Stainless steel weld phased array and tofd combined detection method and system

Abstract

The present application relates to the technical field of nondestructive testing, and particularly relates to a stainless steel weld joint phased array and TOFD combined detection method and system. Based on weld joint parameters, the sound wave path is calculated, and the detection parameter set of the phased array and the TOFD is determined. Scanning is respectively performed, phased array fan-shaped images and TOFD diffraction wave data are acquired to extract defect spatial positions and geometric data. Time domain alignment and space matching are performed on the double-source data, the same defect is identified, the associated signal pairs are extracted, and the timing characteristics are extracted. Finally, the information is fused to determine the weld joint quality. The method realizes complementary and correlation analysis of detection data, and improves the accuracy and reliability of quantitative and qualitative evaluation of defects.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology, and in particular to a method and system for combined phased array and TOFD testing of stainless steel welds. Background Technology

[0002] In the field of non-destructive testing of stainless steel welds, the conventional approach is to use multiple independent testing techniques for evaluation. Phased array ultrasonic testing and time-of-flight diffraction (TOF) ultrasonic testing are two widely used methods. Phased array testing electronically controls the deflection and focusing of the sound beam, generating high-quality images of the weld cross-section, facilitating defect localization and characterization. TOF utilizes the diffracted wave signals at the defect endpoints, accurately calculating the height of the defect by measuring the time difference between the upper and lower diffracted waves, offering advantages for the quantitative assessment of crack-like defects.

[0003] Implementing phased array and time-of-flight diffraction (TOF) methods as two completely independent inspection procedures leads to a disconnect between data acquisition and analysis. Due to the lack of a unified inspection plan and data correlation benchmark, it is difficult to accurately correlate and compare the defect information obtained by the two methods in terms of time and space. This increases the difficulty of data fusion, preventing inspectors from efficiently combining the imaging capabilities of phased array for defect contours with the precise measurement capabilities of TOF for defect height.

[0004] This separate detection mode can lead to incomplete defect information or inconsistent assessments in practical applications. For the same weld defect, phased array images provide its planar location and approximate orientation, while time-of-flight diffraction (TOF) data provides its height value in the depth direction. However, due to the lack of an effective correlation mechanism, it is difficult to confirm whether the two sets of data describe the same physical entity, and it is also impossible to organically combine their respective advantageous characteristics. This affects the comprehensive judgment of the true three-dimensional morphology and hazard of the defect, ultimately impacting the accuracy and reliability of the detection results. Summary of the Invention

[0005] The present invention provides a method and system for joint detection of stainless steel welds using phased array and TOFD, which can solve the problems in the prior art.

[0006] A first aspect of the present invention provides a method for joint detection of stainless steel welds using phased array and TOFD, comprising: Based on the geometric parameters and material acoustic parameters of the stainless steel weld to be inspected, the sound wave propagation path at different depths within the weld cross-section is calculated, and the scanning parameter set of the phased array probe and the arrangement parameter set of the TOFD probe pair are determined. The stainless steel weld to be inspected is scanned according to the set of scanning parameters, phased array detection data is obtained and image processing is performed to generate a sector scan image of the weld cross section and extract the spatial location of the defect response in the image. The stainless steel weld to be inspected is scanned according to the set of arrangement parameters to obtain TOFD inspection data. Based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD inspection data, the depth position and height of the defect are calculated to generate defect geometric data. The phased array detection data and the TOFD detection data are synchronized and aligned in the time domain to establish a dual-source signal association sequence under a unified time reference. Candidate signal association groups are screened by spatially matching the spatial location of the defect response with the depth location in the defect geometric data. Defect reflected echo and upper diffraction wave signals are identified from the candidate signal association groups. Based on the principle of minimizing the sum of the depth deviation between the reflection depth and the depth location of the upper end of the defect and the depth deviation between the diffraction depth and the depth location of the upper end of the defect, signal response pairs generated by the same defect are determined. The time interval between the arrival times of the reflected echo and the diffraction wave in the signal response pair is extracted as a time-series association feature. Based on the defect geometric data and the temporal correlation features, fused defect information is generated, and the weld quality inspection result is determined based on the fused defect information.

[0007] Based on the geometric and acoustic parameters of the stainless steel weld to be inspected, the sound wave propagation paths at different depths within the weld cross-section are calculated, determining the scanning parameter set for the phased array probe and the arrangement parameter set for the TOFD probe pair, including: Based on the weld width, weld thickness, and bevel angle in the geometric parameters, and the longitudinal wave velocity and transverse wave velocity in the material acoustic parameters, the acoustic propagation medium layering of the weld cross section is constructed. For each layer in the acoustic propagation medium layering, the refraction angle and propagation time of the sound wave propagation within the layer, as well as the reflection coefficient and transmission coefficient of the sound wave at the interlayer interface, are calculated to generate the sound wave propagation path at different depth positions within the weld cross section, and the sound energy concentration area and sound energy attenuation area within the weld cross section are identified based on the sound wave propagation path. The focusing depth of the phased array probe is configured to correspond to the depth position of the acoustic energy concentration area, and the deflection angle of the phased array probe is configured to correspond to the interface normal angle of the acoustic energy concentration area, so that the phased array probe can acquire a reflected echo signal with a defect reflection echo signal intensity greater than the background noise signal intensity in the acoustic energy concentration area, thereby obtaining the scanning parameter set. The probe spacing of the TOFD probe pair is configured to correspond to the width range of the acoustic energy attenuation region, and the incident angle of the TOFD probe pair is configured to correspond to the critical incident angle of the acoustic wave in the acoustic energy attenuation region, so that the TOFD probe pair can acquire a highly sensitive diffraction wave signal in the acoustic energy attenuation region, thereby obtaining the set of arrangement parameters.

[0008] The stainless steel weld to be inspected is scanned according to the set of scanning parameters. Phased array detection data is acquired and image processing is performed to generate a sector-shaped scan image of the weld cross-section and extract the spatial location of the defect response in the image, including: Based on the focusing depth and deflection angle in the scanning parameter set, the phased array probe is controlled to scan along the length of the stainless steel weld to be inspected, and reflected echo signals at different depth positions within the weld cross-section are collected to generate the phased array detection data. The arrival time of the reflected echo signal in the phased array detection data is converted into depth coordinates within the weld cross section, and the deflection angle in the phased array detection data is converted into lateral coordinates within the weld cross section, thus establishing a two-dimensional coordinate system composed of the depth coordinates and lateral coordinates of the weld cross section. The amplitude of each reflected echo signal in the phased array detection data is mapped to the pixel grayscale value of the corresponding position in the two-dimensional coordinate system to generate a fan-shaped scan image of the weld cross section. In the fan-shaped scan image, a continuous pixel region whose pixel gray value exceeds a preset gray value threshold is identified as a defect response candidate region, and the average gray value of the defect response candidate region is calculated. Candidate defect response regions that satisfy both an area greater than the lower limit of area and an average gray value greater than the lower limit of average gray value are selected as defect response regions; the depth coordinates and horizontal coordinates of each defect response region in the two-dimensional coordinate system are extracted to generate the spatial location of the defect response in the fan-shaped scan image.

[0009] The stainless steel weld to be inspected is scanned according to the set of arrangement parameters to obtain TOFD inspection data. Based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD inspection data, the depth location and height dimensions of the defect are calculated, and the defect geometric data is generated, including: Based on the set of arrangement parameters, the TOFD probe is configured to scan along the length of the stainless steel weld to be inspected, receive the diffraction wave signal generated by the defect endpoint in the weld cross section, and generate the TOFD detection data. In the TOFD detection data, the diffraction wave signal located within the time window between the direct wave signal and the bottom reflected wave signal is identified, and the diffraction wave signal is classified into upper diffraction wave signal and lower diffraction wave signal according to the order of arrival time. The arrival time of the direct wave signal is calibrated as the zero point; the time difference between the arrival time of the upper diffraction wave signal and the zero point, and the arrival time of the lower diffraction wave signal and the zero point are calculated respectively. Based on the time difference and the longitudinal wave velocity in the material acoustic parameters, the depth position of the upper end point of the defect corresponding to the upper diffraction wave signal and the depth position of the lower end point of the defect corresponding to the lower diffraction wave signal are calculated respectively. Calculate the difference between the depth position of the lower end point of the defect and the depth position of the upper end point of the defect to generate the height dimension of the defect; The depth position of the upper endpoint of the defect is used as the depth position of the defect. The depth position of the defect and the height dimension of the defect are combined to generate the geometric data of the defect.

[0010] The phased array detection data and the TOFD detection data are synchronized and aligned in the time domain to establish a dual-source signal correlation sequence under a unified time reference, including: The scan start time is extracted from the phased array detection data and the TOFD detection data respectively, and the time offset between the two scan start times is calculated. The acquisition timestamps of the phased array detection data and the TOFD detection data are synchronously corrected according to the time offset, and the time coordinates of the phased array detection data and the TOFD detection data are uniformly mapped to the same time base. The scanning path is divided into multiple spatial segments according to the length direction of the stainless steel weld to be inspected, and the scanning time interval corresponding to each spatial segment in the phased array detection data and the scanning time interval corresponding to the TOFD detection data are calculated. For each spatial segment, the reflected echo signal sequence within the scanning time interval is extracted from the phased array detection data, and the diffraction wave signal sequence within the scanning time interval is extracted from the TOFD detection data. The reflected echo signal sequence and the diffraction wave signal sequence are paired in chronological order to generate a signal association group corresponding to the spatial segment. All signal association groups corresponding to the spatial segments are arranged in order of the length direction of the stainless steel weld to be detected, and the acquisition position coordinates of the reflected echo signal sequence and the acquisition position coordinates of the diffraction wave signal sequence are marked in each signal association group. A data structure containing the spatiotemporal correspondence of dual-source signals is constructed to generate the dual-source signal association sequence.

