Electromagnetic nondestructive porosity testing method, medium and system for eliminating moisture influence

Abstract

The present invention belongs to the technical field of concrete testing, specifically relating to a porosity electromagnetic nondestructive testing method, medium, and system that eliminates the influence of moisture. The method comprises the following steps: preparing specimens with varying moisture contents using the medium to be tested and obtaining the porosity of each specimen; obtaining the dielectric constant and conductivity of each specimen using ground penetrating radar (GPR) to construct a data set containing the dielectric constant, conductivity, and porosity; deriving a dielectric model under water-containing conditions and a conductivity model under unsaturated conditions, and simultaneously eliminating the moisture content parameter from the models to obtain a porosity detection model containing unknown parameters; and substituting the data set into the porosity detection model for fitting, thereby obtaining a porosity detection model that is unaffected by moisture. Compared to existing technologies, the present invention addresses the problem of GPR testing of concrete porosity being highly susceptible to moisture interference. This solution eliminates the influence of moisture on calculations during electromagnetic nondestructive testing.

Description

Technical Field

[0001] The present invention belongs to the technical field of concrete detection, and in particular relates to a porosity electromagnetic nondestructive detection method, medium and system for eliminating the influence of moisture. Background Art

[0002] As a key parameter for measuring the performance and durability of concrete structures, porosity profoundly affects the strength, permeability and service life of concrete. Therefore, developing high-precision non-destructive testing technology to evaluate and control the pore structure of concrete is of great significance for improving the long-term reliability and durability of engineering structures.

[0003] Non-destructive testing (NDT) is a method of inspecting and evaluating materials or structures through physical, chemical or mechanical means without destroying the target object. Its significant advantage is that the inspection process will not damage the structure, which is particularly suitable for engineering applications that require high reliability and long-term use. The current mainstream non-destructive testing methods include acoustic wave, elastic wave and electromagnetic wave technology, among which electromagnetic testing has attracted widespread attention due to its high efficiency, portability and reliability. Electromagnetic testing technology represented by ground penetrating radar (GPR) analyzes the attenuation of electromagnetic waves by the medium to invert dielectric parameters and thus evaluate the porosity of the material. However, moisture has a significant impact on dielectric properties and can easily interfere with test results. Therefore, how to effectively reduce moisture interference has become a key issue that needs to be urgently addressed in the current electromagnetic non-destructive testing technology for concrete porosity. Summary of the Invention

[0004] The purpose of the present invention is to solve at least one of the above problems and provide a porosity electromagnetic nondestructive testing method, medium and system that eliminate the influence of moisture, so as to solve the problem that GPR testing of concrete porosity in the prior art is easily interfered by moisture. This solution achieves the elimination of the influence of moisture on the calculation during electromagnetic nondestructive testing.

[0005] The purpose of the present invention is achieved through the following technical solutions:

[0006] The first aspect of the present invention discloses a porosity electromagnetic nondestructive testing method for eliminating the influence of moisture, comprising the following steps:

[0007] T1: Prepare specimens with different moisture contents using the medium to be tested and obtain the porosity of each specimen;

[0008] T2: Use ground penetrating radar to obtain the dielectric constant and conductivity of each specimen, and construct a data set containing dielectric constant, conductivity and porosity;

[0009] T3: Water is taken as one of the components of the medium to be tested to derive the dielectric model under water-containing conditions and the conductivity model under unsaturated conditions. The dielectric model and the conductivity model are combined to eliminate the water content parameter in the model and obtain a porosity detection model containing unknown parameters;

[0010] T4: Substituting the data set obtained in step T2 into the porosity detection model obtained in step T3 to fit the unknown parameters, thereby obtaining a porosity detection model that is not affected by moisture;

[0011] T5: The dielectric constant and conductivity of the medium to be measured are obtained by ground penetrating radar, and the porosity of the medium to be measured is calculated by substituting the dielectric constant and conductivity of the medium to be measured into the porosity detection model obtained in step T4.

[0012] Preferably, the method is used for electromagnetic nondestructive testing of concrete porosity.

[0013] Preferably, in step T1, the porosity of each specimen is obtained by a water absorption method.

[0014] Preferably, in step T2,

[0015] According to the time domain signal of the reflected wave collected by the ground penetrating radar, the dielectric constant of the specimen is obtained by calculating the propagation speed of the wave in the specimen;

[0016] The attenuation coefficient is estimated based on the amplitude attenuation of the reflected wave signal, and the conductivity of the specimen is obtained in combination with the dielectric constant.

