Hydraulic concrete damage acoustic emission positioning method and system

Abstract

The invention discloses a hydraulic concrete damage acoustic emission positioning method and system, and belongs to the technical field of hydraulic concrete damage positioning detection. The system comprises a piezoelectric acoustic emission sensor, a signal acquisition and storage module and a signal analysis module which are sequentially connected through a coaxial cable and a data transmission line to realize signal receiving, processing, storage and analysis. According to the method, acoustic emission signals are collected, a cuckoo search algorithm search domain is determined in combination with a least square method, and after iterative optimization, a Geiger algorithm is used for iteration to obtain a final sound source position. The positioning precision is higher than that of a traditional algorithm, the hydraulic concrete damage position can be accurately detected, and technical support is provided for hydraulic engineering safety.

Description

Technical Field

[0001] This invention belongs to the field of hydraulic concrete damage location and detection technology, and specifically relates to an acoustic emission location method and system for hydraulic concrete damage. Background Technology

[0002] During their service life, hydraulic concrete structures not only have to withstand the combined effects of various dynamic and static loads such as enormous water pressure, temperature loads, and seismic loads, but also the effects of harsh environmental erosion, material aging, and fatigue loads. In addition, the quality of early construction, material performance, and later operation and management can all affect the hydraulic concrete structures, causing them to develop varying degrees of deterioration during their service life. If the hidden dangers and defects in the structure are not accurately and promptly diagnosed and resolved, the safety of the hydraulic concrete structure will deteriorate, constantly affecting the safe operation of water conservancy projects, and in severe cases, causing catastrophic consequences such as destruction.

[0003] For hydraulic concrete structures, damage often exhibits spatiotemporal randomness and concealed location, making damage detection and diagnosis exceptionally difficult. Acoustic emission sensing technology is a rapidly developing and promising non-destructive testing technique in recent years. Compared with other methods, acoustic emission sensing technology has high sensitivity, can provide rapid detection of large components, either overall or locally, and can be used for detection in environments inaccessible to other methods. However, the complexity of hydraulic concrete structures, the attenuation and propagation characteristics of acoustic waves within concrete structures, and the irreversibility of acoustic wave generation result in low accuracy of traditional sound source localization methods. Therefore, improvements to sound source localization algorithms are necessary. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and system for locating acoustic emission damage in hydraulic concrete. By deploying acoustic emission sensors to collect and store acoustic emission signals in hydraulic concrete structures, and combining the method for locating acoustic emission damage in hydraulic concrete structures, the damaged parts can be effectively located.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A method for locating damage to hydraulic concrete using acoustic emission, comprising the following steps: S1. Acoustic emission signals generated by damage to hydraulic concrete structures are collected using an acoustic emission signal analysis module; the acoustic emission signals are generated by energy released from the damaged areas inside the concrete, and their source is the damaged concrete area; the acoustic emission signals generated at the damaged concrete area are the sound sources. S2. Establish the sound source localization equation, use the least squares algorithm to obtain the sound source coordinates, and determine the search domain of the cuckoo search algorithm. ; S3. Define and initialize the objective function, and set the CS-related parameters; the objective function is used to measure the deviation between the calculated value and the actual sound source location; S4. Compare the quality of the initial solutions, and update the other solutions again by Levy random flight; the initial solution is a preliminary estimate of the sound source coordinates; S5. Select the optimal solution according to the solution update rule; the optimal solution is the estimated coordinates that are closer to the actual sound source location. S6. Repeat steps S4 to S5 until the number of iterations reaches [number]. Next, after retaining the optimal solution, the solution process is completed, and the coordinates of the found sound source are output; S7. Continue iterating using the Geiger localization algorithm to obtain the final location of the sound source. Preferably, the sub-step of S2 is as follows: S21. In three-dimensional time-difference positioning, establish the sound source localization equation. When the number of sensors is... At that time, the sound source localization equation is: , In the formula: The coordinates of the sound source at the point of concrete damage; For the first The coordinates of each sensor; Wave speed; The moment when concrete damage occurs; For the first The moment when a sensor receives an acoustic emission signal; S22. Linearize the equations to obtain the following system of linear transcendental equations: , The matrix form can be represented as follows: , In the formula: ; ; ; S23. The approximate location of the sound source can be obtained from LS. and the time of injury for: ; S24. Continue using the CS algorithm. Search for the optimal solution within the range, where This represents the maximum positioning error of LS.

[0006] Preferably, the sub-step of S3 is as follows: S31. Define the objective function as follows: , Sound source coordinates ; S32, in the region Randomly generated The initial positions of each solution; S33. Set CS-related parameters, including cuckoo population size. probability of discarding and number of iterations .

