Self-adaptive control TOFD (Time of Flight Diffraction) ultrasonic detection method, system, equipment and medium

Abstract

The invention relates to the technical field of ultrasonic detection, in particular to a self-adaptive control TOFD ultrasonic detection method, system and equipment and a medium. According to the method, firstly, a system parameter model is established based on detection configuration information, then a detection region is divided into overlapped sub-regions, independent detection parameters are set for each sub-region, and parameter adaptive adjustment is performed through real-time signal feature analysis in the detection process; through an overlapping coverage partition strategy and a multilayer parameter optimization mechanism, the uniformity and reliability of large-range detection are improved.

Description

Technical Field

[0001] The present application relates to the technical field of ultrasonic detection, and in particular to an adaptively controlled TOFD ultrasonic detection method, system, equipment and medium. Background Art

[0002] As an important non-destructive testing method, TOFD ultrasonic testing technology is used in the industrial field to detect weld quality. This technology uses the principle of ultrasonic diffraction to locate and evaluate defects through transmitting and receiving probes, and has the advantages of high detection accuracy and strong reliability.

[0003] In the prior art, TOFD detection is usually performed in a fixed parameter setting manner. The system executes the entire detection process according to pre-set detection parameters, and these parameters remain constant during the detection process.

[0004] However, due to the unevenness of material thickness and surface conditions in the inspected area, fixed parameter settings are difficult to adapt to the changing characteristics of the inspection area. This leads to uneven detection sensitivity and unstable signal quality, especially in large-scale inspections, which are prone to missed detections and misjudgments. This situation needs to be further improved. Summary of the invention

[0005] In order to solve the problem that the existing fixed parameter settings are difficult to adapt to the changing characteristics of the detection area, resulting in uneven detection sensitivity and unstable signal quality, the present application provides an adaptively controlled TOFD ultrasonic detection method, system, equipment and medium, which adopts the following technical solutions: In a first aspect, the present application provides an adaptively controlled TOFD ultrasonic detection method, comprising the following steps: Collecting detection configuration information, and generating system parameter information based on the detection configuration information, wherein the detection configuration information includes detection range, material type, and expected defect type; Collecting information of the inspected area, and generating partition detection parameters based on the inspected area information and the system parameter information; wherein the inspected area is divided into a plurality of overlapping sub-areas for independent control, the partition detection parameters include the transmission gain, receiving gain, threshold value and time delay compensation value of each sub-area, and the inspected area information includes material thickness and surface condition; Based on the partition detection parameters and the system parameter information, perform TOFD detection to obtain a detection signal; Based on the detection signal, the partition signal characteristic information is collected, the partition signal characteristic information is compared with a preset standard to obtain a characteristic deviation value, the characteristic deviation value is compared with a preset change threshold value, and if the characteristic deviation value is outside the preset change threshold value range, a parameter optimization instruction is generated; Based on the parameter optimization instruction, parameter correction information is generated, and based on the parameter correction information, partition parameter adjustment is performed.

[0006] By adopting the above technical scheme, in order to solve the problem that the detection parameters in TOFD ultrasonic testing are difficult to adapt to the changes in the characteristics of a large-scale detection area, for example, when inspecting the welds of large pressure vessels, due to the large span of the weld area, the material thickness may gradually change from 20mm to 50mm, and the surface condition may also change from roughness Ra3.2 to Ra6.3. If the traditional fixed parameter setting method is adopted, there will be serious signal attenuation in the thicker area, resulting in missed detection, and in the rough surface area, it may cause misjudgment due to excessive scattering noise. The present application first establishes a system parameter model based on the detection configuration information, and then divides the detection area into overlapping sub-areas and sets independent detection parameters for each sub-area. During the detection process, the parameters are adaptively adjusted through real-time signal feature analysis. The uniformity and reliability of large-scale detection are improved through the overlapping coverage partition strategy and the multi-layer parameter optimization mechanism.

[0007] Optionally, the collecting detection configuration information and generating system parameter information based on the detection configuration information specifically includes: Based on the material type, obtaining material acoustic characteristic parameters; Based on the detection range and the expected defect type, obtaining probe combination parameters; The material acoustic characteristic parameters and the probe combination parameters are associated to generate the system parameter information.

[0008] By adopting the above technical solution, the present application first obtains acoustic characteristic parameters such as sound velocity and attenuation coefficient according to the material type, and determines the combined parameters such as probe frequency and layout based on the detection range and expected defect type, and then generates system parameters through the systematic association of material acoustic characteristics with probe parameters, thereby ensuring the theoretical rationality of the detection parameter setting.

