A multi-scale defect automated non-destructive testing system for ring forgings

Abstract

The application discloses a kind of multiscale defect automated nondestructive testing system for ring forging, it is related to ring forging detection field, and its technical solution main points are: data acquisition module, the crack data and position data of the ring forging to be detected are acquired, including the rotating platform of bearing and driving ring forging to rotate, the rotating platform is provided with multiple different frequency ultrasonic phased array probes on the circumferential side, the encoder is coaxially connected on the rotating platform, data processing and analysis module, the angle data of crack data and encoder are preprocessed, the crack data after processing is matched with the angle data of encoder rotation, the radial installation position of probe, the space mapping relationship is established, and image is generated, data output module, the image generated by data processing and analysis module is analyzed and processed, defect recognition and feature extraction are carried out, crack morphology parameters and spatial position information are integrated, and database is established.

Description

Technical Field

[0001] This invention relates to the field of ring forging inspection, and more specifically, to an automated non-destructive testing system for multi-scale defects in ring forgings. Background Technology

[0002] Ring forgings are ring-shaped forgings formed by ring rolling. The metal raw materials undergo multiple forging processes, causing the metal material to undergo plastic deformation under pressure, gradually forming a hollow ring structure. The internal metal structure is more dense and uniform, and the grains are refined, effectively eliminating defects such as porosity, looseness, and shrinkage cavities caused by casting, and significantly improving the overall strength, toughness, fatigue resistance, and wear resistance.

[0003] After ring forgings are formed through multiple processes such as forging, heat treatment, and machining, some ring forgings are prone to residual defects such as forging cracks, porosity, inclusions, and segregation. However, most ring forgings are used in heavy-load and high-pressure conditions. Small defects will continue to expand during long-term operation under stress, which will lead to component fracture and equipment failure. Therefore, it is necessary to inspect the ring forgings after they are processed.

[0004] The main testing methods for ring forgings include ultrasonic testing, magnetic particle testing, and penetrant testing. When using ultrasonic testing, the operator needs to select an ultrasonic probe with an appropriate frequency and specifications according to the different ring forgings. The probe is placed against the surface of the workpiece and moved smoothly along a preset trajectory. The testing instrument emits a high-frequency ultrasonic beam that penetrates the forging body. The ultrasonic waves propagate in a straight line in the medium. When they encounter internal cracks in the forging, they are reflected, refracted, and scattered. Some of the sound waves are transmitted back to the probe and converted into electrical signals, which are finally presented on the instrument display screen in the form of waveforms and images.

[0005] However, current acoustic testing generally uses a single-frequency probe. When dealing with thick-walled ring forgings, a single-frequency probe is difficult to detect defects at different depth levels. Low-frequency acoustic waves have strong penetration but insufficient resolution, making it difficult to identify fine surface cracks. High-frequency acoustic waves have high imaging accuracy but limited penetration depth, making it difficult to effectively detect deep defects in ring forgings. Consequently, operators need to change different frequency probes and perform repeated tests for multi-scale crack defects such as surface, middle, and deep cracks in ring forgings. The entire testing process is cumbersome and time-consuming, and prone to missed or false detections, reducing the efficiency and stability of non-destructive testing of ring forgings.

[0006] Therefore, in order to solve the above-mentioned technical problems, this application proposes an automated non-destructive testing system for multi-scale defects in ring forgings. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the present invention aims to provide an automated non-destructive testing system for multi-scale defects in ring forgings.

[0008] To achieve the above objectives, the present invention provides the following technical solution: an automated non-destructive testing system for multi-scale defects in ring forgings, comprising: a data acquisition module for acquiring crack data and location data of the ring forging to be tested, including a rotating platform that supports and drives the ring forging to rotate, multiple ultrasonic phased array probes of different frequencies are arranged on the periphery of the rotating platform, and an encoder is coaxially connected to the rotating platform; a data processing and analysis module that communicates with the data acquisition module to preprocess the crack data and the angle data of the encoder, match the processed crack data with the angle data of the encoder rotation and the radial installation position of the probes to establish a spatial mapping relationship, and generate an image; and a data output module that communicates with the data processing and analysis module to analyze and process the image generated by the data processing and analysis module, perform defect identification and feature extraction, integrate crack morphology parameters and spatial location information, and establish a database.