[0011] Candidate signal association groups are filtered by spatially matching the spatial location of the defect response with the depth location in the defect geometric data. Defect reflected echo and upper-end diffraction wave signals are identified from these candidate signal association groups. Based on the principle of minimizing the sum of the depth deviations between the reflection depth and the upper-end depth location of the defect, and the depth deviations between the diffraction depth and the upper-end depth location of the defect, signal response pairs generated by the same defect are determined. The time interval between the arrival times of the reflected echo and the diffraction wave in the signal response pair is extracted as a temporal correlation feature, including: For each signal association group in the dual-source signal association sequence, based on the defect response spatial location, the spatial distance between the position coordinates of the defect in the length direction of the stainless steel weld to be detected and the acquisition position coordinates of the reflected echo signal sequence, and the acquisition position coordinates of the diffraction wave signal sequence are calculated respectively. Signal association groups whose spatial distances are both less than a preset spatial matching threshold are selected as candidate signal association groups. For each candidate signal association group, the signal with the largest reflected wave amplitude is identified from the reflected echo signal sequence as the defect reflected echo and its corresponding reflection depth is extracted. The upper diffraction wave signal is identified from the diffraction wave signal sequence and its corresponding diffraction depth is extracted. The depth deviation between the reflection depth and the depth position of the upper end of the defect, and the depth deviation between the diffraction depth and the depth position of the upper end of the defect are calculated. The defect reflected echo and the upper diffraction wave signal in the candidate signal association group with the smallest sum of the two depth deviations are determined as a signal response pair generated by the same defect. The arrival time of the defect reflection echo and the arrival time of the upper diffraction wave signal in the signal response pair are extracted, and the time interval between the two arrival times is calculated as the time-series correlation feature.

[0012] Based on the defect geometric data and the temporal correlation features, fused defect information is generated, and the weld quality inspection result is determined based on the fused defect information, including: Extract the depth and height dimensions of the defect from the defect geometry data, and extract the horizontal coordinates of the defect from the defect response space. Based on the time-series correlation characteristics, the deviation between the time interval between the arrival time of the phased array reflected wave and the arrival time of the TOFD diffracted wave and the preset standard time interval is calculated. When the deviation is less than the preset time deviation threshold, the depth position and the height of the defect are determined as effective geometric parameters. When the deviation is greater than or equal to the preset time deviation threshold, the depth position and height of the defect are recalculated as corrected geometric parameters based on the time-series correlation characteristics. The effective geometric parameters or the corrected geometric parameters are combined with the horizontal position coordinates of the defect to generate the fused defect information, which includes the three-dimensional spatial position and size parameters of the defect. Based on the fused defect information, the depth position of the defect is compared with a preset depth safety threshold, and the height dimension of the defect is compared with a preset height safety threshold. When the depth position of the defect exceeds the preset depth safety threshold or the height dimension of the defect exceeds the preset height safety threshold, a detection result indicating that the weld quality is unqualified is generated; otherwise, a detection result indicating that the weld quality is qualified is generated.

[0013] A second aspect of the present invention provides a combined phased array and TOFD detection system for stainless steel welds, comprising: The parameter calculation unit is used to calculate the sound wave propagation path at different depths within the weld section based on the geometric parameters and material acoustic parameters of the stainless steel weld to be inspected, and to determine the scanning parameter set of the phased array probe and the arrangement parameter set of the TOFD probe pair. The data acquisition unit is used to scan the stainless steel weld to be inspected according to the scanning parameter set, acquire phased array detection data and perform imaging processing, generate a fan-shaped scan image of the weld cross section and extract the spatial location of the defect response in the image. The defect location unit is used to scan the stainless steel weld to be inspected according to the set of arrangement parameters, obtain TOFD detection data, and calculate the depth position and height of the defect based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD detection data, thereby generating defect geometric data. The signal alignment unit is used to perform time-domain synchronization alignment of the phased array detection data and the TOFD detection data to establish a dual-source signal correlation sequence under a unified time reference. The feature extraction unit is used to filter candidate signal association groups by spatially matching the spatial location of the defect response with the depth location in the defect geometric data, identify defect reflected echo and upper diffraction wave signals from the candidate signal association groups, determine the signal response pairs generated by the same defect based on the principle of minimizing the sum of the depth deviation between the reflection depth and the depth position of the upper end of the defect and the depth deviation between the diffraction depth and the depth position of the upper end of the defect, and extract the time interval between the arrival time of the reflected echo and the diffraction wave in the signal response pair as a temporal association feature. The result generation unit is used to generate fused defect information based on the defect geometric data and the temporal correlation features, and to determine the weld quality inspection result based on the fused defect information.

[0014] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0015] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0016] The beneficial effects of this application are as follows: This method systematically integrates phased array detection and time-of-flight diffraction (TOF) detection, significantly improving the detection rate and quantitative accuracy of internal defects in stainless steel welds. Phased array technology, through sector scanning imaging, can intuitively present the spatial distribution and morphology of defects within the weld cross-section, while TOF, based on precise calculation of diffraction wave time differences, can accurately determine the depth and height of defects. The two technologies complement each other, overcoming the limitations of single methods in detecting specific defect orientations or types, and achieving comprehensive coverage of point-like, strip-like, and area-type defects.

[0017] By pre-calculating the sound wave propagation path and optimizing probe parameters, it was ensured that the sound beams of both detection modes could effectively cover the entire cross-section of the weld, laying the physical foundation for subsequent data fusion. Time-domain synchronization and spatial matching of the acquired phased array image data and diffraction time-difference method waveform data enabled accurate identification of the signal responses of the same defect under two different physical mechanisms. This process established a reliable correlation between the reflected wave signal and the diffracted wave signal, effectively eliminating misjudgments caused by structural noise or false defect signals.

[0018] The extracted temporal correlation features are combined with defect geometric data to generate fused defect information that includes the spatial location, size, orientation, and reflection and diffraction characteristics of defects. This fused information not only provides a richer defect characterization but also enhances the reliability of qualitative defect analysis. For example, by comparing the intensity of reflected signals with the characteristics of diffraction signals, the nature of defects can be determined, such as distinguishing between different types like porosity, inclusions, or lack of fusion, thereby achieving a comprehensive and accurate assessment of weld quality.

[0019] The accuracy and reliability of detection results determined by fusing defect information far exceed those of independent evaluations using a single technology. This method provides a complete solution for non-destructive testing of stainless steel welds, ensuring detection accuracy while also improving the automation and intelligence of the testing process, which is of great value in ensuring the safety and service life of welded structures. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the combined phased array and TOFD detection method for stainless steel welds. Figure 2 This is a schematic diagram of the probe parameter calculation and configuration process. Detailed Implementation

[0021] 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, and 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.

[0022] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0023] Figure 1 This is a schematic flowchart of the combined phased array and TOFD detection method for stainless steel welds according to an embodiment of the present invention. Figure 1 As shown, the combined phased array and TOFD method for detecting stainless steel welds includes: Based on the geometric parameters and material acoustic parameters of the stainless steel weld to be inspected, the sound wave propagation path at different depths within the weld cross-section is calculated, and the scanning parameter set of the phased array probe and the arrangement parameter set of the TOFD probe pair are determined. The stainless steel weld to be inspected is scanned according to the set of scanning parameters, phased array detection data is obtained and image processing is performed to generate a sector scan image of the weld cross section and extract the spatial location of the defect response in the image. The stainless steel weld to be inspected is scanned according to the set of arrangement parameters to obtain TOFD inspection data. Based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD inspection data, the depth position and height of the defect are calculated to generate defect geometric data. The phased array detection data and the TOFD detection data are synchronized and aligned in the time domain to establish a dual-source signal correlation sequence under a unified time reference. By spatially matching the spatial location of the defect response with the depth location in the defect geometric data, candidate signal association groups are filtered. Defect reflected echo and upper diffraction wave signals are identified from the candidate signal association groups. Based on the principle of minimizing the sum of the depth deviation between the reflection depth and the depth location of the upper end of the defect and the depth deviation between the diffraction depth and the depth location of the upper end of the defect, signal response pairs generated by the same defect are determined. The time interval between the arrival times of the reflected echo and the diffraction wave in the signal response pair is extracted as a temporal association feature. Based on the defect geometric data and the temporal correlation features, fused defect information is generated, and the weld quality inspection result is determined based on the fused defect information.

[0024] In one optional implementation, based on the geometric parameters and material acoustic parameters of the stainless steel weld to be inspected, the sound wave propagation paths at different depths within the weld cross-section are calculated, and the scanning parameter set of the phased array probe and the arrangement parameter set of the TOFD probe pair are determined, including: Based on the weld width, weld thickness, and bevel angle in the geometric parameters, and the longitudinal wave velocity and transverse wave velocity in the material acoustic parameters, the acoustic propagation medium layering of the weld cross section is constructed. For each layer in the acoustic propagation medium layering, the refraction angle and propagation time of the sound wave propagation within the layer, as well as the reflection coefficient and transmission coefficient of the sound wave at the interlayer interface, are calculated to generate the sound wave propagation path at different depth positions within the weld cross section, and the sound energy concentration area and sound energy attenuation area within the weld cross section are identified based on the sound wave propagation path. The focusing depth of the phased array probe is configured to correspond to the depth position of the acoustic energy concentration area, and the deflection angle of the phased array probe is configured to correspond to the interface normal angle of the acoustic energy concentration area, so that the phased array probe can acquire a reflected echo signal with a defect reflection echo signal intensity greater than the background noise signal intensity in the acoustic energy concentration area, thereby obtaining the scanning parameter set. The probe spacing of the TOFD probe pair is configured to correspond to the width range of the acoustic energy attenuation region, and the incident angle of the TOFD probe pair is configured to correspond to the critical incident angle of the acoustic wave in the acoustic energy attenuation region, so that the TOFD probe pair can acquire a highly sensitive diffraction wave signal in the acoustic energy attenuation region, thereby obtaining the set of arrangement parameters.

