Ultrasonic phased array aluminum rod internal defect depth detection system, equipment and medium based on sound velocity compensation

Abstract

The application provides an ultrasonic phased array aluminum rod internal defect depth detection system and device based on sound velocity compensation, and a medium, and relates to the technical field of nondestructive testing, and comprises: an acquisition module configured to scan an aluminum rod moving at a constant speed through a detection station by using a ring-shaped ultrasonic phased array probe group to obtain an original ultrasonic reflection signal inside the aluminum rod; and a construction module configured to, based on the original ultrasonic reflection signal, simultaneously collect temperature measurement values of different sections of the aluminum rod by using an inlet side reference temperature sensor, an outlet side reference temperature sensor and a lateral compensation temperature sensor arranged at the aluminum rod detection station, and construct a closed reference area on the aluminum rod section according to the positions of the sensors. The application realizes high-precision detection of the internal defect depth of the aluminum rod.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology, and in particular to a system, equipment and medium for detecting the depth of internal defects in aluminum rods based on sound velocity compensation using ultrasonic phased array. Background Technology

[0002] In the field of high-end equipment such as rail transit, aluminum alloy bars are the core raw materials for key load-bearing structural components. The accurate detection of the depth of defects such as internal shrinkage cavities, inclusions, and cracks is directly related to the safety and reliability of the end products. Ultrasonic phased array technology has become the mainstream solution for aluminum bar defect detection due to its advantages of full coverage of electronic scanning and high detection efficiency. However, aluminum bars often carry significant residual heat after hot rolling, extrusion and other processes, and there are obvious temperature gradients between the center and edge of the cross section and between the inlet and outlet. The sound velocity of aluminum material changes significantly linearly with temperature. This characteristic can easily lead to deviations in the calculation of defect depth.

[0003] A supplier of aluminum bars for a high-speed railway bogie once used a traditional ring-shaped ultrasonic phased array testing system to inspect aluminum alloy bars. When the aluminum bars passed through the inspection station at a constant speed while still carrying residual heat, the system only calibrated the sound velocity based on the temperature of a single point in the inspection environment, without considering the temperature differences within the aluminum bar's cross-section. This led to a misjudgment of a shrinkage cavity defect with a shallow actual depth, which was only discovered after magnetic particle re-inspection. The core technical flaw lies in the fact that the traditional system lacks a precise perception and compensation mechanism for the temperature field distribution of the aluminum bar's cross-section. Relying solely on a single temperature parameter to correct the sound velocity cannot match the differences in the propagation speed of ultrasonic waves in different temperature regions. This results in a deviation in the time-depth conversion of the defect reflection signal, ultimately affecting the accuracy of depth detection and making it difficult to meet the high-precision quality control requirements of high-end equipment for aluminum bars. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a system, equipment and medium for detecting the depth of internal defects in aluminum rods based on sound velocity compensation, so as to achieve high-precision detection of the depth of internal defects in aluminum rods.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0006] Firstly, a sound velocity-compensated ultrasonic phased array aluminum rod internal defect depth detection system includes:

[0007] The acquisition module is used to scan the aluminum rod passing through the detection station at a constant speed using a ring ultrasonic phased array probe group to obtain the original ultrasonic reflection signal inside the aluminum rod.

[0008] The module is used to collect temperature measurements of different cross sections of the aluminum rod based on the original ultrasonic reflection signal, and simultaneously through the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor set at the aluminum rod detection station, and to construct a closed reference area on the cross section of the aluminum rod according to the position of each sensor.

[0009] The calibration module is used to divide the closed reference area into sub-regions, so that each sub-region corresponds to the monitoring coverage of a temperature sensor; determine the temperature adjustment coefficient according to the physical characteristics of each sub-region; and compensate and calibrate each temperature measurement value through the temperature adjustment coefficient to obtain the calibrated temperature distribution characteristics on the cross-section of the aluminum rod.

[0010] The correction module is used to dynamically correct the propagation speed of ultrasonic waves in aluminum rod material based on the temperature distribution characteristics after calibration and by applying a sound velocity compensation algorithm to obtain the corrected sound velocity parameters.

[0011] The separation module is used to analyze the original ultrasonic reflection signal based on the corrected ultrasonic propagation velocity parameters to obtain the separated individual defect reflection signals;

[0012] The processing module is used to process the separated individual defect reflection signals. It locates the boundary points of the defect reflection signals through edge detection, and then performs polygon fitting on the boundary points to form the geometric contour of the defect, defining the boundary positions of various defects to obtain the defect depth detection results.

[0013] Furthermore, the aluminum rod passing through the detection station at a constant speed is scanned using a ring-shaped ultrasonic phased array probe array to obtain the original ultrasonic reflection signal inside the aluminum rod, including:

[0014] The ring-shaped ultrasonic phased array probe group is fixed in a circular manner at the testing station to ensure that the central axis is precisely aligned with the transport trajectory of the aluminum rod, so as to establish a stable scanning reference.

[0015] Based on the scanning reference, when the aluminum rod passes by at a constant speed, the probe group is driven to perform a full-coverage ultrasonic scan on the moving aluminum rod according to the preset excitation timing and focusing rules.

[0016] Triggered by ultrasonic scanning, the ring ultrasonic phased array probe group synchronously receives ultrasonic echo signals from the internal interface and defects of the aluminum rod to obtain the original ultrasonic reflection signal.

[0017] Furthermore, based on the original ultrasonic reflection signal, temperature measurements of different cross-sections of the aluminum rod are simultaneously collected using an inlet-side reference temperature sensor, an outlet-side reference temperature sensor, and a lateral compensation temperature sensor located at the aluminum rod inspection station. A closed reference region is then constructed on the aluminum rod cross-section according to the location of each sensor, including:

[0018] Based on the original ultrasonic reflection signal, the temperature measurement values ​​of the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor are acquired simultaneously.

[0019] Based on all the collected temperature measurements and the corresponding sensor locations, a closed reference region connecting the sensor locations is constructed according to the spatial distribution of the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor across the aluminum rod cross section.

[0020] Furthermore, by dividing the closed reference area into sub-regions, each sub-region corresponds to the monitoring coverage of a temperature sensor; a temperature adjustment coefficient is determined based on the physical characteristics of each sub-region; and the temperature measurements are compensated and calibrated using the temperature adjustment coefficient to obtain the calibrated temperature distribution characteristics on the cross-section of the aluminum rod, including:

[0021] Based on the constructed closed reference region, the region is divided into sub-regions using the Voronoi diagram construction algorithm, so that each sub-region uniquely corresponds to the monitoring coverage of a temperature sensor.

[0022] Based on the divided sub-regions, the temperature adjustment coefficients corresponding to each sub-region are determined according to the physical characteristics of each sub-region relative to the center of the aluminum rod, surface condition, and airflow environment.

[0023] Based on the temperature adjustment coefficient, the original temperature measurements obtained by each temperature sensor are weighted and compensated for calibration, thereby generating the calibrated temperature distribution characteristics across the entire cross-section of the aluminum rod.

[0024] Furthermore, the feature is that, based on the constructed closed reference region, the closed reference region is divided into sub-regions using a Voronoi diagram construction algorithm, so that each sub-region uniquely corresponds to the monitoring coverage area of ​​a temperature sensor, including:

[0025] Based on the constructed closed reference region, the position coordinates of the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor within the region boundary are extracted to obtain the initial set of sensor position coordinates.

[0026] For every two sensor locations in the initial point set, calculate the perpendicular bisector of the line segment connecting the two sensor locations. The perpendicular bisectors intersect within the closed reference region, forming a network of perpendicular bisectors consisting of multiple intersection points.

