A method and system for detecting the compactness of a concrete structure in a bridge

Abstract

The application provides a kind of compactness detection method and system of concrete structure in bridge, it is related to concrete compactness detection technical field, the application can effectively inhibit background noise in concrete box girder by differential processing to echo signal;Further modal decomposition is carried out, high-frequency noise is identified and removed, can greatly reduce the interference brought by steel reinforcement cage, realize the purification of signal;Further, the identification method combining energy intensity and phase characteristics can reduce the influence of signal attenuation on evaluation results, so that the echo signals of deep compactness area and shallow defect area, which are easily confused in energy performance, can be distinguished and identified, thereby distinguishing bellows and cavities, enhancing the overall detection accuracy of the detection system, and the ability to resist false positives and omissions.

Description

Technical Field

[0001] This invention relates to the field of concrete density testing technology, specifically to a method and system for testing the density of concrete structures within bridges. Background Technology

[0002] For concrete box girders used in bridges, in addition to the steel reinforcement skeleton, corrugated pipes made of metal or plastic are usually pre-embedded inside. Steel strands are placed inside the corrugated pipes, and then grouting is done using pure cement grout or other special grouting materials. If the grouting is not dense enough, the steel strands will corrode, so it is necessary to test its density. However, when using the traditional impact echo method for testing, the dense steel reinforcement skeleton will generate scattered noise, greatly affecting the final test results. At the same time, because the corrugated pipes also generate echo signals, and stress waves attenuate during propagation, the echo signals from deep, dense areas and shallow defect areas tend to be similar in energy characteristics. Traditional detection methods that rely solely on amplitude or frequency characteristics cannot fundamentally distinguish between them, easily leading to misjudgments or missed detections in practical engineering.

[0003] In the prior art, CN107607065A discloses a method for analyzing impact echo signals based on variational mode decomposition, including: 1) selecting measurement parameters and equipment operating parameters according to the requirements of the field measurement environment, and acquiring impact echo signals; 2) setting parameters in variational mode decomposition based on the impact echo signals; 3) decomposing the acquired impact echo signals into several intrinsic modulus functions using the variational mode decomposition method, and solving the variational problem; 4) using Hilbert transform to obtain the Hilbert time spectrum of the intrinsic modulus functions; 5) integrating the Hilbert time spectra of different frequencies in the time domain to obtain the final marginal spectrum. Although this scheme can identify defects in concrete structures through impact echo signals, it still relies on frequency characteristics. It is difficult to distinguish defects from corrugated pipes in concrete box girders, and it cannot eliminate noise interference from the steel reinforcement cage, resulting in limited applicability in complex environments such as bridge inspection.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for detecting the density of concrete structures within bridges, in order to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for detecting the density of concrete structures within bridges, comprising the following steps: S1: Conduct impact echo tests on the concrete box girder of the bridge, collect echo signals at each detection point during the test, and perform differential processing on the echo signals and the preset reference signals to obtain the corresponding differential enhancement signals; S2: Perform mode decomposition on the differential enhancement signal to obtain several sets of intrinsic mode components with different center frequencies. Then, based on the center frequencies, filter out the high-frequency noise components in the intrinsic mode components and remove them. Reconstruct the remaining intrinsic mode components to obtain a pure reflection signal. S3: Perform Hilbert transform on the pure reflected signal to construct a complex analytic signal, then deduce the instantaneous phase of the complex analytic signal at any time according to the inverse trigonometric function, and finally obtain the amplitude envelope and phase change rate of the complex analytic signal. S4: Within a preset time window, calculate the total energy of the complex analytical signal, then generate a density index based on the amplitude envelope and phase change rate, compare the density index with a preset index threshold, and combine the total energy and the comparison result to jointly determine whether there are voids in the concrete box girder.

[0007] Preferably, step S1 includes: A signal source is set on the surface of the concrete box girder, and several sets of detection points are arranged in a ring around the signal source. The signal source is used to emit impact signals to the concrete box girder, and the detection points are used to receive echo signals. The echo signals at each detection point are subtracted from the preset reference signal to generate a differential enhancement signal. The reference signal is the echo signal collected during the impact echo test in the pure concrete area.

