Multimedium three-dimensional flaw detection system based on ultrasonic pulse echoes

Abstract

The invention discloses a multi-medium three-dimensional flaw detection system based on ultrasonic pulse echoes. The multi-medium three-dimensional flaw detection system comprises a synchronous data acquisition module, a temperature compensation module, a multi-physical field simulation optimization module, a signal processing module and a three-dimensional imaging and output module, the synchronous data acquisition module scans an object, records coordinates and synchronously transmits and receives ultrasonic echoes; the temperature compensation module calculates real-time sound velocity according to the water temperature, the real-time sound velocity is used by the multi-physics field simulation module, and the multi-physics field simulation module simulates sound wave propagation and generates a defect-free theoretical waveform as a reference by combining intrinsic parameters of an object and sound wave propagation parameters; the signal processing module carries out processing and feature extraction on actually measured echoes, and compares the actually measured echoes with a reference to identify defect signals; and the three-dimensional imaging module associates the signals with the coordinates, a three-dimensional model is generated by adopting slice reconstruction and a compressed sensing algorithm, and defects are visualized, so that the precision, the efficiency and the environmental adaptability of three-dimensional flaw detection can be improved.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology, and in particular to a multi-media three-dimensional flaw detection system based on ultrasonic pulse echo. Background Technology

[0002] In recent years, with the rapid development of marine resource development and marine engineering construction, higher demands have been placed on underwater non-destructive testing technology. Traditional underwater acoustic flaw detection technology, mainly based on sonar and acoustic imaging principles, has been applied in fields such as marine scientific research and underwater structure maintenance, but many technical bottlenecks still need to be overcome: 1. Insufficient environmental adaptability The underwater environment is complex and variable. Temperature fluctuations cause changes in sound velocity, which are significant within the normal operating temperature range, affecting detection accuracy. Changes in salinity alter the acoustic impedance of the medium, and suspended particles cause sound wave scattering, further reducing signal quality. In addition, in high-pressure underwater environments, the sealing structure of traditional detection equipment is prone to failure, and the sound wave propagation path is distorted due to pressure, limiting the reliable application of equipment in deep-water conditions.

[0003] 2. Limited functionality and low detection efficiency Existing technologies are mostly limited to two-dimensional imaging modes, relying on manually set detection thresholds, and have limited ability to identify minute defects. Experimental data shows that they have a high rate of missed detection for sub-millimeter-sized defects. The detection process involves a high degree of human intervention and is time-consuming per operation, making it difficult to meet the needs of rapid and automated inspection and flaw detection in modern marine engineering. At the same time, existing methods lack effective three-dimensional reconstruction capabilities, resulting in insufficient spatial positioning accuracy of defects, which limits their application in precision inspection scenarios.

[0004] 3. Limited by special application scenarios In practical engineering scenarios such as deep-sea exploration and subsea pipeline inspection, traditional equipment has weak penetration ability in turbid water and limited effective detection distance; when facing multi-media interfaces such as steel pipe-concrete-seawater, signal aliasing is prone to occur, affecting the accuracy of defect identification; during long-distance detection, sound wave attenuation is severe, and the signal strength drops sharply with increasing distance, which restricts its practicality in large-scale underwater structure inspection. Summary of the Invention

[0005] This invention provides a multi-media three-dimensional flaw detection system based on ultrasonic pulse echo to overcome the above-mentioned technical problems.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows: A multi-media three-dimensional flaw detection system based on ultrasonic pulse echo includes: a synchronous data acquisition module, a temperature compensation module, a multi-physics simulation optimization module, a signal processing module, and a three-dimensional imaging and output module; The synchronous data acquisition module is used to scan the object under test, record the coordinate information of the corresponding scanning position, synchronously transmit pulse sound waves to the object under test during the scanning process, and receive the echo signal from the object under test in real time. The temperature compensation module is used to calculate the real-time sound velocity value at the current water temperature based on the real-time ambient water temperature, and output it to the multiphysics simulation optimization module as a simulation parameter for simulation. The multiphysics simulation optimization module is used to solve the control equations of each physics field based on the intrinsic parameters of the object under test, the sound wave propagation parameters, and the real-time sound velocity value output by the temperature compensation module. This simulates the "electro-mechanical-acoustic" energy conversion process of the sound wave and the sound pressure at each location obtained by the sound wave during this process. Based on the simulated sound pressure, it generates theoretical waveforms of the reflection from the medium interface and the bottom echo of the object under test in a defect-free state, providing characteristic reference values ​​for defect signal discrimination to the signal processing module. The intrinsic parameters of the object under test include the density and attenuation coefficient of the object under test, and the sound wave propagation parameters include the pulse width and transmission power. The signal processing module is used to receive the echo signal of the object under test output by the synchronous data acquisition module, preprocess the echo signal, reduce noise, extract features, compare the extracted features with feature reference values, and separate defect signals. The three-dimensional imaging and output module is used to associate the echo signal with the scanning coordinate information. It uses a spatial reconstruction method based on slice reconstruction and a lightweight compressed sensing algorithm to generate a three-dimensional shape model based on the echo signal, defect signal and scanning coordinate information, and visualizes the location and information of the defect on the three-dimensional shape model.

