Quantitative detection system and method for pier foundation scouring based on bridge deck hammering guided waves

Abstract

The invention discloses a bridge floor hammering guided wave-based bridge pier foundation scouring quantitative detection system and method, and belongs to the technical field of bridge engineering detection, an excitation device applies an impact force to a bridge floor position to excite a guided wave signal, a multi-point sensor array arranged around a bridge pier is combined to synchronously receive the signal, and efficient and accurate detection of bridge pier foundation scouring is realized. According to the invention, digital processing is carried out on the received signal through the data acquisition module, key characteristic parameters are extracted, a mapping relation between the scour depth and signal characteristics is established in combination with numerical simulation and a machine learning algorithm, positioning and depth quantitative evaluation of a scour area are finally realized, high cost and high risk of underwater operation are avoided, and the working efficiency is improved. The method has high efficiency, accuracy and wide applicability, and can be widely applied to health monitoring and safety assessment of bridge structures.

Description

Technical Field

[0001] The present invention belongs to the technical field of bridge engineering detection, and particularly relates to a quantitative detection system and method for pier foundation scour based on bridge deck impact guided waves. Background Art

[0002] Pier foundation scour is one of the important inducements for bridge structure failure. Especially in extreme environments such as floods and earthquakes, the erosion or scour of the soil or foundation materials around the pier may lead to pier instability or even collapse. Currently, the main methods for pier scour detection include manual diving detection, underwater sonar detection, and ground penetrating radar method. However, these methods have significant limitations: Manual diving detection depends on the diving ability of divers, which is not only costly and has high safety risks, but also has low detection efficiency due to the limitations of fast flowing water and turbid water quality; Although sonar detection and ground penetrating radar can provide scour information with a certain degree of accuracy, the equipment is complex, the operation cost is high, and it is difficult to obtain stable results under complex hydrological conditions.

[0003] In recent years, the method of using the propagation characteristics of guided waves to detect the state of pier foundations has gradually received attention. The propagation characteristics of guided wave signals in structures and media (such as wave velocity, attenuation, frequency change, etc.) are closely related to foundation scour, becoming an effective way to evaluate pier scour. However, most of the existing guided wave detection methods are limited to the underwater environment, where signal excitation and reception are difficult, and data processing and analysis rely on empirical judgment, making it impossible to achieve automation and quantification. Summary of the Invention

[0004] Aiming at the above problems, the present invention aims to provide a quantitative detection system and method for pier foundation scour based on bridge deck impact guided waves, which solves the problem of low detection efficiency existing in the existing pier scour detection methods.

[0005] In order to achieve the above invention purpose, the technical solution adopted by the present invention is as follows: A quantitative detection system for pier foundation scour based on bridge deck impact guided waves is provided, which includes an excitation device, a sensor module, a data acquisition module, a signal processing module, a numerical simulation module, and an intelligent analysis module that are electrically connected to each other; The excitation device is arranged on the bridge and is used to generate guided wave signals; The sensor module includes an above-water acceleration sensor and an underwater hydrophone sensor arranged at different heights of the pier foundation; The data acquisition module is used to receive the signal data collected by the sensor module and perform digital processing on the signal data; The signal processing module preprocesses and stores the signal data after digital processing; The numerical simulation module simulates the propagation characteristics of guided waves in different media by establishing a three-dimensional finite element model to obtain the guided wave propagation characteristics; The intelligent analysis module establishes a non - linear mapping relationship between the guided - wave characteristic parameters and the scouring depth, realizing the automatic positioning of the scouring area and the quantitative evaluation of the depth.

[0006] Furthermore, the excitation device is arranged at the expansion joint, bearing position or bridge deck of the bridge.