[0008] Preferably, when performing mode decomposition on the differential enhancement signal, an adaptive variational mode decomposition algorithm is used. In this algorithm, the number of groups of decomposed intrinsic mode components and the preset penalty factor are both obtained by adaptive optimization. When the center frequency of an intrinsic mode component is higher than a preset frequency threshold, the intrinsic mode component is defined as high-frequency noise.

[0009] Preferably, the logic of the adaptive algorithm is as follows: First, the search space and search step size are set for the number of intrinsic mode components and the penalty factor, respectively; Next, modal decomposition is performed sequentially under each combination of group number and penalty factor, and the envelope entropy of each intrinsic modal component is calculated; Finally, the optimization criterion was minimized to obtain the optimal combination of parameters for the number of groups and the penalty factor.

[0010] Preferably, in step S3, the amplitude envelope is the absolute value of the complex analytic signal, and the phase change rate is the first derivative of the instantaneous phase with respect to time.

[0011] Preferably, the total energy of the complex analytic signal is the integral of the amplitude envelope of the complex analytic signal over time within a preset time window. The density index is obtained by weighted integration of the amplitude envelope and phase change rate of the complex analytic signal within the preset time window and then comparing it with the total energy. The density index is positively correlated with the amplitude envelope and negatively correlated with the phase change rate.

[0012] Preferably, when performing a weighted integration of the amplitude envelope and the phase change rate, the integrand includes a weight term and a normalization term, and the integration variable is time. The weight term is the amplitude envelope, and the normalization term is in the form of an exponential function. The base of the exponential function is the natural logarithm, and the exponent is the negative of the absolute value of the phase change rate.

[0013] Preferably, the logic for determining whether there are voids in a concrete box girder is as follows: First, the total energy of the complex analytical signal is compared with a preset energy threshold. If the total energy of the complex analytical signal is less than the preset energy threshold, the complex analytical signal at the detection point is considered weak, which is a low reflection zone. If the total energy of the complex analytical signal is greater than the preset energy threshold, then the detection point is considered to be a composite area of ​​concrete, steel bars, and corrugated pipe, and the following steps are continued: The density index is compared with a preset index threshold. When the density index is greater than the preset index threshold, it is considered that the complex analytical signal at the detection point is strong and the phase change rate is low, which is a dense composite region. When the density index is less than the preset index threshold, it is considered that the complex analytical signal at the detection point is strong, but the phase change rate is high, indicating a composite region with voids.

[0014] A system for testing the density of concrete structures within bridges, the system being used to perform the aforementioned testing method, specifically comprising: The data acquisition module is used to conduct impact echo tests on the concrete box girder of the bridge, acquire echo signals during the test, and perform differential processing on the echo signals and a preset reference signal to obtain a differential enhancement signal. The data filtering module is used to perform mode decomposition on the differential enhancement signal to obtain several sets of intrinsic mode components with different center frequencies. Then, based on the center frequencies, the part representing high-frequency noise in the intrinsic mode components is filtered out and removed. The remaining intrinsic mode components are then reconstructed to obtain a pure reflection signal. The data analysis module is used to perform Hilbert transform on the pure reflected signal to construct a complex analytic signal, and then deduce the instantaneous phase of the complex analytic signal at any time according to the inverse trigonometric function. Finally, the amplitude envelope and phase change rate of the complex analytic signal are obtained. The data judgment module is used to calculate the total energy of the complex analytical signal within a preset time window, generate a density index based on the amplitude envelope and phase change rate, compare the density index with a preset index threshold, and combine the total energy and the comparison result to jointly determine whether there are voids in the concrete box girder.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention effectively suppresses background noise in concrete box girders by differentially processing the echo signal; furthermore, it performs mode decomposition to identify and eliminate high-frequency noise, greatly reducing interference from the steel reinforcement cage and purifying the signal; and by employing an identification method combining energy intensity and phase characteristics, it reduces the impact of signal attenuation on the evaluation results, enabling the differentiation and identification of echo signals from deep, dense areas and shallow defect areas, which are easily confused in terms of energy performance. This distinguishes between corrugated pipes and voids, enhancing the overall detection accuracy of the detection system and its ability to combat false alarms and missed alarms. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a schematic diagram of the module structure of the detection system in this invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] Example: Please see Figure 1 The present invention provides a technical solution: A method for detecting the density of concrete structures within bridges, comprising the following steps: S1: Conduct impact echo tests on the concrete box girder of the bridge, collect echo signals at each test point during the test, and perform differential processing on the echo signals and the preset reference signals to obtain the corresponding differential enhancement signals.