[0009] Optionally, the material acoustic characteristic parameters include sound velocity and attenuation coefficient, the probe combination parameters include probe frequency and probe arrangement parameters, and associating the material acoustic characteristic parameters with the probe combination parameters to generate the system parameter information specifically includes the following steps: According to the sound velocity, determining the incident angle of the probe; Determining the probe spacing according to the probe incident angle and the sound velocity; The scanning speed is determined according to the probe frequency and the probe spacing.

[0010] By adopting the above technical solution, in actual detection, problems such as insufficient coverage of diffraction waves due to mismatch between material sound velocity and incident angle, or uneven density of sampling points due to mismatch between probe spacing and scanning speed often occur. The present application first determines the optimal incident angle based on the material sound velocity, then calculates the appropriate probe spacing based on the incident angle and sound velocity, and finally optimizes the scanning speed based on the probe frequency and spacing, thereby ensuring the physical correlation between various parameters, and improving the overall matching of system parameters through progressive optimization between parameters.

[0011] Optionally, collecting the inspected area information and generating the partition detection parameters based on the inspected area information and the system parameter information specifically includes the following steps: Dividing the inspected area into a plurality of overlapping sub-areas according to the material thickness and the surface condition; Determine the transmission gain and the receiving gain of each sub-area based on the surface conditions of each sub-area; Based on the material thickness of each sub-region, a threshold value and a time delay compensation value of each sub-region are determined.

[0012] By adopting the above technical solution, in order to solve the problem that the large differences in detection area characteristics in TOFD detection make it difficult for a single parameter setting to meet the detection requirements; this application first divides the detection area into multiple overlapping sub-areas according to the changing characteristics of material thickness and surface condition, and then configures the transmission and receiving gains according to the surface condition, and at the same time optimizes the threshold value and delay compensation based on the material thickness, which not only realizes the regional adaptation of the detection parameters, but also solves the problem of detection uniformity in the characteristic difference area through parameter decoupling configuration and regional overlapping transition.

[0013] Optionally, based on the material thickness of each sub-region, determining the threshold value and the time delay compensation value of each sub-region specifically includes the following steps: Acquiring thickness distribution information of the sub-region, and calculating the acoustic wave attenuation compensation coefficient according to the thickness distribution information; Determining a threshold value of a sub-region based on the sound wave attenuation compensation coefficient; Acquire thickness change gradient information of the sub-area, and calculate the acoustic path difference compensation coefficient according to the thickness change gradient information; Based on the sound path difference compensation coefficient, a time delay compensation value of the sub-area is determined.

[0014] By adopting the above technical solution, the present application first calculates the sound wave attenuation compensation coefficient based on the thickness distribution information and optimizes the threshold value accordingly, then calculates the sound path difference compensation coefficient according to the thickness change gradient information and determines the time delay compensation value, forming a complete parameter compensation system.

[0015] Optionally, the characteristic deviation value is compared with a preset change threshold value, and if the characteristic deviation value is outside the preset change threshold value range, a parameter optimization instruction is generated, which specifically includes the following steps: According to the characteristic deviation value, obtaining partition signal change trend information; Acquiring signal stability status information, and triggering a detection distance calibration instruction according to the signal stability status information; Obtaining a detection distance calibration result, and determining a current detection state based on the detection distance calibration result and the partition signal change trend information; generating an amplitude deviation and a time deviation according to the current detection state; generating a gain adjustment instruction based on the amplitude deviation; A time delay compensation adjustment instruction is generated based on the time deviation.

[0016] By adopting the above technical solution, in actual detection, changes in signal characteristics often occur due to fluctuations in the probe coupling state or deviations in the scanning trajectory. If the gain is directly adjusted only according to the change in signal amplitude, the actual change in the detection state may be concealed. For example, when the coupling is poor, even if the gain compensation is increased, an effective detection signal cannot be obtained. The present application first analyzes the signal change trend, combines the signal stable state to trigger the distance calibration, comprehensively evaluates the current detection state through the calibration results and the change trend, and then extracts the amplitude deviation and time deviation respectively, generates gain adjustment and time compensation instructions, and forms a complete parameter optimization system.