[0007] The present invention also provides a method for quantitatively detecting the scour of bridge pier foundations based on guided - waves hammered on the bridge deck, which includes the following steps: S1. Bridge - deck excitation: Arrange an excitation device on the bridge. The excitation device applies an impact force to the bridge to generate a guided - wave signal, and the guided - wave signal is transmitted along the bridge structure to the bridge pier and foundation. S2. Arrange water - borne acceleration sensors at different height positions of the above - water part of the bridge pier and arrange underwater hydrophones at different depth positions of the underwater part of the bridge pier. The water - borne acceleration sensors and underwater hydrophones synchronously receive the propagation, reflection and transmission of the guided - wave signal. S3. The data acquisition module synchronously and real - time collects the received guided - wave signal and digitally processes the guided - wave signal. The signal processing module pre - processes and stores the digitally processed guided - wave signal. S4. Extract the characteristic parameters of the guided - wave signal from the pre - processed guided - wave signal to obtain the guided - wave signal characteristic parameters. S5. Construct a finite - element model of the bridge - pier - soil - water coupling through the numerical simulation module to simulate the propagation characteristics of guided - waves under different scouring depth conditions. S6. The intelligent analysis module establishes a non - linear mapping relationship between the guided - wave signal characteristics and the scouring depth to complete the automatic positioning of the scouring area and the quantitative evaluation of the depth.

[0008] In the method for quantitatively detecting the scour of bridge - pier foundations based on guided - waves hammered on the bridge deck in the present invention, by exciting a guided - wave signal on the bridge deck, arranging multi - point sensors around the bridge pier to synchronously receive the signal, and combining numerical simulation and intelligent algorithms, a mapping relationship between the scouring depth and the signal characteristics is constructed to achieve the precise positioning and quantitative evaluation of the scouring area. By selecting the method of combining guided - wave signal characteristic extraction with finite - element numerical simulation analysis, the detection of the scour of bridge - pier foundations can be efficiently completed under complex hydrological conditions.

[0009] Furthermore, in step 1, the excitation device is a drop - hammer device, and the calculation formula for the impact force applied by the excitation device to the bridge is: ; The excitation frequency of the impact force of the excitation device is calculated by the formula: ; ; Where, represents the impact force varying with time, which is used to generate guided wave signals on the bridge deck; represents the peak amplitude of the impact force; represents the angular frequency, and t represents time; v is the propagation speed of the guided wave in the pier material; E is the elastic modulus of the pier material; ρ is the density of the pier material; L is the characteristic length of the pier; excitation frequency matches the resonance frequency of the bridge structure.

[0010] Furthermore, in step S2, the guided wave signals received by the waterborne acceleration sensor and the underwater hydrophone sensor satisfy the wave equation: ; where, λ and μ are the Lame constants respectively; they describe the mechanical properties of the soil and the pier material; ρ is the density of the pier material; u is the displacement field. The guided wave signals received by the waterborne acceleration sensor and the underwater hydrophone sensor are time-domain waveforms, and their propagation paths and attenuation characteristics contain the physical information of the medium, providing data support for subsequent analysis.

[0011] Furthermore, in step S3, the preprocessing includes filtering, denoising, and normalization processing of the guided wave signals. Specifically, a low-pass filter is used to remove high-frequency noise for filtering; wavelet transform is used to separate the signal from the background noise for denoising; normalization processing is to standardize the signal amplitude and frequency to ensure the consistency of feature extraction.

[0012] Furthermore, in step S4, the characteristic parameters of the guided wave signals include the arrival time difference of the guided wave signals, the amplitude attenuation coefficient, the frequency change, and the energy change; The calculation formula for the arrival time difference Δt of the guided wave signals is: Δt = t2 - t1; where, t2 and t1 are the times when the guided wave signals propagate to different sensor positions respectively; The amplitude attenuation coefficient α The calculation formula is: ; where, A 1 and A 2 are the amplitudes of the guided wave signals propagating to different sensor positions respectively; The frequency change The calculation formula is: ; where,x ( n ) is a time-domain signal; N represents the total number of signal sampling points, f represents the frequency index in the frequency domain, e represents the Euler number, j represents the imaginary unit; The energy change is expressed by the instantaneous energy of the guided wave signal, and the instantaneous energy E The calculation formula is: ; where, S represents the time-domain guided wave signal received by the sensor, and represents the signal at time t The amplitude of, and the energy change is used to evaluate the influence of the scouring area on the absorption of the guided wave signal.

