Metal structure surface anticorrosion quality detection method and system for water conservancy projects

Abstract

The present invention relates to the technical field of metal material detection, and discloses a method and system for detecting the anti-corrosion quality of the surface of a metal structure used in a water conservancy project. The specific method comprises: performing actual working condition simulation processing; performing detection unit grid division on a three-dimensional model of a metal structure sample; extracting detection unit grid division data, and adaptively detecting the anti-corrosion layers of two working surfaces of the metal structure sample by an acoustic wave detection probe, while transmitting the detection feedback data to an anti-corrosion quality analysis platform; extracting the detection feedback data of the two working surfaces, and evaluating the anti-corrosion quality of the metal structure sample based on the detection feedback data. The present invention solves the problems of insufficient detection accuracy and low detection efficiency caused by the huge amount of detection data collected in the prior art when detecting the anti-corrosion quality of the surface of a metal structure used in a water conservancy project.

Description

Technical Field

[0001] The invention relates to the technical field of metal material detection, and in particular to a method and system for detecting the surface anti-corrosion quality of metal structures used in water conservancy projects. Background Art

[0002] In existing water conservancy projects, the surface anti-corrosion quality inspection methods for metal structures mainly rely on manual operation and conventional non-destructive testing technologies, such as ultrasonic and magnetic particle testing. The above-mentioned detection methods still have some limitations. First, manual operation is easily affected by human factors, and the accuracy and consistency of the test results are difficult to guarantee. Secondly, due to the huge amount of processing data in conventional non-destructive testing technology, there is still room for improvement in the detection accuracy and efficiency of conventional non-destructive testing technology. Especially under complex working conditions, it is difficult to accurately identify and locate the potential defects and corrosion points of the anti-corrosion layer. This leads to a large difference between the evaluation results of the quality of the anti-corrosion layer by the existing detection methods and the actual use conditions, making it difficult to provide reliable anti-corrosion performance guarantees.

[0003] In the existing disclosed invention technologies, such as the Chinese patent application with publication number CN115931696A, a device and method for detecting the surface corrosion quality of metal structures of water conservancy projects are disclosed. The invention includes a fixed seat, and an adjustment support mechanism is provided on the surface of the fixed seat, and the adjustment support mechanism can enable the detection device to adapt to pipes with different inner diameters. When the invention detects the metal pipes of the water conservancy project, the extrusion block can squeeze the rusted part inside the metal pipe, and the rusty debris will be squeezed and fall off, which is conducive to making the detection more accurate and avoiding the rusty debris from affecting the detection results. The sliding plate and the limit plate can keep the position of the detection plate when it moves to the groove with more serious corrosion, so that the sliding plate can record the most serious corrosion depth in the pipe, which is convenient for the detection personnel to understand the corrosion condition of the pipe and avoid the problem that the metal pipe cannot detect the corrosion condition inside the pipe, causing hidden dangers to the use of the metal pipe.

[0004] The above patent lacks optimization of the amount of collected detection data and has the problems described in the background technology. Summary of the invention

[0005] The technical problem to be solved by the present invention is to address the problems of insufficient detection accuracy and low detection efficiency caused by the huge amount of detection data collected in the existing technology when detecting the surface anti-corrosion quality of metal structures used in water conservancy projects. A method and system for detecting the surface anti-corrosion quality of metal structures used in water conservancy projects are proposed.

[0006] In order to achieve the above object, the technical solution of the method for detecting the surface anticorrosion quality of metal structures in water conservancy projects of the present invention comprises the following steps:

[0007] S1: Take the metal structure sample to be tested, and place the metal structure sample in the actual working condition simulation box to perform actual working condition simulation processing;

[0008] S2: For the metal structure sample that has completed the actual working condition simulation, a three-dimensional model is established according to the size data of the metal structure sample, and the three-dimensional model of the metal structure sample is divided into detection unit grids;

[0009] S3: Extract the detection unit grid division data, use the acoustic wave detection probe to adaptively detect the anti-corrosion layers on the two working surfaces of the metal structure sample, and transmit the detection feedback data to the anti-corrosion quality analysis platform;

[0010] S4: Extract the detection feedback data of the two working surfaces, and evaluate the anti-corrosion quality of the metal structure sample based on the detection feedback data.

[0011] Specifically, S1 includes the following specific steps:

[0012] S11: taking a metal structure sample to be tested, and placing the metal structure sample in an actual working condition simulation box to perform actual working condition simulation processing, wherein the actual working condition simulation processing includes actual working environment parameter simulation and actual working state simulation;

[0013] The actual working environment parameter simulation includes: simulating temperature parameters, humidity parameters and ultraviolet parameters in four seasons in an actual working condition simulation box;

[0014] The actual working state simulation includes: simulating the initial water level of the water conservancy project in the actual working condition simulation box, and gradually changing the water levels on both sides by controlling the water inlet and drainage systems, simulating the lifting and lowering working state of the metal structure sample under different water level differences; wherein, the setting of the initial water level includes: the cross setting of the first water level mode and the second water level mode;

[0015] The first water level mode is specifically: the water level on the left side of the metal structure sample is higher than the water level on the right side of the metal structure sample by k centimeters, wherein the left side surface of the metal structure sample after being placed in the actual working condition simulation box is the positive working surface, and the right side surface is the negative working surface;

[0016] The second water level mode is specifically: the water level on the right side of the metal structure sample is k centimeters higher than the water level on the left side of the metal structure sample;

[0017] S12: Complete 50 rounds of actual working condition simulation tests;

[0018] S13: Cleaning the metal structure samples after completing 50 rounds of actual working condition simulation tests.

