An ultrasonic flaw detection method and system based on pulse reflection

Abstract

The application relates to the technical field of ultrasonic flaw detection, in particular to an ultrasonic flaw detection method and system based on pulse reflection, which has the technical scheme as follows: S1, collecting real-time vibration information and temperature information of a measured body; S2, constructing a propagation disturbance representation model based on the information in S1; S3, generating a compensation excitation pulse; S4, emitting the compensation excitation pulse; S5, collecting echo signals and obtaining residual signals through matched filtering and cross-correlation processing, and updating phase correction amounts and amplitude coefficients based on the signals and reference echoes to realize closed-loop compensation; the application collects vibration, temperature and geometric data through multiple sensors, constructs a propagation disturbance model and dynamically calculates phase correction amounts and amplitude weighting coefficients, compensates for environmental influences, generates a compensation pulse, emits and processes echo signals using an array transducer, realizes high-precision defect detection, adopts a closed-loop control mechanism, automatically adjusts flaw detection parameters based on residual estimation and feedback, and ensures stability.

Description

Technical Field

[0001] This invention relates to the field of ultrasonic flaw detection technology, and specifically to an ultrasonic flaw detection method and system based on pulse reflection. Background Technology

[0002] Ultrasonic testing technology is widely used for defect detection in various industrial components, especially in high-requirement industries such as aerospace, automotive, construction, and petrochemicals. Traditional ultrasonic testing methods mainly rely on fixed frequencies and simple signal processing techniques, which can effectively identify defects such as cracks and holes in metallic materials and single structures, and are suitable for routine testing scenarios. However, in dynamic environments (such as vibration, thermal expansion, or relatively moving components), traditional methods are affected by changes in the external environment, resulting in distortion of the echo signal, which in turn affects the accuracy of defect location and size determination.

[0003] Furthermore, the propagation of ultrasonic signals in composite materials, multilayer structures, or components with complex geometries is affected by complex reflection, refraction, and scattering phenomena. In particular, defects such as micro-cracks and delamination at interlayers or interfaces are difficult to accurately identify and locate using traditional methods. This phenomenon is especially prominent when inspecting heterogeneous materials (such as composite materials) or components with complex shapes, posing serious challenges to the accuracy and reliability of traditional ultrasonic flaw detection methods. To address these issues, we propose an ultrasonic flaw detection method and system based on pulse reflection. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an ultrasonic flaw detection method and system based on pulse reflection, solving the problems mentioned in the background art.

[0005] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0006] This invention provides an ultrasonic flaw detection method based on pulse reflection, comprising the following steps:

[0007] S1. Acquire real-time vibration information, real-time temperature information, geometric parameters, and material reference sound velocity of the tested object. ;

[0008] S2. Based on the information from step S1, construct a propagation disturbance characterization model. The propagation disturbance characterization model includes a temperature and sound speed correction sub-model, a motion and Doppler estimation sub-model, and a vibration and path offset estimation sub-model, which are used to calculate the phase correction and amplitude weighting coefficient of each transducer unit.

[0009] S3. Generate a compensating excitation pulse at the transmitting end: Generate a compensating excitation pulse based on the phase correction amount and amplitude weighting coefficient calculated in step S2. The compensating excitation pulse is a linear frequency modulated pulse or an intra-pulse phase coding sequence. Apply a window function weighting to the excitation pulse and adjust the transmission timing of the low-frequency pulse and the high-frequency pulse according to the real-time signal-to-noise ratio or thickness estimation result.

[0010] S4. Using at least a 2×2 element transducer array, a compensated excitation pulse is emitted according to the phase delay and amplitude control rules of step S3, so that the ultrasonic waves are coherently superimposed on the preset propagation path inside the measured body to construct an echo energy convergence zone.

[0011] S5. Acquire the echo signal and perform matched filtering and cross-correlation processing on the echo signal to obtain the received residual signal. Perform self-reference residual estimation based on the received residual signal and the stored reference echo, and feed back the residual signal to iteratively update the phase correction amount and amplitude weighting coefficient in step S2.

[0012] Preferably, the temperature and sound velocity correction sub-model in step S2 is constructed in the following manner:

[0013]

[0014] in, This is the corrected speed of sound at temperature T. For real-time temperature, For reference temperature, The temperature coefficient of sound velocity in the material;

[0015] The motion and Doppler estimator sub-model is constructed as follows:

[0016]

[0017] in, The corrected frequency, The reference frequency of the excitation signal, The relative velocity of the measured object. The reference speed of sound;

[0018] The vibration and path offset estimation sub-model is constructed as follows:

[0019]

[0020] in, The relative displacement caused by vibration. It represents vibration acceleration.