[0017] In a second aspect, the present application provides an adaptively controlled TOFD ultrasonic detection system, comprising: A system parameter information generating module, used for collecting detection configuration information, and generating system parameter information based on the detection configuration information, wherein the detection configuration information includes detection range, material type and expected defect type; A partition detection parameter generation module is used to collect information about the inspected area and generate partition detection parameters based on the inspected area information and the system parameter information; wherein the inspected area is divided into a number of overlapping sub-areas for independent control, the partition detection parameters include the transmission gain, receiving gain, threshold value and time delay compensation value of each sub-area, and the inspected area information includes material thickness and surface condition; A detection signal acquisition module, used to perform TOFD detection based on the partition detection parameters and the system parameter information to obtain a detection signal; A comparison module, used for collecting partition signal characteristic information based on the detection signal, comparing the partition signal characteristic information with a preset standard to obtain a characteristic deviation value, performing a range comparison between the characteristic deviation value and a preset change threshold, and generating a parameter optimization instruction if the characteristic deviation value is outside the preset change threshold range; The parameter adjustment module is used to generate parameter correction information based on the parameter optimization instruction, and perform partition parameter adjustment based on the parameter correction information.

[0018] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned adaptively controlled TOFD ultrasonic detection method when executing the computer program.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned adaptively controlled TOFD ultrasonic detection method are implemented.

[0020] In summary, the present application includes at least one of the following beneficial technical effects: 1. This application first establishes a system parameter model based on the detection configuration information, then divides the detection area into overlapping sub-areas and sets independent detection parameters for each sub-area. During the detection process, the parameters are adaptively adjusted through real-time signal feature analysis; the uniformity and reliability of large-scale detection are improved through the overlapping coverage partition strategy and multi-layer parameter optimization mechanism; 2. This application first obtains acoustic characteristic parameters such as sound velocity and attenuation coefficient according to the material type, and determines the combined parameters such as probe frequency and layout based on the detection range and expected defect type. Then, the system parameters are generated through the systematic association of the material acoustic characteristics and the probe parameters, ensuring the theoretical rationality of the detection parameter setting; 3. This application first determines the optimal incident angle based on the material sound velocity, then calculates the appropriate probe spacing based on the incident angle and sound velocity, and finally optimizes the scanning speed based on the probe frequency and spacing, ensuring the physical correlation between various parameters, and through progressive optimization between parameters, improving the overall matching of system parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flow chart of a TOFD ultrasonic detection method with adaptive control according to an embodiment of the present application; Figure 2 It is a flowchart of an adaptively controlled TOFD ultrasonic detection method S100 according to an embodiment of the present application; Figure 3It is a flowchart of an adaptively controlled TOFD ultrasonic detection method S200 according to an embodiment of the present application; Figure 4 It is a flowchart of an adaptively controlled TOFD ultrasonic detection method S230 according to an embodiment of the present application; Figure 5 It is a flowchart of an adaptively controlled TOFD ultrasonic detection method S400 according to an embodiment of the present application; Figure 6 It is a module schematic diagram of a TOFD ultrasonic detection system with adaptive control according to an embodiment of the present application; Figure 7 It is a diagram of the internal structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0023] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0024] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0025] In a first aspect, the present application provides an adaptively controlled TOFD ultrasonic detection method, referring to Figure 1 , including the following steps: S100: Collect detection configuration information, and generate system parameter information based on the detection configuration information.

[0026] Among them, the detection configuration information includes the detection range, material type and expected defect type.

[0027] In this embodiment, the detection range is used to determine the geometric size information of the workpiece to be detected, the material type is used to determine the acoustic wave propagation characteristic parameters, and the expected defect type is used to optimize the detection strategy. The collection of these configuration information is completed by manual input or automatic recognition.

[0028] Specifically, taking the pressure vessel weld inspection as an example, the inspection range can be set to an area of ​​100mm on both sides of the weld and 2000mm in length; the main defect types expected to be detected are weld incomplete fusion and cracks. Based on these input information, the system can automatically generate system parameter information including probe frequency selection, scanning range setting, etc.

[0029] S200 , collecting information of the inspected area, and generating partition detection parameters based on the inspected area information and system parameter information.

[0030] The inspected area is divided into several overlapping sub-areas for independent control. The partition detection parameters include the transmission gain, receiving gain, threshold value and time delay compensation value of each sub-area. The inspected area information includes material thickness and surface condition.

[0031] In this embodiment, the material thickness information can be obtained by ultrasonic thickness measurement or mechanical measurement, and the surface condition can be determined by roughness meter measurement or visual inspection. The system will partition the inspection area based on this information and configure independent inspection parameters for each sub-area.