[0007] Preferably, the sub-step of S4 is as follows: S41. Substitute the randomly generated initial position into the objective function, compare the merits of the initial solutions, and retain the optimal solution; The path formula for the S42 and CS algorithms to find the location of the solution locally using Levy random flight is as follows: , In the formula: For the first The first generation One solution; The step size scaling factor can be obtained through... The scope of the value constraint optimization search; The dot product symbol; It follows a Levy random distribution; S43, after rearrangement, becomes: , In the formula: For the Levy index; It is a constant; and For variables that follow a standard normal distribution, i.e. , ; This is the current optimal solution; Let levy be the random step size distribution function for flight: .

[0008] Preferably, the sub-step of S5 is as follows: The path equation for the S51 and CS algorithms to find new solutions globally through a preference-based random walk is as follows: , In the formula: The scaling factor is Uniformly distributed random numbers within; and For the first Two random solutions; S52, Comparing random numbers With discard probability The size, if Then, according to S51, the solution is randomly changed; if If so, no change is made to the solution.

[0009] Preferably, the sub-step of S7 is as follows: S71. Given an initial iteration point Then, the positioning equation can be obtained as follows: , In the formula: The coordinates of the iteration point; For the first The coordinates of each sensor; Wave speed; The moment when concrete damage occurs; For the first The moment when a sensor receives an acoustic emission signal; S72. The time it takes for the acoustic emission wave to reach each sensor can be expressed using the first-order Taylor expansion of the iterative point coordinates. The expression is: , In the formula: For the first The moment when a sensor receives an acoustic emission wave; To calculate the acoustic emission wave reaching the first point using the coordinates of the iterative points The moment of each sensor; To iteratively calculate the distances between the points and each sensor, we have: ; S73, Regarding For each acoustic emission sensor, the expression in S72 can be rearranged into a matrix equation form: , In the formula: ; ; ; S74. Solve the overdetermined equations in S73 using LS: , Will This is used as a new iteration point until the required error setting is met.

[0010] Preferably, in step S33, The value ranges from 10 to 50. The value is 0.25. The value ranges from 10 to 50.

[0011] Preferably, in step S43, Take 1.5, Take 0.01.

[0012] An acoustic emission localization system for damage to hydraulic concrete, employing the aforementioned acoustic emission localization method for damage to hydraulic concrete, includes an acoustic emission sensor, an acoustic emission signal acquisition and storage module, and an acoustic emission signal analysis module; The acoustic emission sensor is a piezoelectric acoustic emission sensor used to sense acoustic emission vibration signals generated by damage to hydraulic concrete and convert them into electrical signals; it is connected to the acoustic emission signal acquisition and storage module via a coaxial cable to transmit the electrical signals to the module. Acoustic emission signal acquisition and storage module: It consists of a signal amplifier, filter, A / D converter and memory card connected in sequence; it is used to amplify and filter the received electrical signal, convert it into a digital signal by A / D, and then store it on the memory card. Acoustic emission signal analysis module: It consists of a memory card, a computer processor, a display, data reading software and a positioning analysis program; the memory card receives and temporarily stores digital signals, the data reading software reads the signals and transmits them to the computer processor, the processor runs the positioning analysis program to calculate the coordinates of the sound source, and the display is used to show the positioning results.

[0013] After the acoustic emission signal is received by the acoustic emission sensor, it is connected to the acoustic emission signal acquisition and storage module via a coaxial cable, where the voltage signal is converted into a digital signal and stored.

[0014] The acoustic emission signal acquisition and storage module is connected to the acoustic emission signal analysis module via a data transmission line.

[0015] A computer device, comprising: One or more processors, wherein one or more executable programs are stored on the processors; When the one or more executable programs are executed by the one or more processors, they are used to implement the acoustic emission localization method for damage to hydraulic concrete.

[0016] A storage medium storing an executable program, which, when executed, is used to implement the aforementioned acoustic emission localization method for damage to hydraulic concrete.