[0021] Preferably, the phase correction amount in step S2 Calculate according to the following formula:

[0022]

[0023] in:

[0024] The reference frequency for the excitation pulse;

[0025] For the first The propagation distance corresponding to each array element;

[0026] ;

[0027] The relative velocity of the object being measured.

[0028] Preferably, the amplitude weighting coefficient Calculated in the following form:

[0029]

[0030] in, For reference amplitude, The material attenuation coefficient, This corresponds to the propagation distance.

[0031] Preferably, the self-reference residual estimation in step S5 obtains multiple time delay residuals by cross-correlation matching between the real-time echo signal and the reference echo signal stored in groups according to environmental conditions, and iteratively updates the phase correction amount based on the least squares criterion or Kalman filter.

[0032] Preferably, within the same detection area, low-frequency pulses and high-frequency pulses are emitted in a time sequence, wherein low-frequency pulses are used for deep defect detection and high-frequency pulses are used for shallow defect detection.

[0033] The present invention also provides an ultrasonic flaw detection system based on pulse reflection, comprising:

[0034] The parameter acquisition module is used to acquire the geometric parameters of the measured object and the material reference sound velocity. Vibration signals and temperature signals;

[0035] The modeling and compensation unit is used to construct a propagation disturbance characterization model based on the output of the parameter acquisition module, and output the phase correction amount and amplitude weighting coefficient corresponding to each transducer array element.

[0036] A pulse generation and transmission unit is used to generate a compensated excitation pulse based on the phase correction amount and amplitude weighting coefficient, and to transmit the compensated excitation pulse through a transducer array of at least 2×2 elements.

[0037] The receiving and signal processing unit is used to acquire the echo signal and perform matched filtering and cross-correlation operations on the echo signal to extract the residual signal;

[0038] Reference signal storage unit, used to group and store reference echo sequences according to environmental conditions;

[0039] A closed-loop control unit is used to iteratively correct the propagation disturbance characterization model based on the residual signal and the reference echo sequence, and update the transmission parameters of the compensation excitation pulse.

[0040] Preferably, the system supports a time reversal function, which reverses the time domain of the acquired echo signal and retransmits it to form energy focusing at the defect.

[0041] Preferably, the transducer array supports a phase resolution of ≤1° per channel and a delay resolution of ≤1ns, and supports independent amplitude adjustment.

[0042] In summary, the present invention has the following main beneficial effects:

[0043] This invention solves the errors and instabilities caused by temperature changes, vibrations, or relative motion in traditional ultrasonic flaw detection methods under dynamic environments by introducing a dynamic compensation mechanism for temperature, vibration, and motion. Based on pulse reflection compensation-type excitation pulse generation technology, combined with real-time phase correction and amplitude weighting coefficients, it effectively compensates for these dynamic disturbances, ensuring signal accuracy and defect location precision.

[0044] This invention utilizes a closed-loop control mechanism, employing self-referenced residual estimation and dynamically updated compensating excitation pulses to adapt to environmental changes and optimize the flaw detection process in real time. It can automatically adjust the transmission parameters of ultrasonic signals based on real-time temperature, vibration, and motion data, ensuring high accuracy even in complex environments. Furthermore, it can be adjusted in real time according to the needs of different materials and complex structures, effectively addressing complex phenomena such as reflection, refraction, and scattering, and ensuring stable flaw detection performance in various application scenarios. Attached Figure Description

[0045] Figure 1 This is a flowchart of the method framework of the present invention. Detailed Implementation

[0046] 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 some embodiments of the present invention, but not all embodiments. Based on the described 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.

[0047] The following embodiments are used to illustrate the present invention, but should not be used to limit the scope of protection of the present invention. The conditions in the embodiments can be further adjusted according to specific conditions, and simple improvements to the method of the present invention under the premise of the concept of the present invention are all within the scope of protection claimed by the present invention.

[0048] Example 1

[0049] Experimental objective: To verify how the pulse reflection-based ultrasonic flaw detection method can adapt to complex temperature changes, vibrations, and motion environments by dynamically adjusting the phase correction and amplitude weighting coefficients, thereby achieving high-precision defect detection.

