reset to I, and the above-mentioned traversal and correlation coefficient calculation process is performed again. If the secondary echo is still not found under the current correlation_threshold value, the value of correlation_threshold is decremented by 0.01 again until the value of correlation_threshold is less than the minimum threshold min_threshold; if the value of correlation_threshold is less than min_threshold and the second echo is still not found, it means that there is a problem with the waveform itself or the first waveform selection is incorrect, and it is necessary to return to the preparation stage and make corresponding adjustments before retesting.

[0053] Furthermore, the adjustment includes two types of situations. The first type is when the wall thickness of a new pipe without a severely corroded rough surface is calculated by the correlation coefficient algorithm. If the second echo cannot be found due to an error in selecting the first waveform, such as the waveform is not completely selected or many irrelevant waveforms are selected, it is necessary to return to the preparation stage and re-select the first waveform position; if the ultrasonic waveform effect is poor, you can consider lowering the min_threshold value in the preparation stage to see if the secondary echo can be successfully found. If the min_threshold is less than 0.5 and the secondary echo still cannot be found, it means that there is a problem with the ultrasonic sensor equipment and needs to be checked; the second type is that the wall thickness values ​​measured in the past were all normal, and the second echo suddenly could not be found in a certain measurement thereafter, which means that a more serious corrosion defect has occurred near the ultrasonic probe, causing the ultrasonic waveform to be distorted, and the first echo obtained at the originally manually selected position is no longer suitable as a template, and it is necessary to use the spatiotemporal adaptive cross-correlation algorithm mentioned later for calculation.

[0054] Step S34, after successfully finding the second echo, calculate the wall thickness value according to the time difference between the second echo and the template waveform, the sampling frequency, the interpolation multiple, etc., and compare the calculated result with the reference value to verify its rationality and save it; Specifically, if there is a value of r(i) greater than or equal to the current correlation coefficient threshold correlation_threshold, the wall thickness value is calculated; The Num variable is used to represent the difference between the first data point index of the second echo found and the first data point index of the first echo manually selected. The variables B and V are used to represent the sampling frequency and the interpolation multiple of the cubic spline interpolation method respectively. The unit of the material sound velocity v is m / s. Then the formula for calculating the wall thickness is: If the calculated wall thickness value differs from the wall thickness reference value or the previously calculated wall thickness universal value within the range of ±10%, the wall thickness value calculated for this test and the secondary echo data point information found will be stored; the wall thickness reference value is the wall thickness marked when the pipeline is produced and shipped, and this factory-marked wall thickness is the wall thickness reference value; the calculated universal wall thickness value is the wall thickness value calculated using the ordinary correlation coefficient algorithm when there is no severe corrosion and roughness around the ultrasonic probe. These wall thickness values ​​may change with the movement of the ultrasonic probe or the passage of time, but the changes will be slow and smooth, and there will be no sudden mutations that exceed 10% or more of the original wall thickness of the pipeline.

[0055] Step S35: If the calculated wall thickness value is abnormal, it is very likely that the signal is affected by defects, and it is necessary to adjust the template waveform by using a spatiotemporal adaptive cross-correlation measurement algorithm for calculation; Specifically, if the calculated wall thickness value differs from the wall thickness reference value or the previously calculated universal wall thickness value by more than ±10%, it means that the wall thickness value result is abnormal. It is very likely that a more obvious defect has appeared near the position where the ultrasonic signal is collected in the pipeline, resulting in a scattering effect of the ultrasonic signal. The first echo obtained at the manually selected position is no longer suitable as a template; generally speaking, if the wall thickness value calculated in a certain time suddenly differs from the wall thickness reference value or the previously calculated universal wall thickness value by 10% or more, it means that the wall thickness value calculation result is incorrect, because a fixed-diameter pipe that passes the factory test will not have such a large diameter error, and even if the wall thickness changes, it will not be so drastic.

[0056] Step S36, for this situation, the present invention proposes a spatiotemporal adaptive cross-correlation measurement algorithm. That is, if the corrosion and roughness of the pipe wall near the ultrasonic sensor gradually affect the overall waveform of the ultrasonic signal due to changes in space or time, and the first echo obtained at the manually selected position when the initial overall waveform is less affected by the corrosion defect is no longer suitable as a template for traversal detection of the secondary echo, then the secondary echo found in the process of wall thickness calculation at the last farther distance or last time within the normal range of the wall thickness value calculation result is used as a new waveform matching template to replace the first echo obtained at the manually selected position when the initial overall waveform is less affected by the corrosion defect; the normal range means that the calculated wall thickness value is within ±10% of the wall thickness reference value or the wall thickness universal value calculated previously.

