Method for detecting internal quality of concrete in complex environment of diversion tunnel based on elastic waves

Abstract

The invention relates to a diversion tunnel complex environment concrete internal quality detection method based on elastic waves, and belongs to the technical field of concrete engineering nondestructive testing. The concrete lining thickness, the defect depth, the void position and the concrete elasticity modulus are calculated according to the wave velocity of the elastic wave, and the concrete strength can be converted through the concrete elasticity modulus. The method can detect and evaluate the concrete quality of the diversion tunnel lining project in a complex environment, provides targeted measures in the aspects of thicker tunnel lining, humid environment, noise interference and the like, and has the characteristics of convenience, high accuracy, rapidness and high efficiency, so that the concrete quality of the diversion tunnel lining project in the complex environment is scientifically and accurately detected and evaluated, and necessary prevention measures are taken for the tunnel project with hidden dangers. And disasters are avoided, so that safe production and operation of tunnel engineering are guaranteed.

Description

Technical Field

[0001] The invention belongs to the technical field of nondestructive testing of concrete engineering, and in particular relates to an elastic wave technology detection method for the internal quality of concrete in a complex environment of a water diversion tunnel. Background Art

[0002] As vital infrastructure for the national economy, water conservancy projects are constantly underpinned by quality. In recent years, my country has seen significant investment in water diversion projects, with numerous hydraulic tunnels being constructed. Due to the complexities of hydraulic tunnel construction, the quality of tunnel linings directly impacts project safety. When inspecting the quality of tunnel concrete linings, nondestructive testing should be used whenever possible to minimize disruption to the structure.

[0003] At present, the commonly used non-destructive testing methods for water diversion tunnel linings are: rebound method, ultrasonic method, radar method, and impact echo method. These methods cannot be performed in water environment or humid environment. Hydraulic tunnels are basically in contact with mountain surrounding rocks. Especially in areas with developed groundwater, a water-rich environment or a humid environment is inevitably formed in the tunnel, which brings great difficulties to the quality inspection of concrete lining. At present, sampling inspection can only avoid these construction sections, but this situation is more common and exists for a long time in water diversion tunnels. The humid environment section in the tunnel is long and the project volume is large. Avoiding inspection brings hidden dangers to the overall quality and safety of the tunnel. The rebound method is limited to testing the surface strength of concrete and has low accuracy. It cannot be tested in wet areas. Ultrasonic waves are extremely sensitive to moisture and are not suitable for use in water diversion tunnels. Ground penetrating radar is widely used in tunnel detection, but due to the dense steel bars in the lining concrete, generally two layers of steel bars are common, and the steel bars will cause significant interference to electromagnetic waves. In this case, elastic wave technology can be used instead of electromagnetic wave technology to detect the internal quality of concrete. However, in a humid environment, the moisture content of concrete also has a certain impact on the radar electromagnetic wave velocity, elastic wave velocity and spectrum. Currently, concrete cannot be tested in a humid environment. In addition, water diversion tunnels also have problems such as thick linings due to severe over-excavation, high noise from TBM excavation and exhaust ventilation in the tunnel, all of which affect acoustic wave detection. How to detect the quality of water diversion tunnel lining concrete under complex conditions, especially the internal quality (including lining thickness, internal defects and void locations, strength, etc.), is an urgent problem that needs to be solved.

[0004] Therefore, the prior art urgently needs a new technical solution to solve the above problems. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method for detecting the internal quality of concrete in a complex environment of a water diversion tunnel based on elastic waves. By establishing a fitting curve between the concrete moisture content and the elastic wave velocity ratio, the elastic wave velocity of the concrete in the dry state is calculated. The concrete lining thickness, crack depth, defect depth and concrete elastic modulus are calculated from the elastic wave velocity. The concrete strength can be converted from the concrete elastic modulus. The method can solve the problem of non-destructive testing of concrete in areas with dense lining steel bars and in a humid environment, providing a guarantee for the safe operation of the water diversion tunnel project.