[0017] Preferably, in step T3, the dielectric model under water conditions is:

[0018]

[0019] Where: ε t represents the dielectric constant of concrete, ε w represents the dielectric constant of water, ε j It represents the dielectric constant of the solid part in the medium to be measured, ξ represents the water content, and φ represents the porosity.

[0020] Preferably, in step T3, the conductivity model is:

[0021]

[0022] Where: σ t represents the electrical conductivity of concrete, σ p represents the conductivity of the pore solution, ξ c represents the critical moisture content, m represents the Archie index, and η represents an unknown parameter.

[0023] Preferably, in step T4, the porosity detection model that is not affected by moisture is:

[0024] φ=Aσ t B +Cε t ′+D;

[0025] Where:

[0026]

[0027] in, ε t represents the dielectric constant of concrete, ε w represents the dielectric constant of water, ε j represents the dielectric constant of the solid part of the medium to be measured, φ represents the porosity, σ t represents the electrical conductivity of concrete, σ p represents the conductivity of the pore solution, ξ c represents the critical moisture content, m represents the Archie index, and η represents an unknown parameter.

[0028] Preferably, the method further comprises:

[0029] T4-1: The least squares method is used to optimize the unknown parameters of the porosity detection model obtained in step T4.

[0030] Preferably, in step T2, the acquired data set is divided into sample set A and sample set B in a ratio of 4:1, wherein sample set A is used to perform steps T3 and T4 to fit the unknown parameters, and sample set B is used to perform step T4-1 to optimize the unknown parameters.

[0031] Preferably, step T4-1 includes the following steps:

[0032] T4-1-1: Define the loss function as the sum of squared errors;

[0033] T4-1-2: Solve the partial derivative of the loss function with respect to the parameters and update the parameters Where α is the learning rate;

[0034] T4-1-3: Iteratively optimize until convergence using the gradient descent method.

[0035] A second aspect of the present invention discloses a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any of the above methods.

[0036] A third aspect of the present invention discloses a porosity electromagnetic nondestructive testing system, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are used to execute any of the methods described above.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] This method utilizes machine learning combined with ground-penetrating radar (GPR) technology to measure concrete porosity using dielectric constant and conductivity parameters. This method not only effectively eliminates the effects of moisture on electromagnetic data but also enables rapid and convenient nondestructive testing of the porosity of existing concrete structures. The method achieves excellent results in precision, with high speed and accuracy. In practical applications, test results can be quickly obtained, and any anomalies detected can be quickly located and remedied, significantly improving the efficiency of concrete porosity testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of the porosity electromagnetic nondestructive testing method;

[0040] Figure 2 Schematic diagram of the process for optimizing the least squares method. DETAILED DESCRIPTION

[0041] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is apparent that the embodiments described are only a portion of the embodiments of the invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0042] In the following description, if there are any matters not covered, they can be implemented using existing technologies or conventional methods in the field.

[0043] The dielectric properties of concrete are one of the electromagnetic properties that characterize concrete materials, and are generally expressed in terms of the dielectric constant ε. Φ Or relative dielectric constant ε r To measure, the smaller the relative dielectric constant, the easier it is for microwaves to penetrate the material. The dielectric properties of non-metallic materials are usually expressed by dielectric constant and dielectric loss (or loss tangent). Dielectric constant is a measure of the material's ability to store electromagnetic energy. The larger the dielectric constant, the stronger the material's ability to store electromagnetic energy; while dielectric loss (or loss tangent) is a measure of the material's loss of electromagnetic energy. Both are functions of the frequency of the electromagnetic wave. Mathematically, the two are written in complex form as complex dielectric constant, that is:

[0044] ε Φ=ε0(ε′-jε″);

[0045] Take the relative dielectric constant as:

[0046] εr=εΦ / ε0=ε′-jε″=ε′(1-j×tanδ);

[0047] Where:

[0048] ε Φ represents the dielectric constant of the propagation medium;

[0049] ε0 represents the dielectric constant of free space;

[0050] ε′ represents the potential energy stored in the material in the form of electromagnetic field;

[0051] j represents the imaginary unit;

[0052] ε″ represents the energy lost in the material as heat;

[0053] Tanδ represents the loss tangent, which is the ratio of electromagnetic wave energy lost in the material as heat energy.