[0013] Further, in step S5, the numerical simulation module selects the finite element method (FEM) to simulate the propagation characteristics of guided waves in the pier foundation and soil medium, constructs a pier-soil-water coupling model, and the expression of the pier-soil-water coupling finite element model is:

[0014] where, M , C , K are the mass matrix, damping matrix, and stiffness matrix of the system, respectively; u is the displacement vector, , are the velocity and acceleration vectors, respectively; F is the external excitation force vector.

[0015] Boundary condition setting of the pier-soil-water coupling model: The pier-soil interface is an absorbing boundary to simulate the attenuation of waves; the reflection coefficient is set at the soil-water interface to describe the reflection characteristics of waves in the scouring area. By simulating the propagation characteristics of guided waves under different scouring depth conditions, a training data set is generated to provide basic data for intelligent analysis.

[0016] Further, in step S6, the intelligent analysis module establishes a non-linear mapping relationship between the guided wave signal characteristics and the scouring depth through machine learning or deep learning algorithms.

[0017] Further, in step S6, the machine learning and deep learning algorithms are random forest, support vector machine, or convolutional neural network. Using the calibrated scouring depth data as the training set and inputting it into the machine learning or deep learning algorithm, the non-linear mapping relationship between the guided wave signal characteristics and the scouring depth, and the expression of the non-linear mapping relationship is:

[0018] Among them, is the scour depth; is the time delay of the reflected wave; A is the amplitude of the reflected wave; is the frequency change.

[0019] The beneficial effects of the present invention are as follows: A quantitative detection system and method for pier foundation scour based on bridge deck impact guided waves in the present invention excite guided waves through the bridge deck, without underwater operations, significantly improving the detection efficiency, having the advantage of high efficiency; multi-point reception and feature analysis improve the signal quality, and the evaluation results are more accurate, having the advantage of high detection accuracy; the mapping relationship between the scour depth and the characteristic parameters realizes the precise positioning and quantification of the scour area; it is applicable to the scour detection of different types of piers and under complex hydrological conditions, and can significantly improve the safety assessment efficiency and reliability of pier foundations. Description of the Drawings

[0020] Figure 1 is the principle block diagram of a quantitative detection system for pier foundation scour based on bridge deck impact guided waves.

[0021] Figure 2 is the schematic diagram of the guided wave propagation path.

[0022] Figure 3 is the schematic diagram of the pier-soil-water finite element model.

[0023] Figure 4 is the data processing flow chart.

[0024] Figure 5 is the structure diagram of the intelligent analysis model in the intelligent analysis module. Detailed Embodiments

[0025] The following describes the detailed embodiments of the present invention to facilitate those skilled in the art of the present technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the detailed embodiments. For those of ordinary skill in the art of the present technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0026] Such as Figure 1As shown in the figure, the present invention provides a quantitative detection system for scour of bridge pier foundation based on bridge deck impact guided wave, which includes an excitation device, a sensor module, a data acquisition module, a signal processing module, a numerical simulation module and an intelligent analysis module that are electrically connected to each other; the excitation device is arranged on the bridge and is used to generate guided wave signals; the sensor module includes an above-water acceleration sensor and an underwater hydrophone arranged at different heights of the bridge pier foundation; the data acquisition module is used to receive the signal data collected by the sensor module and perform digital processing on the signal data; the signal processing module preprocesses and stores the digitally processed signal data; the numerical simulation module simulates the propagation characteristics of guided waves in different media by establishing a three-dimensional finite element model to obtain the guided wave propagation characteristics; the intelligent analysis module establishes a non-linear mapping relationship between the guided wave characteristic parameters and the scour depth to realize the automatic positioning of the scour area and the quantitative evaluation of the depth.

[0027] Furthermore, the excitation device is arranged at the expansion joint, bearing position or bridge deck of the bridge. The guided wave signal is excited by an appropriate excitation device on the bridge deck. In this embodiment, the excitation device is a metal hammer or an impact device. Stress waves are generated by external impact, and then the guided waves in the bridge structure are excited. Specifically, excitation can be carried out at the expansion joint, bearing position or other suitable positions on the bridge deck. These positions are selected based on the following considerations: these positions can effectively transmit the guided waves. Especially when the waves propagate to the bridge pier foundation, the signals can be transmitted without being blocked or attenuated. After the guided waves are excited on the bridge deck, the wave propagation path is relatively simple and can quickly transmit to the bridge pier and interact with the foundation.