[0009] Preferably, the data acquisition module includes at least three ultrasonic phased array probes of different frequency bands to detect crack data at different scales in the ring forging. The low-frequency ultrasonic phased array probe detects deep cracks in the ring forging, the medium-frequency ultrasonic phased array probe detects mid-level cracks in the ring forging, and the high-frequency ultrasonic phased array probe detects surface cracks in the ring forging.

[0010] Preferably, the frequency range of the low-frequency ultrasonic phased array probe is 1.0 to 2.0 MHz, the frequency range of the medium-frequency ultrasonic phased array probe is 3.0 to 5.0 MHz, and the frequency range of the high-frequency ultrasonic phased array probe is 8.0 to 15.0 MHz.

[0011] Preferably, the data processing and analysis module includes a data processing submodule, a data association establishment submodule, and a data imaging submodule. The data processing submodule establishes communication with the data acquisition module, synchronously receives crack data detected by the ultrasonic phased array probe and angle data output by the encoder, and preprocesses the data through a filtering algorithm to filter out equipment vibration and electromagnetic noise interference.

[0012] Preferably, in the data association establishment submodule, the rotation center of the rotating platform is taken as the origin, the pre-processed encoder angle value is taken as the polar angle, and the radial installation position of the probe is taken as the polar diameter to establish polar coordinate parameters. The pre-processed crack data is matched with the polar coordinate parameters to establish the mapping relationship between crack data and physical spatial position.

[0013] Preferably, the data imaging submodule employs a linear mapping algorithm that converts physical coordinates to image pixels, transforming the physical polar coordinates corresponding to the ring forging crack data into image pixel coordinates. It then combines bilinear interpolation to perform pixel filling and image smoothing on the discrete crack location data, converts the crack echo amplitude into grayscale values ​​and assigns them to the corresponding pixel points, and generates a two-dimensional image of the crack location and distribution state of the ring forging through data stitching and image rendering.

[0014] Preferably, the data output module performs feature analysis and defect identification on the imaging image according to a preset crack database, extracts the morphological information of the crack in the image through an image feature extraction algorithm, integrates the extracted crack morphological information with the corresponding location information, and constructs a database containing crack features and location information.

[0015] An automated nondestructive testing method for multi-scale defects in ring forgings includes the following steps:

[0016] S1. Equipment setup: Place the ring forging to be tested on a rotating platform. Set multiple ultrasonic phased array probes around the circumference of the rotating platform and coaxially set an encoder on the rotating platform. The rotating platform carries and drives the ring forging to rotate at a constant speed.

[0017] S2. Crack data and angle data acquisition: During the rotation of the rotating platform, at least three ultrasonic phased array probes with different frequency bands arranged around the rotating platform simultaneously carry out detection. The low-frequency probe acquires deep crack data of the ring forging, the medium-frequency probe acquires mid-level crack data, and the high-frequency probe acquires surface crack data. At the same time, the coaxially connected encoder acquires the rotation angle data of the rotating platform in real time.

[0018] S3. Raw data preprocessing: The crack data collected by the probe and the angle data output by the encoder are preprocessed by a filtering algorithm to filter out noise generated by equipment vibration and electromagnetic interference, and remove invalid noise data.

[0019] S4. Establish a spatial position mapping relationship. With the rotation center of the rotating platform as the coordinate origin, the pre-processed encoder angle value is used as the polar angle and the radial installation position of the probe is used as the polar diameter. Construct a polar coordinate parameter system, match the pre-processed crack detection data with the corresponding polar coordinate parameters, and establish a precise mapping relationship between crack data and the physical spatial position of the ring forging.

[0020] S5. Crack image generation and processing: Convert the physical polar coordinates corresponding to the crack into image pixel coordinates, and perform pixel filling and image smoothing processing on the discrete crack location data. At the same time, convert the crack echo amplitude into the corresponding pixel gray value. Through data stitching and image rendering, generate a two-dimensional imaging map showing the location and distribution of cracks in the ring forging.