[0054] The imaginary part of the complex dielectric constant can be correlated with the material's conductivity, reflecting the material's loss characteristics and used to evaluate material properties such as conductivity and polarization loss. The relationship between the imaginary part of the complex dielectric constant, ε″, and the material's conductivity, σ, can be expressed by the following formula:

[0055] σ=ωε0ε″;

[0056] Where:

[0057] ω is the angular frequency, ω = 2πf, where f is the frequency of the signal.

[0058] During nondestructive testing using geological radar, electromagnetic waves emitted by the radar instrument are transmitted into the interior of a medium in the form of broadband pulses. After being reflected by the medium and returning to the surface, the radar's receiving antenna receives the echo signal. As electromagnetic waves propagate through a medium, their path, field strength, and waveform vary depending on the dielectric properties and geometric dimensions of the medium. Therefore, studying the dielectric properties of the target is crucial for radar inspection results. Accurately describing the internal structure of the medium requires analyzing the information contained in the radar's received echo signal, making the dielectric properties of the medium a crucial factor in determining radar inspection results.

[0059] The composite dielectric model is a theoretical model used to describe the dielectric properties of multi-component composite materials. It predicts the material's equivalent dielectric response by integrating the dielectric properties, distribution, structure, and proportions of each component. This model can correlate a material's microscopic composition (such as the proportions of solid, liquid, and gas phases) with its macroscopic electromagnetic response, enabling the detection of information such as moisture content, porosity, and internal defects.

[0060] According to the composite dielectric model theory, concrete can be considered a three-phase composite medium consisting of solid, liquid, and gas. However, the traditional composite dielectric model for concrete can only describe a two-phase composite structure of solid and gas, and water, a polar molecule, significantly affects the dielectric constant.

[0061] Nondestructive testing of concrete can monitor its quality and provide a basis for subsequent maintenance. By analyzing the propagation velocity, reflection intensity, and attenuation characteristics of radar waveforms, the dielectric constant and electromagnetic properties are inferred, and the porosity is calculated using a composite dielectric model. However, moisture affects detection accuracy, so it is particularly important to develop electromagnetic nondestructive testing methods for porosity that are not affected by moisture.

[0062] Based on the above principles, the present invention provides an electromagnetic nondestructive testing method for concrete porosity that is not affected by moisture, such as Figure 1 As shown, the method includes the following steps:

[0063] S1: Prepare concrete specimens and collect electromagnetic signal data sets of concrete specimens;

[0064] S101: Preparation of concrete specimens:

[0065] According to GB / T50081-2019 "Standard for Test Methods of Physical and Mechanical Properties of Ordinary Concrete", standard size specimens were made. During the specimen making process, the controlled variable method was used to obtain concrete specimens with different porosities. By controlling the determined water-cement ratio, aggregate and curing conditions:

[0066] Concrete is mixed to form concrete specimens, and then cured to obtain concrete specimens with different porosities. Each specimen is numbered and grouped into three specimens to facilitate the subsequent concrete porosity test and the corresponding data during the ground penetrating radar non-destructive test.

[0067] S102: Testing Ground Penetrating Radar:

[0068] The cured specimens were immersed in water until the weight no longer changed, and the water in the specimens was controlled to evaporate in an oven to obtain concrete specimens with different moisture contents.

[0069] Concrete specimens with different moisture contents were taken out and non-destructive ground penetrating radar testing was performed on them using a 900MHz antenna using the profile method. The echo information was recorded corresponding to the concrete specimen number to obtain an electromagnetic signal dataset.

[0070] S2: collect concrete porosity data sets of concrete specimens;

[0071] Ground penetrating radar detection was performed on groups of concrete specimens with different moisture contents. Porosity tests were conducted using the water absorption method. Porosity information was recorded corresponding to the concrete specimen numbers to obtain a concrete porosity dataset.

[0072] S3: Processing electromagnetic signal dataset and concrete porosity dataset;

[0073] S301: Based on the time-domain signal of the reflected wave collected by the ground-penetrating radar, the dielectric constant of the measured medium is derived by calculating the wave propagation velocity in the medium. The amplitude attenuation of the reflected wave signal is further analyzed to estimate the attenuation coefficient. Combined with the known dielectric constant, the conductivity of the medium is calculated, ultimately obtaining a dataset of the dielectric constant and conductivity of the concrete medium.