[0027] Based on the vertical bisector network, for each sensor location point, all associated vertical bisectors are determined. The minimum closed region formed by the vertical bisectors around the sensor location point in space is obtained, thus yielding the initial Voronoi polygon corresponding to the sensor.

[0028] Based on the initial Voronoi polygons, each initial Voronoi polygon is spatially compared with the closed reference region. The polygon parts located outside the closed reference region are removed by boundary clipping to obtain the clipped polygon set.

[0029] Based on the cropped polygon set, each retained polygon region is determined as the final sub-region, thereby achieving a unique monitoring coverage area for each sub-region corresponding to a temperature sensor.

[0030] Furthermore, based on the calibrated temperature distribution characteristics, a sound velocity compensation algorithm is applied to dynamically correct the propagation velocity of ultrasound in the aluminum rod material, obtaining the corrected sound velocity parameters, including:

[0031] Based on the calibrated temperature distribution characteristics on the cross section of the aluminum rod, the pre-stored correspondence between the sound velocity and temperature characteristics of the aluminum material is invoked, and the temperature distribution characteristics are converted into corresponding sound velocity distribution data through a sound velocity compensation algorithm.

[0032] Based on sound velocity distribution data, and according to the propagation path characteristics of ultrasound in aluminum rods, the propagation velocity of ultrasound in aluminum rod materials is dynamically calculated and corrected to obtain corrected sound velocity parameters that match the current temperature field of the aluminum rod cross section.

[0033] Furthermore, the original ultrasonic reflection signal is analyzed based on the corrected ultrasonic propagation velocity parameters to obtain the separated individual defect reflection signals, including:

[0034] Based on the corrected sound velocity parameters, the original ultrasonic reflection signal is subjected to time-depth conversion and signal analysis processing to recalculate the propagation path and reflection interface position of the ultrasonic wave.

[0035] Based on the recalculated reflection interface position, when a composite defect feature is identified where reflection signals from different defects are superimposed in the time or spatial domain, the superimposed reflection signals are separated to obtain the separation result.

[0036] Based on the results of the separation process, the separated reflection signal corresponding to a single physical defect inside the aluminum rod is obtained.

[0037] Furthermore, the separated individual defect reflection signals are processed. Edge detection is used to locate the boundary points of the defect reflection signals, and then polygon fitting is performed on these boundary points to form the geometric contour of the defect. This defines the boundary positions of various defects to obtain the defect depth detection results, including:

[0038] Based on the separated individual defect reflection signals, the shape contour extraction algorithm is used for processing. First, edge detection technology is applied to locate the boundary point set of the defect reflection signal.

[0039] Based on the localized boundary point set, polygon fitting is performed on the boundary points to obtain a geometric contour that accurately describes the shape of the defect.

[0040] Based on the geometric profile and the corrected sound velocity parameters, the depth distance between the upper and lower boundaries of the profile and the surface of the aluminum rod is calculated. Based on this, the boundary positions and burial depths of various defects are defined, and the defect depth detection results are finally obtained.

[0041] In a second aspect, a computing device includes:

[0042] One or more processors;

[0043] A storage device for storing one or more programs that, when executed by one or more processors, cause the one or more processors to execute the system.

[0044] Thirdly, a computer-readable storage medium storing a program that, when executed by a processor, performs the system.

[0045] The above-described solution of the present invention has at least the following beneficial effects:

[0046] This invention employs a ring-shaped ultrasonic phased array full-coverage scanning method to acquire the original ultrasonic reflection signal, simultaneously collects the cross-sectional temperature of the aluminum rod using multiple sensors and constructs a closed reference region, divides the corresponding sub-regions of the sensors using the Voronoi diagram algorithm and determines the temperature adjustment coefficient based on the physical characteristics of the sub-regions to achieve precise temperature field calibration, dynamically corrects the ultrasonic propagation speed based on the calibrated temperature distribution using a sound velocity compensation algorithm, performs time-depth conversion on the original signal and separates the composite defect signal, and extracts the geometric contour of the defect and calculates the depth through edge detection and polygon fitting. This overcomes the technical problems of traditional ultrasonic phased array detection systems that rely solely on a single temperature parameter to correct the sound velocity, lack precise perception and compensation of the temperature field distribution of the aluminum rod cross-section, and suffer from sound velocity deviation and defect signal superposition interference caused by temperature gradient, resulting in large error in defect depth detection. Ultimately, it achieves high-precision detection of the internal defect depth of the aluminum rod, improves the accuracy and reliability of defect identification, and is adaptable to continuous aluminum rod production conditions, meeting the quality control requirements of aluminum rods for high-end equipment. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of an ultrasonic phased array aluminum rod internal defect depth detection system based on sound velocity compensation provided in an embodiment of the present invention.

[0048] Figure 2This is a schematic diagram of the process of the present invention, which is based on a constructed closed reference region and uses a Voronoi diagram construction algorithm to divide the closed reference region into sub-regions, so that each sub-region uniquely corresponds to the monitoring coverage area of ​​a temperature sensor.

[0049] Figure 3 This is a schematic diagram of a computing device according to the present invention. Detailed Implementation

[0050] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0051] like Figure 1 As shown, embodiments of the present invention propose a sound velocity-compensated ultrasonic phased array aluminum rod internal defect depth detection system, comprising:

[0052] The acquisition module is used to scan the aluminum rod passing through the detection station at a constant speed using a ring ultrasonic phased array probe group to obtain the original ultrasonic reflection signal inside the aluminum rod.

[0053] The module is used to collect temperature measurements of different cross sections of the aluminum rod based on the original ultrasonic reflection signal, and simultaneously through the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor set at the aluminum rod detection station, and to construct a closed reference area on the cross section of the aluminum rod according to the position of each sensor.

[0054] The calibration module is used to divide the closed reference area into sub-regions, so that each sub-region corresponds to the monitoring coverage of a temperature sensor; determine the temperature adjustment coefficient according to the physical characteristics of each sub-region; and compensate and calibrate each temperature measurement value through the temperature adjustment coefficient to obtain the calibrated temperature distribution characteristics on the cross-section of the aluminum rod.

[0055] The correction module is used to dynamically correct the propagation speed of ultrasonic waves in aluminum rod material based on the temperature distribution characteristics after calibration and by applying a sound velocity compensation algorithm to obtain the corrected sound velocity parameters.

[0056] The separation module is used to analyze the original ultrasonic reflection signal based on the corrected ultrasonic propagation velocity parameters to obtain the separated individual defect reflection signals;

[0057] The processing module is used to process the separated individual defect reflection signals. It locates the boundary points of the defect reflection signals through edge detection, and then performs polygon fitting on the boundary points to form the geometric contour of the defect, defining the boundary positions of various defects to obtain the defect depth detection results.

[0058] In this embodiment of the invention, the invention overcomes the technical problems of lacking accurate perception and compensation of the temperature field of the aluminum rod cross section, sound velocity deviation caused by relying solely on a single temperature parameter to correct the sound velocity, and large detection errors caused by defect signal interference. This is achieved by using a ring ultrasonic phased array probe group to scan and obtain the original ultrasonic reflection signal inside the aluminum rod, multiple temperature sensors to simultaneously collect temperature and construct a closed reference area for the aluminum rod cross section, achieving accurate temperature field calibration through sub-region division and temperature adjustment coefficient, realizing accurate temperature field calibration through sub-region division and temperature adjustment coefficient, dynamically correcting the ultrasonic propagation speed based on the calibrated temperature distribution, analyzing and separating the reflection signal of a single defect based on the corrected sound velocity, and defining the defect boundary and depth through edge detection and polygon fitting. As a result, the invention achieves accurate detection of the depth of defects inside the aluminum rod, improves detection accuracy and reliability, adapts to continuous production detection conditions of aluminum rods, and meets the technical effect of meeting the quality control requirements of aluminum rods for high-end equipment.