[0021] S6. Image Defect Recognition and Feature Extraction: Using a pre-set crack database, feature analysis and defect recognition are performed on the generated two-dimensional crack image to extract the morphological feature parameters of the crack in the image.

[0022] S7. Data integration and database construction: The extracted crack morphology feature parameters are integrated with the corresponding physical spatial location information to construct a crack detection database for ring forgings with crack features and spatial location information.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. In this invention, a rotating platform carries and drives the ring forging to rotate at a uniform speed. With the help of high, medium and low frequency probes arranged around the circumference of the rotating platform, crack detection is specifically covered in different areas of the surface, middle and deep layers of the forging. At the same time, the coaxial encoder can collect rotation angle data in real time, ensuring the continuity and synchronization of position data during the detection process, effectively reducing the occurrence of missed detections and point deviations, and improving the completeness and accuracy of defect data collection for the ring forging.

[0025] 2. In this invention, the accuracy of the original detection data is improved by preprocessing the collected crack data and angle data. By constructing a polar coordinate space system, the crack detection signal is matched with the actual physical position of the ring forging, reducing the occurrence of ambiguity in ultrasonic detection data positioning. At the same time, by generating a two-dimensional crack imaging map, the ultrasonic echo data is transformed into a visual image, which facilitates subsequent defect identification and feature extraction, thereby improving the efficiency of crack detection in ring forgings.

[0026] 3. In this invention, a pre-set crack database is used to perform intelligent feature analysis and defect identification on the generated two-dimensional crack image. Crack morphology parameters are extracted through image feature extraction algorithms. At the same time, the extracted crack morphology features and spatial location information are integrated and summarized to construct a crack detection database for ring forgings, which effectively reduces manual recording errors and improves defect identification accuracy and detection efficiency. Attached Figure Description

[0027] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0028] Figure 1 This is a diagram of the ring forging inspection system architecture of the present invention;

[0029] Figure 2 This is a flowchart of the ring forging inspection method in this invention. Detailed Implementation

[0030] like Figures 1-2As shown, this invention provides an automated non-destructive testing system for multi-scale defects in ring forgings, comprising:

[0031] The data acquisition module acquires crack data and location data of the ring forging to be tested, including a rotating platform that supports and drives the ring forging to rotate. Multiple ultrasonic phased array probes of different frequencies are set on the periphery of the rotating platform, and an encoder is coaxially connected to the rotating platform.

[0032] The data acquisition module includes three ultrasonic phased array probes at different frequency bands to detect crack data at different scales in the ring forging. The low-frequency ultrasonic phased array probe has a frequency of 1.5MHz and is used to detect deep cracks in the ring forging. The medium-frequency ultrasonic phased array probe has a frequency of 4.0MHz and is used to detect mid-level cracks in the ring forging. The high-frequency ultrasonic phased array probe has a frequency of 13.5MHz and is used to detect surface cracks in the ring forging.

[0033] Specifically, the ring forging is placed on the surface of the rotating platform and centered and fixed to ensure that the ring forging, the rotating platform, and the coaxially mounted encoder maintain coaxiality, thereby reducing the detection position deviation caused by eccentric rotation. The rotating platform rotates through a drive mechanism, which consists of a drive motor, a reducer, a transmission gear set, and a transmission shaft. The drive motor serves as the power output source, and the output speed is amplified and adjusted by the reducer. The power is then transmitted to the transmission gear set, which drives the transmission shaft to rotate synchronously through gear meshing. The transmission shaft is securely connected to the rotating platform.