[0032] Specifically, for a special-shaped joint with a thickness gradually transitioning from 20mm to 40mm, the detection area can be divided into three overlapping sub-areas: 20-30mm area, 25-35mm area and 30-40mm area, and adjacent areas overlap by 5mm to ensure the continuity of detection. Each sub-area is configured with corresponding detection parameters according to its characteristics. For example, a higher transmission gain will be set for the thicker area to compensate for the attenuation loss.

[0033] S300: Perform TOFD detection based on partition detection parameters and system parameter information to obtain a detection signal.

[0034] Specifically, TOFD testing uses dual-probe technology, with one probe acting as the transmitter to emit ultrasonic waves and the other probe acting as the receiver to receive diffracted wave signals. During the testing process, the probe pair moves along a preset scanning path to collect ultrasonic testing data from each sub-area in real time.

[0035] S400, based on the detection signal, the partition signal characteristic information is collected, the partition signal characteristic information is compared with the preset standard to obtain a characteristic deviation value, the characteristic deviation value is compared with the preset change threshold value, and if the characteristic deviation value is outside the preset change threshold range, a parameter optimization instruction is generated.

[0036] In this embodiment, the system extracts characteristic parameters of the detection signal in real time, including the shear wave amplitude, the longitudinal wave amplitude ratio and the signal arrival time, and compares them with pre-set standards to evaluate the stability of the detection state.

[0037] Specifically, when the shear wave amplitude of a sub-area is lower than 80% of the preset standard, or the signal arrival time deviation exceeds 0.5μs, the system determines that the detection parameters of the area need to be optimized and adjusted, and then triggers the parameter optimization process.

[0038] S500 , generating parameter correction information based on the parameter optimization instruction, and performing partition parameter adjustment based on the parameter correction information.

[0039] In this embodiment, the system generates corresponding parameter correction instructions based on the characteristic deviation analysis results, including gain adjustment instructions and time compensation adjustment instructions, and performs parameter updates in real time.

[0040] Specifically, when amplitude attenuation is detected, the system generates a +3dB gain adjustment instruction; when it is found that the signal delay increases, a +0.2μs time compensation adjustment instruction is generated.

[0041] In one embodiment, referring to Figure 2 In step S100, the detection configuration information is collected, and the system parameter information is generated based on the detection configuration information, specifically including: S110. Acquire material acoustic characteristic parameters based on material type.

[0042] Among them, the acoustic characteristic parameters of the material mainly include the sound velocity and the attenuation coefficient. In this embodiment, a material database is pre-set, and the system can obtain these parameters by querying the built-in material database or by measuring a standard test block.

[0043] Specifically, when a material type is entered, the system automatically matches the acoustic characteristic parameters of the material. These parameter values ​​can be fine-tuned based on actual measurement results.

[0044] S120. Based on the detection range and expected defect type, obtain probe combination parameters.

[0045] Among them, the system will determine the basic parameter requirements of the probe according to the detection range, and optimize the specific configuration of the probe combination in combination with the expected defect type, significantly improving the pertinence and effectiveness of the detection. The system first classifies and parameterizes common defects according to their characteristics by establishing an expected defect type library. The defect type library contains four major types of defects: cracks (such as transverse cracks, longitudinal cracks, root cracks, etc.), inclusions (such as slag inclusions, sand inclusions, pores, etc.), unfusion (such as root unfusion, side wall unfusion, etc.) and geometric types (such as undercuts, misalignments, excess height, etc.). Each defect is marked with key parameters such as its typical size range, spatial orientation characteristics, and acoustic reflection characteristics. Based on these parameters, the system establishes a defect-probe characteristic mapping relationship to provide a basis for the selection of probe parameters. Specifically, when the detection range is a 30mm thick pressure vessel weld and crack defects are expected to be detected, the system retrieves crack characteristic parameters from the defect type library and recommends the use of a probe pair with a frequency of 5MHz and a chip diameter in combination with the detection range requirements. If the expected defects are mainly slag inclusions, it is recommended to reduce the frequency to 3.5MHz to obtain better penetration based on the acoustic characteristic parameters in the defect library, and may adjust the chip size to 8mm to obtain a larger detection coverage. At the same time, the system will give corresponding detection sensitivity recommendations based on the difficulty of detecting different defect types.

[0046] S130, associating material acoustic characteristic parameters with probe combination parameters to generate system parameter information.