[0007] Furthermore, the multiphysics simulation optimization module includes mutually coupled pressure acoustic physics field, solid mechanical physics field and electrostatic physics field; The electrostatic physical field is used to simulate the process of establishing an electric field and electric displacement field inside the piezoelectric transducer by an electrical signal applied to it. It takes an external driving voltage as input and receives displacement field and strain field data from the solid mechanical physical field for bidirectional coupling. The electric field force inside the piezoelectric transducer is solved to transfer the mechanical vibration energy converted from the electric field energy through the solid mechanical physical field, forming the sound source excitation condition of the pressure acoustic physical field. The solid mechanical physical field is used to simulate the deformation and vibration of the piezoelectric transducer wafer under voltage drive. It is bidirectionally coupled with the electrostatic physical field. It takes the electric field force, object density and sound wave propagation parameters as input to solve for the vibration velocity, displacement field and strain field of the piezoelectric transducer. The vibration velocity is fed back to the pressure acoustic physical field, and the displacement field and strain field are fed back to the electrostatic physical field. The pressure acoustic physical field is used to simulate the propagation and fluctuation of sound waves. It is coupled with the solid mechanical physical field. Based on the vibration velocity, the excitation conditions of the sound source, and the intrinsic parameters and real-time sound velocity of the object under test, it solves the theoretical sound pressure signal corresponding to the propagation, reflection, refraction and attenuation of the sound wave in the object under test. Finally, it outputs the theoretical sound pressure signal of the sound wave reflected back at the medium interface and bottom surface, which is the theoretical waveform.

[0008] Furthermore, the multiphysics simulation optimization module is used to extract the sound pressure data and the curve of sound pressure data changing with time at a specified receiving position of the pressure acoustic physical field, and to form the theoretical waveform of the reflection of the medium interface and the bottom echo of the object under test in a defect-free state.

[0009] Furthermore, the real-time speed of sound at the current water temperature is calculated based on the real-time ambient water temperature, including: The real-time sound velocity value at the current water temperature is calculated based on the real-time ambient water temperature, as shown in formula (1). (1) in, This is the real-time speed of sound value. For the ambient water temperature, This is the speed of sound in dry air at standard atmospheric pressure and a temperature of 0 degrees Celsius. The temperature coefficient of the speed of sound in air.

[0010] Furthermore, the signal processing module is specifically used to preprocess the echo signal through a signal amplification / shortening circuit, reduce noise in the processed echo signal through an adaptive threshold filtering algorithm, extract the peak amplitude, time difference of arrival, signal duration, waveform distortion, and main peak frequency of the spectrum of the echo signal, and compare them with characteristic reference values ​​to separate defective signals. The peak amplitude is the maximum amplitude value of the time domain waveform of the echo signal, the time difference of arrival is the time interval between the start time of the echo signal and the start time of the reference transmitted signal, the signal duration is the time span of the echo signal from the start threshold to the end threshold, the waveform distortion is the deviation coefficient between the actual echo waveform and the standard sine waveform, and the main peak frequency of the spectrum is the frequency value with the highest energy in the frequency domain spectrum of the echo signal.

[0011] Furthermore, the signal processing module preprocesses the echo signal through a signal amplification / attenuation circuit, specifically as follows: The upper and lower limits of the peak range are set. When the peak value of the echo signal is greater than the upper limit of the peak range, the echo signal is suppressed to the peak range by the signal amplification circuit. When the peak value of the echo signal is less than the lower limit of the peak range, the echo signal is amplified to the peak range by the signal amplification circuit.

[0012] Furthermore, the signal processing module performs noise reduction on the processed echo signal using an adaptive threshold filtering algorithm, specifically as follows: The preprocessed echo signal is smoothed to obtain the preprocessed echo signal. Two-dimensional smooth signal matrix with consistent dimensions and based on The adaptive threshold is calculated as shown in formula (2). (2) in, For adaptive threshold matrix, The threshold matrix is ​​a fixed scaling factor. In, each element This refers to the pre-processed echo signal. The dynamic threshold corresponding to the position in row m and column n; Will The calculated adaptive threshold matrix By comparing the signals, echo signals with amplitudes less than the corresponding position thresholds are selected as echo signals for feature extraction, thus completing the noise reduction.