[0050] Experimental equipment and environment:

[0051] Accelerometer: with an accuracy of ±0.01m / s² and a frequency response range of 0-1000Hz, used to collect vibration signals of samples.

[0052] Temperature sensor: Accuracy of ±0.5°C, measurement range of -40°C to 100°C, used for real-time temperature data acquisition.

[0053] Ultrasonic transducer array: 2×2 array, frequency range from 1MHz to 10MHz, supports phase and amplitude control per channel, delay resolution ≤1ns.

[0054] Metal material samples: such as aluminum alloys, steel and other metal materials.

[0055] Experimental procedures, refer to Figure 1 As shown:

[0056] 1. Data Collection

[0057] Accelerometers and temperature sensors were installed in the metallic material sample to collect vibration signals in real time. and temperature data Simultaneously, the geometric parameters of the sample and the reference sound velocity of the material are obtained. .

[0058] Ensure that the data acquisition frequency and accuracy meet the flaw detection accuracy requirements.

[0059] 2. Construct a propagation perturbation characterization model

[0060] Temperature and sound speed correction sub-model: Correcting the speed of sound through temperature Use the formula:

[0061]

[0062] in, For real-time temperature, For reference temperature, The temperature coefficient of sound velocity in the material is used, and real-time temperature data is used to dynamically update this model.

[0063] Motion and Doppler Estimator Sub-model: Vibration Signals Acquired by Accelerometers Calculate relative velocity The frequency of the ultrasonic signal is corrected based on the Doppler effect using the following formula:

[0064]

[0065] in, As the reference excitation frequency, As the reference speed of sound, This represents the relative velocity.

[0066] Vibration and path offset estimation sub-model: based on real-time vibration acceleration signal Estimate the path offset caused by vibration Use the formula:

[0067]

[0068] This estimation corrects the propagation path of the ultrasonic signal.

[0069] Calculation of phase correction and amplitude weighting coefficient:

[0070] Based on the above three sub-models, the phase correction and amplitude weighting coefficient of each transducer unit are calculated as follows:

[0071] Phase correction For each transducer element, the following formula is used for calculation:

[0072]

[0073] in, For the first The propagation distance corresponding to each array element The change in the speed of sound due to temperature. Given the relative motion velocity, this formula is used to calculate the phase correction for each array element in real time.

[0074] Amplitude weighting coefficient Based on the propagation path and material properties, the amplitude weighting coefficient for each array element is calculated using the following formula:

[0075]

[0076] in, For reference amplitude, The material attenuation coefficient, The amplitude weighting coefficient is dynamically adjusted based on the material properties of the measured object and the different propagation paths, corresponding to the propagation distance.

[0077] 3. Generate compensating excitation pulses

[0078] Using the phase correction and amplitude weighting coefficients calculated in step S2, a compensated excitation pulse is generated. A linear frequency modulated pulse or an intra-pulse phase coding sequence is selected, and a window function weighting is applied to reduce interference and distortion of the echo signal.

[0079] The transmission timing of low-frequency pulses and high-frequency pulses is dynamically adjusted based on the real-time signal-to-noise ratio or thickness estimation results.

[0080] 4. Emitter compensating excitation pulse

[0081] Using a transducer array of at least 2×2 elements, compensated excitation pulses are emitted according to the phase delay and amplitude control rules in step S3 to ensure that controllable coherent superposition is generated inside the measured object, thus constructing an echo energy convergence zone.

[0082] The transducer array has a phase resolution of ≤1° and a delay resolution of ≤1ns, and supports independent amplitude and frequency control for each channel.

[0083] 5. Echo signal acquisition and processing

[0084] The echo signal is acquired and subjected to matched filtering and cross-correlation processing to obtain the received residual signal.

[0085] Self-reference residual estimation is performed based on the received residual signal and reference echo, and the residual signal is fed back to the modeling and compensation unit to update the phase correction and amplitude weighting coefficients, thus completing closed-loop control.

[0086] Experimental data recording and analysis:

[0087] To verify the compensation effect of this method in a dynamic environment, an aluminum alloy test block was selected as the test object, and its reference sound velocity was: Ultrasonic flaw detection tests were conducted under different temperature and vibration environments, and compared with the traditional pulse reflection method without the introduction of a compensation model.