[0006] The elastic wave-based method for detecting the internal quality of concrete in a complex environment of a diversion tunnel comprises the following steps, which are performed in sequence:

[0007] Step 1: Conduct elastic wave impact tests on the concrete structure specimens of the water diversion tunnel in a dry state. Using the known specimen thickness and the main frequency measured by the instrument, calculate the elastic wave velocity of the concrete in the dry state. After saturating the specimens, conduct elastic wave impact tests at various moisture contents. Use the natural drying method to test at various moisture contents and calculate the elastic wave velocity of the concrete at each moisture content. Calculate the velocity ratio of each moisture content state to the dry state, establish a fitting curve and residual plot of the concrete moisture content and elastic wave velocity ratio, and evaluate the degree of fit using the residual plot.

[0008] Step 2: Elastic wave testing was conducted at the lining construction site of the water diversion tunnel project. The vibrator used a combination of an impact exciter and manual tapping to rapidly impact the concrete surface, stimulating stress waves within the concrete. A vibration pickup was used to collect longitudinal wave data. The data was then smoothed, filtered, and processed with a BPF. Finally, it was processed with an EMD and Hamming window to reduce the impact of environmental noise during tunnel construction.

[0009] Step 3: Perform Fourier transform (FFT) on the longitudinal wave data processed in step 2 to convert it into a frequency domain signal to form a spectrum graph, and obtain the corresponding peak frequency in the concrete on the spectrum graph;

[0010] Step 4: Using the fitting curve of concrete moisture content and elastic wave velocity ratio obtained in step 1, find out the elastic wave velocity ratio of the concrete moisture content at the construction site, and obtain the actual elastic wave velocity of the concrete moisture content at the construction site after correction;

[0011] Step 5: Calculate the concrete lining thickness, internal defect locations, and voids to be measured using the actual elastic wave velocity obtained in step 4 and the corresponding peak frequency in the concrete obtained in step 3;

[0012] Step 6: The elastic modulus of concrete can be calculated using the actual elastic wave velocity obtained in step 4 and the density of concrete, and the concrete strength can be converted from the elastic modulus.

[0013] The water diversion tunnel concrete structure specimens described in step 1 are formed according to the engineering construction mix ratio and are in a dry state after curing; or the specimens are obtained by core sampling at the construction site.

[0014] The elastic wave test pickup described in step 2 uses a waterproof velocity sensor.

[0015] The actual elastic wave velocity Cp in step 4 实 The calculation formula is:

[0016] Cp 实 =Kc×Cp0

[0017] Where: Kc is the elastic wave velocity ratio, and Cp0 is the elastic wave tested after drying.

[0018] The calculation formula for the concrete lining thickness, internal defect location and void location in step 5 is:

[0019]

[0020] Where H 实 is the actual thickness of the lining or the actual distance of internal defects and voids, in meters; f is the main frequency of the echo, and β is the geometric correction coefficient.

[0021] The calculation formula of the elastic modulus in step 6 is:

[0022]

[0023] Where: υ is Poisson's ratio, E is the elastic model, ρ is the medium density, and Cp is the longitudinal wave velocity.

[0024] The concrete strength described in step 6 is obtained by looking up the GB50010 concrete elastic modulus and strength grade comparison table.

[0025] The above-mentioned design scheme provides the following beneficial effects: A method for testing the internal quality of concrete in complex environments in diversion tunnels based on elastic waves. By establishing a fitting curve between concrete moisture content and elastic wave velocity ratio, the elastic wave velocity of dry concrete is calculated. The elastic wave velocity is then used to calculate the concrete lining thickness, defect depth, void location, and concrete elastic modulus. The concrete elastic modulus can then be used to convert the concrete strength. Targeted measures are also provided for addressing issues such as thick tunnel linings and environmental noise interference. This method is convenient, highly accurate, fast, and efficient, enabling scientific and accurate testing and assessment of the concrete quality of diversion tunnel lining projects in complex environments. This allows for the implementation of necessary preventive measures for tunnel projects with potential hazards, preventing disasters and ensuring the safe production and operation of tunnel projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0027] Figure 1 The figure is a flow chart of the elastic wave-based method for detecting the internal quality of concrete in a complex environment of a diversion tunnel according to the present invention.

[0028] Figure 2 Specific implementation method of the elastic wave-based method for detecting the internal quality of concrete in a complex environment of a water diversion tunnel of the present invention 1. Acceleration spectrum diagram of concrete with different moisture contents.