[0028] During implementation, the excitation device applies an impact force to the bridge structure to generate longitudinal waves (P-waves) and transverse waves (S-waves). By controlling the magnitude and direction of the impact force, guided wave signals with different frequencies can be obtained.

[0029] As Figure 2 shown in the figure, it shows the propagation path after the guided wave signal is excited around the bridge pier. After the signal is emitted on the bridge deck by the excitation device, it conducts along the bridge structure to the bridge pier and propagates to the soil and foundation. The figure marks the propagation direction of the signal, the direction of the reflected wave and the reflected signals received by the sensors at different depth positions. The wave velocities in different media (such as soil, bridge pier, foundation) will change. Especially in the scour area, the wave velocity and attenuation characteristics will change significantly. By analyzing the time delay, amplitude attenuation and frequency change of the signal, the position and depth of the scour area can be inferred.

[0030] The present invention also provides a method for a quantitative detection system for scour of bridge pier foundation based on bridge deck impact guided wave, which includes the steps: S1. Bridge deck excitation: An excitation device is arranged on the bridge. The excitation device applies an impact force to the bridge to generate a guided wave signal, and the guided wave signal is transmitted along the bridge structure to the bridge pier and foundation. Specifically, the transmission process of the guided wave signal is as follows Figure 2 As shown, in step 1, the excitation device is a drop hammer device, and the calculation formula for the impact force applied by the excitation device to the bridge is: ; The excitation frequency of the impact force of the excitation device The calculation formula is: ; ; Among them, represents the impact force varying with time, which is used to generate a guided wave signal on the bridge deck; represents the peak amplitude of the impact force; represents the angular frequency, and t represents time; v is the propagation speed of the guided wave in the pier material; E is the elastic modulus of the pier material; ρ is the density of the pier material; L is the characteristic length of the pier; the excitation frequency matches the resonance frequency of the bridge structure. The excitation signal is transmitted through the continuous structure of the bridge and finally enters the pier foundation area, providing an excitation source for subsequent signal analysis.

[0031] S2. Arrange waterborne acceleration sensors at different height positions on the above-water part of the bridge pier, and arrange underwater hydrophones at different depth positions on the underwater part of the bridge pier. The waterborne acceleration sensors and underwater hydrophones synchronously receive the propagation, reflection, and transmission of the guided wave signal. Specifically, in step S2, the guided wave signals received by the waterborne acceleration sensors and underwater hydrophones satisfy the wave equation: ; Among them, λ and μ are the Lame constants respectively; they describe the mechanical properties of the soil and pier material; ρ is the density of the pier material; u is the displacement field. The guided wave signals received by the waterborne acceleration sensors and underwater hydrophones are time-domain waveforms, and their propagation paths and attenuation characteristics contain the physical information of the medium, providing data support for subsequent analysis. Each sensor has a synchronous acquisition function and can receive signals in real time and convert them into digital data. The waterborne acceleration sensors are mainly used to measure the vibration responses above and below the water of the bridge pier. By arranging multiple acceleration sensors at different heights, the propagation path and attenuation characteristics of the signal can be obtained, and then the scour depth can be calculated.

[0032] The acoustic sensor is used to receive guided wave signals propagated through the underwater medium. Due to the medium characteristics of water, the wave speed and attenuation are quite different from those of signals in air. Therefore, it is necessary to specifically consider its propagation characteristics under different water depths and hydrological conditions.

[0033] S3. The received guided wave signals are synchronously collected in real time by the data acquisition module and digitized. The digitized guided wave signals are preprocessed and stored by the signal processing module. Specifically, in step S3, the preprocessing includes filtering, denoising, and normalization of the guided wave signals. Specifically, a low-pass filter is used to remove high-frequency noise for filtering; wavelet transform is used to separate the signal from the background noise for denoising; normalization is to standardize the signal amplitude and frequency to ensure the consistency of feature extraction. As Figure 4 shown, Figure 4 It details the data processing flow, the whole process from signal acquisition to feature extraction. First, the sensor receives the guided wave signals and transmits them to the data acquisition module. The signals go through preprocessing steps such as sampling, filtering, and denoising. Subsequently, features such as the time delay, amplitude attenuation, and frequency change of the signals are extracted, and the feature data is further normalized. Finally, through machine learning algorithms for analysis and evaluation, the quantitative depth information of the scoured area is output. This process can efficiently convert sensor data into accurate scour detection results.