[0025] like Figure 2 As shown, the method includes: When performing ultrasonic testing on stainless steel welds, the testing parameters need to be determined based on the actual geometry and material properties of the weld. Geometric parameters are obtained by directly measuring the surface features of the weld. Weld width refers to the distance between fusion lines on the weld surface, typically measured using a laser rangefinder with a required accuracy of 0.1 mm. Weld thickness refers to the thickness of the base material, measured at multiple points on both sides of the weld using an ultrasonic thickness gauge, and the average value is taken. Bevel angle refers to the opening angle of the weld bevel, obtained using an angle gauge or 3D scanner; a typical V-groove angle ranges from 45° to 60°. The longitudinal and transverse wave velocities in the material's acoustic parameters need to be measured on a test block made of the same material as the weld. The pulse reflection method is used, with the probe placed vertically on the test block surface, and the round-trip propagation time of the sound wave in a test block of known thickness is recorded. The longitudinal wave velocity is calculated as twice the test block thickness divided by the round-trip time. The transverse wave velocity is measured using an oblique incidence method, calculated by measuring the propagation time and distance of the transverse wave in the test block. For austenitic stainless steel, the longitudinal wave velocity is typically in the range of 5600 to 5900 m / s, and the transverse wave velocity is in the range of 3100 to 3300 m / s. The measurement error of the sound velocity should be controlled within ±1%.

[0026] Based on the acquired geometric and acoustic parameters, a layered model of the acoustic propagation medium of the weld cross-section is established. The model divides the weld cross-section into three main layers: the base metal region, the heat-affected zone (HAZ), and the weld metal region. The base metal region, located on both sides of the weld, exhibits acoustic characteristics consistent with the base material, with stable sound velocity and acoustic impedance. The HAZ, located between the base metal and the weld metal, experiences grain coarsening and microstructure transformation due to the welding thermal cycle, resulting in a 3% to 8% deviation in sound velocity, requiring correction based on welding process parameters and cooling rate. The weld metal region, located at the weld center, exhibits anisotropy in sound wave propagation velocity across different grain orientations due to columnar crystalline structures formed during the solidification process of the deposited metal. The directional difference in transverse wave sound velocity can reach 5% to 12%. When establishing the layered model, the boundary morphology of each layer must also be considered. The interface between the base metal and the HAZ typically presents a smooth transition, while the interface between the HAZ and the weld metal region exhibits an inclined characteristic due to the bevel angle. The interface inclination directly affects the incident and refraction angles of the sound waves.

[0027] For each layer in the layered model, the propagation characteristics of sound waves are calculated. When a sound wave enters another layer, the refraction angle is determined according to Snell's law. The ratio of the sine of the incident angle to the velocity of sound in the incident layer is equal to the ratio of the sine of the refraction angle to the velocity of sound in the refraction layer. In calculating the propagation time within a layer, the actual propagation path length of the sound wave needs to be considered. This length is determined by both the layer thickness and the refraction angle, and the propagation time is equal to the path length divided by the velocity of sound in that layer. At the interlayer interface, sound wave energy is distributed; some energy is reflected back to the incident layer, and some energy is transmitted into the next layer. The calculation of the reflection coefficient involves the difference in acoustic impedance between the two layers and the incident angle of the sound wave. When the ratio of the difference in acoustic impedance to the sum of the acoustic impedances of the two layers is large, the reflection coefficient increases, and more sound energy is reflected. The transmission coefficient represents the ratio of transmitted sound energy to incident sound energy, satisfying the energy conservation relationship; the sum of the reflection coefficient and the transmission coefficient equals 1. For stainless steel welds, the acoustic impedance difference between the base metal and the weld metal typically results in an interface reflection coefficient of 0.15 to 0.25, which means that 15% to 25% of the acoustic energy is reflected by the interface.

[0028] By tracking the propagation path and energy changes of sound waves in each layer, a complete sound wave propagation path at different depths within the weld cross-section is generated. This path includes the entire process of sound waves being emitted from the probe, refracted and reflected through the interfaces of each layer, and finally reaching the target depth. Based on the energy distribution information in the propagation path, regions of concentrated sound energy and regions of attenuation are identified. Regions of concentrated sound energy appear at the natural focusing position of the sound beam and at the locations where interference from multiple reflected waves is enhanced. In these regions, the sound wave intensity is more than 20% higher than the surrounding area, making them suitable for reflection-based detection. Regions of attenuation sound energy appear in the sound beam diffusion area and areas with severe grain scattering. The sound wave intensity attenuates by more than 6 dB during propagation, making conventional reflection-based detection less sensitive, but these regions are suitable for diffraction wave detection. For a typical 20 mm thick stainless steel V-shaped weld with a bevel angle of 50°, regions of concentrated sound energy are mainly distributed at depths of 5 to 8 mm from the weld surface and 15 to 18 mm from the weld surface, while regions of attenuation sound energy are mainly located in the weld root region, at depths of 18 to 20 mm.

[0029] The scanning parameters of the phased array probe need to be configured so that the sound beam covers the main inspection area of ​​the weld and obtains optimal detection sensitivity in the area of ​​concentrated sound energy. The principle of focusing depth configuration is to make the focal point of the sound beam coincide with the center depth of the area of ​​concentrated sound energy. Focusing control is achieved by adjusting the excitation delay time of each element in the phased array probe. For an area of ​​concentrated sound energy with a depth of 6mm, the required focusing depth is 6mm. The corresponding delay time is calculated based on the distance difference from each element to the focal point and the sound velocity of the material. The deflection angle configuration is to make a suitable angle between the main axis of the sound beam and the interface normal of the area of ​​concentrated sound energy. When the interface tilt angle is 25°, the deflection angle should be configured to 25° to ensure that the sound wave is incident perpendicularly on the interface, thereby achieving maximum sound energy transmission and the strongest response of the defect reflection wave. The scanning parameter set also includes the scanning step interval and scanning speed. The step interval is typically set to 50% of the effective aperture of the probe to ensure that the acoustic beam coverage area of ​​adjacent scanning positions overlaps by 50%, avoiding missed detections. The scanning speed needs to be determined based on the data acquisition frequency and step interval to ensure that complete data acquisition is completed at each scanning position. A typical scanning speed is 150 mm / s. Within the area of ​​concentrated acoustic energy, with the above parameter configuration, the amplitude of the defect reflection echo signal can reach 40% to 80% of the full screen height, while the amplitude of the background noise signal is usually less than 5% of the full screen height, resulting in a signal-to-noise ratio exceeding 18 dB, which meets the defect detection requirements.

[0030] The TOFD probe pair arrangement parameters are optimized for acoustic attenuation areas such as the weld root. The probe spacing must ensure that the acoustic wave propagation path between the transmitting and receiving probes covers the entire width of the attenuation region, while guaranteeing temporal separation between the direct wave from the upper surface of the weld and the bottom-reflected wave from the lower surface. For an acoustic attenuation region 12mm wide, a probe spacing of 50 to 70mm is recommended. Too small a spacing results in temporal overlap between the direct wave and the defect diffracted wave, while too large a spacing leads to excessive acoustic attenuation along the propagation path. The incident angle is configured considering the acoustic characteristics of the attenuation region. When coarse grains in this region cause severe transverse wave scattering, an incident angle close to the critical angle can excite more longitudinal wave components and reduce scattering losses. The critical angle of acoustic wave incidence refers to the angle of incidence when the refraction angle of a transverse wave at the interface reaches 90°. It is calculated based on the ratio of the sound velocities of the two media. For stainless steel welds, the critical angle from longitudinal to transverse waves is approximately 33°. Configuring an incident angle of 30° to 32° allows for the acquisition of strong diffracted wave signals within the attenuation region. The setup parameter set also includes fine-tuning parameters for the probe's height and tilt angle. The distance between the probe's bottom surface and the weld surface is controlled by the wedge height, maintaining a coupling layer thickness of 0.5 to 1 mm. Fine-tuning of the tilt angle compensates for unevenness on the weld surface, with an adjustment range of ±2°. With optimized setup parameters, the TOFD method can achieve a detection rate of over 90% for defects with a depth dimension greater than 0.5 mm within the acoustic attenuation region, with a depth positioning accuracy better than 0.3 mm.

[0031] In one optional implementation, the stainless steel weld to be inspected is scanned according to the scanning parameter set to acquire phased array detection data and perform imaging processing to generate a sector-shaped scan image of the weld cross-section and extract the spatial location of the defect response in the image, including: Based on the focusing depth and deflection angle in the scanning parameter set, the phased array probe is controlled to scan along the length of the stainless steel weld to be inspected, and reflected echo signals at different depth positions within the weld cross-section are collected to generate the phased array detection data. The arrival time of the reflected echo signal in the phased array detection data is converted into depth coordinates within the weld cross section, and the deflection angle in the phased array detection data is converted into lateral coordinates within the weld cross section, thus establishing a two-dimensional coordinate system composed of the depth coordinates and lateral coordinates of the weld cross section. The amplitude of each reflected echo signal in the phased array detection data is mapped to the pixel grayscale value of the corresponding position in the two-dimensional coordinate system to generate a fan-shaped scan image of the weld cross section. In the fan-shaped scan image, a continuous pixel region whose pixel gray value exceeds a preset gray value threshold is identified as a defect response candidate region, and the average gray value of the defect response candidate region is calculated. Candidate regions for defect responses that meet the criteria of having an area greater than the lower limit of the area and an average gray value greater than the lower limit of the average gray value are selected as defect response regions. The depth and lateral coordinates of each defect response region in the two-dimensional coordinate system are extracted to generate the spatial location of the defect response in the fan-shaped scan image.

[0032] Based on pre-determined focusing depth and deflection angle parameters in the scanning parameter set, the phased array probe is controlled to continuously scan along the length of the stainless steel weld to be inspected. The phased array probe contains multiple independent piezoelectric crystal elements. By applying different delay time excitations to each element, electronic scanning and dynamic focusing of the sound beam within the weld cross-section are achieved. During the scanning process, the phased array probe moves along the weld length at fixed sampling intervals, emitting ultrasonic beams at each sampling position according to the focusing depth and deflection angle sequences specified in the scanning parameter set. When the sound beam encounters an acoustic impedance discontinuity interface such as a crack, pore, or inclusion within the weld, reflected echo signals are generated. The receiving circuit amplifies, filters, and digitizes the echo signals received by each element, recording the arrival time, amplitude, and corresponding deflection angle information of each echo signal, forming phased array detection data containing multi-dimensional information in the time and spatial domains. Each record in this dataset corresponds to a complete scan waveform at a specific longitudinal position and deflection angle of the weld, typically reaching hundreds of megabytes in size.