[0059] In a preferred embodiment of the present invention, an aluminum rod passing through the detection station at a constant speed is scanned using a ring-shaped ultrasonic phased array probe group to obtain the original ultrasonic reflection signal inside the aluminum rod, including:

[0060] A ring-shaped ultrasonic phased array probe assembly is fixed to the inspection station in a circular manner, ensuring precise alignment of its central axis with the aluminum rod's transport trajectory to establish a stable scanning reference. Specifically, addressing the issue of signal acquisition deviations caused by unstable scanning references in traditional inspection methods, which affect the accuracy of defect depth detection, a dedicated mounting bracket adapted to the ring-shaped ultrasonic phased array probe assembly is first constructed in the pre-set installation area of ​​the inspection station. This bracket, made of high-strength, wear-resistant material, effectively prevents probe position shifts due to vibration during inspection. The entire ring-shaped ultrasonic phased array probe assembly is then embedded into the annular mounting groove of the bracket, forming a complete ring structure and ensuring that the inner circumference of the probe assembly remains concentric with the aluminum rod's transport path. Subsequently, a laser positioning instrument and a high-precision level are used to adjust the spatial attitude of the probe assembly. By fine-tuning the height and level of the bracket, as well as the installation angle of the probe assembly within the bracket, the central axis of the probe assembly is gradually calibrated until it completely coincides with the pre-set transport trajectory of the aluminum rod. Multiple tests are conducted during the calibration process using simulated aluminum rod transport to verify this alignment, ensuring the probe assembly maintains precise alignment with the aluminum rod's transport trajectory throughout the entire inspection process, ultimately establishing a stable and reliable scanning reference.

[0061] Based on the scanning reference, as the aluminum rod passes by at a constant speed, the probe assembly is driven to perform a full-coverage ultrasonic scan of the moving aluminum rod according to the preset excitation timing and focusing rules. Specifically, this includes: optimizing the ultrasonic scanning parameters in advance based on the actual cross-sectional diameter, length specifications, and preset uniform conveying speed of the aluminum alloy rod under test; determining the coverage angle and focusing depth of the ultrasonic beam according to the cross-sectional dimensions of the aluminum rod; and developing corresponding excitation timing sequences for the detection needs of different positions on the aluminum rod to ensure that each element of the probe assembly is activated sequentially in a reasonable order, avoiding signal interference between elements; and simultaneously, based on the acoustic properties of the aluminum material... Based on the characteristics and potential defect types, a suitable focusing law is set to enable the ultrasonic beam to form a precise focus inside the aluminum rod, improving the detection capability of minute defects. When the aluminum rod passes smoothly through the inspection station at a constant speed, the position signal of the aluminum rod is acquired in real time. According to the preset excitation sequence and focusing law, all array elements of the ring ultrasonic phased array probe group are driven to work together, so that the ultrasonic beam is continuously emitted from different angles and covers the entire circumference of the aluminum rod. At the same time, as the aluminum rod is transported, the beam gradually scans along the length of the aluminum rod, realizing a blind-spot-free full-coverage ultrasonic scan of all areas inside the moving aluminum rod.

[0062] Triggered by ultrasonic scanning, the ring-shaped ultrasonic phased array probe group synchronously receives ultrasonic echo signals from the internal interface and defects of the aluminum rod to obtain the original ultrasonic reflection signals. Specifically, this addresses the problem of lost or distorted defect information caused by the asynchronous ultrasonic scanning and signal reception in traditional methods by employing a scanning and reception linkage control mechanism. At the instant the ultrasonic scanning signal is triggered, a start command is simultaneously sent to the ring-shaped ultrasonic phased array probe group to ensure strict timing synchronization with the scanning action. Each element of the probe group switches to signal reception mode in real time while emitting ultrasonic beams, continuously capturing ultrasonic echo signals returning from inside the aluminum rod. These echo signals include not only reflection signals from normal interfaces within the aluminum rod but also reflection signals from potential defects such as shrinkage cavities, inclusions, and cracks. All captured echo signals are classified and recorded according to the reception order and element number. Preliminary filtering is performed to remove noise signals generated by environmental interference, ensuring that the recorded signals accurately reflect the structural characteristics and defect conditions inside the aluminum rod. Through this synchronous reception method, the original ultrasonic reflection signals containing comprehensive information about the interior of the aluminum rod are fully acquired.

[0063] In this embodiment of the invention, by fixing the ring-shaped ultrasonic phased array probe group in a circular manner at the detection station and precisely aligning the central axis with the aluminum rod transport trajectory to establish a stable scanning reference, and then performing a full-coverage ultrasonic scan on the aluminum rod passing at a uniform speed based on the reference according to the preset excitation sequence and focusing rule, while simultaneously receiving ultrasonic echo signals of the internal interface and defects of the aluminum rod, the technical problems of reference offset, incomplete scanning coverage or asynchronous signal reception in traditional ultrasonic scanning, which lead to interference in the original ultrasonic reflection signal and incomplete capture of defect information, are overcome. This ensures the authenticity and integrity of the original ultrasonic reflection signal.

[0064] In a preferred embodiment of the present invention, based on the original ultrasonic reflection signal, temperature measurements of different cross-sections of the aluminum rod are simultaneously collected by an inlet-side reference temperature sensor, an outlet-side reference temperature sensor, and a lateral compensation temperature sensor located at the aluminum rod detection station. A closed reference region is then constructed on the cross-section of the aluminum rod according to the location of each sensor, including:

[0065] Based on the original ultrasonic reflection signal, temperature measurements from the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor are simultaneously acquired. Specifically, the inlet-side reference temperature sensor is first installed near the front section of the aluminum rod entering the testing station, close to the surface of the aluminum rod without affecting its transport. The outlet-side reference temperature sensor is installed near the rear section of the aluminum rod leaving the testing station, axially symmetrically distributed with the inlet-side sensor. The lateral compensation temperature sensor is installed on the circumferential side of the aluminum rod in the middle of the testing station, ensuring that the three sensors cover different sections and positions of the aluminum rod. Once the ultrasonic scan is started and the original ultrasonic reflection signal is acquired... During ultrasonic reflection, acquisition commands are sent synchronously to three temperature sensors to ensure strict timing synchronization between the sensors and the ultrasonic scanning action, capturing the temperature data of the aluminum rod at its respective monitoring position in real time. Throughout the process of the aluminum rod passing through the inspection station at a constant speed, the sensors continuously acquire temperature measurements at fixed time intervals. Each set of temperature data is correlated and matched with the corresponding original ultrasonic reflection signal through a timestamp, ensuring that the temperature acquisition and ultrasonic detection are completely consistent in the time dimension. This avoids the problem of temperature data not matching the defect signal due to timing deviation. At the same time, temperature information of different cross sections of the aluminum rod is comprehensively obtained through multi-position sensor acquisition.