[0088] 1. Experiment on the effect of temperature and sound velocity compensation

[0089] The experiment recorded the measurement results of ultrasonic velocity using both the traditional method and the proposed method under different ambient temperature conditions, as well as the improvement in the overall error of propagation time. The experimental data are shown in Table 1.

[0090] Ambient temperature (°C) Traditional methods for measuring the speed of sound (m / s) The corrected speed of sound (m / s) according to this method Overall error improvement rate of propagation time -10 6388 6303 14.90% 10 6345 6302 15.20% 40 6228 6296 15.60% 60 6115 6294 15.30%

[0091] Table 1 Comparison of sound velocity correction and error improvement under different temperature conditions

[0092] As shown in Table 1, the error in measuring sound velocity using traditional methods increases significantly as the ambient temperature deviates from the reference temperature, leading to an accumulation of errors in propagation time calculation. In contrast, this method introduces a temperature-sound velocity correction sub-model to correct the sound velocity parameters in real time, reducing the overall propagation error of ultrasound under different temperature conditions by an average of approximately 15.25%, demonstrating excellent environmental adaptability.

[0093] 2. Defect location accuracy test

[0094] Under conditions of 25°C and vibration interference of 0.5 m / s², the location and detection of three pre-fabricated microcracks at different depths in the sample were performed. The experimental data, comparing the results of traditional methods with those of this method, are shown in Table 2.

[0095] Defect number Actual depth value Traditional methods for detecting depth Traditional method bias This method detects depth. This method has deviations. 1 5 5.68 0.68 5.11 0.11 2 15 15.85 0.85 15.21 0.21 3 25 26.12 1.12 25.38 0.38

[0096] Table 2 Comparison of Microcrack Detection and Location Errors (Unit: mm)

[0097] As shown in Table 2, under dynamic vibration conditions, the traditional method causes the crack depth positioning deviation to increase significantly with increasing depth due to propagation path offset and time estimation error. However, the proposed method can effectively correct the propagation path disturbance caused by vibration, so that the positioning error of the three cracks is controlled within 0.5 mm, with an average deviation of about 0.23 mm. The positioning accuracy is significantly better than that of the traditional method.

[0098] Conclusion: This embodiment verifies that the ultrasonic flaw detection method based on pulse reflection, after introducing a dynamic compensation mechanism for temperature and vibration, can significantly improve the accuracy of sound velocity estimation and defect location under complex environmental conditions, thereby effectively improving the overall flaw detection accuracy and robustness of the system.

[0099] Example 2

[0100] Experimental Objective: This embodiment aims to verify the application of pulse reflection-based ultrasonic flaw detection methods in composite materials, multilayer structures, or components with complex geometries, especially in dealing with complex reflection, refraction, and scattering phenomena, and how to accurately identify defects such as micro-cracks and delamination at interfaces and between layers.

[0101] Experimental procedure reference Figure 1 :

[0102] 1. Data Collection

[0103] Accelerometers and temperature sensors were installed in composite material and multilayer structure samples to collect vibration signals in real time. and temperature data Simultaneously, the geometric parameters of the sample and the reference sound velocity of the material are obtained. .

[0104] Ensure that the data acquisition frequency and accuracy meet the flaw detection accuracy requirements.

[0105] 2. Construct a propagation perturbation characterization model

[0106] Temperature and sound speed correction sub-model: The effect of temperature on sound speed is corrected using a formula, and the sound speed is dynamically updated. And based on the sound velocity temperature coefficient of the material Make corrections:

[0107]

[0108] in, For reference temperature, The temperature coefficient of sound velocity is the temperature coefficient of a material; different materials (such as carbon fiber, metals, and ceramics) have different... This allows for dynamic correction of the speed of sound based on temperature changes.

[0109] Motion and Doppler Estimator Sub-model: Through the acquisition of vibration signals Estimate relative velocity And dynamically correct the deviation of the ultrasonic frequency:

[0110]

[0111] The model is based on real-time vibration data. Dynamically adjust the frequency to compensate for the influence of motion on ultrasonic signals, especially in multi-layered structures or composite materials with movement.

[0112] Vibration and path offset estimation sub-model: based on real-time vibration acceleration data Estimate the path offset of the material And correct the ultrasonic wave propagation path:

[0113]

[0114] This model corrects for the deviation of ultrasonic wave propagation paths caused by vibration or interface defects (such as delamination or microcracks), ensuring that signals can accurately pass through complex layered structures.