[0017] The present invention can achieve the following beneficial effects: The acoustic emission localization system and method for hydraulic concrete damage provided by this invention can improve the accuracy of acoustic source localization, accurately detect the location of damage in hydraulic concrete structures, and has high localization accuracy and efficiency. This improves the accuracy of concrete damage localization and detection, and provides technical support for ensuring the safety of hydraulic concrete structures. Attached Figure Description

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a schematic diagram of the principle of the present invention; Figure 2 This is a flowchart of the acoustic emission localization method for damage to hydraulic concrete according to the present invention. Figure 3 This is a schematic diagram of the sensor deployment; Figure 4 A schematic diagram of the wave velocity measurement setup; Figure 5 The graph shows the positioning error curves for three positioning algorithms. Figure 6 Location map for LS algorithm; Figure 7 Geiger algorithm localization map; Figure 8 This is the localization map for the LS-CS-Geiger algorithm. Detailed Implementation

[0019] Preferred solutions include Figures 1 to 8 As shown, a method for locating damage to hydraulic concrete using acoustic emission includes the following steps: S1. Use the data reading software in the acoustic emission signal analysis module to read the collected acoustic emission signal; A lead-breaking verification test was conducted on a concrete slab to test and analyze the proposed acoustic emission localization system and method for hydraulic concrete damage. The test setup is as follows: Figure 3 As shown, a total of four acoustic emission sensors were installed on the concrete slab. The signals collected by the acoustic emission sensors were processed by the acoustic emission signal acquisition and storage module. The coordinates and parameters of the acoustic emission sensors are shown in Table 1.

[0020] Table 1 Sensor coordinates and parameters

[0021] Before starting the positioning test, the wave velocity of the P-wave in the concrete is measured. The wave velocity measurement test setup is as follows: Figure 3 As shown in Table 2, the measured wave velocities are used as the location wave velocity. v =3912151.69mm / s.

[0022] Table 2. Wave velocity measurements at each lead break point.

[0023] To reduce errors, the lead was broken three times at each positioning point, and the average value of the received signal time was taken as the basic data for positioning calculation. The average time when each sensor received the acoustic emission signal is shown in Table 3.

[0024] Table 3. Time unit for acoustic emission signals received by each sensor: s

[0025] S2. Establish the sound source localization equation, use the least squares (LS) algorithm to obtain the sound source coordinates, and determine the search domain of the Cuckoo Search (CS) algorithm. ; S21. In three-dimensional time-difference positioning, establish the sound source localization equation. When the number of sensors is... At that time, the sound source localization equation is: , In the formula: The coordinates of the sound source at the point of concrete damage; For the first The coordinates of each sensor; Wave speed; The moment when concrete damage occurs; For the first The moment when a sensor receives an acoustic emission signal; S22. Linearize the equations to obtain the following system of linear transcendental equations: , The matrix form can be represented as follows: , In the formula: ; ; ; S23. The approximate location of the sound source can be obtained from LS. and the time of injury for: ; S24. Continue using the CS algorithm. Search for the optimal solution within the range, where This represents the maximum positioning error of LS.

[0026] S3. Define and initialize the objective function, and set the CS-related parameters; S31. Define the objective function as follows: , Sound source coordinates ; S32, in the region Randomly generated The initial positions of each solution; S33. Set the size of the bird flock to be searched. probability of discarding Number of iterations Parameters such as these.

[0027] S4. Compare the quality of the initial solutions, and update the other solutions using Levy random flight. S41. Substitute the randomly generated initial position into the objective function, compare the merits of the initial solutions, and retain the optimal solution; The path formula for the S42 and CS algorithms to find the location of the solution locally using Levy random flight is as follows: , In the formula: For the first The first generation One solution; The step size scaling factor can be obtained through... The scope of the value constraint optimization search; The dot product symbol; It follows a Levy random distribution; S43, after rearrangement, becomes: , In the formula: For the Levy index; It is a constant; and For variables that follow a standard normal distribution, i.e. , ; This is the current optimal solution; Let levy be the random step size distribution function for flight: .

[0028] S5. Select the optimal solution according to the solution update rules; The path equation for the S51 and CS algorithms to find new solutions globally through a preference-based random walk is as follows: , In the formula: The scaling factor is Uniformly distributed random numbers within; and For the first Two random solutions; S52, Comparing random numbers With discard probability The size, if Then, according to S51, the solution is randomly changed; if If so, no change is made to the solution.

[0029] S6. Repeat steps S4 to S5 until the number of iterations reaches [number]. Next, after retaining the optimal solution, the solution process is completed, and the coordinates of the found sound source are output; S7. Continue iterating using the Geiger localization algorithm to obtain the final location of the sound source.

[0030] S71. Given an initial iteration point Then, the positioning equation can be obtained as follows: , In the formula: The coordinates of the iteration point; For the first The coordinates of each sensor; Wave speed; The moment when concrete damage occurs; For the first The moment when a sensor receives an acoustic emission signal; S72. The time it takes for the acoustic emission wave to reach each sensor can be expressed using the first-order Taylor expansion of the iterative point coordinates. The expression is: , In the formula: For the first The moment when a sensor receives an acoustic emission wave; To calculate the acoustic emission wave reaching the first point using the coordinates of the iterative points The moment of each sensor; To iteratively calculate the distances between the points and each sensor, we have: ; S73, Regarding For each acoustic emission sensor, the expression in S72 can be rearranged into a matrix equation form: , In the formula: ; ; ; S74. Solve the overdetermined equations in S73 using LS: , Will This is used as a new iteration point until the required error setting is met.