[0013] Furthermore, the signal processing module compares the peak amplitude, time difference of arrival, signal duration, waveform distortion, and main peak frequency of the echo signal with characteristic reference values ​​to separate defective signals, specifically: The deviation ranges for peak amplitude, time difference of arrival, signal duration, waveform distortion, and main peak frequency of the spectrum are set respectively. If the deviation value of any feature of the echo signal exceeds the deviation range of the corresponding feature, the echo signal is determined to be a defective signal and the defective signal is separated.

[0014] Furthermore, the three-dimensional imaging and output module is specifically used to stitch together all echo signals at the same height according to the scanning path order using an orthogonal matching tracking algorithm to form multiple two-dimensional images, sparsely sample the separated defect signals, use the OMP algorithm to reconstruct the sparsely sampled defect signals to obtain complete defect information, calculate depth information and horizontal distance based on the complete defect information, superimpose the two-dimensional images, and perform three-dimensional spatial positioning based on the depth information and horizontal distance to obtain a three-dimensional morphology model with defect location, shape, and size. The complete defect information is the complete waveform data of the defect signal.

[0015] Furthermore, depth information and horizontal distance are calculated based on complete defect information, including: The depth information and horizontal distance are calculated based on the time delay of the defect signal echo in the complete defect information, as shown in formulas (3) and (4). (3) (4) in, For depth information, Horizontal distance The sound wave propagation distance is calculated based on the time delay of the defect signal echo and the propagation speed of the ultrasonic wave in the material. The refraction angle of the transducer.

[0016] Beneficial effects: This invention provides a multi-medium three-dimensional flaw detection system based on ultrasonic pulse echo, which has the following advantages: 1. Improved accuracy: By accurately simulating the complete physical process from electrical signal excitation to sound wave propagation through the multi-physics simulation optimization module, the positioning error introduced by mechanical vibration can be effectively reduced, providing the most accurate feature reference value and improving the accuracy of defect judgment; 2. Enhanced environmental adaptability: Through temperature compensation algorithm and adaptive filtering, the detection stability in turbid water and high-pressure environments can be improved by more than 30%; 3. Improved detection efficiency: By denoising and extracting features from the acquired echo signals, the acquired data is reconstructed into a three-dimensional morphological image using imaging software. This allows the location, size, and shape of internal damage (such as slits or holes with a width greater than 1.0 mm) to be presented intuitively, completing the entire process from signal to image analysis, reducing manual intervention, and achieving an order-of-magnitude improvement in detection efficiency. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A system block diagram of a multi-media three-dimensional flaw detection system based on ultrasonic pulse echo is provided for this invention; Figure 2 This is a diagram illustrating the object under test and its 3D model in the first embodiment. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] This embodiment provides a multi-media three-dimensional flaw detection system based on ultrasonic pulse echo, such as... Figure 1 As shown, it includes: a synchronous data acquisition module, a temperature compensation module, a multiphysics simulation optimization module, a signal processing module, and a three-dimensional imaging and output module; The synchronous data acquisition module is used to scan the object under test, record the coordinate information of the corresponding scanning position, synchronously transmit pulse sound waves to the object under test during the scanning process, and receive the echo signal from the object under test in real time. The temperature compensation module is used to calculate the real-time sound velocity value at the current water temperature based on the real-time ambient water temperature, and output it to the multiphysics simulation optimization module as a simulation parameter for simulation. The multiphysics simulation optimization module is used to solve the control equations of each physics field based on the intrinsic parameters of the object under test, the sound wave propagation parameters, and the real-time sound velocity value output by the temperature compensation module. This simulates the "electro-mechanical-acoustic" energy conversion process of the sound wave and the sound pressure at each location obtained by the sound wave during this process. Based on the simulated sound pressure, it generates theoretical waveforms of the reflection from the medium interface and the bottom echo of the object under test in a defect-free state, providing characteristic reference values ​​for defect signal discrimination to the signal processing module. The intrinsic parameters of the object under test include the density and attenuation coefficient of the object under test, and the sound wave propagation parameters include the pulse width and transmission power. The signal processing module is used to receive the echo signal of the object under test output by the synchronous data acquisition module, preprocess the echo signal, reduce noise, extract features, compare the extracted features with feature reference values, and separate defect signals. The three-dimensional imaging and output module is used to associate the echo signal with the scanning coordinate information. It uses a spatial reconstruction method based on slice reconstruction and a lightweight compressed sensing algorithm to generate a three-dimensional shape model based on the echo signal, defect signal and scanning coordinate information, and visualizes the location and information of the defect on the three-dimensional shape model.