[0057] Example 3 like Figure 1 The figure shows the flow chart of the spatiotemporal adaptive cross-correlation calculation of the present application, taking a pipe with a 5mm radius defect as an example. Figure 2 As shown, the actual wall thickness is 22 mm. There is a hemispherical defect with a radius of 5 mm somewhere in the pipeline. The electromagnetic ultrasonic sensor is attached to the pipe wall and moves from far to near the defect and continuously performs ultrasonic thickness measurement.

[0058] Initially, the electromagnetic ultrasonic sensor is far away from the defect. The first echo obtained by manually selecting the position can be used to measure the wall thickness normally using the correlation coefficient method. The following figure shows the ultrasonic waveform when the sensor probe is 12mm away from the defect center. Figure 3 The first echo between the two dotted lines on the left is manually selected, and the second echo between the two dotted lines on the right is found by the algorithm described above. The final calculated wall thickness value is 22.037 mm, and the error is within the allowable range.

[0059] The sensor continues to move towards the defect, and the correlation coefficient algorithm described above is used to perform preliminary wall thickness calculations at different distances from the defect center in the vertical direction. The test results are shown in the following table: It can be seen that when the vertical distance from the defect center is less than 4.8mm, there is a large gap between the calculated wall thickness value and the reference value of the wall thickness and the general value of the wall thickness calculated previously. The waveform processing diagram at a distance of 4.7mm is as follows: Figure 4 As shown, it can be seen that the overall waveform at this time has been greatly distorted compared to when the sensor probe is far away from the defect center in the vertical direction. The "secondary echo" position matched by the first echo manually selected as the template is not the real secondary echo, resulting in a large gap between the calculated wall thickness value and the actual wall thickness value.

[0060] In this embodiment, when the vertical distance from the defect center is 4.8 mm, the calculated wall thickness is 22.1298 mm, which is still within the normal range. The waveform processing effect diagram is as follows: Figure 5 As shown, the saved secondary echo waveform is extracted ( Figure 6 ).

[0061] That is, the second waveform found by the program at 4.8mm from the center of the defect is used as a template to match the data at 4.7mm from the center of the defect, and the position with the largest calculated correlation coefficient value is used as the second echo position of the waveform at 4.7mm from the center of the defect. Since the Num variable represents the difference between the first data point index of the found secondary echo and the first data point index of the manually selected first echo, and the position of the manually selected first echo is fixed and unchanged, the wall thickness value can be calculated. However, as the waveform is severely deformed as it approaches the defect, the position with the largest correlation coefficient value may not be the second echo position we are looking for. Therefore, a restriction condition is added. If the wall thickness value calculated at the position with the largest correlation coefficient value differs from the previously measured wall thickness value by more than 10%, it will be discarded and the wall thickness value at the position with the second largest correlation coefficient value will be calculated, and so on. The waveform processing results are as follows: Figure 7 The output wall thickness value is 22.1452mm, which proves that the matching effect is good.

[0062] In order to further demonstrate the effectiveness of the adaptive crossover algorithm proposed in the present invention, multiple sets of different data tests were conducted.

[0063] The second waveform found by the program at a distance of 4.0mm from the defect center is matched with the waveform at a distance of 3.9mm from the defect center. The wall thickness calculated directly using the ordinary correlation algorithm is 35.343mm. The cross-correlation wall thickness calculated value is 22.176mm. The effect is compared. Figure 8 and Fig. 9, use the second waveform found at 3.0mm away from the defect center to match the waveform at 2.9mm away from the defect center. The normal calculated wall thickness value is 22.6226mm, and the current cross-correlation wall thickness calculated value is 22.068mm. The effect comparison is Fig.10 and Fig.11 shown.

[0064] Use the second waveform found at 2.5mm from the defect center to match the waveform at 2.4mm from the defect center. The normal calculated wall thickness value is 12.5664mm, and the current cross-correlation wall thickness calculated value is 22.053mm. The effect comparison is as follows: Fig.12 and Fig.13 shown.

[0065] The second waveform found at 2.0mm from the defect center is used to match the waveform at 1.9mm from the defect center. The normal calculated wall thickness value is 34.0186mm, and the current cross-correlation wall thickness calculated value is 22.068mm. The effect comparison is as follows: Fig.14 and Fig.15 shown.