[0031] Specifically, the acoustic emission signals collected during the experiment were read using the data reading software of the acoustic emission signal analysis module. A localization analysis program was run on the computer processor to calculate the sound source location. The LS, Geiger localization algorithms, and LS-CS-Geiger algorithm were used to calculate the sound source location, respectively. The localization results and errors of each algorithm are shown in Table 4. The error is taken as... The initial iteration point of the Geiger algorithm is taken as the centroid of the localization plane, and the flock size of the LS-CS-Geiger algorithm is... Set the number of iterations to 20. Take 15.

[0032] Table 4 Positioning Accuracy Calculation Table (Unit: mm)

[0033] The positioning error curves and positioning effect diagrams for the three positioning methods are shown below. Figure 5 and Figures 6-8 As shown in the figure, the positioning error curve and positioning results indicate that the LS-CS-Geiger algorithm has the highest positioning accuracy, followed by the Geiger algorithm, while the LS algorithm has the lowest accuracy. Therefore, introducing the CS search algorithm into sound source localization can improve the accuracy of sound source localization and mitigate the large positioning errors of the LS and Geiger iterative methods at the diagonal of the sensor deployment area. This allows for more accurate calculation of the concrete damage location, providing a reliable basis for subsequent reinforcement and repair projects.

[0034] This invention is based on acoustic emission sensing technology and combines the Geiger localization method, LS, and CS algorithms for locating acoustic emission source signals. The LS-CS algorithm is used to provide initial iteration values ​​for the Geiger localization method, and the Geiger algorithm is used for localization calculations, reducing the number of iterations and improving localization accuracy. This invention can accurately calculate the location of damage in hydraulic concrete, exhibiting high localization accuracy and efficiency, and improving the accuracy of damage location detection in hydraulic concrete.

[0035] The above embodiments are merely preferred technical solutions of the present invention and should not be considered as limitations on the present invention. The scope of protection of the present invention should be limited to the technical solutions described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A method for locating damage to hydraulic concrete using acoustic emission, characterized in that: Includes the following steps: S1. Acoustic emission signals generated by damage to hydraulic concrete structures are collected using an acoustic emission signal analysis module; the acoustic emission signals are generated by energy released from the damaged areas inside the concrete, and their source is the damaged concrete area; the acoustic emission signals generated at the damaged concrete area are the sound sources. S2. Establish the sound source localization equation, use the least squares algorithm to obtain the sound source coordinates, and determine the search domain of the cuckoo search algorithm. ; S3. Define and initialize the objective function, and set the CS-related parameters; the objective function is used to measure the deviation between the calculated value and the actual sound source location; S4. Compare the quality of the initial solutions, and update the other solutions again by Levy random flight; the initial solution is a preliminary estimate of the sound source coordinates; S5. Select the optimal solution according to the solution update rule; the optimal solution is the estimated coordinates that are closer to the actual sound source location. S6. Repeat steps S4 to S5 until the number of iterations reaches [number]. Next, after retaining the optimal solution, the solution process is completed, and the coordinates of the found sound source are output; S7. Continue iterating using the Geiger localization algorithm to obtain the final location of the sound source.

2. The method for acoustic emission localization of damage to hydraulic concrete according to claim 1, characterized in that: The sub-steps of S2 are: S21. In three-dimensional time-difference positioning, establish the sound source localization equation. When the number of sensors is... At that time, the sound source localization equation is: ， In the formula: The coordinates of the sound source at the point of concrete damage; For the first The coordinates of each sensor; Wave speed; The moment when concrete damage occurs; For the first The moment when a sensor receives an acoustic emission signal; S22. Linearize the equations to obtain the following system of linear transcendental equations: ， The matrix form can be represented as follows: ， In the formula: ; ; ; S23. The approximate location of the sound source can be obtained from LS. and the time of injury for: ； S24. Continue using the CS algorithm. Search for the optimal solution within the range, where This represents the maximum positioning error of LS.

3. The method for acoustic emission localization of damage to hydraulic concrete according to claim 1, characterized in that: The sub-steps of S3 are: S31. Define the objective function as follows: ， Sound source coordinates ; S32, in the region Randomly generated The initial positions of each solution; S33. Set CS-related parameters, including cuckoo population size. probability of discarding and number of iterations .