[0034] S4. Extract the characteristic parameters of the guided wave signals from the preprocessed guided wave signals to obtain the characteristic parameters of the guided wave signals. Specifically, according to the received guided wave signals, the reflected waves of the ground line (or scour interface) are extracted. The characteristics of the reflected waves are directly related to the structural changes of the bridge pier foundation, such as the depth and extent of scour. Parameters such as the amplitude, arrival time, and frequency change of the reflected waves are important bases for evaluating the degree of scour. Using the reflected wave data obtained by the multi-point receiving system, analyze its time delay, amplitude change, and waveform change, and then infer the location and depth of the scoured area of the bridge pier foundation. By extracting the characteristics of the reflected waves, important characteristic parameters of the guided wave signals are obtained. The characteristic parameters of the guided wave signals include the time difference of arrival of the guided wave signals, amplitude attenuation coefficient, frequency change, and energy change; The calculation formula for the time difference of arrival Δt of the guided wave signals is: Δt = t2 - t1; where t2 and t1 are the times when the guided wave signals propagate to different sensor positions respectively; the time when the reflected wave arrives at the sensor directly reflects the distance of wave propagation and helps to determine the scour depth.

[0035] Amplitude attenuation coefficient α The calculation formula for is: where A 1 andA are the amplitudes of the guided wave signal propagating to different sensor positions respectively; amplitude attenuation coefficient α reflects the energy loss of the signal propagation path; the attenuation degree of the reflected wave amplitude reflects the change of the medium, and the change of the wave velocity in the scouring area will lead to the attenuation of the signal amplitude.

[0036] Frequency change The calculation formula is as follows: ; wherein, x ( n ) is the time-domain signal; N represents the total number of signal sampling points, f represents the frequency index in the frequency domain, e represents the Euler number, j represents the imaginary unit. The energy change is expressed by the instantaneous energy of the guided wave signal, and the instantaneous energy E The calculation formula is as follows: ; wherein, S represents the time-domain guided wave signal received by the sensor, and represents the amplitude of the signal at time t . The energy change is used to evaluate the influence of the scouring area on the absorption of the guided wave signal. Since the medium characteristics in the scouring area change, the propagation speed of the guided wave will change, which will lead to the frequency shift. By analyzing these characteristics, the depth of the scouring area can be quantitatively evaluated. Commonly used feature extraction methods include time-frequency analysis (such as wavelet transform) and spectral analysis.

[0037] S5. Construct a finite element model of pier-soil-water coupling through the numerical simulation module to simulate the propagation characteristics of guided waves under different scouring depth conditions; as Figure 3 shown, Figure 3 shows the finite element analysis model of the pier foundation area, which includes the calculation domains of the pier, soil and water. The model uses the three-dimensional finite element method to simulate the propagation behavior of the guided wave signal in the pier foundation and the surrounding soil. The boundary conditions consider the contact interface between the pier and the soil, the soil-water interface, and the absorption boundary of the model to simulate the attenuation process of the wave in different media.

[0038] Specifically, the numerical simulation module selects the finite element method (FEM) to simulate the propagation characteristics of guided waves in the pier foundation and soil media, constructs a pier-soil-water coupling model, and the expression of the pier-soil-water coupling finite element model is:

[0039] wherein, M , C, K are the mass matrix, damping matrix, and stiffness matrix of the system, respectively; u is the displacement vector, , are the velocity and acceleration vectors, respectively; F is the external excitation force vector.

[0040] Boundary condition setting of the pier - soil - water coupling model: The pier - soil interface is an absorbing boundary for simulating wave attenuation; the reflection coefficient is set at the soil - water interface to describe the reflection characteristics of waves in the scouring area. By simulating the propagation characteristics of guided waves under different scouring depth conditions, a training dataset is generated to provide basic data for intelligent analysis.