[0021] Specifically, this invention uses a piezoelectric transducer as the core detection unit to construct a complete intelligent processing scheme for ultrasonic detection, realizing integrated innovation across the entire process from theoretical modeling and signal processing to imaging display.

[0022] At the system design level, a multiphysics simulation optimization module accurately simulates the complete physical process of a piezoelectric transducer from electrical signal excitation to sound wave propagation. Simulation is achieved by solving the governing equations describing the nature of different physical fields and their coupling relationships. The set physical fields are automatically associated through field coupling variables (such as piezoelectric coupling and acoustic-structure interaction boundaries), thus fully reproducing the energy conversion of ultrasound from electrical to mechanical to acoustic and the complex propagation effects in multi-medium environments (including interface reflection and multiple echoes). This module is driven by setting the intrinsic parameters (density, sound velocity, attenuation coefficient) of each material layer, and its simulation results provide a precise theoretical basis for optimizing key parameters such as pulse width and detection threshold in actual detection. In terms of signal processing, the original echo signal is optimized and its features are extracted through a signal processing module. When ultrasound propagates in a medium and encounters defects or interfaces, it generates an echo signal containing key information. The system first preprocesses the received signal through the signal processing module. To address interference such as signal overlap (e.g., echoes from different reflecting surfaces superimposed) and multiple reflections that occur in actual detection, the preprocessed signal is denoised to effectively separate noise from the valid signal, thereby improving the signal-to-noise ratio and laying a clear data foundation for subsequent imaging.

[0023] In terms of imaging and visualization, the processed signal data is converted into intuitive two-dimensional images through a 3D imaging and output module. Using the host computer's imaging software as the core, precise distance data corresponding to each scanning position of the probe is received via serial port from an Arduino. The large number of one-dimensional distance data points (840 per group, supporting multiple groups) acquired by the probe during uniform scanning are spatially reconstructed, ultimately generating clear two-dimensional images in real time on the interactive interface. This process achieves the transformation from abstract data to visualized morphology, allowing the location, size, and shape of internal damage (such as slits or holes wider than 1.0 mm) to be intuitively presented, completing the entire process from signal to image analysis.

[0024] In a specific embodiment, the synchronous data acquisition module is used to scan the object under test, record the coordinate information of the corresponding scanning position, and synchronously emit pulse sound waves to the object under test during the scanning process, and receive the echo signal from the object under test in real time. This embodiment employs a high-performance transceiver integrated ultrasonic transducer that transmits pulsed sound waves to the object under test using a directional beamforming algorithm. The transducer is based on a piezoelectric wafer and receiving circuitry sharing a common substrate design, resulting in a volume of only 6.8 cm². 3 The signal coupling efficiency is over 95%, the working frequency is 2.5MHz, and the detection accuracy is ±0.1mm. At the same time, the ultrasonic transducer uses a stepper motor scanning mechanism to scan the object under test, record the corresponding scanning position, and send the scanning information to the host for subsequent three-dimensional imaging.

[0025] This solution can be used for underwater flaw detection. The synchronous data acquisition module is suitable for underwater high pressure (≤5MPa) and turbid environments. By using a directional beamforming algorithm to control the focusing direction and energy distribution of the ultrasonic beam, it reduces beam divergence under high pressure and signal scattering in turbid water, improves the focusing capability of the sound field, reduces propagation attenuation, and achieves a detection depth of ≥1m.

[0026] In a specific embodiment, the temperature compensation module calculates the real-time sound velocity value at the current water temperature based on the real-time ambient water temperature and outputs it to the multiphysics simulation optimization module as a simulation parameter. The real-time sound velocity value at the current water temperature is calculated based on the real-time ambient water temperature, as shown in formula (5). (5) in, This is the real-time speed of sound value. For the ambient water temperature, This is the speed of sound in dry air at standard atmospheric pressure and a temperature of 0 degrees Celsius. The temperature coefficient of the speed of sound in air.

[0027] Temperature fluctuations can cause changes in the speed of sound. Within the normal operating temperature range, the speed of sound changes significantly, affecting the detection accuracy. Therefore, a temperature compensation module is used to reduce the measurement error caused by temperature fluctuations and ensure measurement accuracy.