[0034] After clamping, the equipment starts the automated detection program. The rotating platform carries the ring forging and rotates at a preset constant speed. The coaxial encoder rotates synchronously with the platform, continuously collecting the rotation angle data of the equipment in real time. At the same time, three sets of ultrasonic phased array probes with different frequencies arranged around the rotating platform start working simultaneously. According to the frequency band division, they complete the full coverage acquisition of multi-scale crack signals of the ring forging. Among them, the 1.5MHz low-frequency ultrasonic probe is dedicated to transmitting and receiving ultrasonic signals in the deep internal area of ​​the ring forging, capturing the echo data of deep micro cracks and buried cracks. The 4.0MHz medium-frequency ultrasonic probe focuses on the middle matrix area of ​​the ring forging, accurately collecting crack defect signals in the middle transition area. The 13.5MHz high-frequency ultrasonic probe achieves high-precision scanning of the surface area of ​​the ring forging, identifying surface micro cracks and scratches. The three sets of probes work synchronously and in parallel. During the continuous rotation of the ring forging, they comprehensively collect the original crack echo data of the entire workpiece. Simultaneously, all ultrasonic signal data and encoder real-time angle data are transmitted to the built-in data processing and analysis module of the equipment to complete the data input at the hardware end.

[0035] The data processing and analysis module communicates with the data acquisition module to preprocess the crack data and encoder angle data. It then matches the processed crack data with the encoder rotation angle data and the probe radial installation position to establish a spatial mapping relationship and generate an image.

[0036] The data processing and analysis module includes a data processing submodule, a data association establishment submodule, and a data imaging submodule;

[0037] The data processing submodule establishes communication with the data acquisition module, synchronously receiving crack data detected by the ultrasonic phased array probe and angle data output by the encoder. The data is preprocessed using a filtering algorithm to filter out noise interference from equipment vibration and electromagnetic interference.

[0038] In the data association submodule, the rotation center of the rotating platform is taken as the origin. The pre-processed encoder angle value is used as the polar angle and the radial installation position of the probe is used as the polar diameter to establish polar coordinate parameters. The pre-processed crack data is matched with the polar coordinate parameters to establish the mapping relationship between crack data and physical space position.

[0039] The data imaging submodule employs a linear mapping algorithm that converts physical coordinates to image pixels. This algorithm transforms the physical polar coordinates corresponding to the crack data of the ring forging into image pixel coordinates. Combined with bilinear interpolation, it performs pixel filling and image smoothing on the discrete crack location data. The crack echo amplitude is converted into grayscale values ​​and assigned to the corresponding pixel points. Through data stitching and image rendering, a two-dimensional image of the crack location and distribution of the ring forging is generated.

[0040] Specifically, after the data enters the data processing and analysis module, the data processing submodule completes the preprocessing and purification of the raw data. Mechanical vibration and electromagnetic interference from electrical equipment generated during the on-site operation of the equipment will cause the raw ultrasonic data to be mixed with noise. The module completes the interference filtering through a linear filtering algorithm.

[0041] The core calculation formula of the linear filtering algorithm is: In the formula This refers to the noisy raw crack data acquired by the probe. The fixed filter coefficients calibrated for the equipment. This is the pure and valid detection data after filtering out noise;

[0042] This time-domain filtering operation removes abnormal interference signals, preserves the true crack echo characteristics, and ensures the accuracy of subsequent analysis data.

[0043] After data preprocessing, the data association submodule completes the precise matching between the detection data and the physical space of the crack. The module constructs a detection space coordinate system with the rotation center of the equipment's rotating platform as the origin of the polar coordinates, and defines the rotation angle value output by the encoder in real time as the polar angle. The pre-calibrated radial installation distance of the three sets of ultrasonic probes is defined as the polar diameter. The physical spatial location of each inspection point on the ring forging is uniquely characterized by the polar coordinate system, while relying on... , The general coordinate transformation formula is used to complete the bidirectional conversion between polar coordinates and plane rectangular coordinates. Each set of preprocessed crack echo data is matched with the spatial coordinate parameters at the corresponding time, and a precise spatial mapping relationship between the ultrasonic detection signal and the physical position of the crack entity is established, reducing the occurrence of inaccurate defect location during dynamic rotation detection.

[0044] After spatial mapping and matching are completed, the data imaging submodule initiates image generation operations, relying on a linear mapping algorithm from physical coordinates to image pixels to complete the coordinate transformation, using the formula... Achieve accurate conversion from physical coordinates to image pixel coordinates, whereby... To inspect the physical coordinate values ​​of the ring forging, For the corresponding image pixel coordinates, This is a scaling factor calibrated based on the equipment's detection range and image resolution. The coordinate offset is used to accurately correspond the physical detection points on the ring forging to the pixel points on the imaging interface. For discrete crack data generated by intermittent acquisition of equipment, the system calls the existing bilinear interpolation algorithm to fill the pixel gaps and smooth the image.