[0033] To map phased array detection data to the geometric space of the weld cross-section, a transformation relationship between time-domain parameters and spatial-domain coordinates needs to be established. For the arrival time t of the reflected echo signal, based on the relationship between the propagation speed v of the sound wave in stainless steel and the sound path s = vt / 2 (dividing by 2 because the sound wave travels a round trip path between transmission and reception), the arrival time can be converted into the sound path distance. Considering the wedge refraction effect of the phased array probe, the actual propagation path of the sound beam after entering the weld material at a specific deflection angle θ is not perpendicular. Through geometric relationships, the sound path distance s can be decomposed into a depth component d = scosθ and a transverse component l = ssinθ. The depth component d represents the depth coordinate of the defect within the weld cross-section relative to the probe's incident point, and the transverse component l, combined with the offset of the probe's center position, constitutes the transverse coordinate of the defect. By performing coordinate transformations on the echo signals at all deflection angles, a two-dimensional rectangular coordinate system is established with the weld cross-section depth as the vertical axis and the transverse position as the horizontal axis. The origin of this coordinate system is usually set at the probe scanning centerline on the weld surface.

[0034] Within the established two-dimensional coordinate system, the echo amplitude information in the phased array detection data is mapped to the pixel grayscale values ​​of the image. The specific mapping process is as follows: the two-dimensional coordinate system is divided into several pixel grids, with each pixel corresponding to a small region at a specific depth and lateral position within the weld cross-section. All echo signal records in the phased array detection data are traversed, and the corresponding depth and lateral coordinates are calculated based on the arrival time and deflection angle of each record to determine the pixel location to which the echo signal belongs. The amplitude of the echo signal is converted to a grayscale value within the range of 0 to 255 according to a preset grayscale mapping function. The grayscale mapping function typically uses linear or logarithmic mapping, so that high-amplitude echoes correspond to high grayscale values ​​(close to white), and low-amplitude echoes correspond to low grayscale values ​​(close to black). When multiple echo signals are received at the same pixel location, the grayscale value corresponding to the largest amplitude is taken as the final grayscale value of that pixel. After all pixels have been assigned grayscale values, the generated image exhibits a fan-shaped distribution. This is due to the shape of the coverage area determined by the deflection angle range and propagation distance of the phased array acoustic beam. This image is the fan-shaped scan image of the weld cross-section.

[0035] Automatic defect response identification and localization are performed in the generated fan-shaped scan image using a region growing algorithm based on grayscale threshold segmentation. A preset grayscale threshold is set, which is selected by comprehensively considering the background noise level of the weld material and the typical amplitude characteristics of the defect echo. It is usually set to the average grayscale value of the background noise plus three standard deviations. The fan-shaped image is scanned row by row and column by column. When the grayscale value of a pixel exceeds the preset grayscale threshold, it is marked as a seed point, and the connectivity of its eight neighbors is judged starting from this seed point. If the grayscale values ​​of adjacent pixels also exceed the threshold, they are included in the same continuous region, and the process continues to expand outward until all connected high grayscale pixels are classified. After the complete region growing process, several closed regions composed of continuous high grayscale pixels are formed in the image. These regions are the candidate regions for defect responses.

[0036] For each identified defect response candidate region, feature parameters are calculated and validity is screened. The total number of pixels contained in each candidate region is counted, and the actual area A of the region is converted according to the pixel size, in square millimeters. Simultaneously, the arithmetic mean of the grayscale values ​​of all pixels within the region is calculated. This serves as the average grayscale value for the area, reflecting the overall intensity level of the defect echo. A lower limit value A is set for the area. min and the lower limit of average gray level As a screening criterion, the lower limit of the area is set based on the minimum detectable defect size specified in the inspection standard, typically ranging from 0.5 square millimeters to 2 square millimeters; the lower limit of the average grayscale value must be set higher than the preset grayscale threshold to further eliminate false defect signals with blurred edges. All candidate defect response regions are traversed, and only those simultaneously satisfying A > A are retained. minand The region defined by the condition is identified as the actual defect response region.

[0037] For each confirmed defect response region, its spatial location feature parameters in a two-dimensional coordinate system are extracted, the depth coordinates of all pixels in that region are calculated, and the minimum depth coordinate is taken as the upper depth d of the defect. top The maximum depth coordinate is taken as the lower depth d of the defect. bottom The difference between the two values ​​represents the depth span of the defect. Calculate the lateral coordinates of all pixels in the region, and take the minimum and maximum lateral coordinates to determine the lateral extent of the defect. To characterize the center position of the defect, calculate the centroid d of the depth coordinates of all pixels within the region. center and the centroid l of the horizontal coordinate center Centroid calculation uses a weighted method based on pixel grayscale values, i.e. and G i d i l i These represent the grayscale value, depth coordinates, and lateral coordinates of the i-th pixel, respectively. The depth centroid, lateral centroid, depth span, and lateral span information of each defect response region are combined to form a complete spatial location description of the defect, i.e., defect response spatial location data. This data is stored in a structured list format, where each entry corresponds to a defect identified in the sector scan image, containing its precise geometric location parameters, providing reference coordinate information for subsequent spatial matching with TOFD detection results.

[0038] In one optional implementation, the stainless steel weld to be inspected is scanned according to the set of arrangement parameters to obtain TOFD inspection data. Based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD inspection data, the depth location and height dimension of the defect are calculated, and defect geometric data is generated, including: Based on the set of arrangement parameters, the TOFD probe is configured to scan along the length of the stainless steel weld to be inspected, receive the diffraction wave signal generated by the defect endpoint in the weld cross section, and generate the TOFD detection data. In the TOFD detection data, the diffraction wave signal located within the time window between the direct wave signal and the bottom reflected wave signal is identified, and the diffraction wave signal is classified into upper diffraction wave signal and lower diffraction wave signal according to the order of arrival time. The arrival time of the direct wave signal is calibrated as time zero. Calculate the time difference between the arrival time of the upper diffraction wave signal and the zero time point, and the time difference between the arrival time of the lower diffraction wave signal and the zero time point, respectively. Based on the time difference and the longitudinal wave velocity in the material acoustic parameters, calculate the depth position of the upper end point of the defect corresponding to the upper diffraction wave signal and the depth position of the lower end point of the defect corresponding to the lower diffraction wave signal, respectively. Calculate the difference between the depth position of the lower end point of the defect and the depth position of the upper end point of the defect to generate the height dimension of the defect; The depth position of the upper endpoint of the defect is used as the depth position of the defect. The depth position of the defect and the height dimension of the defect are combined to generate the geometric data of the defect.

[0039] After determining the setup parameter set, the TOFD probe pair needs to be deployed onto the surface of the stainless steel weld to be inspected according to the predetermined parameter configuration. The starting position for the probe pair scanning is determined along the length of the weld, typically extending a certain distance outward from the weld end to ensure effective coverage of the entire weld area. The transmitting and receiving probes are arranged on both sides of the weld with the weld centerline as the axis of symmetry. The distance from the probe tip to the weld center is strictly set according to the PCS value in the setup parameter set. At this point, the sound beams of the two probes converge inside the weld to form the detection sensitive area. To ensure effective sound energy transmission, an appropriate amount of coupling agent is applied between the probe and the workpiece surface, usually a water-soluble or oil-based coupling agent, ensuring close contact between the probe bottom surface and the workpiece surface without air bubbles. The probe pair is driven to continuously scan along the length of the weld at a stable speed, typically controlled between 100 mm / s and 150 mm / s. Too fast a scanning speed will result in insufficient data acquisition density, while too slow a speed will reduce detection efficiency. During the scanning process, the transmitting probe continuously emits longitudinal ultrasonic signals, which propagate into the weld in the form of spherical waves. When the longitudinal waves encounter defects within the weld cross-section, diffraction occurs at the defect endpoints. The diffracted waves propagate in different directions from the upper and lower endpoints of the defect, with some of the diffracted wave energy being captured by the receiving probe. In addition to the defect diffracted waves, the receiving probe also simultaneously receives the direct wave signal propagating directly from the transmitting probe and the bottom-reflected wave signal after reflection from the bottom surface of the workpiece. These different types of acoustic signals arrive at the receiving probe at different times according to their respective propagation paths, thus forming a signal distribution with distinct characteristics on the time axis. The data acquisition system digitizes the received analog signals at a preset sampling frequency, typically set to 100MHz to 200MHz, which is sufficient to ensure accurate acquisition of the longitudinal wave signals. A set of time-amplitude curves is generated for each scanning position, and these curves are arranged in chronological order of the scanning positions to form the TOFD inspection dataset.

[0040] After acquiring TOFD inspection data, it is necessary to identify the valid diffraction wave signals. On the time axis, the direct wave signal appears first, arriving earliest and usually with the strongest amplitude because the propagation path of the direct wave is the shortest. A period of time following the direct wave, diffraction wave signals generated by the defect endpoints appear. When a defect exists inside the weld, the diffraction wave generated by the upper endpoint of the defect has a relatively short propagation distance, thus arriving at the receiving probe earlier, forming the upper diffraction wave signal; while the lower endpoint of the defect is located deeper, and its diffraction wave needs to travel a longer distance to reach the receiving probe, thus arriving later, forming the lower diffraction wave signal. Later still, the bottom reflection wave signal appears. This signal is the longitudinal wave reflected back from the bottom surface of the workpiece, and its arrival time depends on the probe spacing and workpiece thickness. Therefore, the defect diffraction wave signal must lie within the time window between the direct wave signal and the bottom reflection wave signal. By performing time-domain analysis on the TOFD inspection data, the arrival time t of the direct wave signal can be extracted. d The arrival time t of the bottom reflected wave signal b The time window range is determined to be [t]. d , t b Within this time window, abrupt amplitude changes or regions of concentrated energy are searched; the signals corresponding to these locations are the diffracted wave signals. To distinguish between upper and lower diffracted waves, the diffracted wave signals identified within the time window are sorted from earliest to latest according to their arrival time. The earlier arriving signals are classified as upper diffracted wave signals, and their arrival time is denoted as t. u The signals that arrive later are classified as lower-end diffraction wave signals, and their arrival time is denoted as t. l This classification method is based on the physical characteristics of the defect geometry. The upper end is closer to the workpiece surface, while the lower end is farther from the surface, so the arrival time of the diffracted waves has a certain order.