[0028] In a specific embodiment, the multiphysics simulation optimization module is used to solve the control equations of each physics field based on the intrinsic parameters of the object under test, the sound wave propagation parameters, and the real-time sound velocity value output by the temperature compensation module. This simulates the "electro-mechanical-acoustic" energy conversion process of the sound wave and the sound pressure at various locations obtained by the sound wave during this process. Based on the simulated sound pressure, it generates theoretical waveforms of the reflection from the medium interface and the bottom echo of the object under test in a defect-free state, providing characteristic reference values ​​for defect signal discrimination to the signal processing module. The intrinsic parameters of the object under test include its density and attenuation coefficient. The sound wave propagation parameters include the pulse width and transmission power. The electrostatic physical field is used to simulate the process of establishing an electric field and electric displacement field inside the piezoelectric transducer by an electrical signal applied to it. It takes an external driving voltage as input and receives displacement field and strain field data from the solid mechanical physical field for bidirectional coupling. The electric field force inside the piezoelectric transducer is solved to transfer the mechanical vibration energy converted from the electric field energy through the solid mechanical physical field, forming the sound source excitation condition of the pressure acoustic physical field. The solid mechanical physical field is used to simulate the deformation and vibration of the piezoelectric transducer wafer under voltage drive. It is bidirectionally coupled with the electrostatic physical field. It takes the electric field force, object density and sound wave propagation parameters as input to solve for the vibration velocity, displacement field and strain field of the piezoelectric transducer. The vibration velocity is fed back to the pressure acoustic physical field, and the displacement field and strain field are fed back to the electrostatic physical field. The pressure acoustic physical field is used to simulate the propagation and fluctuation of sound waves. It is coupled with the solid mechanical physical field. Based on the vibration velocity, the excitation conditions of the sound source, and the intrinsic parameters and real-time sound velocity of the object under test, it solves the theoretical sound pressure signal corresponding to the propagation, reflection, refraction and attenuation of the sound wave in the object under test. Finally, it outputs the theoretical sound pressure signal of the sound wave reflected back at the medium interface and bottom surface, which is the theoretical waveform. The multiphysics simulation optimization module is also used to extract the sound pressure data and the curve of sound pressure data changing with time at the specified receiving position of the pressure acoustic physical field, and to form the theoretical waveform of the reflection of the medium interface and the bottom echo of the test object under defect-free state; the formation of the propagation waveform of the sound wave based on the sound pressure curve is a conventional technical means for those skilled in the art, and is not specifically described or limited.

[0029] In this solution, the multiphysics simulation optimization module accurately simulates the complete physical process from electrical signal excitation to sound wave propagation, which can effectively reduce the positioning error introduced by mechanical vibration, provide the most accurate feature reference value, and improve the accuracy of defect judgment.

[0030] In a specific embodiment, the signal processing module is used to receive the echo signal of the object under test output by the synchronous data acquisition module, preprocess the echo signal, reduce noise, extract features, and compare the extracted features with feature reference values. The scheme for separating defect signals is as follows: The signal processing module is specifically used to preprocess the echo signal through a signal amplification / attenuation circuit. Set the upper and lower limits of the peak range. When the peak value of the echo signal is greater than the upper limit of the peak range, the echo signal is suppressed to the peak range by the signal amplification circuit. When the peak value of the echo signal is less than the lower limit of the peak range, the echo signal is amplified to the peak range by the signal amplification circuit. Specifically, the signal strength is adjusted to a peak amplitude ≥ 50mV and the defect echo characteristics can be clearly identified. Specifically, this means enhancing the weak attenuation signal after long-distance propagation through an amplification circuit and suppressing the strong attenuation signal after short-distance propagation through a reduction circuit, so that the peak amplitude of the echo signal at different propagation distances tends to be within the range of 50mV ± 5mV. The processed echo signal is denoised using an adaptive threshold filtering algorithm. The echo signal contains two core signal components: one is the multi-medium interface reflection signal, which is generated by specular reflection of ultrasonic waves at the interface between different media (such as water-pipe outer wall, pipe inner wall-pipe internal medium). Its characteristics include regular signal peaks, regular occurrence times (proportional to the interface spacing), and signal intensity that is only related to the acoustic impedance difference between the media on both sides of the interface, without carrying defect information. The other is the internal defect scattering signal, which is generated by non-spectral scattering of ultrasonic waves when they encounter internal defects (such as cracks, holes, slits) in the object under test. Its characteristics include irregular signal peaks, no fixed occurrence times (corresponding to the actual location of the defect), signal intensity that is related to the size, shape, and orientation of the defect, and the signal waveform will broaden due to the wave creep effect at the defect edge (e.g., the defect signal broadening of a 2mm wide slit is approximately 0.2-0.3mm). In this embodiment, the defect signal is required, therefore the multi-medium interface reflection signal needs to be filtered out. The preprocessed echo signal is smoothed to obtain the preprocessed echo signal. Two-dimensional smooth signal matrix with consistent dimensions and based on The adaptive threshold is calculated as shown in formula (6). (6) in, For adaptive threshold matrix, The threshold matrix is ​​a fixed scaling factor. In, each element This refers to the pre-processed echo signal. The dynamic threshold corresponding to the position in the m-th row and n-th column; in this scheme, ratio=0.15; Will The calculated adaptive threshold matrix By comparing the signals, echo signals with amplitudes less than the corresponding position thresholds are selected as echo signals for feature extraction, thus completing the noise reduction.