[0020] Step S1 includes: A signal source is set on the surface of the concrete box girder, and several sets of detection points are arranged in a ring around the signal source. The signal source is used to emit impact signals to the concrete box girder, and the detection points are used to receive echo signals. The echo signals at each detection point are subtracted from the preset reference signal to generate a differential enhancement signal. The reference signal is the echo signal collected during the impact echo test in the pure concrete area.

[0021] In this step, the signal source can use a transmitting transducer to emit stress waves into the interior of the concrete box girder, and receiving transducers are set up at each detection point to obtain the echo signal. When acquiring the reference signal, the pure concrete area can be a pre-placed pure concrete specimen. By subtracting the reference signal from the pure concrete area, the inherent oscillations caused by factors such as aggregates inside the concrete and sensor coupling can be canceled out. The resulting differential enhanced signal is essentially the characteristic terms caused by the steel reinforcement skeleton, corrugated pipes, grouting material inside the corrugated pipes, and any possible voids inside the concrete box girder. This is equivalent to removing the background and thus amplifying these features. Moreover, the ring array method can capture echo signals from multiple angles, thereby avoiding blind spots during the detection process.

[0022] S2: Perform mode decomposition on the differential enhancement signal to obtain several sets of intrinsic mode components with different center frequencies. Then, based on the center frequencies, filter out the high-frequency noise components in the intrinsic mode components and remove them. Finally, reconstruct the remaining intrinsic mode components to obtain a pure reflection signal.

[0023] When performing mode decomposition on the differential enhancement signal, an adaptive variational mode decomposition algorithm (i.e., VMD algorithm) is used, and the number of eigenmode components decomposed in this algorithm is... and preset penalty factors All were obtained using an adaptive algorithm. When the center frequency of the intrinsic mode component is higher than the preset frequency threshold, the intrinsic mode component is defined as high-frequency noise.

[0024] The core logic of the VMD algorithm is to assume differential enhancement signal It consists of several different signal components It consists of (i.e., intrinsic modal components). Since the echo signals caused by the steel reinforcement cage in bridge inspection are usually concentrated at high frequencies, while the echo signals from corrugated pipes and cavities are usually concentrated at mid-to-low frequencies, this method can be used to eliminate the influence of the steel reinforcement cage on the inspection results.

[0025] Specifically, the VMD algorithm includes the following steps: First, perform a Hilbert transform on each intrinsic mode component to obtain its one-sided spectrum, calculated as follows: In the formula Represents the Dirac function, This represents the convolution operator. Indicates the first Each intrinsic mode component Indicates time, Represents the imaginary unit. Indicates the index of the local oscillator modal component; To calculate this component at its center frequency The bandwidth at that point is such that the spectrum of the component needs to be shifted to near the baseband (0Hz), therefore it needs to be multiplied by the vector of the center frequency in the complex plane, i.e.: Then, using the L2 norm to calculate the bandwidth of each component, the final variational constraint model can be expressed as: Its constraints are expressed as: That is, the sum of all intrinsic mode components equals the differential enhancement signal before decomposition. In the formula... Indicates time Find the partial derivative. This indicates that the L2 norm of the expression within the parentheses is being calculated.