[0041] To accurately calculate the depth and height of defects, a unified time reference needs to be established. This reference will be the arrival time t of the direct wave signal. d The time point is calibrated to zero, i.e., let t0 = t d Using this as a reference, the time difference between the upper diffraction wave signal and the zero point is Δt. u =t u -t0, this time difference reflects the time required for the diffracted wave to propagate from the upper end of the defect to the receiving probe. According to the basic principle of sound wave propagation, the propagation distance of a sound wave in a material is equal to the product of the speed of sound and the propagation time. The speed of sound v of the longitudinal wave in stainless steel. LThe acoustic parameters of the material are already given, typically ranging from 5800 m / s to 6100 m / s. The propagation path of the upper diffracted wave is not a simple straight line, but a broken line path from the transmitting probe through the upper end of the defect to the receiving probe. Based on geometric relationships, the depth d of the upper end of the defect... u It can be determined in the following way: First, calculate the total path length L of the sound wave propagation. u =v L ·Δt u Then, combining the probe spacing S (i.e., twice the PCS value) and the propagation geometry of the diffracted wave, the trigonometric relationship is used to solve for d. u Specifically, if the horizontal positions of the transmitting and receiving probes are taken as the origin and endpoint of the coordinate system, respectively, and the horizontal coordinate of the upper endpoint of the defect is located near the midpoint between the two, its depth d u satisfy Approximately equal to L u / 2 (considering symmetrical paths). The numerical solution yields... Similarly, the time difference between the lower diffracted wave signal and the zero point is Δt. l =t l -t0 corresponds to a propagation path length of L. l =v L ·Δt l Depth location of the lower end of the defect .

[0042] Obtain the depth d of the upper end point of the defect u and the depth d of the lower endpoint l Then, the height dimension h of the defect can be obtained by calculating the difference between the two, that is, h=d l -d u This height dimension directly reflects the extent of the defect along the weld depth direction and is an important indicator for evaluating the severity of the defect. To fully describe the spatial location of the defect, the depth position d of the upper endpoint of the defect is usually used. u As a depth marker for this defect, the upper endpoint is closer to the weld surface, making its location easier to compare and verify with phased array detection results. The depth position d... uCombined with the height dimension h, this forms defect geometric data, which is recorded in a structured form, typically including scan location coordinates, depth location, height dimension, and corresponding diffraction wave amplitude information. For multiple defects detected within the same scan area, their respective defect geometric data are generated and stored numbered according to the scan location sequence. This defect geometric data provides a precise geometric description of the defect within the weld cross-section, laying the foundation for subsequent fusion analysis with phased array detection results. It also provides a quantitative basis for defect nature judgment and weld quality assessment. The entire data processing process is implemented using automated algorithms, enabling the generation of defect geometric data within a short time after the scan is completed, greatly improving detection efficiency and the objectivity of the results.

[0043] In one optional implementation, the phased array detection data and the TOFD detection data are synchronized and aligned in the time domain to establish a dual-source signal correlation sequence under a unified time reference, including: The scan start time is extracted from the phased array detection data and the TOFD detection data respectively, and the time offset between the two scan start times is calculated. The acquisition timestamps of the phased array detection data and the TOFD detection data are synchronously corrected according to the time offset, and the time coordinates of the phased array detection data and the TOFD detection data are uniformly mapped to the same time base. The scanning path is divided into multiple spatial segments according to the length direction of the stainless steel weld to be inspected, and the scanning time interval corresponding to each spatial segment in the phased array detection data and the scanning time interval corresponding to the TOFD detection data are calculated. For each spatial segment, the reflected echo signal sequence within the scanning time interval is extracted from the phased array detection data, and the diffraction wave signal sequence within the scanning time interval is extracted from the TOFD detection data. The reflected echo signal sequence and the diffraction wave signal sequence are paired in chronological order to generate a signal association group corresponding to the spatial segment. All signal association groups corresponding to the spatial segments are arranged in order of the length direction of the stainless steel weld to be detected, and the acquisition position coordinates of the reflected echo signal sequence and the acquisition position coordinates of the diffraction wave signal sequence are marked in each signal association group. A data structure containing the spatiotemporal correspondence of dual-source signals is constructed to generate the dual-source signal association sequence.

[0044] In the collaborative operation of phased array detection and TOFD detection, the data generated by the two detection technologies are often asynchronous in the time dimension. This asynchrony mainly stems from differences in the start-up time of the detection equipment, delays in the data acquisition triggering mechanism, and slight fluctuations in the scanning speed. To achieve effective fusion of the two detection data, precise time-domain synchronization and alignment processing is required for the acquired phased array detection data and TOFD detection data.

[0045] When extracting the scan start time from phased array detection data, the time point when the phased array probe first emits an ultrasonic pulse is identified as a reference marker. Specifically, the timestamp of the first A-scan signal recorded by the phased array detection system is read. This timestamp is typically generated by the internal clock system of the detection equipment, with an accuracy down to the microsecond level. Simultaneously, the scan start time is extracted from the TOFD detection data and determined by locating the TOFD probe at the time point when it first receives the direct-pass wave signal. The direct-pass wave is the signal generated when the sound wave emitted by the transmitting probe propagates directly to the receiving probe; it arrives earliest and has distinct waveform characteristics, serving as a reliable time reference.

[0046] The time difference is obtained by subtracting the start time of the phased array detection data from the start time of the TOFD detection data scan. This time difference reflects the deviation between the two detection systems in terms of startup and data acquisition start time. If the time offset is positive, it indicates that the data acquisition of the TOFD detection system is later than that of the phased array detection system; if it is negative, the opposite is true. This time offset becomes a key parameter for subsequent time synchronization correction.

[0047] Based on the calculated time offset, the acquisition timestamps of the phased array detection data and the TOFD detection data are synchronized and corrected. During the correction process, a time reference from one of the detection systems is selected as a unified reference system, typically the phased array detection system. The original timestamp of each sampling point in the TOFD detection data is subtracted from the time offset to align the origins of the time coordinates of the two sets of detection data. After correction, the phased array detection data and the TOFD detection data are uniformly mapped on the time axis, and any given absolute time point can accurately correspond to the corresponding position in the two datasets.

[0048] The entire scanning path is divided into multiple spatial segments along the length of the stainless steel weld to be inspected. During the division process, the number of spatial segments and the start and end positions of each segment are determined based on the total length of the weld and the preset segment interval. For example, for a weld with a length of 2 meters, if the segment interval is set to 100 millimeters, the weld will be divided into 20 spatial segments, each 100 millimeters in length. Each spatial segment is numbered sequentially along the length of the weld, forming an ordered spatial segment sequence.

[0049] For each spatial segment, calculate its corresponding scanning time interval in the phased array detection data. Based on the probe's scanning speed and the start and end coordinates of the spatial segment, determine the start and end times of the probe scanning through that region. Assuming the scanning speed is a constant value v, the start position of the spatial segment is x1, the end position is x2, and the scanning start position is x0, then the scanning start time for that spatial segment is t1 = (x1 - x0) / v, and the end time is t2 = (x2 - x0) / v, with the scanning time interval being [t1, t2]. Calculate the corresponding scanning time interval for that spatial segment in the TOFD detection data using the same method. Since the two detection systems have completed time synchronization calibration, theoretically, the two time intervals should be completely consistent or only have slight deviations due to minor differences in the scanning path.

[0050] When extracting the reflected echo signal sequence within a specified scanning time interval from the phased array detection data, the phased array detection dataset is traversed, and all A-scan signals with timestamps within that interval are selected. Each A-scan signal contains ultrasonic wave reflection information received by the probe at a specific location, specific focusing depth, and specific deflection angle. These A-scan signals are organized in chronological order of acquisition to form the reflected echo signal sequence for that spatial segment. Simultaneously, the diffraction wave signal sequence within the same scanning time interval is extracted from the TOFD detection data. Each sampling point in the TOFD detection data records the diffraction wave amplitude received by the receiving probe at a specific time. All sampling data within that time interval are extracted in chronological order to form the diffraction wave signal sequence.

[0051] The reflected echo signal sequence and the diffraction wave signal sequence are paired in chronological order. Specifically, using the acquisition time point of the phased array detection data as a reference, for each A-scan signal in the reflected echo signal sequence, the diffraction wave sampling point with the closest timestamp in the TOFD detection data is found, establishing a correspondence between the two. Considering the difference between the sampling intervals of the phased array system and the TOFD system, the time difference is allowed within a certain threshold range during pairing; this threshold is typically set to the larger value of the sampling periods of the two systems. Through this pairing method, a signal association group is formed, containing paired data of the phased array reflected signal and the TOFD diffraction signal. This signal association group corresponds to the detection information within a specific spatial segment.

[0052] In each signal association group, the acquisition position coordinates of the reflected echo signal sequence are marked. These acquisition position coordinates consist of three dimensions: coordinates along the weld length, lateral coordinates perpendicular to the weld, and the distance from the probe center to the weld centerline. This coordinate information is typically recorded in real-time by the scanning encoder and stored synchronously with the phased array detection data. Similarly, the acquisition position coordinates of the diffraction wave signal sequence are also marked, and the position information of the TOFD probe pair during the scanning process is also provided by the encoder system. Because the installation positions of the phased array probe and the TOFD probe pair have a fixed offset, the position coordinates need to be transformed according to the geometric relationship of the probe arrangement to ensure that the position coordinates of the two detection methods are expressed in the same spatial reference frame.

[0053] When constructing a data structure containing the spatiotemporal correspondence of dual-source signals, a multidimensional array or structured data table is used for organization. Each record in the data structure corresponds to a set of associated data at a specific time and location, including fields such as: acquisition timestamp under a unified time reference, weld length direction coordinates, phased array A-scan signal data, TOFD diffraction wave amplitude data, phased array probe beam deflection angle, phased array focusing depth, center-to-center spacing of the TOFD probe pair, and spatial segment number. This data structure not only preserves the complete information of the original detection data but also establishes a clear correspondence between phased array detection and TOFD detection in the temporal and spatial dimensions.