[0019] Specifically, in S2, the detection unit grid division of the three-dimensional model of the metal structure sample specifically includes: according to the probe cross-sectional area of ​​the acoustic wave detection probe, the positive working surface and the reverse working surface of the metal structure sample in the three-dimensional model are evenly divided into multiple detection unit grids, wherein the unit area of ​​each detection unit grid is consistent with the probe cross-sectional area.

[0020] Specifically, in S3, the cross section of the acoustic wave detection probe is a square, and the width of each of the four sides is L. The detection array is composed of a number of acoustic wave transmitters. The probe cross section of the acoustic wave detection probe has honeycomb-shaped honeycomb holes, wherein each honeycomb hole is embedded with an acoustic wave transmitter, and the switching state of each acoustic wave transmitter is adaptively controlled by the anti-corrosion quality analysis platform.

[0021] Specifically, S3 includes the following specific steps:

[0022] S31: extracting detection unit grid division data, and establishing a two-dimensional detection unit grid coordinate system of the positive working surface, a two-dimensional detection unit grid coordinate system of the reverse working surface, and a two-dimensional probe cross-section coordinate system;

[0023] Among them, the coordinates of each detection unit grid on the positive working surface are ;

[0024] The coordinates of each detection unit grid on the reverse working surface are ;

[0025] The coordinates of each acoustic wave transmitter on the cross section of the acoustic wave detection probe are ;

[0026] S32: Adaptively detect the anti-corrosion layer on the positive working surface of the metal structure sample by using an acoustic wave detection probe;

[0027] S33: At the same time, the detection feedback data of the positive working surface is transmitted to the anti-corrosion quality analysis platform, wherein the detection feedback data includes: a set of corrosion depths of corrosion points in the anti-corrosion layer of the positive working surface of the metal structure sample; , the corrosion depth of the corrosion points in the anti-corrosion layer of the anti-working surface of the metal structure sample ;

[0028] The edge of each corrosion point includes multiple corrosion sub-points; the corrosion depth of each corrosion point is the maximum corrosion depth of all corrosion sub-points;

[0029] The total number of corrosion points in the anti-corrosion layer on the working surface is U, They represent the corrosion depth of the u-th corrosion point and the corrosion depth of the U-th corrosion point in the anti-corrosion layer on the positive working surface respectively;

[0030] The total number of corrosion points in the anti-corrosion layer on the working surface is V, They represent the corrosion depth of the vth corrosion point and the corrosion depth of the Vth corrosion point in the anti-corrosion layer on the counter-working surface respectively;

[0031] S34: Repeat S31-S33, and perform adaptive detection on the anti-corrosion layer on the reverse working surface of the metal structure sample by using the ultrasonic detection probe to obtain detection feedback data of the two working surfaces of the metal structure sample.

[0032] Specifically, in S32, the adaptive detection includes:

[0033] S321: Place the acoustic wave detection probe on the positive working surface of the metal structure sample at coordinates The detection is performed on the detection unit grid, wherein the detection process includes: keeping all the sound wave transmitters on the cross section of the sound wave detection probe in an open state;

[0034] S322: Extract coordinates The detection feedback data obtained on the detection unit grid is used to determine the switching demand of the acoustic wave transmitter. The switching demand determination is specifically as follows:

[0035] When there is no peak echo, it means that there is no corrosion sub-point on the corresponding detection unit grid. Move the acoustic wave detection probe to the right to the coordinate On the detection unit grid, keep all the sound wave transmitters on the cross section of the sound wave detection probe turned on and continue the detection;

[0036] When multiple high peak echoes are received, the coordinates of the acoustic wave transmitter corresponding to each high peak echo detected are extracted, and the coordinates of the acoustic wave transmitter corresponding to each high peak echo are connected by a curve on the two-dimensional probe cross-sectional coordinate system;

[0037] If the curve area obtained after connecting the curves is a closed area, it means that the corrosion points on the corresponding detection unit grid are complete. Move the acoustic wave detection probe to the coordinate On the detection unit grid, keep all the sound wave transmitters on the cross section of the sound wave detection probe turned on and continue the detection;

[0038] If the curve area obtained after the curves are connected is an unclosed area, it means that the corrosion points on the corresponding detection unit grid are incomplete, and S323 is executed.