[0026] In practical engineering applications, the Lagrange multiplier operator needs to be introduced to solve this variational constraint model. and a penalty factor The variational constrained model is transformed into a variational unconstrained model using the augmented Lagrangian function, the expression of which is: In the formula This represents the augmented Lagrangian function. Since the above function expression is in standard form, its specific construction and solution process will not be elaborated upon here; it is only used to illustrate the number of eigenmode components. and preset penalty factors The relationship with the VMD model. In a conventional VMD model, these two parameters are usually specified based on expert experience. However, they are strongly correlated with the decomposition effect of the VMD model. For example, if the number of groups and the penalty factor are set too small, the noise separation generated by the steel reinforcement skeleton will not be thorough enough; if the number of groups and the penalty factor are set too large, the echo signal will be excessively fragmented. Therefore, an adaptive algorithm is needed for optimization, the logic of which is as follows: First, the search space and search step size are set for the number of intrinsic mode components and the penalty factor, respectively; Next, modal decomposition is performed sequentially for each combination of group number and penalty factor, and the envelope entropy of each intrinsic modal component is calculated using the following formula: In the formula Indicates the first The envelope entropy of each intrinsic mode component. This represents the number of signal samples (because of time). In practical engineering applications, it is discrete, meaning that a signal is acquired at each moment, so it can also be equivalent to a signal index. The envelope sequence after normalization of the intrinsic mode component is represented by the following formula: In the formula The envelope of the intrinsic mode component can be obtained by performing a Hilbert transform on the intrinsic mode component.

[0027] The smaller the envelope entropy, the stronger the impulse nature of the signal and the higher the signal-to-noise ratio. Therefore, minimizing the average envelope entropy is used as the optimization criterion to obtain the optimal parameter combination of the number of groups and the penalty factor. The objective function can be expressed as: Since the echo signals from the steel reinforcement cage are mostly scattered signals, which are disordered and random, their envelope entropy is large. In contrast, the echo signals from the corrugated pipe and voids are mostly pulsed reflection signals with smaller envelope entropy. Therefore, by using an adaptive algorithm for optimization, the VMD algorithm can find an ordered decomposition method, thereby greatly improving the accuracy of its decomposition results. When filtering the decomposed intrinsic mode components, the preset frequency threshold can be determined based on the center frequency of the stress wave emitted by the signal source, generally set between 1.5 and 2.5 times the center frequency of the signal source. The finally filtered pure reflection signal can be expressed as... .

[0028] S3: Perform a Hilbert transform on the pure reflected signal to construct a complex analytic signal. Its expression is: In the formula The complex part of a complex analytic signal is represented by a pure reflected signal. We obtain the result by performing a Hilbert transform. This represents the absolute value of a complex analytic signal, which is also the magnitude of the signal. Indicates time The instantaneous phase below; Then, by using the inverse trigonometric function, the instantaneous phase of the complex analytic signal at any given time can be derived, and its calculation formula is: Finally, the amplitude envelope and phase change rate of the complex analytic signal are obtained.

[0029] In step S3, the amplitude envelope is the absolute value of the complex analytic signal, i.e. The rate of phase change is the first derivative of the instantaneous phase with respect to time, i.e. .

[0030] It is understandable that when a sound wave signal is reflected at the interface between two media, the reflection coefficient... Depending on the acoustic impedance of the two media, the calculation formula is: In the formula , These represent the acoustic impedances of the interfaces between the two media.

[0031] Because the wall thickness of corrugated pipes is usually smaller than the wavelength of the stress wave used (when the nominal diameter of the corrugated pipe is ≤500mm, the wall thickness of stainless steel corrugated pipes is usually 0.2~1.5mm; when the diameter is >500mm, the wall thickness of stainless steel corrugated pipes is usually 1.5~3.0mm; the wall thickness of plastic corrugated pipes is usually only 2~3mm; the wavelength of the stress wave used for testing is usually between 50mm~100mm), when the grouting inside the corrugated pipe is dense, the wall of the corrugated pipe can be regarded as a transitional thin layer, and the entire corrugated pipe can be regarded as a whole, exhibiting the characteristics of a continuous medium. Although there will still be reflection at this time, due to the acoustic impedance of concrete (approximately...), The acoustic impedance of the grout inside the corrugated pipe is similar to that of the grout (because the main material is concrete), and the reflection coefficient is a positive number. The reflected wave generated by the pipe wall is weak and does not undergo phase reversal. Conversely, if the grout inside the corrugated pipe is not dense enough, an air interface (i.e., voids) will exist between the corrugated pipe and the grout. Since the acoustic impedance of air is almost negligible, the reflection coefficient is approximately -1, resulting in a stronger reflected wave and a 180° phase reversal.