[0066] Based on all collected temperature measurements and their corresponding sensor locations, a closed reference region connecting the sensor locations is constructed according to the spatial distribution of the inlet-side reference temperature sensor, outlet-side reference temperature sensor, and lateral compensation temperature sensor across the aluminum rod cross-section. Specifically, this involves: first, precisely calibrating the installation positions of the three sensors; second, using a laser rangefinder and coordinate positioning tools, determining the specific spatial coordinates of the inlet-side reference temperature sensor, outlet-side reference temperature sensor, and lateral compensation temperature sensor across the aluminum rod cross-section, clarifying the positional relationship of each sensor relative to the center and surface of the aluminum rod; third, organizing all collected temperature measurements and binding each temperature data point to its corresponding sensor spatial coordinates to form a correlated dataset containing both temperature and position information; fourth, based on the dataset and the spatial distribution characteristics of the three sensors across the aluminum rod cross-section, using the sensor coordinates as key nodes and a connection method adapted to the shape of the aluminum rod cross-section, sequentially connecting the inlet-side sensor location, the lateral compensation sensor location, and the outlet-side sensor location, then returning to the inlet-side sensor location, thus constructing a complete closed reference region. This closed reference region accurately covers the main temperature monitoring range of the aluminum rod detection cross-section, ensuring that each temperature measurement value clearly corresponds to a specific location within the region.

[0067] In this embodiment of the invention, by employing a technique that simultaneously acquires temperature measurements from the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor based on the original ultrasonic reflection signal, and then combining all acquired temperature measurements with the corresponding sensor positions, and constructing a closed reference region by connecting the sensor positions according to the spatial distribution of each sensor across the aluminum rod cross section, the technical problems of traditional detection relying solely on a single temperature parameter, failing to accurately capture the temperature distribution differences across the aluminum rod cross section, and having asynchronous temperature acquisition and ultrasonic detection leading to a lack of specificity and completeness in temperature data are overcome. This achieves the technical effect of comprehensively and synchronously acquiring the temperatures of different cross sections of the aluminum rod, establishing a precise correspondence between temperature measurements and the positions of the aluminum rod cross sections, and improving the reliability of temperature sensing.

[0068] In a preferred embodiment of the present invention, the closed reference region is divided into sub-regions, so that each sub-region corresponds to the monitoring coverage of a temperature sensor; a temperature adjustment coefficient is determined according to the physical characteristics of each sub-region; and the temperature measurement values ​​are compensated and calibrated using the temperature adjustment coefficient to obtain the calibrated temperature distribution characteristics on the cross-section of the aluminum rod, including:

[0069] Based on the constructed closed reference region, the region is divided into sub-regions using a Voronoi diagram construction algorithm, ensuring that each sub-region uniquely corresponds to the monitoring coverage of a single temperature sensor. Specifically, this involves: first, extracting the boundary coordinates of the closed reference region, as well as the specific location coordinates of the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor within the region, thus clarifying the spatial location of each sensor. Based on this coordinate data, the Voronoi diagram construction algorithm is used to calculate the perpendicular bisectors of the line segments between every two sensor locations. These perpendicular bisectors intersect within the closed reference region, forming a uniformly distributed network. Then, based on this network, with each sensor location as the core, all relevant perpendicular bisectors surrounding that location are determined, forming an initial closed polygon. Next, each initial polygon is spatially compared to the boundary of the closed reference region. Polygons extending beyond the reference region boundary are clipped, retaining only those within the reference region. After clipping, each retained polygon becomes an independent sub-region, and each sub-region corresponds to only one temperature sensor, thus clearly defining the monitoring coverage of each sensor.

[0070] Based on the divided sub-regions, and according to the physical characteristics of each sub-region relative to the center of the aluminum rod, its surface condition, and the airflow environment, a temperature adjustment coefficient corresponding to each sub-region is determined. Specifically, this includes: for the distance of the sub-region relative to the center of the aluminum rod, sub-regions closer to the center dissipate heat more slowly and have relatively higher temperatures, while sub-regions farther from the center dissipate heat more quickly and have relatively lower temperatures, and different distance levels are defined based on this heat dissipation pattern; for the surface condition of the sub-regions, the presence of oxide layer scratches or roughness differences on the surface of the aluminum rod corresponding to each sub-region is observed, and areas with rough surfaces or oxide layers have different heat conduction and dissipation rates compared to smooth surfaces; for the airflow environment of the sub-regions, the airflow intensity and flow direction around each sub-region are detected, and areas with strong airflow are more likely to have lower temperatures due to heat loss, while areas with stable or weak airflow have relatively stable temperatures; by comprehensively evaluating these three physical characteristics, each sub-region is assigned a temperature adjustment coefficient that reflects the actual temperature influencing factors.

[0071] Based on the temperature adjustment coefficient, the original temperature measurements obtained by each temperature sensor are weighted and compensated for calibration, thereby generating the calibrated temperature distribution characteristics across the entire cross-section of the aluminum rod. Specifically, this involves: first, establishing the correlation between the temperature adjustment coefficient of each sub-region and the original temperature measurement value of the corresponding sensor, with the temperature calibration of each sub-region based on the original measurement value of the corresponding sensor; second, calculating the weighted average of the corresponding original temperature measurement values ​​according to the temperature adjustment coefficient of each sub-region, with sub-regions having larger adjustment coefficients indicating that their physical properties have a significant impact on temperature, and assigning them higher weights during the weighting process; and third, integrating the calibrated temperatures of all sub-regions after completing the temperature calibration of a single sub-region, and combining this with the overall structure of the aluminum rod cross-section, using reasonable interpolation to fill the temperature data gaps between sub-regions, ensuring the continuity and integrity of the temperature distribution, and finally generating a comprehensive and accurate calibrated temperature distribution characteristic that reflects the temperature conditions at different locations across the entire cross-section of the aluminum rod.

[0072] In this embodiment of the invention, because a closed reference region is constructed and a Voronoi diagram construction algorithm is used to divide the region into sub-regions so that each sub-region uniquely corresponds to the monitoring coverage of a temperature sensor, and then the corresponding temperature adjustment coefficient is determined based on the physical characteristics of each sub-region relative to the center of the aluminum rod, the surface state, and the airflow environment, and finally the original temperature measurement values ​​of each sensor are weighted and compensated based on the coefficients, the technical problem of not being able to accurately match the temperature measurement with the sensor monitoring range, not considering the influence of the physical characteristics of different regions on the temperature, resulting in temperature measurement deviations and difficulty in forming an accurate temperature field of the aluminum rod cross section is overcome. Thus, the spatial assignment of the temperature sensor monitoring range is clearly defined, the temperature compensation calibration is more in line with the actual working conditions, and an accurate and comprehensive calibrated temperature distribution characteristic is generated on the entire cross section of the aluminum rod.

[0073] like Figure 2 As shown, in another preferred embodiment of the present invention, the feature is that, based on the constructed closed reference region, the closed reference region is divided into sub-regions using a Voronoi diagram construction algorithm, so that each sub-region uniquely corresponds to the monitoring coverage area of ​​a temperature sensor, including:

[0074] Based on the constructed closed reference region, the position coordinates of the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor within the region boundary are extracted to obtain the initial point set of sensor position coordinates. Specifically, this includes: first, clarifying the specific boundary range of the constructed closed reference region, which is determined based on the actual size of the aluminum rod detection cross-section and the sensor installation layout, fully covering the key areas of the aluminum rod that require temperature monitoring; then, using a laser positioning instrument and high-precision coordinate measuring equipment, the positions of the inlet-side reference temperature sensor, the outlet-side reference temperature sensor, and the lateral compensation temperature sensor are acquired. During the acquisition process, the probe of the equipment is kept close to the effective sensing part of the sensor to ensure that the coordinates of the actual monitoring point of the sensor are measured; to avoid installation errors or equipment measurement deviations, the coordinates of each sensor are repeatedly acquired three times, and the average of the three measurement results is taken as the final coordinate data; the final coordinate data of the three sensors are classified and organized according to sensor type to form an initial point set containing the precise spatial position information of each sensor. The point set clearly records the specific landing point of each temperature sensor within the closed reference region.