[0039] Specifically, in S32, the adaptive detection further includes:

[0040] S323: Predict the acoustic wave transmitter that needs to be turned on when the acoustic wave detection probe performs detection on the next detection unit grid through the corrosion sub-point prediction algorithm. The corrosion sub-point prediction algorithm specifically includes: obtaining the corrosion depth of the corrosion sub-point according to the echo position of the acoustic wave transmitter corresponding to each high peak echo on the detected detection unit grid. The edge distance from the echo position , where the total number of corrosion sub-points detected on the detected detection unit grid is E;

[0041] The corrosion depth of the corrosion sub-point It is 0.5 times the product of the propagation speed of the sound wave in the metal structure sample and the echo duration; the edge distance of the echo position is the difference between the edge width L of the acoustic wave detection probe and the horizontal coordinate of the echo position;

[0042] S324: According to S323, the corrosion intensity factor and the corrosion shape factor of the corrosion sub-point are calculated, wherein the corrosion intensity factor The calculation formula is: ;

[0043] The corrosion shape factor The calculation formula is ;

[0044] S325: Calculate the corrosion trend factor of each corrosion sub-point according to S323-S324 , the calculation formula is:

[0045] ;

[0046] in, is the multivariate data regression coefficient, where , is the regression error;

[0047] S326: respectively predicting the corrosion probability value corresponding to the actual echo position of each acoustic wave transmitter on the next detection unit grid when the acoustic wave detection probe performs detection on the next detection unit grid. The calculation strategy of the corrosion probability value is specifically as follows:

[0048] ;

[0049] in, is the corrosion probability value corresponding to the actual echo position of the nth acoustic wave transmitter on the next detection unit grid; e represents the eth corrosion sub-point detected on the detected detection unit grid;

[0050] It represents the weight coefficient of the straight-line distance between the actual echo position of the nth acoustic wave transmitter on the next detection unit grid and the eth corrosion sub-point, , It represents the straight-line distance between the actual echo position of the nth acoustic wave transmitter on the next detection unit grid and the eth corrosion sub-point;

[0051] S327: Preset a corrosion probability threshold. When the corrosion probability value corresponding to the actual echo position of the nth acoustic wave transmitter on the next detection unit grid is greater than or equal to the corrosion probability threshold, the nth acoustic wave transmitter is turned on when the next detection unit grid is subjected to acoustic wave detection. Otherwise, the nth acoustic wave transmitter is turned off.

[0052] Specifically, in S32, the adaptive detection further includes:

[0053] S328: Repeat S326-S327, and An acoustic wave transmitter is used to determine the switching demand;

[0054] S329: When the acoustic wave detection probe performs acoustic wave detection on the next detection unit grid, the anti-corrosion quality analysis platform adaptively controls the switch state of the acoustic wave transmitter according to the switch demand judgment result.

[0055] Specifically, S4 includes the following specific steps:

[0056] S41: extracting detection feedback data of two working surfaces;

[0057] S42: Importing the detection feedback data of the two working surfaces into the positive anti-corrosion quality coefficient calculation strategy and the negative anti-corrosion quality coefficient calculation strategy respectively, the positive anti-corrosion quality coefficient calculation strategy is:

[0058] ;

[0059] in, It is the positive anti-corrosion quality coefficient of the positive working surface of the metal structure sample;

[0060] It is the average corrosion depth of the corrosion points on the positive working surface of the metal structure sample;

[0061] The anti-corrosion quality coefficient calculation strategy is:

[0062] ;

[0063] in, It is the anti-corrosion quality coefficient of the anti-working surface of the metal structure sample;

[0064] It is the average corrosion depth of the corrosion points on the reverse working surface of the metal structure sample;

[0065] S43: Comprehensively evaluate the anti-corrosion quality of the metal structure sample according to the positive anti-corrosion quality coefficient and the negative anti-corrosion quality coefficient. The strategy of the comprehensive evaluation is specifically as follows:

[0066] ;

[0067] in, It is the comprehensive anti-corrosion quality coefficient of metal structure samples.

[0068] In addition, the metal structure surface anti-corrosion quality detection system for water conservancy projects of the present invention includes the following modules:

[0069] Actual working condition simulation module, detection unit grid division module, adaptive detection module and anti-corrosion quality assessment module;

[0070] The actual working condition simulation module is used to obtain the metal structure sample to be tested, and place the metal structure sample in the actual working condition simulation box to perform actual working condition simulation processing;

[0071] The detection unit grid division module is used to establish a three-dimensional model of the metal structure sample that has completed the actual working condition simulation according to the size data of the metal structure sample, and to perform detection unit grid division on the three-dimensional model of the metal structure sample;

[0072] The adaptive detection module is used to extract the detection unit grid division data, and to perform adaptive detection on the anti-corrosion layers of the two working surfaces of the metal structure sample through the acoustic wave detection probe, and to transmit the detection feedback data to the anti-corrosion quality analysis platform;

[0073] The anti-corrosion quality evaluation module is used to extract detection feedback data of two working surfaces and evaluate the anti-corrosion quality of the metal structure sample according to the detection feedback data.

[0074] A storage medium stores instructions, and when a computer reads the instructions, the computer executes the metal structure surface anticorrosion quality detection method for water conservancy projects.

[0075] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned metal structure surface anti-corrosion quality detection method for water conservancy projects when executing the computer program.

[0076] Compared with the prior art, the technical effects of the present invention are as follows:

[0077] 1. The present invention adopts a three-dimensional model for grid division and acoustic wave detection, which can more accurately evaluate the quality of the anti-corrosion layer on the surface of the metal structure, improve the accuracy of the detection results, and reduce the errors caused by human operation.