[0029] Figure 3 Specific implementation method of the internal quality detection method of complex environment concrete in water diversion tunnel based on elastic waves of the present invention 1. The relationship curve between concrete moisture content and wave velocity ratio, a is the fitting curve diagram, and b is the residual diagram.

[0030] Figure 4 Specific implementation method 2 of the elastic wave-based method for detecting the internal quality of concrete in a complex environment of a water diversion tunnel of the present invention is an acceleration spectrum diagram of concrete with different moisture contents.

[0031] Figure 5 Specific implementation method 2 of the present invention for detecting the internal quality of concrete in a complex environment of a water diversion tunnel based on elastic waves is shown in FIG2 . A is a fitting curve diagram, and b is a residual diagram.

[0032] Figure 6 Specific implementation method 3 of the elastic wave-based method for detecting the internal quality of concrete in a complex environment of a water diversion tunnel of the present invention is an acceleration spectrum diagram of concrete with different moisture contents.

[0033] Figure 7 Specific implementation method 3 of the present invention for detecting the internal quality of concrete in a complex environment of a water diversion tunnel based on elastic waves is shown in FIG3 , where a is a fitting curve diagram and b is a residual diagram.

[0034] Figure 8 This is a specific implementation method of the complex environment concrete internal quality detection method of the water diversion tunnel based on elastic waves of the present invention. The relationship curve between the concrete moisture content and the wave velocity ratio in the water-binder ratio range of 0.35-0.55 is shown. a is the fitting curve diagram and b is the residual diagram. DETAILED DESCRIPTION

[0035] Internal quality inspection method of concrete in complex environment of diversion tunnel based on elastic wave, such as Figure 1 As shown, the following steps are included:

[0036] Step 1. Shape the concrete according to the construction mix ratio, and after curing for 28 days (or sampling by drilling cores at the construction site), conduct an elastic wave impact test in a dry state. Based on the known thickness of the specimen and the main frequency measured by the instrument, the elastic wave velocity of the concrete in the dry state is calculated according to the relevant formula. After the specimen is soaked to saturation, start the elastic wave impact test under different moisture contents. Use the natural drying method to test under different moisture contents and calculate the elastic wave velocity of the concrete under different moisture contents. Then calculate the velocity ratio of different moisture contents to the dry state, establish a fitting curve and residual graph of the concrete moisture content and elastic wave velocity ratio, and evaluate the degree of fitting through the residual graph;

[0037] The specific steps of step one are:

[0038] ① According to the construction mix ratio, six specimens of 150×150×150 mm were formed indoors. After 28 days of curing, the specimens were fully soaked and then removed. Alternatively, six core samples of Φ100×150 mm were drilled from the construction site and soaked for 4 days until saturated and then removed.

[0039] ② Conduct elastic wave testing on the specimen (core sample). An accelerometer is placed at the center of the specimen (core sample). The instrument's hammer strikes four points around the sensor, each 3 cm from the sensor. The instrument captures the time-domain signal generated by the vibration and converts it into a frequency-domain signal using a Fast Fourier Transform (FFT), creating a spectrum from which the dominant echo frequency can be read. Acquisition should ensure that at least four valid reference data points are available for each specimen (core sample). If the value of a particular specimen differs from its mean by more than ±15%, that value is discarded and the average of the remaining test data is taken to ensure test accuracy. The average of the six specimens (core samples) is then taken as the test value.

[0040] ③ Dry the specimen (core sample) naturally until the specimen reaches a constant weight, and obtain the specimen dry mass M0; test the specimen (core sample) mass M every 5 to 8 hours. i , and at the same time, perform step ② elastic wave test, and the echo main frequency f can be read out through the spectrum diagram.

[0041] ④ Calculate the elastic wave velocity at different water contents using the echo main frequency read from the spectrum and the known specimen (core sample) thickness. The elastic wave (P wave) velocity Cp is calculated as follows:

[0042]

[0043] Where: Cp is the propagation velocity of P wave, m / s;

[0044] f is the main frequency of the echo, 1 / s;

[0045] d is the thickness of the specimen (core sample), m;

[0046] β is the geometric correction coefficient, which is taken as 0.96.