[0075] For every two sensor locations in the initial point set, the perpendicular bisector of the line segment connecting the two sensor locations is calculated. These perpendicular bisectors intersect within the closed reference region, forming a network of perpendicular bisectors consisting of multiple intersection points. Specifically, based on the acquired initial point set of sensor location coordinates, all possible pairwise combinations of the three sensor locations are first performed to form several pairs of sensor location points. For each pair, the line segment connecting the two sensor locations is first determined. The midpoint of the line segment is found through geometric analysis. Then, the direction perpendicular to the line segment is determined based on its extension direction. This perpendicular direction is then extended from the midpoint of the line segment to both sides, forming the perpendicular bisector of the line segment. During the extension process, the boundary of the closed reference region is strictly referenced. Once the perpendicular bisector reaches the boundary of the closed reference region, the extension stops, retaining only the portion of the perpendicular bisector located within the closed reference region. All sensor location pairs are processed in the same way. All retained perpendicular bisectors intersect and connect within the closed reference region, ultimately forming a uniformly distributed network of perpendicular bisectors covering the entire closed reference region.

[0076] Based on the perpendicular bisector network, for each sensor location point, all associated perpendicular bisectors are determined. The minimum closed region formed by the perpendicular bisectors around the sensor location point in space is obtained, resulting in the initial Voronoi polygon corresponding to the sensor. Specifically, to establish the core monitoring area corresponding to each sensor, based on the formed perpendicular bisector network, for each sensor location point in the initial point set, all perpendicular bisectors associated with the sensor are identified one by one. Specifically, for a given sensor location point, the perpendicular bisectors corresponding to all point pairs composed of the sensor and other sensors are perpendicular bisectors associated with the sensor. The perpendicular bisectors are essentially the boundary lines between the monitoring ranges of the sensor and other sensors. Subsequently, these associated perpendicular bisectors are connected sequentially according to spatial geometric order to form a closed figure centered on the sensor location point in space. This closed figure is the minimum region around the sensor location point, completely delineating the sensor's most direct monitoring range, which is the initial Voronoi polygon corresponding to the sensor.

[0077] Based on the initial Voronoi polygons, each initial Voronoi polygon is spatially compared with the closed reference region. Boundary clipping is then performed to remove polygon portions outside the closed reference region, resulting in a clipped polygon set. Specifically, considering that the initial Voronoi polygons are calculated based on sensor location points, some of their contours may extend beyond the boundary of the closed reference region. Since the closed reference region is the effective monitoring range of the aluminum rod's detection cross-section, the portion exceeding this range has no practical monitoring significance and may even cause deviations in subsequent temperature calibration; therefore, boundary clipping is necessary for the initial Voronoi polygons. Firstly, the initial Voronoi polygons are... The coordinates of all vertices of each initial Voronoi polygon are compared point by point with the boundary coordinates of the closed reference region to determine whether each vertex is within the closed reference region. At the same time, it is analyzed whether each edge of the polygon intersects with the boundary of the closed reference region. For polygon vertices and edges that exceed the boundary of the closed reference region, they are precisely trimmed according to the boundary contour of the closed reference region, and the polygon parts located outside the closed reference region are removed. At the same time, the intersection points of the polygons with the boundary of the closed reference region are used as new vertices and reconnected to form a complete polygon. After such trimming, a set of polygons in which all parts are located within the closed reference region is obtained.

[0078] Based on the cropped polygon set, each retained polygon region is determined as the final sub-region, thus ensuring that each sub-region uniquely corresponds to the monitoring coverage of a temperature sensor. Specifically, this addresses the issue of inconsistent temperature sensor monitoring ranges and the inability to achieve a precise one-to-one correspondence. A comprehensive verification and confirmation process is performed on the cropped polygon set. First, the integrity of each polygon region is checked to ensure that each polygon fully covers the effective monitoring range of its corresponding sensor, without any missing monitoring range due to cropping. Then, the independence between different polygons is checked to ensure that there are no overlapping areas between any two polygons, avoiding interference with subsequent temperature measurement data. Finally, the overall coverage of all polygons is checked to ensure that the area formed by all polygons fully covers the entire closed reference area, with no temperature monitoring blind spots. After verifying integrity, independence, and coverage, each verified polygon region is officially determined as the final sub-region, and each final sub-region uniquely corresponds to the monitoring coverage of a temperature sensor.

[0079] In this embodiment of the invention, because an initial point set is obtained by extracting the position coordinates of each temperature sensor based on a constructed closed reference region, and a perpendicular bisector network is formed by calculating the perpendicular bisectors of line segments for every two sensor position points in the initial point set, and a minimum closed initial Voronoi polygon is formed around each sensor position point, the initial Voronoi polygon is compared with the closed reference region in terms of spatial position and the boundary is clipped, and the polygon region retained after clipping is determined as the final sub-region, the technical means of overcoming the technical problem that the monitoring coverage of the temperature sensor lacks a clear spatial definition and cannot accurately correspond to the specific area of ​​the aluminum rod cross section, resulting in confusion between the temperature measurement value and the spatial region, thereby achieving the technical effect that each final sub-region can uniquely and accurately correspond to the monitoring coverage of a temperature sensor, and improving the accuracy of temperature field zoning perception.

[0080] In a preferred embodiment of the present invention, based on the calibrated temperature distribution characteristics, a sound velocity compensation algorithm is applied to dynamically correct the propagation velocity of ultrasonic waves in the aluminum rod material to obtain the corrected sound velocity parameters, including:

[0081] Based on the calibrated temperature distribution characteristics on the aluminum rod cross-section, the pre-stored correspondence between the sound velocity and temperature characteristics of aluminum is invoked. A sound velocity compensation algorithm converts the temperature distribution characteristics into corresponding sound velocity distribution data. Specifically, this involves: firstly, pre-stored correspondence between the sound velocity and temperature characteristics of aluminum based on extensive experimental data. This correspondence covers the sound velocity variation patterns of the target aluminum alloy material in different temperature ranges and has undergone multiple verifications and calibrations to ensure data accuracy; secondly, after obtaining the calibrated temperature distribution characteristics on the aluminum rod cross-section, the temperature distribution characteristics are analyzed to determine the precise temperature values ​​of each sub-region of the aluminum rod cross-section. These sub-regions are previously... After being divided into independent regions using the Voronoi diagram algorithm and calibrated for temperature, the temperature data of each region accurately reflects the actual temperature conditions at its location. Subsequently, the pre-stored correspondence between sound velocity and temperature characteristics is invoked, and the temperature values ​​of each sub-region are matched and queried one by one. The sound velocity compensation algorithm converts the temperature data of each sub-region into the corresponding sound velocity data. For possible temperature transition regions between sub-regions, linear interpolation is used to supplement the sound velocity data to ensure the continuity and integrity of the sound velocity distribution. Finally, sound velocity distribution data corresponding one-to-one with the temperature distribution of the aluminum rod cross-section is formed, and the data clearly presents the sound velocity differences at different locations on the aluminum rod cross-section.