[0078] 2. The adaptive detection technology of the present invention makes the detection process more intelligent. The acoustic wave detection probe can automatically adjust the detection strategy according to the feedback data, which reduces the amount of data collection, makes the final processed detection data representative and targeted, improves the detection efficiency, and saves labor costs.

[0079] 3. The present invention imports the detection feedback data into the anti-corrosion quality analysis platform, and combines the calculation of the positive anti-corrosion quality coefficient and the negative anti-corrosion quality coefficient to help build a systematic anti-corrosion quality evaluation model and provide data support for long-term monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0081] Figure 1 It is a schematic flow chart of the method for detecting the surface anticorrosion quality of metal structures used in water conservancy projects of the present invention;

[0082] Figure 2 It is a structural schematic diagram of the metal structure surface anti-corrosion quality detection system for water conservancy projects of the present invention;

[0083] Figure 3 This is an example diagram of the process of detecting the anti-corrosion quality of the surface of a metal structure for a water conservancy project according to the present invention;

[0084] Figure 4 This is an example diagram of the cross section of the acoustic wave detection probe of the present invention. DETAILED DESCRIPTION

[0085] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0086] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0087] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0088] Example 1

[0089] like Figure 1 As shown, the method for detecting the surface anti-corrosion quality of a metal structure used in a water conservancy project according to an embodiment of the present invention comprises the following specific steps:

[0090] S1: Take the metal structure sample to be tested, and place the metal structure sample in the actual working condition simulation box to perform actual working condition simulation processing;

[0091] S1 includes the following specific steps:

[0092] S11: taking a metal structure sample to be tested, and placing the metal structure sample in an actual working condition simulation box to perform actual working condition simulation processing, wherein the actual working condition simulation processing includes actual working environment parameter simulation and actual working state simulation;

[0093] The actual working environment parameter simulation includes: simulating temperature parameters, humidity parameters and ultraviolet parameters in four seasons in an actual working condition simulation box;

[0094] The actual working state simulation includes: simulating the initial water level of the water conservancy project in the actual working condition simulation box, and gradually changing the water levels on both sides by controlling the water inlet and drainage systems, simulating the lifting and lowering working state of the metal structure sample under different water level differences; wherein, the setting of the initial water level includes: the cross setting of the first water level mode and the second water level mode;

[0095] The first water level mode is specifically: the water level on the left side of the metal structure sample is higher than the water level on the right side of the metal structure sample by k centimeters, wherein the left side surface of the metal structure sample after being placed in the actual working condition simulation box is the positive working surface, and the right side surface is the negative working surface;

[0096] The second water level mode is specifically: the water level on the right side of the metal structure sample is k centimeters higher than the water level on the left side of the metal structure sample;

[0097] Furthermore, the setting of the left and right sides of the metal structure sample does not mean any limitation on the order of metal structure sample detection. The execution order of the detection process should be determined by the functions and internal logic of each module, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0098] S12: Complete 50 rounds of actual working condition simulation tests;

[0099] S13: Cleaning the metal structure samples after completing 50 rounds of actual working condition simulation tests.

[0100] S2: For the metal structure sample that has completed the actual working condition simulation, a three-dimensional model is established according to the size data of the metal structure sample, and the three-dimensional model of the metal structure sample is divided into detection unit grids;

[0101] In S2, the detection unit grid division of the three-dimensional model of the metal structure sample specifically includes: according to the probe cross-sectional area of ​​the acoustic wave detection probe, the positive working surface and the reverse working surface of the metal structure sample in the three-dimensional model are evenly divided into a plurality of detection unit grids, wherein the unit area of ​​each detection unit grid is consistent with the probe cross-sectional area.

[0102] S3: Extract the detection unit grid division data, use the acoustic wave detection probe to adaptively detect the anti-corrosion layers on the two working surfaces of the metal structure sample, and transmit the detection feedback data to the anti-corrosion quality analysis platform;

[0103] like Figure 4 As shown in S3, the cross section of the acoustic wave detection probe is a square, and the width of the four sides is L. The detection array is composed of a number of acoustic wave transmitters. The probe cross section of the acoustic wave detection probe has honeycomb-shaped honeycomb holes, wherein each honeycomb hole is embedded with an acoustic wave transmitter, and the switching state of each acoustic wave transmitter is adaptively controlled by the anti-corrosion quality analysis platform.

[0104] S3 includes the following specific steps:

[0105] S31: extracting detection unit grid division data, and establishing a two-dimensional detection unit grid coordinate system of the positive working surface, a two-dimensional detection unit grid coordinate system of the reverse working surface, and a two-dimensional probe cross-section coordinate system;

[0106] Among them, the coordinates of each detection unit grid on the positive working surface are ;

[0107] The coordinates of each detection unit grid on the reverse working surface are ;

[0108] The coordinates of each acoustic wave transmitter on the cross section of the acoustic wave detection probe are ;

[0109] S32: Adaptively detect the anti-corrosion layer on the positive working surface of the metal structure sample by using an acoustic wave detection probe;

[0110] S33: At the same time, the detection feedback data of the positive working surface is transmitted to the anti-corrosion quality analysis platform, wherein the detection feedback data includes: a set of corrosion depths of corrosion points in the anti-corrosion layer of the positive working surface of the metal structure sample; , the corrosion depth of the corrosion points in the anti-corrosion layer of the anti-working surface of the metal structure sample ;