[0047] ⑤ Divide the elastic wave (P wave) velocity obtained in each test by the elastic wave (P wave) velocity in the dry state (when w is 0) to obtain the wave velocity ratio Kc at each moisture content:

[0048]

[0049] Where: Kc i is the wave velocity ratio at each water content;

[0050] Cpi is the elastic wave (P wave) of the ith test, m / s;

[0051] Cp0 is the elastic wave (P wave) tested after drying, m / s.

[0052] ⑥ Calculate the concrete moisture content w by the mass of the specimen (core sample) weighed each time i :

[0053]

[0054] Where i is the number of tests;

[0055] W i is the moisture content of the i-th test;

[0056] M i is the mass of the specimen in the i-th test.

[0057] ⑦ According to the elastic wave (P wave) velocity ratio Kc under different concrete moisture contents and the corresponding concrete moisture content w, a correlation formula is established to establish a fitting curve and a residual graph. The fitting curve is:

[0058] Kc=a+b×w (4)

[0059] Where a is the intercept;

[0060] b is the slope.

[0061] The residual is the difference between the observed value and the value predicted by the model, and the residual sum of squares is the sum of these squared residuals. The residual sum of squares RSS is obtained through the residual plot.

[0062] ⑧Evaluate the fitting degree of the relationship curve between elastic wave velocity ratio and concrete moisture content.

[0063] The wave velocity ratio is selected instead of the wave velocity to build the curve because the wave velocity is greatly affected by the materials in the concrete. If the wave velocity is used to build the curve, an infinite number of curves need to be built, which is too much work and has limited guiding significance. The wave velocity ratio is used to build a curve for the same type of materials with different moisture contents, which has strong regularity and great guiding significance. Therefore, the present invention uses the wave velocity ratio and the concrete moisture content to build the fitting curve.

[0064] The residual sum of squares (RSS) is a key metric in statistics used to measure how well a model fits the data. It represents the sum of the squared deviations between the model's predicted values ​​and the actual observed values. Specifically, the residual is the difference between the observed value and the value predicted by the model, while the residual sum of squares is the sum of these squared residuals. In statistics, when trying to fit data using a regression line or other model, the smaller the residual sum of squares, the better the model fits the data. This is because a smaller RSS indicates a smaller difference between the model's predicted values ​​and the actual observed values. Conversely, a larger RSS may indicate that the model does not capture the patterns or trends in the data well, potentially indicating overfitting or underfitting. Therefore, the goal of model optimization is to minimize the residual sum of squares and improve the model's predictive accuracy. When the RSS value approaches 0, it means that the model's predicted values ​​are very close to the actual observed values, indicating a high degree of model fit.

[0065] Step 2: Elastic wave testing was conducted on the diversion tunnel lining site using an impact echometer. The vibrator used a combination of a spring-loaded exciter and manual tapping. The vibration pickup was waterproof to facilitate use in water-rich areas of the tunnel.

[0066] Specifically, the impact exciter uses a heavy-duty rebound hammer or an impact pneumatic hammer. Traditional manual tapping can cause arm fatigue or discomfort after prolonged use, affecting inspection accuracy. Furthermore, tapping the diversion tunnel vault is extremely inconvenient, impacting inspection results. To address the weak penetration of manual tapping due to the thick lining of the diversion tunnel, a heavy-duty or impact pneumatic hammer is used instead of manual tapping. A waterproof velocity sensor is used as the vibration pickup.

[0067] Step 3: On-site elastic wave testing: Use an impact exciter to quickly impact the concrete surface to stimulate stress waves inside the concrete. The collected P-wave (longitudinal wave) data is smoothed, filtered, and processed with BPF. It is then processed with EMD and Hamming window to eliminate environmental interference noise during tunnel construction.

[0068] Step 4: Use Fast Fourier Transform (FFT) to convert it into a frequency domain signal to form a spectrum diagram, on which the corresponding peak frequency in the concrete can be obtained.

[0069] Specifically, the Fourier transform decomposes the wave into sine waves and cosine waves. The frequency, amplitude, and phase of the decomposed sine waves or cosine waves are the frequency spectra of the original waveform to be decomposed. The time domain diagram of the elastic wave is transformed by Fourier transform, and the single simple harmonic wave with the largest amplitude after decomposition is taken as the main frequency.

[0070] Step 5: Find out the elastic wave velocity ratio of the concrete moisture content at the construction site through the fitting curve of concrete moisture content and elastic wave velocity ratio in step 1. After correction, get the actual elastic wave velocity of the concrete moisture content at the construction site. The formula is: Cp 实 =Kc×Cp0 (5).