[0082] Based on sound velocity distribution data, and according to the propagation path characteristics of ultrasound in aluminum rods, the propagation velocity of ultrasound in aluminum rod materials is dynamically calculated and corrected to obtain corrected sound velocity parameters that match the current temperature field of the aluminum rod cross-section. Specifically, after obtaining the sound velocity distribution data, the propagation path characteristics of ultrasound inside the aluminum rod are analyzed based on the installation position of the ring ultrasonic phased array probe group, the focusing law, and the cross-sectional dimensions of the aluminum rod. After being emitted from the probe, the ultrasound needs to pass through different regions of the aluminum rod to reach the internal defect location and then reflect back to the probe. Its propagation path will vary depending on the depth and location of the defect within the aluminum rod, and it will traverse multiple sub-regions with different temperatures and sound velocities. By tracking the emission angle, propagation direction, and expected arrival time of the ultrasound in real time... The defect location is precisely determined, identifying all sub-regions traversed by each propagation path. Subsequently, based on the sound velocity distribution data, the sound velocity values ​​of each sub-region traversed by the path are extracted. Combining the length proportion of each sub-region in the path, the overall propagation velocity of the ultrasonic wave on the path is dynamically calculated and weighted. As the aluminum rod passes through the inspection station at a constant speed, the changes in the temperature distribution of the aluminum rod cross-section are continuously monitored, and the sound velocity distribution data is updated synchronously. Based on the new sound velocity distribution and the real-time changes in the propagation path, the calculation results of the ultrasonic wave propagation velocity are dynamically adjusted to achieve dynamic correction of the ultrasonic wave propagation velocity. This ensures that the sound velocity parameters corresponding to each propagation path can accurately match the current temperature field of the aluminum rod cross-section, eliminating the sound velocity deviation caused by temperature gradient and propagation path differences at the root.

[0083] In this embodiment of the invention, because the technical means of using the pre-stored correspondence between the sound velocity and temperature characteristics of aluminum material based on the temperature distribution characteristics after the aluminum rod cross-section calibration, converting the temperature distribution characteristics into corresponding sound velocity distribution data through the sound velocity compensation algorithm, and then combining the propagation path characteristics of ultrasound in the aluminum rod to dynamically calculate and correct the ultrasonic propagation velocity, the technical problem of relying solely on a single temperature parameter to correct the sound velocity, without considering the temperature gradient of the aluminum rod cross-section and the difference in the ultrasonic propagation path, resulting in a mismatch between the sound velocity parameter and the actual working conditions, and thus causing time-depth conversion deviation of the defect reflection signal, is overcome. This achieves the goal of obtaining a corrected sound velocity parameter that accurately matches the current temperature field of the aluminum rod cross-section, thereby eliminating the influence of temperature on the ultrasonic propagation velocity from the root.

[0084] In a preferred embodiment of the present invention, the original ultrasonic reflection signal is analyzed based on the corrected ultrasonic propagation velocity parameters to obtain the separated individual defect reflection signals, including:

[0085] Based on the corrected sound velocity parameters, the original ultrasonic reflection signal undergoes time-depth conversion and signal analysis processing to recalculate the propagation path and reflection interface position of the ultrasonic wave. Specifically, after obtaining the corrected sound velocity parameters, the depth analysis process of the original ultrasonic reflection signal is initiated. The original ultrasonic reflection signal contains echo information from the normal interface and various defects inside the aluminum rod, but the information exists in the form of time signals, which needs to be converted into spatial position information through time-depth conversion. Based on the precise sound velocity values ​​of different regions in the corrected sound velocity parameters, combined with the propagation time of the ultrasonic signal, time-depth conversion calculation is performed on each echo signal one by one. That is, based on the total time of the ultrasonic wave from the probe, propagation to the reflection interface and back to the probe, and the sound velocity distribution in each region along the propagation path, the distance from the reflection interface to the surface of the aluminum rod is accurately calculated. At the same time, the system combines the array element distribution, excitation timing and focusing rules of the ring ultrasonic phased array probe group to reverse deduce the actual propagation path of the ultrasonic wave inside the aluminum rod, clarifying which array element the ultrasonic wave is emitted from, which regions it passes through, and which reflection interface it finally reaches, and accurately re-determines the reflection interface position corresponding to each echo signal, including the internal and external interfaces of the aluminum rod and the boundary interfaces of various defects.

[0086] Based on the recalculated reflective interface positions, when composite defect features are identified where reflective signals from different defects overlap in the time or spatial domains, the overlapping reflective signals are separated to obtain the separation results. Specifically, after recalculating all reflective interface positions, the system performs correlation analysis on the position information and corresponding echo signals. First, it analyzes the spatial distribution of all reflective interfaces to determine if multiple reflective interfaces are spatially close or if their corresponding echo signals overlap in the time axis. When it is found that echo signals from different reflective interfaces exhibit peak overlap or waveform distortion in the time domain, or that adjacent reflective interface positions of different defects in the spatial domain cause signal interference, composite defect features can be identified. These features are typically caused by aluminum... The superimposed echo signal is formed by the combined action of multiple similar physical defects within the rod. Subsequently, a signal separation processing flow is initiated. Based on the precise positional differences of each reflecting interface and the corresponding sound velocity parameters, the superimposed echo signal is split. By analyzing the waveform characteristics, amplitude variations, and phase information of the superimposed signal, combined with the inherent characteristics of the reflected signals from different defects, the portions of the superimposed signal belonging to different reflecting interfaces are separated one by one. For example, for signals superimposed in the time domain, signal segments of different time periods are extracted and enhanced according to the propagation time differences corresponding to each defect. For signals superimposed in the spatial domain, echo signals in different directions are separated using beamforming technology based on the spatial positional differences of the reflecting interfaces, ultimately obtaining a set of preliminarily separated signal segments, ensuring that each signal segment corresponds to an independent reflecting interface.

[0087] Based on the results of the separation process, the separated reflection signal corresponding to a single physical defect inside the aluminum rod is obtained. Specifically, this includes: further verifying and refining the results of the second separation process to ensure that the separated signal accurately corresponds to a single physical defect inside the aluminum rod; re-associating each separated signal segment with the recalculated reflection interface position to determine whether the waveform characteristics, amplitude, and duration of each signal segment match the defect type corresponding to the reflection interface; simultaneously, considering the processing characteristics of the aluminum rod and common defect morphologies, the signal segments are screened to remove false signal segments caused by interface reflection interference, environmental noise, etc. For the verified signal segments, signal enhancement and noise reduction processing are performed to further improve the clarity and recognizability of the signal, ensuring that the signal can completely reflect the characteristic information of the corresponding defect; finally, each refined effective signal segment becomes the separated reflection signal corresponding to a single physical defect inside the aluminum rod.

[0088] In this embodiment of the invention, by employing time-depth conversion and signal analysis of the original ultrasonic reflection signal based on the corrected sound velocity parameter, recalculating the ultrasonic propagation path and the position of the reflection interface, and then identifying and separating the composite defect features superimposed in the time or spatial domain based on the reflection interface position, the technical means of obtaining the reflection signal of the corresponding single physical defect is overcome. This overcomes the technical problems of distorted reflection signal analysis and masked information of single defects caused by the failure to use accurately corrected sound velocity parameters for signal analysis and the inability to identify and separate superimposed defect signals. As a result, the technical effect of accurately restoring the ultrasonic propagation path and the position of the defect reflection interface, completely splitting the composite defect signal, obtaining a clear and independent reflection signal of a single defect, and further improving the accuracy of defect detection is achieved.