[0111] The edge of each corrosion point includes multiple corrosion sub-points; the corrosion depth of each corrosion point is the maximum corrosion depth of all corrosion sub-points;

[0112] The total number of corrosion points in the anti-corrosion layer on the working surface is U, They represent the corrosion depth of the u-th corrosion point and the corrosion depth of the U-th corrosion point in the anti-corrosion layer on the positive working surface respectively;

[0113] The total number of corrosion points in the anti-corrosion layer on the working surface is V, They represent the corrosion depth of the vth corrosion point and the corrosion depth of the Vth corrosion point in the anti-corrosion layer on the counter-working surface respectively;

[0114] S34: Repeat S31-S33, and perform adaptive detection on the anti-corrosion layer on the reverse working surface of the metal structure sample by using the ultrasonic detection probe to obtain detection feedback data of the two working surfaces of the metal structure sample.

[0115] In S32, the adaptive detection includes:

[0116] S321: Figure 3 As shown, the acoustic wave detection probe is placed on the positive working surface of the metal structure sample with the coordinates The detection is performed on the detection unit grid, wherein the detection process includes: keeping all the sound wave transmitters on the cross section of the sound wave detection probe in an open state;

[0117] S322: Extract coordinates The detection feedback data obtained on the detection unit grid is used to determine the switching demand of the acoustic wave transmitter. The switching demand determination is specifically as follows:

[0118] When there is no peak echo, it means that there is no corrosion sub-point on the corresponding detection unit grid. Move the acoustic wave detection probe to the right to the coordinate On the detection unit grid, keep all the sound wave transmitters on the cross section of the sound wave detection probe turned on and continue the detection;

[0119] When multiple high peak echoes are received, the coordinates of the acoustic wave transmitter corresponding to each high peak echo detected are extracted, and the coordinates of the acoustic wave transmitter corresponding to each high peak echo are connected by a curve on the two-dimensional probe cross-sectional coordinate system;

[0120] If the curve area obtained after connecting the curves is a closed area, it means that the corrosion points on the corresponding detection unit grid are complete. Move the acoustic wave detection probe to the right to the coordinate On the detection unit grid, keep all the sound wave transmitters on the cross section of the sound wave detection probe turned on and continue the detection;

[0121] If the curve area obtained after the curves are connected is an unclosed area, it means that the corrosion points on the corresponding detection unit grid are incomplete, and S323 is executed.

[0122] In S32, the adaptive detection further includes:

[0123] S323: Predict the acoustic wave transmitter that needs to be turned on when the acoustic wave detection probe performs detection on the next detection unit grid through the corrosion sub-point prediction algorithm. The corrosion sub-point prediction algorithm specifically includes: obtaining the corrosion depth of the corrosion sub-point according to the echo position of the acoustic wave transmitter corresponding to each high peak echo on the detected detection unit grid. The edge distance from the echo position , where the total number of corrosion sub-points detected on the detected detection unit grid is E;

[0124] The corrosion depth of the corrosion sub-point It is 0.5 times the product of the propagation speed of the sound wave in the metal structure sample and the echo duration; the edge distance of the echo position is the difference between the edge width L of the acoustic wave detection probe and the horizontal coordinate of the echo position;

[0125] S324: According to S323, the corrosion intensity factor and the corrosion shape factor of the corrosion sub-point are calculated, wherein the corrosion intensity factor The calculation formula is: ;

[0126] The corrosion shape factor The calculation formula is ;

[0127] S325: Calculate the corrosion trend factor of each corrosion sub-point according to S323-S324 , the calculation formula is:

[0128] ;

[0129] in, is the multivariate data regression coefficient, where , is the regression error;

[0130] S326: respectively predicting the corrosion probability value corresponding to the actual echo position of each acoustic wave transmitter on the next detection unit grid when the acoustic wave detection probe performs detection on the next detection unit grid. The calculation strategy of the corrosion probability value is specifically as follows:

[0131] ;

[0132] in, is the corrosion probability value corresponding to the actual echo position of the nth acoustic wave transmitter on the next detection unit grid; e represents the eth corrosion sub-point detected on the detected detection unit grid;

[0133] It represents the weight coefficient of the straight-line distance between the actual echo position of the nth acoustic wave transmitter on the next detection unit grid and the eth corrosion sub-point, , It represents the straight-line distance between the actual echo position of the nth acoustic wave transmitter on the next detection unit grid and the eth corrosion sub-point;

[0134] S327: Preset a corrosion probability threshold. When the corrosion probability value corresponding to the actual echo position of the nth acoustic wave transmitter on the next detection unit grid is greater than or equal to the corrosion probability threshold, the nth acoustic wave transmitter is turned on when the next detection unit grid is subjected to acoustic wave detection. Otherwise, the nth acoustic wave transmitter is turned off.

[0135] In S32, the adaptive detection further includes:

[0136] S328: Repeat S326-S327, and An acoustic wave transmitter is used to determine the switching demand;

[0137] S329: When the acoustic wave detection probe performs acoustic wave detection on the next detection unit grid, the anti-corrosion quality analysis platform adaptively controls the switch state of the acoustic wave transmitter according to the switch demand judgment result.