[0045] The bilinear interpolation algorithm first extracts the coordinates and corresponding gray values ​​of all valid crack feature pixels, mapping the discrete data into a two-dimensional pixel grid. Positions within the grid where no data was collected form pixel gaps. Then, based on the principle of bilinear interpolation, gap filling and image smoothing are performed. Let any coordinate to be solved in the two-dimensional pixel grid be... Take the four nearest known valid pixels in its vicinity, and record their coordinates as follows: , , , The corresponding pixel grayscale values ​​are respectively , , , ,exist Linear interpolation is performed on the two horizontal pixel rows respectively to obtain the intermediate transition grayscale value. and Based on the two transition values, a quadratic linear interpolation is performed in the y-direction to calculate the gray value of the point to be determined. Repeat the above calculations for all discrete gap positions within the grid, gradually filling in all missing pixels. By relying on the weighted fusion of gray levels of four adjacent points, pixel breaks caused by the acquisition interval are eliminated, and the continuous reconstruction and overall smoothing of the crack image are realized simultaneously. This allows the discretely distributed crack features to form a coherent and naturally transitioning visual form, effectively reducing the jagged edges and breaks caused by dynamic scanning imaging, and improving image continuity and clarity.

[0046] Simultaneously, through the linear grayscale transformation formula The conversion from signal to image is completed, where... This represents the real-time crack echo amplitude. and The grayscale values ​​in the 0-255 range are directly assigned to the corresponding pixels based on the pre-calibrated echo amplitude limit parameters of the equipment. Through multi-probe data stitching and full-domain image rendering, a two-dimensional high-definition imaging image that can fully present the specific location and distribution of cracks in the ring forging is generated, completing the transformation from raw detection data to visualized defect images.

[0047] The data output module communicates with the data processing and analysis module to analyze and process the images generated by the data processing and analysis module, perform defect identification and feature extraction, integrate crack morphology parameters and spatial location information, and establish a database.

[0048] In the data output module, feature analysis and defect identification are performed on the imaging image based on the preset crack database. The morphological information of the crack in the image is extracted by the image feature extraction algorithm. The extracted crack morphological information is integrated with the corresponding location information to construct a database containing crack features and location information.

[0049] Specifically, the visualized imaging results are synchronously transmitted to the device's data output module. The module calls mature image feature extraction, edge detection, and morphological operation algorithms in the field of machine vision to automatically analyze the defect features in the imaging image. The algorithm extracts the initial contour of the crack through the Canny edge detection operator, uses morphological closing operation to connect the fracture edges and fill the small holes, and then combines adaptive threshold segmentation to obtain a binary mask of the crack, thereby achieving accurate separation of the crack from the background.

[0050] Meanwhile, the algorithm performs skeletonization processing on the mask, refining the crack area into skeleton lines of single-pixel width through repeated morphological erosion, and calculating the cumulative pixel length along the skeleton path, which is then converted into physical length by combining pixel equivalent.

[0051] The crack area is obtained by counting the total number of non-zero pixels in the mask, and the average width is obtained by dividing the area by the length. The maximum width and width distribution can be obtained by scanning the intersection points with the edge along the skeleton normal direction. For the crack direction, the algorithm calculates the minimum bounding rectangle of the skeleton and uses the major axis direction angle to represent the overall direction. By performing topological analysis on the branch points on the skeleton, the crack is automatically classified into linear, Y-shaped, X-shaped or mesh-like morphological types.

[0052] The extracted morphological feature parameters are associated with the precise spatial location information matched in the early stage. The crack profile is mapped to the actual physical coordinate system of the workpiece through coordinate transformation, so as to realize the integrated data integration of crack morphological features and physical location.

[0053] The integrated multi-dimensional defect data is then compared and analyzed with the equipment's built-in preset crack standard database. Based on quantitative indicators such as length, width, and direction, and standard grading thresholds, the defects are automatically classified, identified, and judged. The crack characteristic parameters and spatial location data are uniformly organized and entered into the equipment's local database for archiving and storage, facilitating subsequent data traceability, re-inspection and comparison, and workpiece quality analysis.