[0032] In simple terms, because the walls of a corrugated pipe are relatively thin, its reflection characteristics are determined by both the pipe wall and the medium inside. When the grouting is tight, the inside of the pipe wall contains grout; when the grouting is loose, the inside of the pipe wall contains air. Therefore, although reflection will occur in both cases (because the acoustic impedance of a corrugated pipe is approximately...),... (greater than the acoustic impedance of concrete), but when the grouting is dense, there will be no phase reversal of reflection, while when the grouting is not dense, phase reversal will occur, thus distinguishing between corrugated pipes and voids.

[0033] Therefore, it is understandable that, since signal strength attenuates with propagation distance (i.e., depth), the echo signals reflected from shallower corrugated pipes and those reflected from deeper cavities may have similar signal strengths, making them difficult to distinguish using traditional identification methods. However, this scheme employs an identification method that combines signal strength with phase characteristics, which reduces this uncertainty and significantly improves the accuracy of cavity identification.

[0034] S4: Within a preset time window, calculate the total energy of the complex analytical signal, then generate a density index based on the amplitude envelope and phase change rate, compare the density index with a preset index threshold, and combine the total energy and the comparison result to jointly determine whether there are voids in the concrete box girder.

[0035] The total energy of a complex analytic signal is the integral of the amplitude envelope of the complex analytic signal over time within a preset time window. The density index is obtained by weighted integration of the amplitude envelope and phase change rate of the complex analytic signal within a preset time window and then comparing it with the total energy. The density index is positively correlated with the amplitude envelope and negatively correlated with the phase change rate.

[0036] When performing a weighted integration of the amplitude envelope and the rate of phase change, the integrand includes a weight term and a normalization term, with time as the integration variable. The weight term is the amplitude envelope, and the normalization term is in the form of an exponential function. The base of the exponential function is the natural logarithm, and the exponent is the negative of the absolute value of the rate of phase change.

[0037] Density Index The expression is: In the formula , These represent the start and end times of the time window, respectively. From the function expression of the density index, it can be seen that when voids exist, the phase flips, and the instantaneous phase change rate increases sharply, thus rapidly lowering the numerator of the function expression and significantly reducing the density index. Simultaneously, the denominator is the total energy of the complex analytic signal, which is equivalent to normalizing the numerator to avoid the influence of dimensions, depth attenuation, and other factors on the result. For example, if a void at detection point 1 causes an echo signal, how would the density index at that point be calculated? hour, Larger The density is relatively small; at detection point 2, there is an echo signal caused by the reflection from the corrugated pipe. Calculate the density index of this point. hour, Smaller If the values ​​are relatively large, and no normalization is performed, the values ​​of the two (equivalent to the numerator) may be similar, thus confusing the judgment results.

[0038] Furthermore, a void is a geometric space with a certain volume, which can cause persistent phase disturbances across the entire reflection envelope. Therefore, integrating the time window is used, which is equivalent to comprehensively evaluating all performance within the time window. If it is just a momentary abnormal interference point, after integration and smoothing, its impact on the overall density index is minimal, thus avoiding misjudgments caused by random outliers during the acquisition process.

[0039] The logic for determining whether there are voids in a concrete box girder is as follows: First, the total energy of the complex analytical signal is compared with a preset energy threshold. If the total energy of the complex analytical signal is less than the preset energy threshold, the complex analytical signal at the detection point is considered weak, which is a low reflection area, that is, an area with basically no echo signal, usually a pure concrete area, which is not within the recognition range of this embodiment. If the total energy of the complex analytical signal is greater than the preset energy threshold, it means that the signal strength of the complex analytical signal is strong, that is, there is an echo signal. Then, the detection point is considered to be a composite area of ​​concrete, steel bars, and corrugated pipe, and the following steps are continued: The density index is compared with a preset index threshold. When the density index is greater than the preset index threshold, it is considered that the complex analytical signal at the detection point is strong and the phase change rate is low, which is a dense composite region. When the density index is less than the preset index threshold, it is considered that the complex analytical signal at the detection point is strong, but the phase change rate is high, indicating a composite region with voids.