[0138] S4: Extract the detection feedback data of the two working surfaces, and evaluate the anti-corrosion quality of the metal structure sample based on the detection feedback data.

[0139] S4 includes the following specific steps:

[0140] S41: extracting detection feedback data of two working surfaces;

[0141] S42: Importing the detection feedback data of the two working surfaces into the positive anti-corrosion quality coefficient calculation strategy and the negative anti-corrosion quality coefficient calculation strategy respectively, the positive anti-corrosion quality coefficient calculation strategy is:

[0142] ;

[0143] in, It is the positive anti-corrosion quality coefficient of the positive working surface of the metal structure sample;

[0144] It is the average corrosion depth of the corrosion points on the positive working surface of the metal structure sample;

[0145] The anti-corrosion quality coefficient calculation strategy is:

[0146] ;

[0147] in, It is the anti-corrosion quality coefficient of the anti-working surface of the metal structure sample;

[0148] It is the average corrosion depth of the corrosion points on the reverse working surface of the metal structure sample;

[0149] S43: Comprehensively evaluate the anti-corrosion quality of the metal structure sample according to the positive anti-corrosion quality coefficient and the negative anti-corrosion quality coefficient. The strategy of the comprehensive evaluation is specifically as follows:

[0150] ;

[0151] in, It is the comprehensive anti-corrosion quality coefficient of metal structure samples.

[0152] Example 2

[0153] like Figure 2 As shown, the metal structure surface anti-corrosion quality detection system for water conservancy projects according to an embodiment of the present invention includes the following modules:

[0154] Actual working condition simulation module, detection unit grid division module, adaptive detection module and anti-corrosion quality assessment module;

[0155] The actual working condition simulation module is used to obtain the metal structure sample to be tested, and place the metal structure sample in the actual working condition simulation box to perform actual working condition simulation processing;

[0156] The detection unit grid division module is used to establish a three-dimensional model of the metal structure sample that has completed the actual working condition simulation according to the size data of the metal structure sample, and to perform detection unit grid division on the three-dimensional model of the metal structure sample;

[0157] The adaptive detection module is used to extract the detection unit grid division data, and to perform adaptive detection on the anti-corrosion layers of the two working surfaces of the metal structure sample through the acoustic wave detection probe, and to transmit the detection feedback data to the anti-corrosion quality analysis platform;

[0158] The anti-corrosion quality evaluation module is used to extract detection feedback data of two working surfaces and evaluate the anti-corrosion quality of the metal structure sample according to the detection feedback data.

[0159] Example 3

[0160] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0161] The processor executes the above-mentioned metal structure surface anti-corrosion quality detection method for water conservancy projects by calling the computer program stored in the memory.

[0162] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the metal structure surface anticorrosion quality detection method for water conservancy projects provided by the above method embodiment. The electronic device may also include other components for realizing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0163] Example 4

[0164] This embodiment provides a storage medium on which a rewritable computer program is stored;

[0165] When the computer program runs on a computer device, the computer device is enabled to execute the above-mentioned method for detecting the surface anti-corrosion quality of metal structures used in water conservancy projects.

[0166] For example, the storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0167] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0168] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0169] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0170] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0171] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0172] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0173] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0174] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0175] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0176] In summary, the technical effects of the present invention are as follows:

[0177] 1. The present invention adopts a three-dimensional model for grid division and acoustic wave detection, which can more accurately evaluate the quality of the anti-corrosion layer on the surface of the metal structure, improve the accuracy of the detection results, and reduce the errors caused by human operation.

[0178] 2. The adaptive detection technology of the present invention makes the detection process more intelligent. The acoustic wave detection probe can automatically adjust the detection strategy according to the feedback data, which reduces the amount of data collection, makes the final processed detection data representative and targeted, improves the detection efficiency, and saves labor costs.

[0179] 3. The present invention imports the detection feedback data into the anti-corrosion quality analysis platform, and combines the calculation of the positive anti-corrosion quality coefficient and the negative anti-corrosion quality coefficient to help build a systematic anti-corrosion quality evaluation model and provide data support for long-term monitoring.