[0031] Specifically, the smoothing process in this solution can be achieved using mean smoothing, Gaussian smoothing, or median smoothing, which are conventional techniques for those skilled in the art and will not be described or limited in detail. The peak amplitude, time difference of arrival, signal duration, waveform distortion, and main peak frequency of the echo signal are extracted and compared with characteristic reference values ​​to separate defective signals. The peak amplitude is the maximum amplitude value of the echo signal's time-domain waveform; the time difference of arrival is the time interval between the start time of the echo signal and the start time of the reference transmitted signal; the signal duration is the time span of the echo signal from the start threshold to the end threshold; the waveform distortion is the deviation coefficient between the actual echo waveform and the standard sine waveform; and the main peak frequency is the frequency value with the highest energy in the frequency domain spectrum of the echo signal. The deviation ranges for peak amplitude, time difference of arrival, signal duration, waveform distortion, and main peak frequency of the spectrum are set respectively. If the deviation value of any feature of the echo signal exceeds the deviation range of the corresponding feature, the echo signal is determined to be a defective signal and the defective signal is separated.

[0032] Specifically, if the peak amplitude deviation exceeds ±20% of the reference value, the arrival time difference deviation exceeds ±15% of the reference value, the signal duration deviation exceeds ±25% of the reference value, the waveform distortion deviation exceeds ±30% of the reference value (i.e., the normalized cross-correlation coefficient is less than 0.7), or the frequency deviation of the main peak of the spectrum exceeds ±10% of the reference value, any deviation of any characteristic quantity that meets the above conditions is judged as a defective signal and is retained.

[0033] In this scheme, a signal amplification / reduction circuit is used to adjust the echo signal intensity to compensate for the attenuation caused by the propagation distance of the ultrasonic wave in the medium. The adjusted signal intensity is negatively correlated with the attenuation caused by the propagation distance: the longer the propagation distance (the greater the attenuation), the higher the signal amplification factor; the shorter the propagation distance (the smaller the attenuation), the higher the signal reduction factor, ensuring that the adjusted signal can meet the needs of subsequent defect feature extraction and imaging processing.

[0034] In a specific embodiment, the three-dimensional imaging and output module is used to associate the echo signal with the scan coordinate information. It employs a spatial reconstruction method based on "slice reconstruction" and a lightweight compressed sensing algorithm to generate a three-dimensional topography model based on the echo signal, defect signal, and scan coordinate information. The scheme for visualizing the location and information of the defect on the three-dimensional topography model is as follows: The 3D imaging and output module is specifically used to stitch together all echo signals at the same height according to the scanning path sequence using an orthogonal matching tracking algorithm to form multiple 2D images. The separated defect signals are sparsely sampled, and the OMP algorithm is used to reconstruct the sparsely sampled defect signals to obtain complete defect information. Depth information and horizontal distance are calculated based on the complete defect information. The 2D images are then superimposed, and 3D spatial positioning is performed based on the depth information and horizontal distance to obtain a 3D topography model with the defect location, shape, and size. The complete defect information is the complete waveform data of the defect signal. The depth information and horizontal distance are calculated based on the time delay of the defect signal echo in the complete defect information, as shown in formulas (7) and (8). (7) (8) in, For depth information, Horizontal distance The sound wave propagation distance is calculated based on the time delay of the defect signal echo and the propagation speed of the ultrasonic wave in the material. The refraction angle of the transducer.

[0035] In this solution, by precisely associating echo signals, defect signals and scanning coordinates, and using the "slice reconstruction" method, the traditional one-dimensional waveform signal is transformed into an intuitive three-dimensional shape model. This can accurately present the three-dimensional spatial location, size, burial depth and distribution pattern of defects inside the object, realizing the leap from "detecting signals" to "locating defects", and greatly improving the accuracy and reliability of detection. By integrating a lightweight compressed sensing algorithm and utilizing the sparsity of defect signals, it allows for the high-precision reconstruction of complete information by collecting a small amount of data at a rate far lower than the Nyquist sampling rate. This significantly reduces the amount of data collected and the transmission and processing time. Without losing key information, it significantly accelerates the generation speed of 3D models, meeting the needs of rapid on-site detection and real-time analysis.

[0036] The effectiveness of the system in this application is verified using the following examples. First embodiment: Multilayer media detection Three wooden boards (1.5mm thick) were stacked, with a 2mm slit defect created in the middle layer. The above steps were repeated. The inspection results are as follows. Figure 2 As shown in the figure, the test results demonstrate that the system can clearly identify the location of the slit, verifying its ability to detect internal defects in multi-layered media.