[0054] Working principle: S1. Equipment setup: Place the ring forging to be tested on a rotating platform. Set multiple ultrasonic phased array probes around the circumference of the rotating platform and set an encoder coaxially on the rotating platform. The rotating platform carries and drives the ring forging to rotate at a constant speed.

[0055] S2. Crack data and angle data acquisition: During the rotation of the rotating platform, at least three ultrasonic phased array probes with different frequency bands arranged around the rotating platform simultaneously carry out detection. The low-frequency probe acquires deep crack data of the ring forging, the medium-frequency probe acquires mid-level crack data, and the high-frequency probe acquires surface crack data. At the same time, the coaxially connected encoder acquires the rotation angle data of the rotating platform in real time.

[0056] S3. Raw data preprocessing: The crack data collected by the probe and the angle data output by the encoder are preprocessed by a filtering algorithm to filter out noise generated by equipment vibration and electromagnetic interference, and remove invalid noise data.

[0057] S4. Establish a spatial position mapping relationship. With the rotation center of the rotating platform as the coordinate origin, the pre-processed encoder angle value is used as the polar angle and the radial installation position of the probe is used as the polar diameter. Construct a polar coordinate parameter system, match the pre-processed crack detection data with the corresponding polar coordinate parameters, and establish a precise mapping relationship between crack data and the physical spatial position of the ring forging.

[0058] S5. Crack image generation and processing: Convert the physical polar coordinates corresponding to the crack into image pixel coordinates, and perform pixel filling and image smoothing processing on the discrete crack location data. At the same time, convert the crack echo amplitude into the corresponding pixel gray value. Through data stitching and image rendering, generate a two-dimensional imaging map showing the location and distribution of cracks in the ring forging.

[0059] S6. Image Defect Recognition and Feature Extraction: Using a pre-set crack database, feature analysis and defect recognition are performed on the generated two-dimensional crack image to extract the morphological feature parameters of the crack in the image.

[0060] S7. Data integration and database construction: The extracted crack morphology feature parameters are integrated with the corresponding physical spatial location information to construct a crack detection database for ring forgings with crack features and spatial location information.

[0061] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Anyone skilled in the art can readily implement the invention based on the accompanying drawings and the description above. However, any modifications, alterations, or variations made by those skilled in the art without departing from the scope of the present invention, using the disclosed technical content, are equivalent embodiments of the present invention. Furthermore, any modifications, alterations, or variations made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the present invention.

Claims

1. An automated non-destructive testing system for multi-scale defects in ring forgings, characterized in that, include: The data acquisition module acquires crack data and location data of the ring forging to be tested, including a rotating platform that supports and drives the ring forging to rotate. Multiple ultrasonic phased array probes of different frequencies are set on the periphery of the rotating platform, and an encoder is coaxially connected to the rotating platform. The data processing and analysis module communicates with the data acquisition module to preprocess the crack data and encoder angle data. It then matches the processed crack data with the encoder rotation angle data and the probe radial installation position to establish a spatial mapping relationship and generate an image. The data output module communicates with the data processing and analysis module to analyze and process the images generated by the data processing and analysis module, perform defect identification and feature extraction, integrate crack morphology parameters and spatial location information, and establish a database.

2. The automated non-destructive testing system for multi-scale defects in ring forgings according to claim 1, characterized in that: The data acquisition module includes at least three ultrasonic phased array probes of different frequency bands to detect crack data at different scales in the ring forging. The low-frequency ultrasonic phased array probe detects deep cracks in the ring forging, the medium-frequency ultrasonic phased array probe detects mid-level cracks in the ring forging, and the high-frequency ultrasonic phased array probe detects surface cracks in the ring forging.

3. The automated non-destructive testing system for multi-scale defects in ring forgings according to claim 2, characterized in that: The frequency range of the low-frequency ultrasonic phased array probe is 1.0 to 2.0 MHz, the frequency range of the medium-frequency ultrasonic phased array probe is 3.0 to 5.0 MHz, and the frequency range of the high-frequency ultrasonic phased array probe is 8.0 to 15.0 MHz.