[0040] The energy threshold can be set based on expert experience, such as the average energy of the reference signal from the pure concrete specimen in step S1; alternatively, it can be determined based on the actual echo signal acquired. Specifically, the time-axis pre-fetching method can be used to acquire the time period before the first pulse in the echo signal, and then the root mean square of the signal energy within that time period can be calculated as the energy threshold. This is because during that time period, the echo signal reflects not the reflections caused by factors such as the reinforcing steel frame, corrugated pipe, or voids, but rather the reflections caused by factors such as electronic noise and environmental influences. Either method can be chosen.

[0041] In this step, an initial screening is performed using an energy threshold to ensure that the received echo signal has sufficient energy and is not low-energy noise. Then, a density index is used for judgment. This means that if an echo signal is present and the phase is stable, the detection point is judged as a dense composite region. If an echo signal is present and the phase fluctuates violently, the detection point is judged as a composite region with voids. This greatly reduces the impact of noise on the judgment results and improves the overall anti-false alarm capability of the system.

[0042] Please see Figure 2 The present invention also provides a compaction testing system for concrete structures inside bridges, used to perform the above-mentioned testing method, specifically including: a data acquisition module, a data filtering module, a data analysis module, and a data judgment module.

[0043] The data acquisition module is used to conduct impact echo tests on the concrete box girders of bridges, collect echo signals during the test, and perform differential processing on the echo signals and preset reference signals to obtain differential enhancement signals. The data filtering module is used to perform mode decomposition on the differential enhancement signal to obtain several sets of intrinsic mode components with different center frequencies. Then, based on the center frequencies, the high-frequency noise components in the intrinsic mode components are filtered out and removed. The remaining intrinsic mode components are then reconstructed to obtain a clean reflection signal. The data analysis module is used to perform Hilbert transform on the pure reflected signal to construct a complex analytic signal, and then deduce the instantaneous phase of the complex analytic signal at any time according to the inverse trigonometric function. Finally, the amplitude envelope and phase change rate of the complex analytic signal are obtained. The data judgment module is used to calculate the total energy of the complex analytical signal within a preset time window, and then generate a density index based on the amplitude envelope and phase change rate. The density index is compared with a preset index threshold, and the total energy and the comparison result are combined to jointly determine whether there are voids in the concrete box girder.

[0044] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0045] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0046] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0047] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for detecting the density of concrete structures within bridges, characterized in that, The specific steps include: S1: Conduct impact echo tests on the concrete box girder of the bridge, collect echo signals at each detection point during the test, and perform differential processing on the echo signals and the preset reference signals to obtain the corresponding differential enhancement signals; S2: Perform mode decomposition on the differential enhancement signal to obtain several sets of intrinsic mode components with different center frequencies. Then, based on the center frequencies, filter out the high-frequency noise components in the intrinsic mode components and remove them. Reconstruct the remaining intrinsic mode components to obtain a pure reflection signal. When performing mode decomposition on the differential enhancement signal, an adaptive variational mode decomposition algorithm is used. In this algorithm, the number of groups of decomposed intrinsic mode components and the preset penalty factor are both obtained by adaptive optimization. When the center frequency of an intrinsic mode component is higher than the preset frequency threshold, the intrinsic mode component is defined as high-frequency noise. S3: Perform Hilbert transform on the pure reflected signal to construct a complex analytic signal, then deduce the instantaneous phase of the complex analytic signal at any time according to the inverse trigonometric function, and finally obtain the amplitude envelope and phase change rate of the complex analytic signal. S4: Within a preset time window, calculate the total energy of the complex analytical signal, then generate a density index based on the amplitude envelope and phase change rate, compare the density index with a preset index threshold, and combine the total energy and the comparison result to jointly determine whether there are voids in the concrete box girder. The total energy of the complex analytical signal is the integral of the amplitude envelope of the complex analytical signal over time within a preset time window. The density index is obtained by weighted integration of the amplitude envelope and phase change rate of the complex analytical signal within a preset time window and then comparing it with the total energy. The density index is positively correlated with the amplitude envelope and negatively correlated with the phase change rate. When performing a weighted integration of the amplitude envelope and the rate of phase change, the integrand includes a weight term and a normalization term, with time as the integration variable. The weight term is the amplitude envelope, and the normalization term is in the form of an exponential function. The base of the exponential function is the natural logarithm, and the exponent is the negative of the absolute value of the rate of phase change. Density Index The expression is: In the formula , These represent the start and end times of the time window, respectively. Represents a complex analytic signal. Indicates time, Indicates the time complexity of the complex analytic signal The instantaneous phase below.