[0037] Second Example: PVC Pipe Defect Detection System setup: Place the device on the experimental platform, fill the acrylic water tank with water, and fix the PVC pipe sample to be tested at the bottom of the water tank.

[0038] Parameter settings: The transducer frequency was set to 2.5MHz, the motor scanning speed was adjusted to 0.03cm / s, and the optimal scanning spacing was determined to be 1mm through COMSOL simulation.

[0039] Activate the temperature compensation algorithm, input the real-time water temperature (e.g., 20℃), and calculate the speed of sound c = 331.45 + 0.61 × 20 = 343.45 m / s.

[0040] Data Acquisition: The motor drives the transducer to scan the pipeline laterally, simultaneously acquiring echo signals. When the transducer detects a defect (such as a crack in the inner wall of the pipeline), an abnormal peak value appears in the echo signal.

[0041] 3D Reconstruction: By registering multiple sets of 2D slice data, a 3D model of PVC pipe defects can be generated, and the defect location (e.g., depth H=10mm, horizontal distance L=20mm) and size (e.g., crack length 5mm) can be marked.

[0042] In summary, this system organically integrates simulation prediction, signal acquisition, signal processing, and imaging display modules through modular design, featuring ease of operation, intuitive imaging, and adaptability to various media environments. Experimental verification shows that the system has excellent identification capabilities for defects wider than 1.0 mm, making it particularly suitable for non-destructive testing and teaching demonstrations of structures such as underwater pipelines and composite panels. It also shows promising application prospects in fields such as marine engineering inspection and materials science experiments.

[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-media three-dimensional flaw detection system based on ultrasonic pulse echo, characterized in that, include: Synchronous data acquisition module, temperature compensation module, multiphysics simulation optimization module, signal processing module, and three-dimensional imaging and output module; The synchronous data acquisition module is used to scan the object under test, record the coordinate information of the corresponding scanning position, synchronously transmit pulse sound waves to the object under test during the scanning process, and receive the echo signal from the object under test in real time. The temperature compensation module is used to calculate the real-time sound velocity value at the current water temperature based on the real-time ambient water temperature, and output it to the multiphysics simulation optimization module as a simulation parameter for simulation. The multiphysics simulation optimization module is used to solve the control equations of each physics field based on the intrinsic parameters of the object under test, the sound wave propagation parameters, and the real-time sound velocity value output by the temperature compensation module. This simulates the "electro-mechanical-acoustic" energy conversion process of the sound wave and the sound pressure at each location obtained by the sound wave during this process. Based on the simulated sound pressure, it generates theoretical waveforms of the reflection from the medium interface and the bottom echo of the object under test in a defect-free state, providing characteristic reference values ​​for defect signal discrimination to the signal processing module. The intrinsic parameters of the object under test include the density and attenuation coefficient of the object under test, and the sound wave propagation parameters include the pulse width and the transmission power. The signal processing module is used to receive the echo signal of the object under test output by the synchronous data acquisition module, preprocess the echo signal, reduce noise, extract features, compare the extracted features with feature reference values, and separate defect signals. The three-dimensional imaging and output module is used to associate the echo signal with the scanning coordinate information. It uses a spatial reconstruction method based on slice reconstruction and a lightweight compressed sensing algorithm to generate a three-dimensional shape model based on the echo signal, defect signal and scanning coordinate information, and visualizes the location and information of the defect on the three-dimensional shape model.

2. The multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 1, characterized in that, The multiphysics simulation optimization module includes mutually coupled pressure acoustic physics field, solid mechanical physics field and electrostatic physics field; The electrostatic physical field is used to simulate the process of establishing an electric field and electric displacement field inside the piezoelectric transducer by an electrical signal applied to it. It takes an external driving voltage as input and receives displacement field and strain field data from the solid mechanical physical field for bidirectional coupling. The electric field force inside the piezoelectric transducer is solved to transfer the mechanical vibration energy converted from the electric field energy through the solid mechanical physical field, forming the sound source excitation condition of the pressure acoustic physical field. The solid mechanical physical field is used to simulate the deformation and vibration of the piezoelectric transducer wafer under voltage drive. It is bidirectionally coupled with the electrostatic physical field. It takes the electric field force, object density and sound wave propagation parameters as input to solve for the vibration velocity, displacement field and strain field of the piezoelectric transducer. The vibration velocity is fed back to the pressure acoustic physical field, and the displacement field and strain field are fed back to the electrostatic physical field. The pressure acoustic physical field is used to simulate the propagation and fluctuation of sound waves. It is coupled with the solid mechanical physical field. Based on the vibration velocity, the excitation conditions of the sound source, and the intrinsic parameters and real-time sound velocity of the object under test, it solves the theoretical sound pressure signal corresponding to the propagation, reflection, refraction and attenuation of the sound wave in the object under test. Finally, it outputs the theoretical sound pressure signal of the sound wave reflected back at the medium interface and bottom surface, which is the theoretical waveform.