[0071] Step 6: Calculate the unknown concrete lining thickness, internal defect location, and voids by using the corresponding peak frequency in the concrete obtained in step 4 and the actual elastic wave velocity corrected in step 5. The formula is:

[0072] Where: H 实 is the actual thickness of the lining or the actual distance of internal defects and voids, m;

[0073] Step 7: The elastic modulus of concrete can be calculated based on the actual elastic wave velocity corrected in step 5 and the density of concrete, and the concrete strength can be converted from the elastic modulus.

[0074] When a P wave propagates in a three-dimensional medium, its propagation velocity can be expressed by the following formula:

[0075]

[0076] Where: Cp 实 is the longitudinal wave velocity;

[0077] E is the elastic modulus;

[0078] υ is Poisson's ratio;

[0079] ρ is the density of the medium.

[0080] The elastic modulus calculation formula of concrete can be derived from formula (7):

[0081]

[0082] It can be obtained from the corresponding table of concrete elastic modulus and strength grade in "Code for Design of Concrete Structures" GB50010.

[0083] Table 1 Correspondence between concrete elastic modulus and strength grade (MPa)

[0084]

[0085] Example 1:

[0086] ① Six specimens of 150×150×150mm were formed indoors with a water-cement ratio of 0.35. After 28 days of curing, the specimens were fully soaked and taken out.

[0087] ② Conduct elastic wave test on the specimen. Place an acceleration sensor in the center of the specimen and use the hammer provided by the instrument to strike four points around the sensor. Each striking point is 3 cm away from the sensor. Capture the time domain signal generated by the vibration and use fast Fourier transform (FFT) to convert it into a frequency domain signal to form a spectrum diagram. The main frequency of the echo can be read from the spectrum diagram.

[0088] ③ Dry the specimen naturally until the specimen has a constant weight, and obtain the specimen dry mass M0; test the specimen mass M every 5 to 8 hours. i , and elastic wave test is carried out at the same time. The main frequency f of the echo can be read out through the spectrum diagram. Figure 2 .

[0089] ④ Calculate the elastic wave velocity under different moisture contents through the echo main frequency read from the spectrum diagram and the known specimen thickness.

[0090] ⑤ Divide the elastic wave (P wave) velocity obtained in each test by the elastic wave (P wave) velocity in the dry state to obtain the wave velocity ratio Kc at each moisture content. i .

[0091] ⑥ Calculate the concrete moisture content w by the mass of the specimen weighed each time i, .

[0092] ⑦ The calculation results are shown in Table 2. The fitting curve and residual graph are established. Figure 3 , Figure 3 The fitting curve of concrete moisture content and wave velocity ratio can be obtained as intercept a=0.99346±0.4743, slope b=0.01473±0.15461, Figure 3 The residual plot of b shows the residual sum of squares to be 3.75599×10 -4 When the RSS value approaches 0, it means that the predicted value of the model is very close to the actual observed value, which indicates that the model has a high degree of fit.

[0093] Table 2 Elastic wave test results of concrete with a water-binder ratio of 0.35

[0094]

[0095]

[0096] ⑧Evaluate the fitting degree of the relationship curve between elastic wave velocity ratio and concrete moisture content.

[0097] Example 2:

[0098] Take 6 test pieces of 150×150×150mm molded indoors, with a water-binder ratio of 0.45, and carry out other steps as in Example 1. The spectrum is shown in FIG. Figure 4 , the calculation results are shown in Table 3, the fitting curve and residual graph are shown in Figure 5 .

[0099] Table 3 Elastic wave test results of concrete with a water-binder ratio of 0.45

[0100] Concrete moisture content (%) Main frequency Hz Elastic wave velocity (m / s) Wave speed ratio 0.00 10835 3386 1.000 0.56 10854 3392 1.002 0.98 10918 3412 1.008 1.63 10931 3416 1.009 2.51 11094 3467 1.024 3.12 11152 3485 1.029 3.92 11247 3513 1.038 4.15 11507 3596 1.062 4.83 11696 3655 1.079 5.62 11914 3723 1.100

[0101] Figure 5 The fitting curve of concrete moisture content and wave velocity ratio can be obtained as intercept a=0.98806±0.57223, slope b=0.01722±0.17456, Figure 5 The residual plot of b shows the residual sum of squares to be 10.4×10 -4 When the RSS value approaches 0, it means that the predicted value of the model is very close to the actual observed value, which indicates that the model has a high degree of fit.