[0074] S302: Divide the dielectric constant and conductivity data sets obtained in S301 into two groups at a ratio of 4:1, one of which is marked as sample set A and the other is marked as sample set B;

[0075] S303: Mark the sample set A and the sample set B respectively, so that each set of dielectric constant and conductivity corresponds to the concrete strength obtained from the actual test.

[0076] S4: Derive a concrete porosity detection model and training parameters that are not affected by moisture;

[0077] S401: Taking water as one of the components of concrete medium, derive the dielectric model of concrete under water-containing conditions, namely:

[0078]

[0079] Where:

[0080] ε t represents the dielectric constant of concrete;

[0081] ε w Represents the dielectric constant of water, generally taken as 78;

[0082] ε j Indicates the dielectric constant of the solid part in the medium to be measured;

[0083] ξ represents the moisture content;

[0084] φ represents the porosity;

[0085] make

[0086] S402: Based on Archie's law, derive the conductivity model of concrete in the unsaturated state, namely:

[0087] σ t =ησ p ·(ξ-ξ c ) (m-1) ;

[0088] Where: σ t Indicates the electrical conductivity of concrete;

[0089] σ p represents the electrical conductivity of the pore solution;

[0090] ξ c represents the critical moisture content;

[0091] m represents the Archie index;

[0092] η represents an unknown parameter (empirical parameter).

[0093] S403: The dielectric constant model formula is combined with the conductivity model formula, the moisture content parameter ξ is eliminated, and the model is simplified to obtain a concrete porosity detection model, which includes an unknown parameter η, that is:

[0094] φ=Aσ t B +Cε t ′+D;

[0095] Where:

[0096]

[0097] S404: Using the sample set A obtained in S302 as model training data, inputting the sample set A, fitting unknown parameters, and obtaining a concrete porosity detection model that is not affected by moisture.

[0098] S5: Validate and tune the model;

[0099] S501: Using the sample set B obtained in S302 as an input parameter, input it into the concrete porosity non-destructive testing model obtained in S403 that is not affected by moisture content;

[0100] S502: Compare the output of the concrete porosity nondestructive testing model with the corresponding porosity data in sample set B;

[0101] S503: Based on the comparison results, the least square method is used to optimize the fitting parameters in the concrete porosity nondestructive testing model, such as Figure 2 As shown, the specific steps include:

[0102] S50301: Define the loss function as the sum of squared errors;

[0103] S50302: Solve the partial derivative of the loss function with respect to the parameters and update the parameters θ←θ-α▽L(θ), where α is the learning rate;

[0104] S50303: Optimize the parameters through iterative gradient descent until convergence or the error is small (less than the set threshold).

[0105] The training data set A is fed into the concrete porosity nondestructive testing model to fit the unknown model parameters. The test data set B is then used to verify the fit of the concrete porosity nondestructive testing model. The sum of squares of the model errors is calculated and used as the loss function for subsequent least squares optimization of the model parameters.

[0106] The least squares method is used to optimize the model parameters, and the loss function is defined as the sum of squared errors. The partial derivatives of the loss function with respect to the parameters are solved to find the direction and size of the parameter adjustment. Through the gradient descent iterative algorithm, the parameters are continuously adjusted to minimize the loss function and improve the accuracy of the model.

[0107] S6: Application model;

[0108] A pre-planned inspection path is used on the surface of the water-bearing concrete structure. A ground-penetrating radar (GPR) with a 900 MHz antenna is used to inspect the structure along the planned path. Echo information is obtained and processed according to S301. The processed data is input into the nondestructive porosity testing model for non-water-bearing concrete to obtain the concrete porosity.

[0109] In summary, this method utilizes machine learning combined with ground-penetrating radar (GPR) technology to measure concrete porosity using dielectric constant and conductivity parameters. This method not only effectively eliminates the influence of moisture on electromagnetic data but also enables rapid and convenient nondestructive testing of the porosity of existing concrete structures, achieving excellent results in precision and accuracy. When used in practice, any anomalies detected can be quickly located and remedied, significantly improving the efficiency of concrete porosity testing.

[0110] In other embodiments, the porosity electromagnetic nondestructive testing method can also be used for other multi-component composite media. When conducting test processing, a specimen made of the corresponding medium is used, and when performing calculations, the parameters of the corresponding medium are used.