[0089] In a preferred embodiment of the present invention, the separated individual defect reflection signals are processed by locating the boundary points of the defect reflection signals through edge detection, and then polygon fitting is performed on the boundary points to form the geometric contour of the defect, defining the boundary positions of various defects to obtain the defect depth detection results, including:

[0090] Based on the separated individual defect reflection signals, a shape contour extraction algorithm is used for processing. First, edge detection technology is applied to locate the boundary point set of the defect reflection signal. Specifically, after acquiring the separated individual defect reflection signals, the signals are preprocessed. Although the separated signals have removed defect superposition interference, there may still be a small amount of environmental noise or signal fluctuations. Smoothing technology is used to weaken these interference factors and retain the key features related to the defect boundary in the signal. Subsequently, the shape contour extraction algorithm is started, and edge detection technology is applied to analyze the preprocessed signal. Abrupt changes in signal amplitude usually occur at the boundary of the defect reflection signal. Edge detection technology identifies the start and end points of such amplitude changes to determine the boundary position of the defect signal. During the detection process, the amplitude change curve of the signal is scanned point by point. When the amplitude change rate exceeds a preset threshold, the point is marked as a potential boundary point. To avoid misjudgment, each potential boundary point is verified by surrounding signal segments to confirm whether it belongs to a continuous boundary feature rather than an isolated noise point. After multiple rounds of screening and verification, all valid boundary points are arranged according to the temporal order or spatial correspondence of the signal to form a complete and accurate set of defect reflection signal boundary points.

[0091] Based on the localized boundary point set, polygon fitting is performed on the boundary points to obtain a geometric contour that accurately describes the defect shape. Specifically, this includes: after obtaining the boundary point set, further optimization is performed on the point set. Each point in the boundary point set is checked one by one, and abnormal isolated points caused by minor signal fluctuations or detection errors are removed. These isolated points do not conform to the distribution pattern of surrounding points and will affect the accuracy of the fitted contour. Simultaneously, the boundary point set is ordered to ensure that all points are distributed sequentially according to the actual contour of the defect, avoiding distortion of the fitted contour due to disordered point order. Then, the polygon fitting process is initiated, based on the boundary point set... The feature is fitted using a stepwise approximation method. During the fitting process, adjacent key boundary points are first connected to form an initial polygon. Then, according to the preset fitting accuracy requirements, the vertex positions of the polygon are continuously adjusted so that each edge of the polygon can approximate the distribution trajectory of the boundary point set as closely as possible. For parts of the defect contour with large curvature, more boundary points are retained as fitting vertices to ensure accurate restoration of the shape features of the part. For parts with relatively smooth contours, the number of vertices is appropriately simplified to improve processing efficiency while ensuring accuracy. After multiple iterations and adjustments, a geometric contour that accurately describes the actual shape and size of the defect is finally obtained.

[0092] Based on the geometric profile, the depth distance between the upper and lower boundaries of the profile and the surface of the aluminum rod is calculated according to the corrected sound velocity parameters. Based on this, the boundary positions and burial depths of various defects are defined, and the defect depth detection results are finally obtained. Specifically, after obtaining the accurate defect geometric profile, the signal feature points corresponding to the upper and lower boundaries of the geometric profile are first identified. The upper boundary corresponds to the position of the reflected signal when the ultrasonic wave first contacts the defect surface, and the lower boundary corresponds to the position of the reflected signal when the ultrasonic wave reaches the bottom of the defect. Subsequently, the system retrieves the corrected sound velocity parameters obtained after temperature compensation calibration. These parameters are precise data dynamically corrected based on the specific temperature distribution of the aluminum rod cross-section, accurately reflecting the propagation speed of ultrasound in the defect area. Combining the ultrasound signal propagation time corresponding to the upper and lower boundaries of the geometric contour, and the corrected sound velocity parameters, the depth distances of the upper and lower boundaries relative to the aluminum rod surface are calculated. Specifically, the distance from the upper boundary of the defect to the aluminum rod surface is obtained by multiplying the time it takes for the ultrasound to propagate from the aluminum rod surface to the upper boundary of the defect by the corrected sound velocity corresponding to the propagation path; this is the burial depth of the defect. Similarly, the distance from the lower boundary of the defect to the aluminum rod surface is calculated; this is the maximum depth of the defect. Based on the overall distribution of the geometric contour, the specific boundary position and extension range of the defect on the aluminum rod cross-section are defined. Finally, the data on the burial depth, maximum depth, and boundary position of the defect are integrated and summarized to form a complete and accurate defect depth detection result.

[0093] In this embodiment of the invention, because it uses a shape contour extraction algorithm based on the separated single defect reflection signal, firstly, edge detection technology is applied to locate the boundary point set of the defect reflection signal, then polygon fitting is performed on the boundary point set to obtain a geometric contour that accurately describes the shape of the defect, and finally, based on the geometric contour and the corrected sound velocity parameters, the depth distance between the upper and lower boundaries of the contour and the surface of the aluminum rod is calculated to define the defect boundary position and burial depth, the technical means overcomes the technical problems of large defect depth calculation deviation and unclear boundary position due to multiple defect signal interferences, ambiguous boundary positioning, inaccurate contour description, and lack of accurate sound velocity support. Thus, it achieves the technical effect of accurately capturing the boundary features of the defect signal, forming a geometric contour that highly matches the actual defect, accurately calculating the defect burial depth and boundary position, and outputting accurate and reliable defect depth detection results, meeting the technical requirements of high-end equipment for high-precision detection of internal defects in aluminum rods.

[0094] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the system as described above. All implementations in the above system embodiments are applicable to this embodiment and can achieve the same technical effects.

[0095] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the system as described above. All implementations in the above system embodiments are applicable to this embodiment and can achieve the same technical effects.

[0096] The prediction system according to embodiments of the present invention may correspond to the system described in the embodiments of the present invention, and the above and other operations and / or functions of each module of the prediction system are respectively for implementing Figure 1 The corresponding processes of the system in the illustrated embodiment will not be described in detail here for the sake of brevity.

[0097] This application also provides a computing device. This computing device can utilize a server.

[0098] like Figure 3 As shown in the figure, this is a schematic diagram of a computing device provided in an embodiment of this application. The computing device 700 includes a bus 701, a processor 702, a communication interface 703, and a memory 704. The processor 702, the memory 704, and the communication interface 703 communicate with each other via the bus 701.

[0099] The 701 bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0100] The processor 702 can be any one or more of the following processors: central processing unit (CPU), graphics processing unit (GPU), microprocessor (MP), or digital signal processor (DSP).

[0101] Communication interface 703 is used for external communication. Memory 704 may include volatile memory, such as random access memory (RAM). Memory 704 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD). Memory 704 stores executable code, which processor 702 executes to perform the aforementioned industrial equipment remaining life prediction method.

[0102] Specifically, in implementing the industrial equipment remaining life prediction system shown in the above embodiments, and where each module or unit of the industrial equipment remaining life prediction system described in the above embodiments is implemented by software, the software or program code required to execute the functions of each module / unit in the industrial equipment remaining life prediction system described in the above embodiments can be partially or entirely stored in the memory 704. The processor 702 executes the program code corresponding to each unit stored in the memory 704 to execute the aforementioned industrial equipment remaining life prediction method.

[0103] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that a computing device can store, or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive). The computer-readable storage medium includes instructions that instruct a computing device to execute the aforementioned industrial equipment remaining life prediction method.

[0104] This application also provides a computer program product comprising one or more computer instructions. When the computer instructions are loaded and executed on a computing device, all or part of the processes or functions described in this application are generated.

[0105] The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, or data center to another website, computer, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0106] When the computer program product is executed by a computer, the computer performs any of the aforementioned methods for predicting the remaining useful life of industrial equipment. The computer program product can be a software installation package; when any of the aforementioned methods for predicting the remaining useful life of industrial equipment is required, the computer program product can be downloaded and executed on the computer.