[0180] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for detecting the surface corrosion quality of metal structures used in water conservancy projects, characterized in that: The method comprises the following specific steps: S1: Take the metal structure sample to be tested, and place the metal structure sample in the actual working condition simulation box to perform actual working condition simulation processing; S2: For the metal structure sample that has completed the actual working condition simulation, a three-dimensional model is established according to the size data of the metal structure sample, and the three-dimensional model of the metal structure sample is divided into detection unit grids; S3: Extract the detection unit grid division data, use the acoustic wave detection probe to adaptively detect the anti-corrosion layers on the two working surfaces of the metal structure sample, and transmit the detection feedback data to the anti-corrosion quality analysis platform; S31: extracting detection unit grid division data, and establishing a two-dimensional detection unit grid coordinate system of the positive working surface, a two-dimensional detection unit grid coordinate system of the reverse working surface, and a two-dimensional probe cross-section coordinate system; Among them, the coordinates of each detection unit grid on the positive working surface are ; The coordinates of each detection unit grid on the reverse working surface are ; The coordinates of each acoustic wave transmitter on the cross section of the acoustic wave detection probe are ; S32: Adaptively detect the anti-corrosion layer on the positive working surface of the metal structure sample by using an acoustic wave detection probe; S321: Place the acoustic wave detection probe on the positive working surface of the metal structure sample at coordinates The detection is performed on the detection unit grid, wherein the detection process includes: keeping all the sound wave transmitters on the cross section of the sound wave detection probe in an open state; S322: Extract coordinates The detection feedback data obtained on the detection unit grid is used to determine the switching demand of the acoustic wave transmitter. The switching demand determination is specifically as follows: When there is no peak echo, it means that there is no corrosion sub-point on the corresponding detection unit grid. Move the acoustic wave detection probe to the coordinates On the detection unit grid, keep all the sound wave transmitters on the cross section of the sound wave detection probe turned on and continue the detection; When multiple high peak echoes are received, the coordinates of the acoustic wave transmitter corresponding to each high peak echo detected are extracted, and the coordinates of the acoustic wave transmitter corresponding to each high peak echo are connected by a curve on the two-dimensional probe cross-sectional coordinate system; If the curve area obtained after connecting the curves is a closed area, it means that the corrosion points on the corresponding detection unit grid are complete. Move the acoustic wave detection probe to the coordinate On the detection unit grid, keep all the sound wave transmitters on the cross section of the sound wave detection probe turned on and continue the detection; If the curve area obtained after the curves are connected is an unclosed area, it means that the corrosion points on the corresponding detection unit grid are incomplete, and the switch demand judgment strategy of the acoustic wave transmitter is executed; S33: At the same time, the detection feedback data of the positive working surface is transmitted to the anti-corrosion quality analysis platform, wherein the detection feedback data includes: a set of corrosion depths of corrosion points in the anti-corrosion layer of the positive working surface of the metal structure sample; , the corrosion depth of the corrosion points in the anti-corrosion layer of the anti-working surface of the metal structure sample ; The edge of each corrosion point includes multiple corrosion sub-points; the corrosion depth of each corrosion point is the maximum corrosion depth of all corrosion sub-points; The total number of corrosion points in the anti-corrosion layer on the working surface is U, They represent the corrosion depth of the u-th corrosion point and the corrosion depth of the U-th corrosion point in the anti-corrosion layer on the positive working surface respectively; The total number of corrosion points in the anti-corrosion layer on the working surface is V, They represent the corrosion depth of the vth corrosion point and the corrosion depth of the Vth corrosion point in the anti-corrosion layer on the counter-working surface respectively; S34: repeating S31-S33, adaptively detecting the anti-corrosion layer on the reverse working surface of the metal structure sample by using the acoustic wave detection probe, and obtaining detection feedback data of two working surfaces of the metal structure sample; S4: Extract the detection feedback data of the two working surfaces, and evaluate the anti-corrosion quality of the metal structure sample based on the detection feedback data.

2. The method for detecting the surface anticorrosion quality of metal structures used in water conservancy projects according to claim 1 is characterized in that: S1 includes the following specific steps: S11: taking a metal structure sample to be tested, and placing the metal structure sample in an actual working condition simulation box to perform actual working condition simulation processing, wherein the actual working condition simulation processing includes actual working environment parameter simulation and actual working state simulation; The actual working environment parameter simulation includes: simulating temperature parameters, humidity parameters and ultraviolet parameters in four seasons in an actual working condition simulation box; The actual working state simulation includes: simulating the initial water level of the water conservancy project in the actual working condition simulation box, and gradually changing the water levels on both sides by controlling the water inlet and drainage systems, simulating the lifting and lowering working state of the metal structure sample under different water level differences; wherein, the setting of the initial water level includes: the cross setting of the first water level mode and the second water level mode; The first water level mode is specifically: the water level on the left side of the metal structure sample is higher than the water level on the right side of the metal structure sample by k centimeters, wherein the left side surface of the metal structure sample after being placed in the actual working condition simulation box is the positive working surface, and the right side surface is the negative working surface; The second water level mode is specifically: the water level on the right side of the metal structure sample is k centimeters higher than the water level on the left side of the metal structure sample; S12: Complete 50 rounds of actual working condition simulation tests; S13: Cleaning the metal structure samples after completing 50 rounds of actual working condition simulation tests.

3. The method for detecting the surface anticorrosion quality of metal structures used in water conservancy projects according to claim 2 is characterized in that: In S2, the detection unit grid division of the three-dimensional model of the metal structure sample specifically includes: according to the probe cross-sectional area of ​​the acoustic wave detection probe, the positive working surface and the reverse working surface of the metal structure sample in the three-dimensional model are evenly divided into a plurality of detection unit grids, wherein the unit area of ​​each detection unit grid is consistent with the probe cross-sectional area.

4. The method for detecting the surface anticorrosion quality of metal structures used in water conservancy projects according to claim 3 is characterized in that: In S3, the cross section of the acoustic wave detection probe is a square, and the width of each of the four sides is L. The detection array is composed of a number of acoustic wave transmitters. The probe cross section of the acoustic wave detection probe has honeycomb-shaped honeycomb holes, wherein each honeycomb hole is embedded with an acoustic wave transmitter, and the switching state of each acoustic wave transmitter is adaptively controlled by the anti-corrosion quality analysis platform.