[0115] Phase correction and amplitude weighting coefficient:

[0116] Phase correction: Calculated for each array element using the following formula:

[0117]

[0118] in, For the propagation distance of the array element, , For relative motion velocity, this formula compensates for phase shifts caused by temperature changes and motion, ensuring signal propagation accuracy in multilayer structures.

[0119] Amplitude weighting factor: Calculated using the following formula, depending on material properties and propagation path:

[0120]

[0121] in, For reference amplitude, The attenuation coefficient of the material, This coefficient is dynamically adjusted to accommodate the propagation characteristics of different materials and interlayer attenuation, thus determining the propagation distance.

[0122] 3. Generate compensating excitation pulses

[0123] Based on the phase correction and amplitude weighting coefficients calculated in step S2, a compensated excitation pulse is generated. An appropriate linear frequency modulated pulse or intra-pulse phase coding sequence is selected, and window function weighting is applied to reduce signal interference and distortion. At the same time, the pulse transmission timing is adjusted according to environmental changes.

[0124] 4. Emitter compensating excitation pulse

[0125] Using a 2×2 array of transducers, compensated excitation pulses are emitted according to the phase delay and amplitude control rules in step S3. Each array element channel supports independent phase and amplitude control to ensure that the signal can penetrate composite materials and multi-layer structures of different materials.

[0126] 5. Echo signal acquisition and processing

[0127] The echo signal is acquired and subjected to matched filtering and cross-correlation processing to extract the received residual signal.

[0128] Self-reference residual estimation is performed based on the residual signal and the stored reference echo, and the feedback signal is used to iteratively update the phase correction and amplitude weighting coefficients to achieve closed-loop control.

[0129] Experimental data recording and analysis:

[0130] To address the complex reflection, refraction, and scattering phenomena commonly found in composite materials (CFRP / GFRP) and multilayer structures, an ultrasonic detection method using a 2×2 element transducer array was employed. The detection performance of this method and traditional methods under complex material conditions was compared and analyzed.

[0131] 1. Experiment on the propagation error of complex materials

[0132] Under simulated operating conditions (vibration frequency range 5–15 Hz), different types of composite materials and laminated structures were tested, and the propagation path error and improvement effect of the two methods were recorded. The experimental results are shown in Table 3.

[0133] Sample type Environmental interference Traditional method path error rate Path error rate of this method Relative reduction in error 16-layer CFRP single board 5Hz vibration 2.90% 2.40% 17.20% 32-layer CFRP single board 10Hz vibration 4.60% 3.70% 19.50% CFRP / aluminum alloy laminated structure 15Hz vibration 5.30% 4.30% 18.80%

[0134] As shown in Table 3, in composite materials and multilayer structures, the traditional method suffers significantly increased error in propagation path modeling due to the large number of interlayer interfaces and significant differences in material acoustic parameters. This method addresses this by dynamically adjusting the phase correction. and amplitude weighting coefficient Joint correction of the array echo signal reduces the propagation path error by an average of about 18.5%, significantly improving the modeling accuracy under complex media conditions.

[0135] 2. Interface Defect Identification Capability Experiment

[0136] For micro-delamination defects of 0.2 mm in multi-layer structures, 100 repeated inspections were conducted under the same working conditions. The identification results are as follows:

[0137] Traditional method: Due to the dispersed echo energy and susceptibility to motion interference, the effective identification count is 74 times, and the defect identification rate is 74%.

[0138] The method of this application: by introducing a self-referenced residual estimation mechanism and a closed-loop parameter update strategy, the effective identification number reaches 97 times, and the defect identification rate is improved to 97%.

[0139] Conclusion: This embodiment further verifies that when faced with complex reflection, refraction and scattering conditions in composite materials and multilayer structures, the proposed method can rely on a dynamic correction model and closed-loop control mechanism to achieve accurate compensation for propagation path and echo characteristics, thereby efficiently and stably identifying minute defects at interfaces and between layers, and has good engineering application value.

[0140] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that, unless otherwise defined, the technical or scientific terms used in this invention should be understood in the ordinary sense by those skilled in the art to which this invention pertains, and the terms "comprising" or "including" or similar terms used in this invention mean that the element or object preceding the word covers the element or object listed after the word and its equivalents.