[0041] S6. Establish a non - linear mapping relationship between the guided wave signal characteristics and the scouring depth through the intelligent analysis module to complete the automatic positioning and depth quantitative evaluation of the scouring area. By using algorithms such as support vector machine (SVM), random forest (RF), or convolutional neural network (CNN) to establish an intelligent analysis model in the intelligent analysis module, the intelligent analysis model can automatically identify and locate the scouring area and conduct quantitative evaluation.

[0042] The training process of the intelligent analysis model is as follows: Using the calibrated scouring depth data as the training set and inputting it into machine learning or deep learning algorithms, the non - linear mapping relationship between the guided wave signal characteristics and the scouring depth. The expression of the non - linear mapping relationship is:

[0043] where, is the scouring depth; is the time delay of the reflected wave; A is the amplitude of the reflected wave; is the frequency change.

[0044] As Figure 5 shown, Figure 5 shows the overall structure of the intelligent analysis model, which mainly includes a data input layer, a feature extraction layer, a machine learning model layer, and an output layer. The data input layer receives the pre - processed signal characteristics, including time delay, amplitude attenuation, and frequency change, etc.; the feature extraction layer extracts key features through algorithms; the machine learning model layer uses methods such as support vector machine, random forest, or deep neural network to train the extracted features and establish a mapping relationship between the scouring depth and the signal characteristics; the output layer outputs the specific scouring depth value according to the training results. Through this intelligent analysis model, the system can quickly and accurately evaluate the pier foundation scouring under complex environments.

[0045] In summary, in the quantitative detection method for pier foundation scour based on bridge deck impact guided waves in the present invention, guided wave signals are excited on the bridge deck, multi-point sensors are arranged around the pier to synchronously receive signals, and combined with numerical simulation and intelligent algorithms, a mapping relationship between the scour depth and signal characteristics is constructed to achieve precise positioning and quantitative evaluation of the scour area. By selecting the method of combining guided wave signal feature extraction with finite element numerical simulation analysis, the detection of pier foundation scour can be efficiently completed under complex hydrological conditions, which is applicable to the scour detection of different types of piers and complex hydrological conditions, avoiding the high costs and high risks of underwater operations, and having high efficiency, precision and wide applicability, and can be widely applied to the health monitoring and safety assessment of bridge structures.

Claims

1. A quantitative detection system for scour of bridge pier foundation based on bridge deck impact guided wave, characterized in that It includes an excitation device, a sensor module, a data acquisition module, a signal processing module, a numerical simulation module and an intelligent analysis module which are electrically connected to each other; The excitation device is arranged on the bridge and is used to generate guided wave signals; The sensor module includes an above-water acceleration sensor and an underwater hydrophone sensor arranged at different heights of the pier foundation; The data acquisition module is used to receive the signal data collected by the sensor module and perform digital processing on the signal data; The signal processing module preprocesses and stores the signal data after digital processing; The numerical simulation module simulates the propagation characteristics of guided waves in different media by establishing a three-dimensional finite element model to obtain the guided wave propagation characteristics; The intelligent analysis module establishes a non-linear mapping relationship between the guided wave characteristic parameters and the scour depth to realize the automatic positioning of the scour area and the quantitative evaluation of the depth.

2. The quantitative detection system for pier foundation scour based on bridge deck impact guided wave according to claim 1, characterized in that, The excitation device is arranged at the expansion joint, the support position or the bridge deck of the bridge.

3. A quantitative detection method for scour of bridge pier foundation based on bridge deck impact guided wave, which uses the quantitative detection system for scour of bridge pier foundation by impact guided wave on bridge deck according to any one of the above claims 1 to 2, characterized in that, The quantitative detection method for scour of pier foundation based on bridge deck impact guided waves includes the steps: S1. Bridge deck excitation: Arrange an excitation device on the bridge. The excitation device applies an impact force to the bridge to generate a guided wave signal, and the guided wave signal is transmitted along the bridge structure to the pier and the foundation; S2. Arrange above-water acceleration sensors at different height positions of the above-water part of the pier and arrange underwater hydrophone sensors at different depth positions of the underwater part of the pier. The above-water acceleration sensors and the underwater hydrophone sensors synchronously receive the propagation, reflection and transmission of the guided wave signal; S3. The data acquisition module performs real-time synchronous acquisition on the received guided wave signal and performs digital processing on the guided wave signal. The signal processing module preprocesses and stores the guided wave signal after digital processing; S4. Extract the guided wave signal characteristic parameters from the preprocessed guided wave signal to obtain the guided wave signal characteristic parameters; S5. Construct a pier-soil-water domain coupled finite element model through the numerical simulation module to simulate the propagation characteristics of guided waves under different scour depth conditions; S6. Establish a non-linear mapping relationship between the guided wave signal characteristics and the scour depth through the intelligent analysis module to complete the automatic positioning of the scour area and the quantitative evaluation of the depth.