[0111] The above description of the embodiments is intended to facilitate understanding and use of the invention by those skilled in the art. It will be apparent that those skilled in the art can readily make various modifications to these embodiments and apply the general principles described herein to other embodiments without requiring inventive effort. Therefore, the present invention is not limited to the above-described embodiments. Improvements and modifications made by those skilled in the art based on the disclosure of the present invention, without departing from the scope of the present invention, should be within the scope of protection of the present invention.

Claims

1. A porosity electromagnetic nondestructive testing method for eliminating the influence of moisture, characterized in that: The steps include: T1: Prepare specimens with different moisture contents using the medium to be tested and obtain the porosity of each specimen; T2: Use ground penetrating radar to obtain the dielectric constant and conductivity of each specimen, and construct a data set containing dielectric constant, conductivity and porosity; T3: Water is taken as one of the components of the medium to be tested to derive the dielectric model under water-containing conditions and the conductivity model under unsaturated conditions. The dielectric model and the conductivity model are combined to eliminate the water content parameter in the model and obtain a porosity detection model containing unknown parameters; T4: Substituting the data set obtained in step T2 into the porosity detection model obtained in step T3 to fit the unknown parameters, thereby obtaining a porosity detection model that is not affected by moisture; T5: The dielectric constant and conductivity of the medium to be measured are obtained by ground penetrating radar, and the porosity of the medium to be measured is calculated by substituting the dielectric constant and conductivity of the medium to be measured into the porosity detection model obtained in step T4.

2. The electromagnetic nondestructive testing method for porosity that eliminates the influence of moisture according to claim 1, characterized in that: In step T2, According to the time domain signal of the reflected wave collected by the ground penetrating radar, the dielectric constant of the specimen is obtained by calculating the propagation speed of the wave in the specimen; The attenuation coefficient is estimated based on the amplitude attenuation of the reflected wave signal, and the conductivity of the specimen is obtained in combination with the dielectric constant.

3. The electromagnetic nondestructive testing method for porosity that eliminates the influence of moisture according to claim 1, characterized in that: In step T3, the dielectric model under water conditions is: ； Where: represents the dielectric constant of concrete, represents the dielectric constant of water, Indicates the dielectric constant of the solid part of the medium to be measured, Indicates the moisture content, Indicates porosity.

4. The electromagnetic nondestructive testing method for porosity that eliminates the influence of moisture according to claim 1, characterized in that: In step T3, the conductivity model is: ； Where: represents the electrical conductivity of concrete, represents the conductivity of the pore solution, represents the critical moisture content, represents the Archie index, Indicates unknown parameters.

5. The electromagnetic nondestructive testing method for porosity that eliminates the influence of moisture according to claim 1, characterized in that: In step T4, the porosity detection model that is not affected by moisture is: ； Where: ； ； ； ； in, , , ; represents the dielectric constant of concrete, represents the dielectric constant of water, Indicates the dielectric constant of the solid part of the medium to be measured, represents the porosity, represents the electrical conductivity of concrete, represents the conductivity of the pore solution, represents the critical moisture content, represents the Archie index, Indicates unknown parameters.

6. The electromagnetic nondestructive testing method for porosity that eliminates the influence of moisture according to claim 1, characterized in that: The method further comprises: T4-1: The least squares method is used to optimize the unknown parameters of the porosity detection model obtained in step T4.

7. The electromagnetic nondestructive testing method for porosity to eliminate the influence of moisture according to claim 6, characterized in that: In step T2, the acquired data set is divided into sample set A and sample set B in a ratio of 4:1, wherein sample set A is used to perform steps T3 and T4 to fit the unknown parameters, and sample set B is used to perform step T4-1 to optimize the unknown parameters.

8. The electromagnetic nondestructive testing method for porosity that eliminates the influence of moisture according to claim 6, characterized in that: Step T4-1 includes the following steps: T4-1-1: Define the loss function as the sum of squared errors; T4-1-2: Solve the partial derivative of the loss function with respect to the parameters and update the parameters ,in is the learning rate; T4-1-3: Iteratively optimize until convergence using the gradient descent method.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 8.

10. A porosity electromagnetic nondestructive testing system, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are used to execute the method according to any one of claims 1 to 8.

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