2. The method for detecting the density of concrete structures within bridges according to claim 1, characterized in that: Step S1 includes: A signal source is set on the surface of the concrete box girder, and several sets of detection points are arranged in a ring around the signal source. The signal source is used to emit impact signals to the concrete box girder, and the detection points are used to receive echo signals. The echo signals at each detection point are subtracted from the preset reference signal to generate a differential enhancement signal. The reference signal is the echo signal collected during the impact echo test in the pure concrete area.

3. The method for detecting the density of concrete structures within bridges according to claim 2, characterized in that: The logic of the adaptive algorithm is as follows: First, the search space and search step size are set for the number of intrinsic mode components and the penalty factor, respectively; Next, modal decomposition is performed sequentially under each combination of group number and penalty factor, and the envelope entropy of each intrinsic modal component is calculated; Finally, the optimization criterion was minimized to obtain the optimal combination of parameters for the number of groups and the penalty factor.

4. The method for detecting the density of concrete structures within bridges according to claim 3, characterized in that: In step S3, the amplitude envelope is the absolute value of the complex analytic signal, and the phase change rate is the first derivative of the instantaneous phase with respect to time.

5. The method for detecting the density of concrete structures within bridges according to claim 4, characterized in that: The logic for determining whether there are voids in a concrete box girder is as follows: First, the total energy of the complex analytical signal is compared with a preset energy threshold. If the total energy of the complex analytical signal is less than the preset energy threshold, the complex analytical signal at the detection point is considered weak, which is a low reflection zone. If the total energy of the complex analytical signal is greater than the preset energy threshold, then the detection point is considered to be a composite area of ​​concrete, steel bars, and corrugated pipe, and the following steps are continued: The density index is compared with a preset index threshold. When the density index is greater than the preset index threshold, it is considered that the complex analytical signal at the detection point is strong and the phase change rate is low, which is a dense composite region. When the density index is less than the preset index threshold, it is considered that the complex analytical signal at the detection point is strong, but the phase change rate is high, indicating a composite region with voids.

6. A system for detecting the density of concrete structures within bridges, characterized in that: The detection system is used to perform the detection method as described in any one of claims 1-5, specifically including: The data acquisition module is used to conduct impact echo tests on the concrete box girder of the bridge, acquire echo signals during the test, and perform differential processing on the echo signals and a preset reference signal to obtain a differential enhancement signal. The data filtering module is used to perform mode decomposition on the differential enhancement signal to obtain several sets of intrinsic mode components with different center frequencies. Then, based on the center frequencies, the part representing high-frequency noise in the intrinsic mode components is filtered out and removed. The remaining intrinsic mode components are then reconstructed to obtain a pure reflection signal. The data analysis module is used to perform Hilbert transform on the pure reflected signal to construct a complex analytic signal, and then deduce the instantaneous phase of the complex analytic signal at any time according to the inverse trigonometric function. Finally, the amplitude envelope and phase change rate of the complex analytic signal are obtained. The data judgment module is used to calculate the total energy of the complex analytical signal within a preset time window, generate a density index based on the amplitude envelope and phase change rate, compare the density index with a preset index threshold, and combine the total energy and the comparison result to jointly determine whether there are voids in the concrete box girder.

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