[0107] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An ultrasonic phased array aluminum rod internal defect depth detection system based on sound velocity compensation, characterized in that, The method comprises the following steps: An acquisition module is configured to scan an aluminum rod moving at a constant speed through a detection station by using a ring-shaped ultrasonic phased array probe group to obtain original ultrasonic reflection signals inside the aluminum rod; A construction module is configured to collect temperature measurement values of different cross sections of the aluminum rod based on the original ultrasonic reflection signals, the reference temperature sensors arranged at the entrance and exit of the detection station, and the lateral compensation temperature sensors, and to construct a closed reference area on the cross section of the aluminum rod according to the positions of the sensors; A calibration module is configured to divide the closed reference area into sub-areas by using a Voronoi diagram construction algorithm, so that each sub-area corresponds to the monitoring coverage range of a temperature sensor, and to determine a temperature adjustment coefficient according to the physical characteristics of each sub-area; The temperature adjustment coefficient is used to compensate and calibrate the temperature measurement values, so as to obtain the calibrated temperature distribution characteristics on the cross section of the aluminum rod, which comprises the following steps: The closed reference area is divided into sub-areas by using a Voronoi diagram construction algorithm, so that each sub-area uniquely corresponds to the monitoring coverage range of a temperature sensor, which comprises the following steps: The position coordinates of the reference temperature sensors arranged at the entrance and exit of the detection station and the lateral compensation temperature sensors within the boundary of the closed reference area are extracted to obtain an initial point set of the sensor position coordinates; for each two sensor position points in the initial point set, the perpendicular bisector of the line segment connecting the two sensor position points is calculated, the perpendicular bisectors intersect in the closed reference area to form a perpendicular bisector network composed of multiple intersection points; for each sensor position point, all related perpendicular bisectors are determined, the smallest closed area formed by the perpendicular bisectors in space around the sensor position point is obtained, and the initial Voronoi polygon corresponding to the sensor is obtained; the initial Voronoi polygon is compared with the closed reference area in terms of spatial position, the polygon part located outside the closed reference area is removed through boundary clipping processing, and a set of clipped polygons is obtained; each retained polygon region is determined as a final sub-area based on the set of clipped polygons, so that each sub-area uniquely corresponds to the monitoring coverage range of a temperature sensor; Based on the divided sub-areas, the temperature adjustment coefficients corresponding to the sub-areas are determined according to the physical characteristics of the sub-areas relative to the center of the aluminum rod, the surface state, and the airflow environment; The original temperature measurement values obtained by the temperature sensors are weighted and compensated based on the temperature adjustment coefficients, and the calibrated temperature distribution characteristics on the entire cross section of the aluminum rod are generated accordingly; A correction module is configured to dynamically correct the propagation speed of ultrasonic waves in the aluminum rod material by using a sound speed compensation algorithm based on the calibrated temperature distribution characteristics, and to obtain a corrected sound speed parameter; A separation module is configured to analyze the original ultrasonic reflection signals based on the corrected ultrasonic propagation speed parameter to obtain separated single defect reflection signals. The processing module is configured to process the separated single defect reflection signal, locate the boundary points of the defect reflection signal through edge detection, perform polygon fitting on the boundary points, form a geometric contour of the defect, and define the boundary positions of various defects to obtain a defect depth detection result.

2. The ultrasonic phased array aluminum rod internal defect depth detection system based on sound velocity compensation according to claim 1, characterized in that, The original ultrasonic reflection signal inside the aluminum rod is obtained by scanning the aluminum rod passing through the detection station at a constant speed by using the annular ultrasonic phased array probe group, including: The annular ultrasonic phased array probe group is fixed in a surrounding manner on the detection station, and the central axis is accurately aligned with the conveying track of the aluminum rod to establish a stable scanning reference; Based on the scanning reference, when the aluminum rod passes at a constant speed, the probe group is driven to perform full-coverage ultrasonic scanning on the moving aluminum rod according to the preset excitation timing and focusing rules; Based on the triggering of the ultrasonic scanning, the annular ultrasonic phased array probe group synchronously receives ultrasonic echo signals from the internal interfaces and defects of the aluminum rod to obtain the original ultrasonic reflection signal.

3. The ultrasonic phased array aluminum rod internal defect depth detection system based on sound velocity compensation according to claim 2, characterized in that, Based on the original ultrasonic reflection signal, the temperature measurement values of different cross sections of the aluminum rod are synchronously collected by the reference temperature sensors arranged at the inlet side, the outlet side and the lateral compensation side of the aluminum rod detection station, and a closed reference area is constructed on the cross section of the aluminum rod according to the positions of the sensors, including: Based on the original ultrasonic reflection signal, the temperature measurement values of the reference temperature sensors arranged at the inlet side, the outlet side and the lateral compensation side are synchronously collected; Based on all the collected temperature measurement values and corresponding sensor positions, a closed reference area connecting the positions of the sensors is constructed according to the spatial distribution of the reference temperature sensors arranged at the inlet side, the outlet side and the lateral compensation side on the cross section of the aluminum rod.

4. The ultrasonic phased array aluminum rod internal defect depth detection system based on sound velocity compensation according to claim 3, characterized in that, According to the calibrated temperature distribution characteristics, the speed compensation algorithm is applied to dynamically correct the propagation speed of ultrasonic waves in the aluminum rod material to obtain the corrected speed parameter, including: Based on the calibrated temperature distribution characteristics on the cross section of the aluminum rod, the pre-stored corresponding relationship between the speed of aluminum material and temperature characteristics is called, and the temperature distribution characteristics are converted into corresponding speed distribution data through the speed compensation algorithm; Based on the speed distribution data, the propagation speed of ultrasonic waves in the aluminum rod material is dynamically calculated and corrected according to the propagation path characteristics of ultrasonic waves in the aluminum rod to obtain the corrected speed parameter matched with the current temperature field of the cross section of the aluminum rod.

5. The ultrasonic phased array aluminum rod internal defect depth detection system based on sound velocity compensation according to claim 4, characterized in that, The original ultrasonic reflection signal is analyzed and processed according to the corrected ultrasonic propagation speed parameter to obtain the separated single defect reflection signal, including: Based on the corrected speed parameter, the original ultrasonic reflection signal is processed by time-depth conversion and signal analysis to recalculate the propagation path and reflection interface position of the ultrasonic wave; Based on the recalculated reflection interface position, when the composite defect characteristics formed by the superposition of reflection signals from different defects in the time domain or the spatial domain are identified, the superimposed reflection signals are separated to obtain the separation result; Based on the separation result, the separated reflection signal corresponding to the single physical defect inside the aluminum rod is obtained.

6. The ultrasonic phased array aluminum rod internal defect depth detection system based on sound velocity compensation according to claim 5, characterized in that, The separated single defect reflection signal is processed by a shape contour extraction algorithm, the boundary points of the defect reflection signal are located by edge detection, and the boundary points are polygonally fitted to form a geometric contour of the defect, and the boundary positions of various defects are defined to obtain a defect depth detection result, including: Based on the separated single defect reflection signal, the shape contour extraction algorithm is processed, and first, the edge detection technology is applied to locate the boundary point set of the defect reflection signal; Based on the located boundary point set, the boundary points are polygonally fitted to obtain a geometric contour accurately describing the shape of the defect; Based on the geometric contour, the depth distance of the upper boundary and the lower boundary on the contour relative to the surface of the aluminum bar is calculated according to the corrected sound velocity parameter, the boundary positions and the buried depths of various defects are defined according to the depth distance, and finally, the defect depth detection result is obtained.

7. A computing device, comprising: Comprise: One or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, so that the one or more processors execute the system as claimed in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a program, and the program is executed by the processor to execute the system as claimed in any one of claims 1 to 6.

Images