[0054] All signal association groups corresponding to the spatial segments are arranged sequentially along the length of the stainless steel weld to be inspected. During the arrangement, the signal association groups are connected sequentially using the spatial segment number as an index to form a continuous data sequence covering the entire weld. The signal association groups of adjacent spatial segments in this sequence are smoothly connected in time and space, avoiding data gaps or overlaps. The final generated dual-source signal association sequence possesses complete spatiotemporal continuity, providing a unified data foundation for subsequent defect identification and signal response matching. Through this association sequence, the corresponding phased array detection signal and TOFD detection signal can be quickly retrieved at any specified weld location, enabling efficient collaborative analysis of data from the two detection technologies.

[0055] In one optional implementation, candidate signal association groups are filtered by spatially matching the spatial location of the defect response with the depth location in the defect geometry data. Defect reflected echo and upper-end diffraction wave signals are identified from the candidate signal association groups. Signal response pairs generated by the same defect are determined based on the principle of minimizing the sum of the depth deviations between the reflection depth and the upper-end depth location of the defect, and the depth deviations between the diffraction depth and the upper-end depth location of the defect. The time interval between the arrival times of the reflected echo and the diffraction wave in the signal response pair is extracted as a temporal correlation feature, including: For each signal association group in the dual-source signal association sequence, based on the defect response spatial location, the spatial distance between the position coordinates of the defect in the length direction of the stainless steel weld to be detected and the acquisition position coordinates of the reflected echo signal sequence, and the acquisition position coordinates of the diffraction wave signal sequence are calculated respectively. Signal association groups whose spatial distances are both less than a preset spatial matching threshold are selected as candidate signal association groups. For each candidate signal association group, the signal with the largest reflected wave amplitude is identified from the reflected echo signal sequence as the defect reflected echo and its corresponding reflection depth is extracted. The upper diffraction wave signal is identified from the diffraction wave signal sequence and its corresponding diffraction depth is extracted. The depth deviation between the reflection depth and the depth position of the upper end of the defect, and the depth deviation between the diffraction depth and the depth position of the upper end of the defect are calculated. The defect reflected echo and the upper diffraction wave signal in the candidate signal association group with the smallest sum of the two depth deviations are determined as a signal response pair generated by the same defect. The arrival time of the defect reflection echo and the arrival time of the upper diffraction wave signal in the signal response pair are extracted, and the time interval between the two arrival times is calculated as the time-series correlation feature.

[0056] In the established dual-source signal correlation sequence, each signal correlation group contains a reflected echo signal sequence and a diffraction wave signal sequence with similar acquisition position coordinates. For each signal correlation group, the position coordinates of the defect along the weld length direction are first obtained from the phased array detection data. These position coordinates are determined by the encoder position information of the defect response in the sector scan image. Simultaneously, the acquisition position coordinates of the reflected echo signal sequence and the diffraction wave signal sequence in this signal correlation group are extracted. These two acquisition position coordinates correspond to the actual positions of the phased array probe and the TOFD probe pair during the scanning process, respectively.

[0057] The spatial distance between the defect location coordinates and the coordinates of the reflected echo signal sequence acquisition position is calculated. This spatial distance reflects the degree of deviation of the defect from the phased array probe scanning position along the weld length. For stainless steel welds, since the probe moves along the weld length for scanning, defects within the beam coverage area will generate reflected echoes at multiple scanning positions. The spatial distance is calculated using the absolute difference between the defect location coordinates and the acquisition position coordinates, in millimeters. Similarly, the spatial distance between the defect location coordinates and the coordinates of the diffraction wave signal sequence acquisition position is calculated. This distance reflects the degree of deviation of the defect from the TOFD probe's center position.

[0058] Signal association groups are filtered based on a preset spatial matching threshold. This threshold is set by comprehensively considering the beamwidth of the phased array probe, the beam coverage of the TOFD probe pair, and the diffusion characteristics of sound waves in stainless steel. For austenitic stainless steel welds with grain sizes ranging from 20 to 80 micrometers, the preset spatial matching threshold is typically set between 8 and 15 millimeters. When the spatial distance between the defect location coordinates and the coordinates of the reflected echo signal sequence acquisition location is less than the preset spatial matching threshold, and the spatial distance between the defect location coordinates and the coordinates of the diffraction wave signal sequence acquisition location is also less than the preset spatial matching threshold, this signal association group is selected as a candidate signal association group. This dual spatial distance constraint ensures that both the reflected echo and diffraction waves in the candidate signal association group originate from defects within the effective beam coverage area.

[0059] For each candidate signal association group, defect-reflected echoes are identified from the reflected echo signal sequence. This sequence contains all reflected wave signals acquired at that location, originating from defects, grain interfaces within the weld, or other acoustic discontinuities. By traversing all signals in the reflected echo signal sequence, the amplitude of each signal is extracted, and the signal with the largest amplitude is identified as the defect-reflected echo. The signal with the largest amplitude typically corresponds to strong sound wave reflection at the defect interface, reflecting the main acoustic response characteristics of the defect. The reflection depth corresponding to this defect-reflected echo is extracted. This depth is calculated using the arrival time of the defect-reflected echo and the propagation speed of sound waves in stainless steel, representing the depth position of the defect relative to the weld surface.

[0060] The upper diffraction wave signal is identified from the diffraction wave signal sequence. This sequence contains all diffraction wave signals acquired at the sampling location, including the upper diffraction wave, the lower diffraction wave, and any present lateral waves. The identification of the upper diffraction wave signal is based on its arrival time characteristics; the upper diffraction wave arrives earlier than the lower diffraction wave and appears as the first obvious diffraction peak in the time-domain waveform. By analyzing the time-domain waveform of the diffraction wave signal sequence, the diffraction wave signal with the earliest arrival time and amplitude exceeding the noise baseline is identified as the upper diffraction wave signal. The diffraction depth corresponding to this upper diffraction wave signal is extracted. The diffraction depth is calculated using the arrival time of the upper diffraction wave signal, the spacing between the TOFD probe pairs, and the geometric relationship of the acoustic wave propagation path, representing the depth position of the upper endpoint of the defect relative to the weld surface.

[0061] The depth deviation between the reflection depth and the depth position of the upper endpoint of the defect is calculated. The depth position of the upper endpoint is directly obtained from the defect geometry data, which has been calculated using the arrival time difference between the upper and lower diffraction wave signals in the TOFD detection data. The depth deviation is expressed as the absolute difference between the reflection depth and the depth position of the upper endpoint of the defect, in millimeters. This depth deviation reflects the consistency between the defect depth identified by phased array detection and the upper endpoint depth determined by TOFD detection. Simultaneously, the depth deviation between the diffraction depth and the depth position of the upper endpoint of the defect is also calculated. This deviation reflects the degree of matching between the depth information extracted from the current upper diffraction wave signal and the determined depth position in the defect geometry data.

[0062] The two depth deviations are added together to obtain the comprehensive depth deviation of the candidate signal association group. This comprehensive depth deviation reflects the degree of matching between the defect reflection echo and the upper diffraction wave signal in the candidate signal association group and the target defect in the depth dimension. All candidate signal association groups are traversed, and the comprehensive depth deviation for each group is calculated and compared. The defect reflection echo and upper diffraction wave signal in the candidate signal association group with the smallest comprehensive depth deviation are identified as the signal response pair generated by the same defect. This matching criterion based on the minimum comprehensive depth deviation ensures that the identified signal response pair has the highest correlation in spatial location and accurately corresponds to the same physical defect.

[0063] After identifying the signal response pair, time-series correlation features are extracted. The arrival time is extracted from the defect reflection echo, which represents the temporal position of the reflected echo signal within the acquired waveform. This is typically determined by identifying the peak of the reflected echo or the moment it exceeds an amplitude threshold. The arrival time is also extracted from the upper diffraction wave signal, which represents the temporal position of the upper diffraction wave within the acquired waveform. This is also determined by identifying the peak of the diffraction wave or the moment it exceeds an amplitude threshold. The time interval between the arrival time of the defect reflection echo and the arrival time of the upper diffraction wave signal is calculated. The time interval is the absolute difference between the two arrival times, expressed in microseconds.

[0064] The time interval, as a temporal correlation feature, reflects the time difference in signal responses generated by the same defect in phased array reflected waves and TOFD diffracted waves. This time difference is affected by the probe placement, the sound wave propagation path, and the acoustic properties of the stainless steel material. For defects in stainless steel welds with depths ranging from 5 mm to 30 mm, the temporal correlation feature is typically between 0.5 microseconds and 10 microseconds. The temporal correlation feature provides crucial temporal correlation information for subsequent signal fusion and comprehensive defect feature analysis, contributing to improved reliability of joint detection and accuracy of defect identification. By establishing signal response pairs and extracting temporal correlation features, deep fusion of phased array detection data and TOFD detection data in both the temporal and spatial domains is achieved, providing a reliable data foundation for the comprehensive evaluation of weld quality.

[0065] In one optional implementation, generating fused defect information based on the defect geometry data and the temporal correlation features, and determining the weld quality inspection result based on the fused defect information includes: Extract the depth and height dimensions of the defect from the defect geometry data, and extract the horizontal coordinates of the defect from the defect response space. Based on the time-series correlation characteristics, the deviation between the time interval between the arrival time of the phased array reflected wave and the arrival time of the TOFD diffracted wave and the preset standard time interval is calculated. When the deviation is less than the preset time deviation threshold, the depth position and the height of the defect are determined as effective geometric parameters. When the deviation is greater than or equal to the preset time deviation threshold, the depth position and height of the defect are recalculated as corrected geometric parameters based on the time-series correlation characteristics. The effective geometric parameters or the corrected geometric parameters are combined with the horizontal position coordinates of the defect to generate the fused defect information, which includes the three-dimensional spatial position and size parameters of the defect. Based on the fused defect information, the depth position of the defect is compared with a preset depth safety threshold, and the height dimension of the defect is compared with a preset height safety threshold. When the depth position of the defect exceeds the preset depth safety threshold or the height dimension of the defect exceeds the preset height safety threshold, a detection result indicating that the weld quality is unqualified is generated; otherwise, a detection result indicating that the weld quality is qualified is generated.