4. The automated non-destructive testing system for multi-scale defects in ring forgings according to claim 1, characterized in that: The data processing and analysis module includes a data processing submodule, a data association establishment submodule, and a data imaging submodule; The data processing submodule establishes communication with the data acquisition module, synchronously receiving crack data detected by the ultrasonic phased array probe and angle data output by the encoder. The data is preprocessed using a filtering algorithm to filter out noise interference from equipment vibration and electromagnetic interference.

5. The automated non-destructive testing system for multi-scale defects in ring forgings according to claim 4, characterized in that: In the data association submodule, the rotation center of the rotating platform is taken as the origin. The pre-processed encoder angle value is used as the polar angle and the radial installation position of the probe is used as the polar diameter to establish polar coordinate parameters. The pre-processed crack data is matched with the polar coordinate parameters to establish the mapping relationship between crack data and physical spatial position.

6. The automated non-destructive testing system for multi-scale defects in ring forgings according to claim 5, characterized in that: The data imaging submodule employs a linear mapping algorithm that converts physical coordinates to image pixels. This algorithm transforms the physical polar coordinates corresponding to the crack data of the ring forging into image pixel coordinates. Combined with bilinear interpolation, it performs pixel filling and image smoothing on the discrete crack location data. The crack echo amplitude is converted into grayscale values ​​and assigned to the corresponding pixel points. Through data stitching and image rendering, a two-dimensional image of the crack location and distribution state of the ring forging is generated.

7. The automated non-destructive testing system for multi-scale defects in ring forgings according to claim 1, characterized in that: The data output module performs feature analysis and defect identification on the imaging image based on a preset crack database. It extracts the morphological information of the crack in the image through an image feature extraction algorithm, integrates the extracted crack morphological information with the corresponding location information, and constructs a database containing crack features and location information.

8. An automated non-destructive testing method for multi-scale defects in ring forgings, and an automated non-destructive testing system for multi-scale defects in ring forgings according to any one of claims 1-7, characterized in that: Includes the following steps: S1. Equipment setup: Place the ring forging to be tested on a rotating platform. Set multiple ultrasonic phased array probes around the circumference of the rotating platform and coaxially set an encoder on the rotating platform. The rotating platform carries and drives the ring forging to rotate at a constant speed. S2. Crack data and angle data acquisition: During the rotation of the rotating platform, at least three ultrasonic phased array probes with different frequency bands arranged around the rotating platform simultaneously carry out detection. The low-frequency probe acquires deep crack data of the ring forging, the medium-frequency probe acquires mid-level crack data, and the high-frequency probe acquires surface crack data. At the same time, the coaxially connected encoder acquires the rotation angle data of the rotating platform in real time. S3. Raw data preprocessing: The crack data collected by the probe and the angle data output by the encoder are preprocessed by a filtering algorithm to filter out noise generated by equipment vibration and electromagnetic interference, and remove invalid noise data. S4. Establish a spatial position mapping relationship. With the rotation center of the rotating platform as the coordinate origin, the pre-processed encoder angle value is used as the polar angle and the radial installation position of the probe is used as the polar diameter. Construct a polar coordinate parameter system, match the pre-processed crack detection data with the corresponding polar coordinate parameters, and establish a precise mapping relationship between crack data and the physical spatial position of the ring forging. S5. Crack image generation and processing: Convert the physical polar coordinates corresponding to the crack into image pixel coordinates, and perform pixel filling and image smoothing processing on the discrete crack location data. At the same time, convert the crack echo amplitude into the corresponding pixel gray value. Through data stitching and image rendering, generate a two-dimensional imaging map showing the location and distribution of cracks in the ring forging. S6. Image Defect Recognition and Feature Extraction: Using a pre-set crack database, feature analysis and defect recognition are performed on the generated two-dimensional crack image to extract the morphological feature parameters of the crack in the image. S7. Data integration and database construction: The extracted crack morphology feature parameters are integrated with the corresponding physical spatial location information to construct a crack detection database for ring forgings with crack features and spatial location information.

Images