[0102] Example 3:

[0103] Six 150×150×150mm specimens were formed indoors, with a water-binder ratio of 0.55. Other procedures were carried out as in Example 1. The spectrum is shown in the figure. Figure 6 , the calculation results are shown in Table 4, the fitting curve and residual graph are shown in Figure 7 .

[0104] Table 4 Elastic wave test results of concrete with a water-binder ratio of 0.55

[0105] Concrete moisture content (%) Main frequency Hz Elastic wave velocity (m / s) Wave speed ratio 0.00 10624 3320 1.000 0.26 10669 3334 1.004 0.69 10704 3345 1.008 1.23 10845 3389 1.021 2.05 10931 3416 1.029 2.88 11174 3492 1.052 3.24 11258 3518 1.060 4.35 11357 3549 1.069 5.07 11546 3608 1.087 6.02 11718 3662 1.103

[0106] Figure 7 The fitting curve of concrete moisture content and wave velocity ratio can be obtained as intercept a=0.99876±0.51852, slope b=0.01727±0.15932, Figure 3 The residual plot of b shows the residual sum of squares to be 1.01487×10 -4 When the RSS value approaches 0, it means that the predicted value of the model is very close to the actual observed value, which indicates that the model has a high degree of fit.

[0107] The residual sum of squares is an important metric in statistics used to measure how well a model fits the data. It represents the sum of the squared deviations between the model's predicted values ​​and the true observed values. Specifically, the residual is the difference between the observed value and the value predicted by the model, while the residual sum of squares is the sum of these squared residuals.

[0108] In statistics, when fitting data using a regression line or other model, the smaller the residual sum of squares (RSS), the better the model fits the data. This is because a smaller RSS means the difference between the model's predicted values ​​and the actual observed values ​​is smaller. Conversely, a larger RSS may indicate that the model does not capture the patterns or trends in the data well, potentially exhibiting overfitting or underfitting issues. Therefore, the goal of model optimization is to minimize the residual sum of squares and improve the model's predictive accuracy. When the RSS value approaches 0, it means that the model's predicted values ​​are very close to the actual observed values, indicating a high degree of model fit.

[0109] From the three types of concrete with different water-binder ratios in Examples 1 to 3, the fitting degree of the curve between the elastic wave velocity ratio and the concrete moisture content is relatively high. The different moisture contents of the three types of concrete are combined together to evaluate the fitting degree of the curve between the elastic wave velocity ratio and the concrete moisture content in the water-binder ratio range of 0.35-0.55.

[0110] Figure 8 The fitting curve of concrete moisture content and wave velocity ratio can be obtained as intercept a=0.99203±0.32902, slope b=0.01672±0.09982, Figure 8 The residual plot of b shows the residual sum of squares (RSS) of 0.00241. When the RSS value approaches 0, it means that the model's predicted value is very close to the actual observed value, indicating that the model has a high degree of fit. The fitting curve of concrete moisture content and wave velocity ratio is:

[0111] Wave velocity ratio Kc=0.99203+0.01672w(9)

[0112] Figure 8 It shows that the elastic wave velocity ratio of the three types of concrete has a high degree of fit with the concrete moisture content. In the range of water-binder ratio 0.35-0.55, the elastic wave velocity of concrete can be corrected using the fitting curve formula (9), thereby obtaining its elastic wave velocity in the dry state. After correction, the thickness, internal defect location, void location, elastic modulus and strength of the lining concrete of the water diversion tunnel to be tested can be accurately calculated according to steps 2 to 7.

[0113] This technical solution provides a fitting curve for the ratio of concrete moisture content to elastic wave velocity, allowing the elastic wave velocity of dry concrete to be calculated. This elastic wave velocity is then used to calculate the concrete lining thickness, defect depth, and concrete elastic modulus. The concrete elastic modulus can then be used to convert the concrete strength. This method also provides targeted measures for thick tunnel linings and environmental noise interference. It is convenient, accurate, fast, and efficient, enabling scientific and accurate testing and assessment of concrete quality in diversion tunnel lining projects in complex environments. This allows for the implementation of necessary preventive measures for tunnel projects with potential hazards, preventing disasters and ensuring the safe production and operation of tunnel projects. The method has broad application prospects.