[0066] After completing data acquisition and signal correlation for both phased array and TOFD detection, the defect features acquired by the two methods need to be deeply fused to generate comprehensive defect assessment information. The defect geometric data obtained from the TOFD detection data includes the defect's position along the weld depth direction and its height along that direction. These parameters are calculated by analyzing the arrival time difference between the upper and lower diffracted waves received by the TOFD probe. Simultaneously, the defect response spatial location extracted from the sector scan image of the phased array detection includes the horizontal coordinates of the defect along the weld length direction, reflecting the distance of the defect relative to the weld start point or reference point. By extracting these two types of data, a geometric feature description of the defect in different spatial dimensions can be obtained.

[0067] After obtaining the preliminary defect geometry parameters, the reliability of these parameters needs to be verified using temporal correlation characteristics. Temporal correlation characteristics reflect the time relationship between the signal responses generated by the same defect in both phased array and TOFD probe systems. For real-world defects, there is a definite physical relationship between the arrival times of the signals generated by the two detection methods. The phased array probe uses the pulse reflection method; the sound wave emitted from the probe encounters the defect interface and is reflected, returning to the probe for reception. The corresponding acoustic path is the round-trip distance from the probe to the defect. The TOFD probe receives the diffracted wave from the defect end. The sound wave originates from the transmitting probe, diffracts at the defect end, and propagates to the receiving probe. The corresponding acoustic path is the one-way distance from the transmitting probe through the defect end to the receiving probe. Because the sound wave propagation paths of the two methods are different, given the probe placement, weld geometry, and material sound velocity, the necessary temporal relationship between the arrival times of the phased array reflected wave and the TOFD diffracted wave can be calculated using a theoretical acoustic model. This theoretical relationship corresponds to a preset standard time interval.

[0068] The measured time interval is obtained by subtracting the arrival time of the phased array reflected wave from the arrival time of the TOFD diffracted wave. The difference between this measured time interval and the preset standard time interval is calculated as the deviation value. The magnitude of this deviation value reflects the degree of consistency between the detection results of the two methods. When the deviation value is small, specifically less than the preset time deviation threshold, it indicates that the detection results of the two methods corroborate each other. In this case, the defect depth location and height dimensions directly calculated by the TOFD method can be considered accurate and reliable, and these parameters are determined as effective geometric parameters. The setting of the preset time deviation threshold needs to comprehensively consider various factors such as the time measurement accuracy of the equipment, the sound velocity measurement error, and the probe positioning error. It is usually determined after multiple calibration experiments on a standard test block. The typical value is in the range of 0.1 microseconds to 0.5 microseconds, and the specific value is related to the configuration of the detection system and the characteristics of the weld material.

[0069] When the deviation value is greater than or equal to the preset time deviation threshold, it indicates a significant inconsistency between the detection results of the two methods. This situation can be caused by various reasons. The presence of regions with coarse grains and severe anisotropy within the stainless steel weld causes deflection of the acoustic wave propagation path, resulting in errors in the defect location calculated based on the homogeneous medium assumption. In this case, the defect geometric parameters need to be corrected. The correction process utilizes the acoustic wave propagation time information contained in the time-series correlation features, combined with the defect's horizontal position and azimuth information obtained from the phased array probe, and employs an iterative calculation method to re-determine the actual spatial location of the defect. Specifically, a set of equations can be established between the acoustic wave propagation time and the defect's spatial coordinates. This set of equations includes the phased array reflected wave propagation time equation and the TOFD diffraction wave propagation time equation, with the unknowns being the defect's depth and height. By numerically solving this set of equations, defect geometric parameters that simultaneously satisfy the time constraints of both detection methods are obtained, and these parameters are used as the corrected geometric parameters. Weighting coefficients can be introduced during the correction process to adjust the weights of each equation based on the reliability differences of different detection methods under specific defect types. For example, for defects with greater depth, the depth measurement of the TOFD method is usually more accurate and can be given a higher weight.

[0070] After verifying and correcting the geometric parameters, the confirmed effective depth position and height dimension are combined with the horizontal position coordinates extracted from the phased array detection results. This combination process establishes a three-dimensional spatial description framework for the defect, where the depth position represents the distance of the defect from the surface in the weld thickness direction, the horizontal position coordinates represent the position of the defect along the weld length direction, and the height dimension represents the extension range of the defect along the depth direction. In addition to these basic geometric parameters, the fused defect information can also include supplementary information such as defect type discrimination results, signal amplitude characteristics, and waveform characteristics. The defect type can be initially discerned based on the reflection wave morphology characteristics in the phased array scan image. For example, point defects correspond to concentrated reflection signals, strip defects correspond to linearly distributed reflection signals, and unfused defects usually exhibit characteristics distributed along the fusion line. The waveform characteristics of the TOFD signal can also assist in type discrimination; the diffraction waves of crack-type defects usually have sharp peaks, while the diffraction waves of porosity-type defects are relatively flat. By comprehensively utilizing multi-dimensional features, the generated fused defect information can completely describe the spatial location, geometric dimensions, and physical properties of the defect.

[0071] Based on the generated fusion defect information, the severity of the defects needs to be assessed according to weld quality acceptance standards. The depth and location of the defect are important evaluation indicators. Defects located near the weld surface have a relatively small impact on the structural load-bearing capacity, while defects located in the middle or root of the weld are in stress concentration areas and are more hazardous. The depth location in the fusion defect information is compared with a preset depth safety threshold, which is determined based on the weld's service conditions, load-bearing requirements, and relevant technical specifications. For pressure vessel welds, according to relevant standards, defects located less than one-third of the weld depth require special attention. For structural steel welds, different depth ranges correspond to different allowable defect sizes. The height of the defect directly reflects its extension range; larger defects are more likely to cause stress concentration and crack propagation. The height of the defect in the fusion defect information is compared with a preset height safety threshold, which is also set according to relevant standards and is usually related to the weld thickness; for example, some standards stipulate that the defect height must not exceed a specific percentage of the weld thickness.

[0072] A strict judgment logic is employed when performing quality assessments. If the depth of a defect exceeds a preset safety threshold (i.e., the defect is within a dangerous depth range), the weld is deemed unqualified regardless of other parameters. Similarly, if the height of a defect exceeds a preset safety threshold (i.e., the defect extends too far), the weld is also deemed unqualified. Only when both the depth and height of the defect are within the safety threshold range is a qualified weld assessment result generated. This judgment logic ensures the effective identification of potentially dangerous defects and conforms to the conservative principles of engineering safety. For welds deemed unqualified, the specific location and dimensions of the defect must be clearly marked in the inspection results to provide a basis for subsequent repair or reinforcement. For qualified welds, the inspection results also need to record complete defect information as foundational data for quality traceability and long-term service monitoring. The entire process of generating quality inspection results realizes the transformation from multi-source inspection data to unified quality judgment, ensuring the scientific rigor and reliability of stainless steel weld quality assessment.

[0073] A second aspect of the present invention provides a combined phased array and TOFD detection system for stainless steel welds, comprising: The parameter calculation unit is used to calculate the sound wave propagation path at different depths within the weld section based on the geometric parameters and material acoustic parameters of the stainless steel weld to be inspected, and to determine the scanning parameter set of the phased array probe and the arrangement parameter set of the TOFD probe pair. The data acquisition unit is used to scan the stainless steel weld to be inspected according to the scanning parameter set, acquire phased array detection data and perform imaging processing, generate a fan-shaped scan image of the weld cross section and extract the spatial location of the defect response in the image. The defect location unit is used to scan the stainless steel weld to be inspected according to the set of arrangement parameters, obtain TOFD detection data, and calculate the depth position and height of the defect based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD detection data, thereby generating defect geometric data. The signal alignment unit is used to perform time-domain synchronization alignment of the phased array detection data and the TOFD detection data to establish a dual-source signal correlation sequence under a unified time reference. The feature extraction unit is used to filter candidate signal association groups by spatially matching the spatial location of the defect response with the depth location in the defect geometric data, identify defect reflected echo and upper diffraction wave signals from the candidate signal association groups, determine the signal response pairs generated by the same defect based on the principle of minimizing the sum of the depth deviation between the reflection depth and the depth position of the upper end of the defect and the depth deviation between the diffraction depth and the depth position of the upper end of the defect, and extract the time interval between the arrival time of the reflected echo and the diffraction wave in the signal response pair as a temporal association feature. The result generation unit is used to generate fused defect information based on the defect geometric data and the temporal correlation features, and to determine the weld quality inspection result based on the fused defect information.

[0074] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0075] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0076] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0077] 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 method for combined phased array and TOFD detection of stainless steel welds, characterized in that, include: Based on the geometric parameters and material acoustic parameters of the stainless steel weld to be inspected, the sound wave propagation path at different depths within the weld cross-section is calculated, and the scanning parameter set of the phased array probe and the arrangement parameter set of the TOFD probe pair are determined. The stainless steel weld to be inspected is scanned according to the set of scanning parameters, phased array detection data is obtained and image processing is performed to generate a sector scan image of the weld cross section and extract the spatial location of the defect response in the image. The stainless steel weld to be inspected is scanned according to the set of arrangement parameters to obtain TOFD inspection data. Based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD inspection data, the depth position and height of the defect are calculated to generate defect geometric data. The phased array detection data and the TOFD detection data are synchronized and aligned in the time domain to establish a dual-source signal association sequence under a unified time reference. Candidate signal association groups are screened by spatially matching the spatial location of the defect response with the depth location in the defect geometric data. Defect reflected echo and upper diffraction wave signals are identified from the candidate signal association groups. Based on the principle of minimizing the sum of the depth deviation between the reflection depth and the depth location of the upper end of the defect and the depth deviation between the diffraction depth and the depth location of the upper end of the defect, signal response pairs generated by the same defect are determined. The time interval between the arrival times of the reflected echo and the diffraction wave in the signal response pair is extracted as a time-series association feature. Based on the defect geometric data and the temporal correlation features, fused defect information is generated, and the weld quality inspection result is determined based on the fused defect information.