5. The method for detecting the surface anticorrosion quality of metal structures used in water conservancy projects according to claim 4 is characterized in that: The switching demand judgment strategy of the acoustic wave transmitter includes: S323: Predict the acoustic wave transmitter that needs to be turned on when the acoustic wave detection probe performs detection on the next detection unit grid through the corrosion sub-point prediction algorithm. The corrosion sub-point prediction algorithm specifically includes: obtaining the corrosion depth of the corrosion sub-point according to the echo position of the acoustic wave transmitter corresponding to each high peak echo on the detected detection unit grid. The edge distance from the echo position , where the total number of corrosion sub-points detected on the detected detection unit grid is E; The corrosion depth of the corrosion sub-point It is 0.5 times the product of the propagation speed of the sound wave in the metal structure sample and the echo duration; the edge distance of the echo position is the difference between the edge width L of the acoustic wave detection probe and the horizontal coordinate of the echo position; S324: According to S323, the corrosion intensity factor and the corrosion shape factor of the corrosion sub-point are calculated, wherein the corrosion intensity factor The calculation formula is: ; The corrosion shape factor The calculation formula is ; S325: Calculate the corrosion trend factor of each corrosion sub-point according to S323-S324 , the calculation formula is: ； in, is the multivariate data regression coefficient, where , is the regression error; S326: respectively predicting the corrosion probability value corresponding to the actual echo position of each acoustic wave transmitter on the next detection unit grid when the acoustic wave detection probe performs detection on the next detection unit grid. The calculation strategy of the corrosion probability value is specifically as follows: ； in, is the corrosion probability value corresponding to the actual echo position of the nth acoustic wave transmitter on the next detection unit grid; e represents the eth corrosion sub-point detected on the detected detection unit grid; It represents the weight coefficient of the straight-line distance between the actual echo position of the nth acoustic wave transmitter on the next detection unit grid and the eth corrosion sub-point, , It represents the straight-line distance between the actual echo position of the nth acoustic wave transmitter on the next detection unit grid and the eth corrosion sub-point; S327: Preset a corrosion probability threshold. When the corrosion probability value corresponding to the actual echo position of the nth acoustic wave transmitter on the next detection unit grid is greater than or equal to the corrosion probability threshold, the nth acoustic wave transmitter is turned on when the next detection unit grid is subjected to acoustic wave detection. Otherwise, the nth acoustic wave transmitter is turned off.

6. The method for detecting the surface anticorrosion quality of metal structures used in water conservancy projects according to claim 5 is characterized in that: The switching demand judgment strategy of the acoustic wave transmitter also includes: S328: Repeat S326-S327, and An acoustic wave transmitter is used to determine the switching demand; S329: When the acoustic wave detection probe performs acoustic wave detection on the next detection unit grid, the anti-corrosion quality analysis platform adaptively controls the switch state of the acoustic wave transmitter according to the switch demand judgment result.

7. The method for detecting the surface anticorrosion quality of metal structures used in water conservancy projects according to claim 6, characterized in that: S4 includes the following specific steps: S41: extracting detection feedback data of two working surfaces; S42: Importing the detection feedback data of the two working surfaces into the positive anti-corrosion quality coefficient calculation strategy and the negative anti-corrosion quality coefficient calculation strategy respectively, the positive anti-corrosion quality coefficient calculation strategy is: ； in, It is the positive anti-corrosion quality coefficient of the positive working surface of the metal structure sample; It is the average corrosion depth of the corrosion points on the positive working surface of the metal structure sample; The anti-corrosion quality coefficient calculation strategy is: ； in, It is the anti-corrosion quality coefficient of the anti-working surface of the metal structure sample; It is the average corrosion depth of the corrosion points on the reverse working surface of the metal structure sample; S43: Comprehensively evaluate the anti-corrosion quality of the metal structure sample according to the positive anti-corrosion quality coefficient and the negative anti-corrosion quality coefficient. The strategy of the comprehensive evaluation is specifically as follows: ； in, It is the comprehensive anti-corrosion quality coefficient of metal structure samples.

8. A metal structure surface anti-corrosion quality detection system for water conservancy projects, used to implement the metal structure surface anti-corrosion quality detection method for water conservancy projects as described in any one of claims 1 to 7, characterized in that: The system includes the following modules: Actual working condition simulation module, detection unit grid division module, adaptive detection module and anti-corrosion quality assessment module; The actual working condition simulation module is used to obtain the metal structure sample to be tested, and place the metal structure sample in the actual working condition simulation box to perform actual working condition simulation processing; The detection unit grid division module is used to establish a three-dimensional model of the metal structure sample that has completed the actual working condition simulation according to the size data of the metal structure sample, and to perform detection unit grid division on the three-dimensional model of the metal structure sample; The adaptive detection module is used to extract the detection unit grid division data, and to perform adaptive detection on the anti-corrosion layers of the two working surfaces of the metal structure sample through the acoustic wave detection probe, and to transmit the detection feedback data to the anti-corrosion quality analysis platform; The anti-corrosion quality evaluation module is used to extract detection feedback data of two working surfaces and evaluate the anti-corrosion quality of the metal structure sample according to the detection feedback data.

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