[0114] It will be understood that the present invention is described by way of some embodiments, and it will be appreciated by those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are intended to be protected by the present invention.

Claims

1. The elastic wave-based method for detecting the internal quality of concrete in complex environments of a diversion tunnel is characterized by: The process includes the following steps, which are performed in sequence: Step 1: Conduct elastic wave impact tests on the concrete structure specimens of the water diversion tunnel in a dry state. Using the known specimen thickness and the main frequency measured by the instrument, calculate the elastic wave velocity of the concrete in the dry state. After saturating the specimens, conduct elastic wave impact tests at various moisture contents. Use the natural drying method to test at various moisture contents and calculate the elastic wave velocity of the concrete at each moisture content. Calculate the velocity ratio of each moisture content state to the dry state, establish a fitting curve and residual plot of the concrete moisture content and elastic wave velocity ratio, and evaluate the degree of fit using the residual plot. Step 2: Elastic wave testing was conducted at the lining construction site of the water diversion tunnel project. The vibrator used a combination of an impact exciter and manual tapping to rapidly impact the concrete surface, stimulating stress waves within the concrete. A vibration pickup was used to collect longitudinal wave data. The data was then smoothed, filtered, and processed with a BPF. Finally, it was processed with an EMD and Hamming window to reduce the impact of environmental noise during tunnel construction. Step 3: Perform Fourier transform (FFT) on the longitudinal wave data processed in step 2 to convert it into a frequency domain signal to form a spectrum graph, and obtain the corresponding peak frequency in the concrete on the spectrum graph; Step 4: Using the fitting curve of concrete moisture content and elastic wave velocity ratio obtained in step 1, find out the elastic wave velocity ratio of the concrete moisture content at the construction site, and obtain the actual elastic wave velocity of the concrete moisture content at the construction site after correction; Step 5: Calculate the concrete lining thickness, internal defect locations, and void locations to be measured using the actual elastic wave velocity obtained in step 4 and the corresponding peak frequency in the concrete obtained in step 3; Step 6: The elastic modulus of concrete can be calculated using the actual elastic wave velocity obtained in step 4 and the density of concrete, and the concrete strength can be converted from the elastic modulus.

2. The method for detecting the internal quality of concrete in a complex environment of a water diversion tunnel based on elastic waves according to claim 1 is characterized by the following steps: The water diversion tunnel concrete structure test specimen is formed according to the engineering construction mix ratio and is a dry state test specimen after curing; or the test specimen is obtained by core sampling at the construction site.

3. The elastic wave-based method for detecting the internal quality of concrete in complex environments of a diversion tunnel according to claim 1 is characterized by: The elastic wave test pickup described in step 2 uses a waterproof velocity sensor.

4. The elastic wave-based method for detecting the internal quality of concrete in complex environments of a diversion tunnel according to claim 1 is characterized by: The actual elastic wave velocity Cp in step 4 实 The calculation formula is: Cp 实 =Kc×Cp0 Where: Kc is the elastic wave velocity ratio, and Cp0 is the elastic wave tested after drying.

5. The elastic wave-based method for detecting the internal quality of concrete in complex environments of a diversion tunnel according to claim 1 is characterized by: The calculation formula for the concrete lining thickness, internal defect location and void location in step 5 is: Where H 实 The actual thickness of the lining or the actual distance of internal defects and voids, in meters; f is the main frequency of the echo, and β is the geometric correction coefficient.

6. The elastic wave-based method for detecting the internal quality of concrete in complex environments of a diversion tunnel according to claim 1 is characterized by: The calculation formula of the elastic modulus in step 6 is: Where: υ is Poisson's ratio, E is the elastic modulus, ρ is the medium density, and Cp is the longitudinal wave velocity.

7. The elastic wave-based method for detecting the internal quality of concrete in complex environments of a diversion tunnel according to claim 1 is characterized by: The concrete strength described in step 6 is obtained by looking up the GB50010 concrete elastic modulus and strength grade comparison table.

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