[0047] Among them, the generation of system parameter information requires comprehensive analysis and correlation calculation of material properties and probe parameters. By establishing a mapping relationship between acoustic parameters and probe characteristics, a set of optimized system operating parameters can be obtained. The optimal incident angle is calculated based on the first critical angle of the shear wave (obtained by the ratio of the shear wave speed of sound to the longitudinal wave speed of sound), usually 1.8-2.0 times the first critical angle; the probe spacing is determined based on the workpiece thickness, the incident angle, and the distance from the center of the sound beam to the workpiece surface; the initial gain value needs to be calculated by comprehensively considering the basic gain, material attenuation compensation, and sound wave diffusion loss.

[0048] Specifically, when the material shear wave velocity is 3240m / s and a 5MHz probe is selected, the system will first calculate the first critical angle, based on which the optimal incident angle is determined to be 60 degrees; then, based on the workpiece thickness and the incident angle, the probe spacing is calculated to be 75mm. For gain setting, the system uses 20dB as the basic gain, superimposes the material attenuation compensation value (determined by the attenuation coefficient and the sound path distance) and the diffusion loss compensation value (calculated by the logarithm of the sound path distance), and finally sets the initial gain to 42dB to ensure sufficient detection sensitivity.

[0049] In one embodiment, referring to Figure 3 In step S200, the detected area information is collected, and the partition detection parameters are generated based on the detected area information and system parameter information, which specifically includes the following steps: S210 , dividing the inspected area into a plurality of overlapping sub-areas according to material thickness and surface conditions.

[0050] In this embodiment, the system determines the partition position by analyzing the thickness change rate and the surface roughness gradient.

[0051] Specifically, when the thickness difference between adjacent areas is greater than a preset thickness threshold, sub-areas are divided at the thickness mutation point; when the surface roughness change exceeds a preset roughness threshold, sub-areas are divided at the surface condition mutation point; the overlap between adjacent sub-areas is not less than a preset overlap ratio, and the preset overlap ratio is determined based on the maximum thickness of the detection area; the detection range of each sub-area does not exceed a preset maximum detection span, and the preset maximum detection span is determined based on the detection sensitivity of the probe.

[0052] S220: Determine the transmission gain and the receiving gain of each sub-area based on the surface conditions of each sub-area.

[0053] The system first calculates the coupling loss caused by surface roughness, and then determines the compensation gain value based on the reflection loss of the sound wave at the interface. At the same time, in order to avoid noise interference caused by overcompensation, the system sets an upper limit for gain compensation.

[0054] S230 : Determine a threshold value and a time delay compensation value for each sub-region based on the material thickness of each sub-region.

[0055] The setting of the threshold value needs to consider the influence of material thickness on the echo amplitude. Generally, a dynamic threshold strategy is adopted to dynamically adjust the threshold value with the sound path distance. The time delay compensation value is mainly used to compensate for the time offset caused by the difference in sound path in different thickness areas to ensure the timing consistency of the detection signal.

[0056] In one embodiment, referring to Figure 4 In step S230, based on the material thickness of each sub-region, the threshold value and the time delay compensation value of each sub-region are determined, which specifically includes the following steps: S231. Obtain thickness distribution information of the sub-region, and calculate the acoustic wave attenuation compensation coefficient according to the thickness distribution information.

[0057] In this embodiment, the thickness distribution information includes the maximum thickness, the minimum thickness and the thickness variation characteristics in the sub-region.

[0058] Specifically, the system first obtains the thickness distribution curve of the area, and then calculates the sound path loss based on the material attenuation coefficient. When the sound wave propagates in this area, the minimum sound path and the maximum sound path are calculated, and the attenuation compensation coefficient range can be obtained based on this. The compensation coefficient increases exponentially with the sound path distance.

[0059] S232: Determine a threshold value of the sub-area based on the sound wave attenuation compensation coefficient.

[0060] The threshold value is determined by a dynamic threshold strategy, combining the acoustic wave attenuation compensation coefficient with the reference threshold value to generate a threshold curve that changes with the sound path. In this embodiment, the system analyzes historical detection data in advance to establish a mapping relationship between the threshold value and the attenuation compensation coefficient to ensure uniformity of detection sensitivity.

[0061] Specifically, the system generates a complete threshold curve by piecewise linear interpolation, so that the threshold value changes smoothly with the sound path.