3. The multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 1, characterized in that, The multiphysics simulation optimization module is used to extract the sound pressure data and the curve of sound pressure data changing with time at a specified receiving position of the pressure acoustic physical field, and to generate the theoretical waveform of the reflection of the medium interface and the bottom echo of the object under test in a defect-free state.

4. The multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 1, characterized in that, Calculate the real-time speed of sound at the current water temperature based on the real-time ambient water temperature, including: The real-time sound velocity value at the current water temperature is calculated based on the real-time ambient water temperature, as shown in formula (1). （1） in, This is the real-time speed of sound value. For the ambient water temperature, This is the speed of sound in dry air at standard atmospheric pressure and a temperature of 0 degrees Celsius. The temperature coefficient of the speed of sound in air.

5. The multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 1, characterized in that, The signal processing module is specifically used to preprocess the echo signal through a signal amplification / shortening circuit, reduce noise in the processed echo signal through an adaptive threshold filtering algorithm, extract the peak amplitude, time difference of arrival, signal duration, waveform distortion, and main peak frequency of the spectrum of the echo signal, and compare them with characteristic reference values ​​to separate defective signals. The peak amplitude is the maximum amplitude value of the time domain waveform of the echo signal, the time difference of arrival is the time interval between the start time of the echo signal and the start time of the reference transmitted signal, the signal duration is the time span of the echo signal from the start threshold to the end threshold, the waveform distortion is the deviation coefficient between the actual echo waveform and the standard sine waveform, and the main peak frequency of the spectrum is the frequency value with the highest energy in the frequency domain spectrum of the echo signal.

6. The multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 5, characterized in that, The signal processing module preprocesses the echo signal through a signal amplification / attenuation circuit, specifically as follows: The upper and lower limits of the peak range are set. When the peak value of the echo signal is greater than the upper limit of the peak range, the echo signal is suppressed to the peak range by the signal amplification circuit. When the peak value of the echo signal is less than the lower limit of the peak range, the echo signal is amplified to the peak range by the signal amplification circuit.

7. A multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 5, characterized in that, The signal processing module uses an adaptive threshold filtering algorithm to reduce noise in the processed echo signal, specifically as follows: The preprocessed echo signal is smoothed to obtain the preprocessed echo signal. Two-dimensional smooth signal matrix with consistent dimensions and based on The adaptive threshold is calculated as shown in formula (2). （2） in, For adaptive threshold matrix, The threshold matrix is ​​a fixed scaling factor. In, each element This refers to the pre-processed echo signal. The dynamic threshold corresponding to the position in row m and column n; Will The calculated adaptive threshold matrix By comparing the signals, echo signals with amplitudes less than the corresponding position thresholds are selected as echo signals for feature extraction, thus completing the noise reduction.

8. A multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 5, characterized in that, The signal processing module compares the peak amplitude, time difference of arrival, signal duration, waveform distortion, and main peak frequency of the echo signal with characteristic reference values ​​to separate defective signals, specifically: The deviation ranges for peak amplitude, time difference of arrival, signal duration, waveform distortion, and main peak frequency of the spectrum are set respectively. If the deviation value of any feature of the echo signal exceeds the deviation range of the corresponding feature, the echo signal is determined to be a defective signal and the defective signal is separated.

9. A multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 1, characterized in that, The three-dimensional imaging and output module is specifically used to stitch together all echo signals at the same height according to the scanning path order using an orthogonal matching tracking algorithm to form multiple two-dimensional images. The separated defect signals are sparsely sampled, and the OMP algorithm is used to reconstruct the sparsely sampled defect signals to obtain complete defect information. The depth information and horizontal distance are calculated based on the complete defect information. The two-dimensional images are superimposed, and three-dimensional spatial positioning is performed based on the depth information and horizontal distance to obtain a three-dimensional morphological model with the defect location, shape, and size. The complete defect information is the complete waveform data of the defect signal.

10. A multi-media three-dimensional flaw detection system based on ultrasonic pulse echo according to claim 9, characterized in that, Calculate depth information and horizontal distance based on complete defect information, including: The depth information and horizontal distance are calculated based on the time delay of the defect signal echo in the complete defect information, as shown in formulas (3) and (4). （3） （4） in, For depth information, Horizontal distance The sound wave propagation distance is calculated based on the time delay of the defect signal echo and the propagation speed of the ultrasonic wave in the material. The refraction angle of the transducer.

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