4. The quantitative detection method for scour of bridge pier foundation based on bridge deck impact guided wave according to claim 3, characterized in that, In step S1, the excitation device is a drop hammer device, and the calculation formula for the excitation device to apply an impact force to the bridge is: ； The excitation frequency of the impact force of the excitation device The calculation formula is as follows: ； ； Among them, represents the impact force that changes with time and is used to generate guided wave signals on the bridge deck; represents the peak amplitude of the impact force; represents the angular frequency, and t represents time; v is the propagation speed of the guided wave in the pier material; E is the elastic modulus of the pier material; ρ is the density of the pier material; L is the characteristic length of the pier; excitation frequency matches the resonance frequency of the bridge structure.

5. The quantitative detection method for scour of pier foundation based on bridge deck impact guided wave according to claim 3, characterized in that, In step S2, the guided wave signals received by the above-water acceleration sensors and the underwater hydrophone sensors satisfy the wave equation: ； Among them, λ and μ are Lame constants respectively, describing the mechanical properties of the soil and the pier material; ρ is the density of the pier material; u is the displacement field.

6. The quantitative detection method for scour of pier foundation based on bridge deck impact guided wave according to claim 3, wherein, In step S3, the preprocessing includes filtering, denoising and normalization processing of the guided wave signal.

7. The quantitative detection method for scour of bridge pier foundation based on bridge deck impact guided wave according to claim 3, characterized in that In step S4, the guided wave signal characteristic parameters include the arrival time difference of the guided wave signal, the amplitude attenuation coefficient, the frequency change and the energy change; The calculation formula for the arrival time difference Δt of the guided wave signal is: Δt = t2 - t1; Wherein, t2 and t1 are respectively the times when the guided wave signal propagates to different sensor positions; Amplitude attenuation coefficient α The calculation formula is as follows: ； Among them, A 1 and A 2 are respectively the amplitudes of the guided wave signal propagating to different sensor positions; Frequency change The calculation formula is as follows: ； Among them, x ( n ) is the time-domain signal; N represents the total number of signal sampling points, f represents the frequency index in the frequency domain, e represents the Euler number, j represents the imaginary unit; The energy change is expressed by the instantaneous energy of the guided wave signal, and the instantaneous energy E is calculated by the formula: ； Among them, S represents the time-domain guided wave signal received by the sensor, indicating the signal at time t amplitude, and the energy change is used to evaluate the influence of the scoured area on the absorption of the guided wave signal.

8. The quantitative detection method for scour of bridge pier foundation based on bridge deck impact guided wave according to claim 3, characterized in that In step S5, the expression of the pier-soil-water domain coupled finite element model is: Among them, M , C , K are the mass matrix, damping matrix and stiffness matrix of the system respectively; u is the displacement vector, , are the velocity and acceleration vectors respectively; F is the external excitation force vector.

9. The quantitative detection method for scour of pier foundation based on bridge deck impact guided wave according to claim 3, wherein In step S6, the intelligent analysis module establishes a non-linear mapping relationship between the guided wave signal characteristics and the scour depth through machine learning or deep learning algorithms.

10. The quantitative detection method for scour of bridge pier foundation based on bridge deck hammering guided wave according to claim 9, characterized in that, In step S6, the calibrated scour depth data is used as the training set and input into a machine learning or deep learning algorithm to derive the non-linear mapping relationship between the guided wave signal features and the scour depth. The expression of the non-linear mapping relationship is as follows: Among them, is the scour depth; is the time delay of the reflected wave; A is the amplitude of the reflected wave; is the frequency change.

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