[0141] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An ultrasonic flaw detection method based on pulse reflection, characterized in that, Includes the following steps: S1. Acquire real-time vibration information, real-time temperature information, geometric parameters, and material reference sound velocity of the tested object. ; S2. Based on the information from step S1, construct a propagation disturbance characterization model. The propagation disturbance characterization model includes a temperature and sound speed correction sub-model, a motion and Doppler estimation sub-model, and a vibration and path offset estimation sub-model, which are used to calculate the phase correction and amplitude weighting coefficient of each transducer unit. S3. Generate a compensating excitation pulse at the transmitting end: Generate a compensating excitation pulse based on the phase correction amount and amplitude weighting coefficient calculated in step S2. The compensating excitation pulse is a linear frequency modulated pulse or an intra-pulse phase coding sequence. Apply a window function weighting to the excitation pulse and adjust the transmission timing of the low-frequency pulse and the high-frequency pulse according to the real-time signal-to-noise ratio or thickness estimation result. S4. Using at least a 2×2 element transducer array, a compensated excitation pulse is emitted according to the phase delay and amplitude control rules of step S3, so that the ultrasonic waves are coherently superimposed on the preset propagation path inside the measured body to construct an echo energy convergence zone. S5. Acquire the echo signal and perform matched filtering and cross-correlation processing on the echo signal to obtain the received residual signal. Perform self-reference residual estimation based on the received residual signal and the stored reference echo, and feed back the residual signal to iteratively update the phase correction amount and amplitude weighting coefficient in step S2.

2. The ultrasonic flaw detection method based on pulse reflection according to claim 1, characterized in that, The temperature and sound velocity correction sub-model in step S2 is constructed as follows: in, This is the corrected speed of sound at temperature T. For real-time temperature, For reference temperature, The temperature coefficient of sound velocity in the material; The motion and Doppler estimator sub-model is constructed as follows: in, The corrected frequency, The reference frequency of the excitation signal, The relative velocity of the measured object. The reference speed of sound; The vibration and path offset estimation sub-model is constructed as follows: in, The relative displacement caused by vibration. It represents vibration acceleration.

3. The ultrasonic flaw detection method based on pulse reflection according to claim 1, characterized in that, Phase correction amount in step S2 Calculate according to the following formula: in: The reference frequency for the excitation pulse; For the first The propagation distance corresponding to each array element; ； The relative velocity of the object being measured.

4. The ultrasonic flaw detection method based on pulse reflection according to claim 1, characterized in that, The amplitude weighting coefficient Calculated in the following form: in, For reference amplitude, The material attenuation coefficient, This corresponds to the propagation distance.

5. The ultrasonic flaw detection method based on pulse reflection according to claim 1, characterized in that, The self-reference residual estimation in step S5 obtains multiple time delay residuals by cross-correlation matching between the real-time echo signal and the reference echo signal stored in groups according to environmental conditions, and iteratively updates the phase correction amount based on the least squares criterion or Kalman filter.

6. The ultrasonic flaw detection method based on pulse reflection according to claim 1, characterized in that, Within the same detection area, low-frequency pulses and high-frequency pulses are emitted in a time sequence, with low-frequency pulses used for deep defect detection and high-frequency pulses used for shallow defect detection.

7. An ultrasonic flaw detection system based on pulse reflection, characterized in that, include: The parameter acquisition module is used to acquire the geometric parameters of the measured object and the material reference sound velocity. Vibration signals and temperature signals; The modeling and compensation unit is used to construct a propagation disturbance characterization model based on the output of the parameter acquisition module, and output the phase correction amount and amplitude weighting coefficient corresponding to each transducer array element. A pulse generation and transmission unit is used to generate a compensated excitation pulse based on the phase correction amount and amplitude weighting coefficient, and to transmit the compensated excitation pulse through a transducer array of at least 2×2 elements. The receiving and signal processing unit is used to acquire the echo signal and perform matched filtering and cross-correlation operations on the echo signal to extract the residual signal; Reference signal storage unit, used to group and store reference echo sequences according to environmental conditions; A closed-loop control unit is used to iteratively correct the propagation disturbance characterization model based on the residual signal and the reference echo sequence, and update the transmission parameters of the compensation excitation pulse.

8. The ultrasonic flaw detection system based on pulse reflection according to claim 7, characterized in that, The system supports time reversal, which reverses the time domain of the acquired echo signal and retransmits it to create energy focus at the defect.

9. The ultrasonic flaw detection system based on pulse reflection according to claim 7, characterized in that, The transducer array supports a phase resolution of ≤1° per channel and a delay resolution of ≤1ns, and supports independent amplitude adjustment.

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