Claims

1. A temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components, characterized in that: The steps include: Step S1, building an experimental system, placing a rough wall pipe, an ultrasonic sensor device, and a PC server implementing a spatiotemporal adaptive cross-correlation calculation method at a fixed detection position; Step S2: The ultrasonic sensor device generates ultrasonic waves, which are transmitted to the interior of the rough wall structure through the coupling agent, and are reflected and transmitted back to the ultrasonic sensor when encountering an interface; Step S3: The ultrasonic signal collected by the ultrasonic sensor device is transmitted to the PC server for time-space adaptive cross-correlation calculation to obtain an accurate value of the pipe wall thickness.

2. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 1, characterized in that: Step S1 specifically includes: Step S11, keep the ultrasonic sensor device in contact with the pipeline, connect the PC server and the ultrasonic sensor through wireless communication, and prepare for the experiment.

3. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 1, characterized in that: The specific steps of step S2 include: Step S21, coupling between the ultrasonic sensor and the pipeline, the coupled ultrasonic echo signal has a large amplitude, is clear, and is symmetrical, and the echo delay and waveform are stable; Step S22, the ultrasonic sensor is connected to the PC server via wireless communication. The ultrasonic sensor wirelessly transmits the collected data to the LoRa gateway through the integrated LoRa module, and the LoRa gateway then sends the data to the PC server via the IP protocol.

4. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 1, characterized in that: The specific steps of spatiotemporal adaptive cross-correlation calculation in step S3 include: Step S31, preparation stage: processing ultrasonic data by cubic spline interpolation method, setting correlation coefficient threshold, and manually selecting the first echo signal position to provide a matching template for subsequent waveform matching and wall thickness calculation; Step S32, defining the correlation coefficient threshold and traversal range, and explaining the change rule of the current correlation coefficient threshold; Step S33, by gradually increasing the matching starting point i and calculating the correlation coefficient between the template waveform and the target waveform, find the second echo that meets the threshold value for subsequent wall thickness calculation; if the secondary echo with a correlation coefficient value greater than the current correlation coefficient threshold value is not found, then decrease the current correlation coefficient threshold value and traverse again; Step S34, after finding the second echo, calculate the wall thickness value according to the time difference between the second echo and the template waveform, the sampling frequency, and the interpolation multiple, and compare the calculated result with the reference value to verify its rationality and save it; Step S35: If the calculated wall thickness value is abnormal, since the signal is affected by defects, it is necessary to adjust the template waveform for time-space adaptive cross-correlation measurement algorithm for calculation; Step S36, use the secondary echo found in the process of wall thickness calculation at the last farther distance or last time within the normal range of the wall thickness calculation result as a new waveform matching template to replace the first echo obtained by manually selecting the position when the initial overall waveform is less affected by corrosion defects; the normal range means that the calculated wall thickness value differs from the wall thickness reference value or the common wall thickness value calculated previously within ±10%.

5. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 4, characterized in that: Step S31 includes the following steps: Step S311: Select the cubic spline interpolation method to perform interpolation operation, and construct a cubic polynomial S for each pair of adjacent data points by means of piecewise cubic polynomials. i (x), whose general formula is: ； where a i , b i 、c i and d i are the unknown coefficients, which are determined by the following constraints: each piecewise polynomial satisfies the interpolation points at both ends of the interval, that is, S i (x i )=y i and S i (x i +1)=y i+1 ; At each connection point x i The adjacent piecewise function S on i (x) and S i+1 The first and second order derivatives of (x) are continuous, that is, S ’ i (x i+1 )=S ’ i+1 (x i+1 ) and S ” i (x i+1 )=S ” i+1 (x i+1 ); at the same time, natural boundaries or fixed boundaries are used at the interval boundaries to determine the derivative values ​​of the first and last segments; The final piecewise function S of the cubic spline interpolation i (x) is expressed as: ； Among them, M i and M i+1 is the second-order derivative, h i =x i+1 -x i ; Step S312, determining the threshold of the correlation coefficient, the threshold of the correlation coefficient includes the maximum threshold of the correlation coefficient and the minimum threshold of the correlation coefficient, which are represented by variables max_threshold and min_threshold respectively, the max_threshold is set to 0.95, and the min_threshold is set to 0.75; Step S313, select the first echo position of the pipe wall ultrasonic signal, select the waveform at the position as a template to match the subsequent waveform signal and then calculate the wall thickness. The first echo, the range only includes the echo signal.

6. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 5, characterized in that: In each interval [x i ,x i+1 ], divide it into smaller equal intervals according to the required interpolation density, insert k points between every two original data points, that is, divide it into k+1 equal intervals, and then use S i (x) Calculate the y value of the interpolated point.

7. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 5, characterized in that: Step S32 is specifically as follows: define variables i, N and correlation_threshold; wherein i represents the serial number of the first data point of the waveform segment to be matched and the correlation coefficient to be calculated, and I represents the serial number of the first data point of the manually selected first echo signal segment, then i=I at the initial time; N represents the number of data points of the manually selected first echo signal segment, and M represents the serial number of the last data point of the entire interpolated waveform, then Z=MN, and Z represents the end point of the manually selected first echo signal segment as the template waveform for backward traversal to calculate the correlation coefficient value; correlation_threshold is the current correlation coefficient threshold, and initially the value of correlation_threshold is equal to the value of the maximum threshold max_threshold. If the template waveform does not find a second echo with a correlation coefficient value greater than or equal to the current correlation coefficient threshold, i.e., correlation_threshold, during this backward traversal, the value of correlation_threshold will gradually decrease, and the traversal will be performed again until the value of correlation_threshold is equal to the value of the minimum threshold min_threshold.

8. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 7, characterized in that: Step S33 is specifically as follows: perform a self-add operation on i to simulate the first echo signal segment manually selected as the template waveform to traverse backward to calculate the correlation coefficient value of the first data point sequence number of the matching target waveform segment; the value range of i is (I, Z], and it is determined whether the value of i is greater than Z. If not, the correlation coefficient value of the template waveform and the target waveform is calculated; x(n) is used to represent the first echo signal manually selected, the first echo signal is the template signal, y represents the original ultrasound signal, and y is used i (n) represents the target signal segment with which the template signal will traverse the target signal segment with which the correlation coefficient value is to be calculated. The calculation formula of the correlation coefficient value is as follows: ； where y i (n)=y(i+n), i≤n≤N+i-1, n represents the index of the ultrasonic signal segment sample point, is the average value of the signal segment x(n), is the signal segment y i The average value of (n), y i (n) The new signal generated as the value of i changes during the traversal process of searching for the secondary echo is a signal consisting of N consecutive points selected from the original signal y; If the value of a certain r(i) is greater than or equal to the current correlation_threshold value, all data points between the current i-th data point and the i+N-th data point are taken as the second echo found and directly enter the wall thickness value calculation stage; If the value of i is greater than the Z value during the process of continuous self-increment, it means that no secondary echo with a correlation coefficient value greater than or equal to the current correlation coefficient threshold correlation_threshold is obtained, then the value of correlation_threshold is decremented by 0.01, and then the value of i is reset to I, and the above-mentioned process of traversing and calculating the correlation coefficient is repeated. If the secondary echo is still not found under the current value of correlation_threshold, the value of correlation_threshold is decremented by 0.01 again until the value of correlation_threshold is less than the minimum threshold min_threshold; if the value of correlation_threshold is less than min_threshold and the second echo is still not found, it means that there is a problem with the waveform itself or the first waveform selection is incorrect, and it is necessary to return to the preparation stage for readjustment and then retest.

9. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 8, characterized in that: Step S34 is specifically as follows: if there is a value of r(i) greater than or equal to the current correlation coefficient threshold correlation_threshold, then the wall thickness value is calculated; The Num variable is used to represent the difference between the first data point index of the second echo found and the first data point index of the first echo manually selected. The variables B and V are used to represent the sampling frequency and the interpolation multiple of the cubic spline interpolation method respectively. The unit of the material sound velocity v is m / s. Then the formula for calculating the wall thickness is: ； If the calculated wall thickness value differs from the wall thickness reference value or the previously calculated wall thickness universal value within the range of ±10%, the wall thickness value calculated in this test and the secondary echo data point information found will be stored; the wall thickness reference value is the wall thickness marked when the pipe is produced and shipped out of the factory; The calculated universal value of wall thickness is the wall thickness value calculated using the ordinary correlation coefficient algorithm when there is no serious corrosion roughness around the ultrasonic probe.

10. The temporal and spatial adaptive cross-correlation measurement method for ultrasonic signals of rough wall components according to claim 9, characterized in that: Step S35 is specifically as follows: if the calculated wall thickness value differs from the wall thickness reference value or the previously calculated wall thickness universal value by more than ±10%, it means that the wall thickness value result is abnormal, and the first echo obtained at the manually selected position is no longer suitable as a template.

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