[0062] S233, obtaining thickness change gradient information of the sub-region, and calculating the acoustic path difference compensation coefficient according to the thickness change gradient information.

[0063] Among them, the thickness change gradient information reflects the rate of change of the thickness of the detection area. The system calculates the local gradient by analyzing the thickness difference of adjacent measuring points. The calculation of the acoustic path difference compensation coefficient needs to consider the geometric relationship between the incident angle and the thickness change, and establish the functional relationship between the acoustic path difference and the thickness gradient.

[0064] S234: Determine a time delay compensation value of the sub-area based on the sound path difference compensation coefficient.

[0065] In this embodiment, the determination of the time delay compensation value requires converting the acoustic path difference compensation coefficient into a compensation amount in the time domain. The system calculates the change in sound wave propagation time based on the material sound velocity and the acoustic path difference, and realizes the timing alignment of the signal through a pre-established compensation model.

[0066] In one embodiment, referring to Figure 5 In step S400, the characteristic deviation value is compared with the preset change threshold value. If the characteristic deviation value is outside the preset change threshold value range, a parameter optimization instruction is generated, which specifically includes the following steps: S410. Obtain partition signal change trend information according to the characteristic deviation value.

[0067] In this embodiment, the partition signal change trend information reflects the change law of the detection signal in the spatial and temporal dimensions. The system analyzes the N frames of continuously collected signal data, extracts the change trend of characteristic parameters such as signal amplitude and phase, and establishes the corresponding relationship between signal characteristics and detection positions.

[0068] Specifically, when inspecting a weld area, the system records the signal feature sequence of each sampling point. If the signal amplitude shows a continuous downward trend within a 100mm scanning distance, and the decline exceeds 3dB, it is recorded as a "negative gradual change" trend; if the signal amplitude suddenly decreases by more than 5dB, it is recorded as a "step change" trend.

[0069] S420: Acquire signal stability status information, and trigger a detection distance calibration instruction according to the signal stability status information.

[0070] In this embodiment, the signal stability state refers to the waveform characteristics of the detection signal remaining relatively constant within a certain time range. The system evaluates the stability level of the signal by calculating the statistical characteristics of the signal such as the variance and standard deviation. When the signal stability meets the preset conditions, the system automatically triggers the detection distance calibration process.

[0071] S430, obtaining a detection distance calibration result, and determining a current detection state based on the detection distance calibration result and partition signal change trend information.

[0072] The detection distance calibration result includes the comparison information between the sound path measurement value and the theoretical value. The system correlates the calibration result with the signal change trend and comprehensively evaluates the working status of the detection system.

[0073] Specifically, when the calibration result shows that the deviation between the measured sound path and the theoretical value exceeds 0.5mm, and the signal shows a "negative gradual change" trend, the system determines that the current detection state is a "parameter offset" state. This state indicates that the detection parameters need to be compensated and adjusted to maintain the accuracy of the detection.

[0074] S440: Generate an amplitude deviation and a time deviation according to the current detection state.

[0075] The system calculates these two types of deviation values ​​by comparing the characteristic parameters of the measured signal and the reference signal. The deviation calculation process takes into account the spatial distribution characteristics and time series characteristics of the signal.

[0076] S450: Generate a gain adjustment instruction based on the amplitude deviation.

[0077] The gain adjustment command is used to compensate for the systematic deviation of the signal amplitude. The system calculates the required gain compensation amount according to the size and direction of the amplitude deviation and generates the corresponding adjustment command. The gain adjustment adopts a progressive strategy to avoid signal distortion caused by over-compensation.

[0078] S460: Generate a time delay compensation adjustment instruction based on the time deviation.

[0079] The time delay compensation adjustment instruction is used to correct the timing relationship of the signal. The system converts the time deviation into the offset of the sampling point and realizes signal alignment by adjusting the sampling timing.

[0080] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0081] In the second aspect, the present application provides an adaptively controlled TOFD ultrasonic detection system. The adaptively controlled TOFD ultrasonic detection system of the present application is described below in combination with the above-mentioned adaptively controlled TOFD ultrasonic detection method.