2. The method according to claim 1, characterized in that, Based on the geometric and acoustic parameters of the stainless steel weld to be inspected, the sound wave propagation paths at different depths within the weld cross-section are calculated, determining the scanning parameter set for the phased array probe and the arrangement parameter set for the TOFD probe pair, including: Based on the weld width, weld thickness, and bevel angle in the geometric parameters, and the longitudinal wave velocity and transverse wave velocity in the material acoustic parameters, the acoustic propagation medium layering of the weld cross section is constructed. For each layer in the acoustic propagation medium layering, the refraction angle and propagation time of the sound wave propagation within the layer, as well as the reflection coefficient and transmission coefficient of the sound wave at the interlayer interface, are calculated to generate the sound wave propagation path at different depth positions within the weld cross section, and the sound energy concentration area and sound energy attenuation area within the weld cross section are identified based on the sound wave propagation path. The focusing depth of the phased array probe is configured to correspond to the depth position of the acoustic energy concentration area, and the deflection angle of the phased array probe is configured to correspond to the interface normal angle of the acoustic energy concentration area, so that the phased array probe can acquire a reflected echo signal with a defect reflection echo signal intensity greater than the background noise signal intensity in the acoustic energy concentration area, thereby obtaining the scanning parameter set. The probe spacing of the TOFD probe pair is configured to correspond to the width range of the acoustic energy attenuation region, and the incident angle of the TOFD probe pair is configured to correspond to the critical incident angle of the acoustic wave in the acoustic energy attenuation region, so that the TOFD probe pair can acquire a highly sensitive diffraction wave signal in the acoustic energy attenuation region, thereby obtaining the set of arrangement parameters.

3. The method according to claim 2, characterized in that, The stainless steel weld to be inspected is scanned according to the set of scanning parameters. Phased array detection data is acquired and image processing is performed to generate a sector-shaped scan image of the weld cross-section and extract the spatial location of the defect response in the image, including: Based on the focusing depth and deflection angle in the scanning parameter set, the phased array probe is controlled to scan along the length of the stainless steel weld to be inspected, and reflected echo signals at different depth positions within the weld cross-section are collected to generate the phased array detection data. The arrival time of the reflected echo signal in the phased array detection data is converted into depth coordinates within the weld cross section, and the deflection angle in the phased array detection data is converted into lateral coordinates within the weld cross section, thus establishing a two-dimensional coordinate system composed of the depth coordinates and lateral coordinates of the weld cross section. The amplitude of each reflected echo signal in the phased array detection data is mapped to the pixel grayscale value of the corresponding position in the two-dimensional coordinate system to generate a fan-shaped scan image of the weld cross section. In the fan-shaped scan image, a continuous pixel region whose pixel gray value exceeds a preset gray value threshold is identified as a defect response candidate region, and the average gray value of the defect response candidate region is calculated. Candidate defect response regions that satisfy both an area greater than the lower limit of area and an average gray value greater than the lower limit of average gray value are selected as defect response regions; the depth coordinates and horizontal coordinates of each defect response region in the two-dimensional coordinate system are extracted to generate the spatial location of the defect response in the fan-shaped scan image.

4. The method according to claim 1, characterized in that, The stainless steel weld to be inspected is scanned according to the set of arrangement parameters to obtain TOFD inspection data. Based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD inspection data, the depth location and height dimensions of the defect are calculated, and the defect geometric data is generated, including: Based on the set of arrangement parameters, the TOFD probe is configured to scan along the length of the stainless steel weld to be inspected, receive the diffraction wave signal generated by the defect endpoint in the weld cross section, and generate the TOFD detection data. In the TOFD detection data, the diffraction wave signal located within the time window between the direct wave signal and the bottom reflected wave signal is identified, and the diffraction wave signal is classified into upper diffraction wave signal and lower diffraction wave signal according to the order of arrival time. The arrival time of the direct wave signal is calibrated as the zero point; the time difference between the arrival time of the upper diffraction wave signal and the zero point, and the arrival time of the lower diffraction wave signal and the zero point are calculated respectively. Based on the time difference and the longitudinal wave velocity in the material acoustic parameters, the depth position of the upper end point of the defect corresponding to the upper diffraction wave signal and the depth position of the lower end point of the defect corresponding to the lower diffraction wave signal are calculated respectively. Calculate the difference between the depth position of the lower end point of the defect and the depth position of the upper end point of the defect to generate the height dimension of the defect; The depth position of the upper endpoint of the defect is used as the depth position of the defect. The depth position of the defect and the height dimension of the defect are combined to generate the geometric data of the defect.

5. The method according to claim 4, characterized in that, The phased array detection data and the TOFD detection data are synchronized and aligned in the time domain to establish a dual-source signal correlation sequence under a unified time reference, including: The scan start time is extracted from the phased array detection data and the TOFD detection data respectively, and the time offset between the two scan start times is calculated. The acquisition timestamps of the phased array detection data and the TOFD detection data are synchronously corrected according to the time offset, and the time coordinates of the phased array detection data and the TOFD detection data are uniformly mapped to the same time base. The scanning path is divided into multiple spatial segments according to the length direction of the stainless steel weld to be inspected, and the scanning time interval corresponding to each spatial segment in the phased array detection data and the scanning time interval corresponding to the TOFD detection data are calculated. For each spatial segment, the reflected echo signal sequence within the scanning time interval is extracted from the phased array detection data, and the diffraction wave signal sequence within the scanning time interval is extracted from the TOFD detection data. The reflected echo signal sequence and the diffraction wave signal sequence are paired in chronological order to generate a signal association group corresponding to the spatial segment. All signal association groups corresponding to the spatial segments are arranged in order of the length direction of the stainless steel weld to be detected, and the acquisition position coordinates of the reflected echo signal sequence and the acquisition position coordinates of the diffraction wave signal sequence are marked in each signal association group. A data structure containing the spatiotemporal correspondence of dual-source signals is constructed to generate the dual-source signal association sequence.

6. The method according to claim 5, characterized in that, Candidate signal association groups are filtered by spatially matching the spatial location of the defect response with the depth location in the defect geometric data. Defect reflected echo and upper-end diffraction wave signals are identified from these candidate signal association groups. Based on the principle of minimizing the sum of the depth deviations between the reflection depth and the upper-end depth location of the defect, and the depth deviations between the diffraction depth and the upper-end depth location of the defect, signal response pairs generated by the same defect are determined. The time interval between the arrival times of the reflected echo and the diffraction wave in the signal response pair is extracted as a temporal correlation feature, including: For each signal association group in the dual-source signal association sequence, based on the defect response spatial location, the spatial distance between the position coordinates of the defect in the length direction of the stainless steel weld to be detected and the acquisition position coordinates of the reflected echo signal sequence, and the acquisition position coordinates of the diffraction wave signal sequence are calculated respectively. Signal association groups whose spatial distances are both less than a preset spatial matching threshold are selected as candidate signal association groups. For each candidate signal association group, the signal with the largest reflected wave amplitude is identified from the reflected echo signal sequence as the defect reflected echo and its corresponding reflection depth is extracted. The upper diffraction wave signal is identified from the diffraction wave signal sequence and its corresponding diffraction depth is extracted. The depth deviation between the reflection depth and the depth position of the upper end of the defect, and the depth deviation between the diffraction depth and the depth position of the upper end of the defect are calculated. The defect reflected echo and the upper diffraction wave signal in the candidate signal association group with the smallest sum of the two depth deviations are determined as a signal response pair generated by the same defect. The arrival time of the defect reflection echo and the arrival time of the upper diffraction wave signal in the signal response pair are extracted, and the time interval between the two arrival times is calculated as the time-series correlation feature.

7. The method according to claim 1, characterized in that, Based on the defect geometric data and the temporal correlation features, fused defect information is generated, and the weld quality inspection result is determined based on the fused defect information, including: Extract the depth and height dimensions of the defect from the defect geometry data, and extract the horizontal coordinates of the defect from the defect response space. Based on the time-series correlation characteristics, the deviation between the time interval between the arrival time of the phased array reflected wave and the arrival time of the TOFD diffracted wave and the preset standard time interval is calculated. When the deviation is less than the preset time deviation threshold, the depth position and the height of the defect are determined as effective geometric parameters. When the deviation is greater than or equal to the preset time deviation threshold, the depth position and height of the defect are recalculated as corrected geometric parameters based on the time-series correlation characteristics. The effective geometric parameters or the corrected geometric parameters are combined with the horizontal position coordinates of the defect to generate the fused defect information, which includes the three-dimensional spatial position and size parameters of the defect. Based on the fused defect information, the depth position of the defect is compared with a preset depth safety threshold, and the height dimension of the defect is compared with a preset height safety threshold. When the depth position of the defect exceeds the preset depth safety threshold or the height dimension of the defect exceeds the preset height safety threshold, a detection result indicating that the weld quality is unqualified is generated; otherwise, a detection result indicating that the weld quality is qualified is generated.

8. A combined phased array and TOFD detection system for stainless steel welds, used to implement the method as described in any one of claims 1-7, characterized in that, include: The parameter calculation unit is used to calculate the sound wave propagation path at different depths within the weld section based on the geometric parameters and material acoustic parameters of the stainless steel weld to be inspected, and to determine the scanning parameter set of the phased array probe and the arrangement parameter set of the TOFD probe pair. The data acquisition unit is used to scan the stainless steel weld to be inspected according to the scanning parameter set, acquire phased array detection data and perform imaging processing, generate a fan-shaped scan image of the weld cross section and extract the spatial location of the defect response in the image. The defect location unit is used to scan the stainless steel weld to be inspected according to the set of arrangement parameters, obtain TOFD detection data, and calculate the depth position and height of the defect based on the arrival time difference between the upper and lower diffraction wave signals in the TOFD detection data, thereby generating defect geometric data. The signal alignment unit is used to perform time-domain synchronization alignment of the phased array detection data and the TOFD detection data to establish a dual-source signal correlation sequence under a unified time reference. The feature extraction unit is used to filter candidate signal association groups by spatially matching the spatial location of the defect response with the depth location in the defect geometric data, identify defect reflected echo and upper diffraction wave signals from the candidate signal association groups, determine the signal response pairs generated by the same defect based on the principle of minimizing the sum of the depth deviation between the reflection depth and the depth position of the upper end of the defect and the depth deviation between the diffraction depth and the depth position of the upper end of the defect, and extract the time interval between the arrival time of the reflected echo and the diffraction wave in the signal response pair as a temporal association feature. The result generation unit is used to generate fused defect information based on the defect geometric data and the temporal correlation features, and to determine the weld quality inspection result based on the fused defect information.

9. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

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