4. The method for locating damage to hydraulic concrete according to claim 1, characterized in that: The sub-steps of S4 are: S41. Substitute the randomly generated initial position into the objective function, compare the merits of the initial solutions, and retain the optimal solution; The path formula for the S42 and CS algorithms to find the location of the solution locally using Levy random flight is as follows: ， In the formula: For the first The first generation One solution; The step size scaling factor can be obtained through... The scope of the value constraint optimization search; The dot product symbol; It follows a Levy random distribution; S43, after rearrangement, becomes: ， In the formula: For the Levy index; It is a constant; and For variables that follow a standard normal distribution, i.e. , ; This is the current optimal solution; Let levy be the random step size distribution function for flight: 。 5. The method for locating damage to hydraulic concrete according to claim 1, characterized in that: The sub-steps of S5 are: The path equation for the S51 and CS algorithms to find new solutions globally through a preference-based random walk is as follows: ， In the formula: The scaling factor is Uniformly distributed random numbers within; and For the first Two random solutions; S52, Comparing random numbers With discard probability The size, if Then, according to S51, the solution is randomly changed; if If so, no change is made to the solution.

6. The method for acoustic emission localization of damage to hydraulic concrete according to claim 1, characterized in that: The sub-steps of S7 are: S71, Given an initial iteration point Then, the positioning equation can be obtained as follows: ， In the formula: The coordinates of the iteration point; For the first The coordinates of each sensor; Wave speed; The moment when concrete damage occurs; For the first The moment when a sensor receives an acoustic emission signal; S72. The time it takes for the acoustic emission wave to reach each sensor can be expressed using the first-order Taylor expansion of the iterative point coordinates. The expression is: ， In the formula: For the first The moment when a sensor receives an acoustic emission wave; To calculate the acoustic emission wave reaching the first point using the coordinates of the iterative points The moment of each sensor; To iteratively calculate the distances between the points and each sensor, we have: ; S73, Regarding For each acoustic emission sensor, the expression in S72 can be rearranged into a matrix equation form: ， In the formula: ; ; ; S74. Solve the overdetermined equations in S73 using LS: ， Will This is used as a new iteration point until the required error setting is met.

7. The method for acoustic emission localization of damage in hydraulic concrete according to claim 3, characterized in that: In step S33, The value ranges from 10 to 50. The value is 0.

25. The value ranges from 10 to 50.

8. The method for acoustic emission localization of damage to hydraulic concrete according to claim 4, characterized in that: In step S43, Take 1.5, Take 0.

01.

9. A hydraulic concrete damage acoustic emission localization system, characterized in that: The method for locating damage to hydraulic concrete using acoustic emission according to any one of claims 1-8 includes an acoustic emission sensor, an acoustic emission signal acquisition and storage module, and an acoustic emission signal analysis module. The acoustic emission sensor is a piezoelectric acoustic emission sensor used to sense acoustic emission vibration signals generated by damage to hydraulic concrete and convert them into electrical signals; it is connected to the acoustic emission signal acquisition and storage module via a coaxial cable to transmit the electrical signals to the module. Acoustic emission signal acquisition and storage module: It consists of a signal amplifier, filter, A / D converter and memory card connected in sequence; it is used to amplify and filter the received electrical signal, convert it into a digital signal by A / D, and then store it on the memory card. Acoustic emission signal analysis module: It consists of a memory card, a computer processor, a display, data reading software and a positioning analysis program; the memory card receives and temporarily stores digital signals, the data reading software reads the signals and transmits them to the computer processor, the processor runs the positioning analysis program to calculate the coordinates of the sound source, and the display is used to show the positioning results.

10. The acoustic emission localization system for damage to hydraulic concrete according to claim 9, characterized in that: After the acoustic emission signal is received by the acoustic emission sensor, it is connected to the acoustic emission signal acquisition and storage module via a coaxial cable, where the voltage signal is converted into a digital signal and stored.

11. The acoustic emission localization system for damage to hydraulic concrete according to claim 9, characterized in that: The acoustic emission signal acquisition and storage module is connected to the acoustic emission signal analysis module via a data transmission line.

12. A computer device, characterized in that: include: One or more processors, wherein one or more executable programs are stored on the processors; When the one or more executable programs are executed by the one or more processors, they are used to implement the acoustic emission localization method for damage to hydraulic concrete according to any one of claims 1-8.

13. A storage medium, characterized in that: It stores an executable program, which, when executed, is used to implement the acoustic emission localization method for damage to hydraulic concrete according to any one of claims 1-8.

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