[0082] Reference Figure 6 , an adaptively controlled TOFD ultrasonic detection system, comprising: A system parameter information generation module, used to collect detection configuration information and generate system parameter information based on the detection configuration information, wherein the detection configuration information includes detection range, material type and expected defect type; A partition detection parameter generation module is used to collect information about the inspected area and generate partition detection parameters based on the inspected area information and system parameter information; wherein the inspected area is divided into a number of overlapping sub-areas for independent control, and the partition detection parameters include the transmission gain, receiving gain, threshold value and time delay compensation value of each sub-area, and the inspected area information includes material thickness and surface condition; A detection signal acquisition module is used to perform TOFD detection and acquire detection signals based on partition detection parameters and system parameter information; A comparison module is used to collect partition signal feature information based on the detection signal, compare the partition signal feature information with a preset standard, obtain a feature deviation value, compare the feature deviation value with a preset change threshold value, and generate a parameter optimization instruction if the feature deviation value is outside the preset change threshold range; The parameter adjustment module is used to generate parameter correction information based on the parameter optimization instruction, and perform partition parameter adjustment based on the parameter correction information.

[0083] In one embodiment, the system parameter information generation module specifically includes: A material acoustic characteristic parameter acquisition unit, used for acquiring material acoustic characteristic parameters based on material type; A probe combination parameter acquisition unit, used for acquiring probe combination parameters based on a detection range and an expected defect type; The system parameter association unit is used to associate the material acoustic characteristic parameters with the probe combination parameters to generate system parameter information.

[0084] In one embodiment, the material acoustic characteristic parameters include the sound velocity and the attenuation coefficient, the probe combination parameters include the probe frequency and the probe arrangement parameters, and the system parameter association unit specifically includes: An incident angle determination unit, used for determining the incident angle of the probe according to the sound velocity; A probe spacing determination unit, used for determining the probe spacing according to the probe incident angle and the sound velocity; The scanning speed determination unit is used to determine the scanning speed according to the probe frequency and the probe spacing.

[0085] In one embodiment, the partition detection parameter generation module specifically includes: An area division unit is used to divide the inspected area into a number of overlapping sub-areas according to the material thickness and surface condition; A gain determination unit, used to determine a transmission gain and a receiving gain of each sub-area based on the surface conditions of each sub-area; The threshold compensation determination unit is used to determine the threshold value and the time delay compensation value of each sub-region based on the material thickness of each sub-region.

[0086] In one embodiment, the threshold compensation determination unit specifically includes: An attenuation compensation calculation unit, used to obtain thickness distribution information of the sub-area and calculate the sound wave attenuation compensation coefficient according to the thickness distribution information; A threshold value determination unit, used to determine a threshold value of a sub-area based on a sound wave attenuation compensation coefficient; An acoustic path difference compensation calculation unit, used to obtain thickness change gradient information of the sub-area, and calculate an acoustic path difference compensation coefficient according to the thickness change gradient information; The time delay compensation determination unit is used to determine the time delay compensation value of the sub-area based on the sound path difference compensation coefficient.

[0087] In one embodiment, the comparison module specifically includes: A trend acquisition unit, used to acquire the partition signal change trend information according to the characteristic deviation value; A calibration trigger unit, used to obtain signal stability status information, and trigger a detection distance calibration instruction according to the signal stability status information; A state determination unit, used to obtain a detection distance calibration result, and determine a current detection state based on the detection distance calibration result and the partition signal change trend information; A deviation generating unit, used for generating an amplitude deviation and a time deviation according to a current detection state; A gain adjustment instruction generating unit, used for generating a gain adjustment instruction based on the amplitude deviation; The time compensation instruction generating unit is used to generate a time delay compensation adjustment instruction based on the time deviation.

[0088] In one embodiment, the present application provides an electronic device, which may be a server, and its internal structure diagram may be as follows: Figure 7As shown. The electronic device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the electronic device is used to store data. The network interface of the electronic device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an adaptively controlled TOFD ultrasonic detection method is implemented.

[0089] Those skilled in the art will understand that Figure 7 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0090] In one embodiment, an electronic device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0091] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0092] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. An adaptively controlled TOFD ultrasonic detection method, characterized in that: The steps include: Collecting detection configuration information, and generating system parameter information based on the detection configuration information, wherein the detection configuration information includes detection range, material type, and expected defect type; Collecting information of the inspected area, and generating partition detection parameters based on the inspected area information and the system parameter information; wherein the inspected area is divided into a plurality of overlapping sub-areas for independent control, the partition detection parameters include the transmission gain, receiving gain, threshold value and time delay compensation value of each sub-area, and the inspected area information includes material thickness and surface condition; Based on the partition detection parameters and the system parameter information, perform TOFD detection to obtain a detection signal; Based on the detection signal, the partition signal characteristic information is collected, the partition signal characteristic information is compared with a preset standard to obtain a characteristic deviation value, the characteristic deviation value is compared with a preset change threshold value, and if the characteristic deviation value is outside the preset change threshold value range, a parameter optimization instruction is generated; Based on the parameter optimization instruction, parameter correction information is generated, and based on the parameter correction information, partition parameter adjustment is performed.

2. The TOFD ultrasonic detection method with adaptive control according to claim 1, characterized in that: Collecting detection configuration information and generating system parameter information based on the detection configuration information specifically includes: Based on the material type, obtaining material acoustic characteristic parameters; Based on the detection range and the expected defect type, obtaining probe combination parameters; The material acoustic characteristic parameters and the probe combination parameters are associated to generate the system parameter information.

3. The TOFD ultrasonic detection method with adaptive control according to claim 2, characterized in that: The material acoustic characteristic parameters include sound velocity and attenuation coefficient, and the probe combination parameters include probe frequency and probe arrangement parameters. The material acoustic characteristic parameters and the probe combination parameters are associated to generate the system parameter information, which specifically includes the following steps: According to the sound velocity, determining the incident angle of the probe; Determining the probe spacing according to the probe incident angle and the sound velocity; The scanning speed is determined according to the probe frequency and the probe spacing.

4. The TOFD ultrasonic detection method with adaptive control according to claim 1, characterized in that: Collecting the inspected area information and generating the partition detection parameters based on the inspected area information and the system parameter information specifically includes the following steps: Dividing the inspected area into a plurality of overlapping sub-areas according to the material thickness and the surface condition; Determine the transmission gain and the receiving gain of each sub-area based on the surface conditions of each sub-area; Based on the material thickness of each sub-region, a threshold value and a time delay compensation value of each sub-region are determined.

5. The TOFD ultrasonic detection method with adaptive control according to claim 4, characterized in that: Based on the material thickness of each sub-region, determining the threshold value and time delay compensation value of each sub-region specifically includes the following steps: Acquiring thickness distribution information of the sub-region, and calculating the acoustic wave attenuation compensation coefficient according to the thickness distribution information; Determining a threshold value of a sub-region based on the sound wave attenuation compensation coefficient; Acquire thickness change gradient information of the sub-area, and calculate the acoustic path difference compensation coefficient according to the thickness change gradient information; Based on the sound path difference compensation coefficient, a time delay compensation value of the sub-area is determined.

6. The TOFD ultrasonic detection method with adaptive control according to claim 1, characterized in that: Comparing the characteristic deviation value with a preset change threshold value, and if the characteristic deviation value is outside the preset change threshold value range, generating a parameter optimization instruction, specifically comprising the following steps: According to the characteristic deviation value, obtaining partition signal change trend information; Acquiring signal stability status information, and triggering a detection distance calibration instruction according to the signal stability status information; Obtaining a detection distance calibration result, and determining a current detection state based on the detection distance calibration result and the partition signal change trend information; generating an amplitude deviation and a time deviation according to the current detection state; generating a gain adjustment instruction based on the amplitude deviation; A time delay compensation adjustment instruction is generated based on the time deviation.

7. An adaptively controlled TOFD ultrasonic detection system, characterized in that: include: A system parameter information generating module, used for collecting detection configuration information, and generating system parameter information based on the detection configuration information, wherein the detection configuration information includes detection range, material type and expected defect type; A partition detection parameter generation module is used to collect information about the inspected area and generate partition detection parameters based on the inspected area information and the system parameter information; wherein the inspected area is divided into a number of overlapping sub-areas for independent control, the partition detection parameters include the transmission gain, receiving gain, threshold value and time delay compensation value of each sub-area, and the inspected area information includes material thickness and surface condition; A detection signal acquisition module, used to perform TOFD detection based on the partition detection parameters and the system parameter information to obtain a detection signal; A comparison module, used for collecting partition signal characteristic information based on the detection signal, comparing the partition signal characteristic information with a preset standard to obtain a characteristic deviation value, performing a range comparison between the characteristic deviation value and a preset change threshold, and generating a parameter optimization instruction if the characteristic deviation value is outside the preset change threshold range; The parameter adjustment module is used to generate parameter correction information based on the parameter optimization instruction, and perform partition parameter adjustment based on the parameter correction information.

8. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the TOFD ultrasonic detection method with adaptive control described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the adaptively controlled TOFD ultrasonic detection method according to any one of claims 1 to 6 are implemented.

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