Die detection device for aluminum alloy tension bar

Abstract

The invention provides a mold detection device for an aluminum alloy tension bar, and relates to the technical field of mold detection, and the mold detection device comprises a mold inner cavity online monitoring module, a locking mechanism health state diagnosis module, a parting surface sealing performance detection module and a mold detection report output module. The shape precision and surface precision data can be comprehensively obtained through the mold inner cavity online monitoring module so as to avoid the defects of burrs, size out-of-tolerance and the like of a tension bar, and faults such as thread abrasion, lubrication failure or clamping seat deformation and the like can be accurately evaluated through the locking mechanism health state diagnosis module so as to avoid mold leakage, flash and production interruption; a trace amount of low-pressure gas is injected after mold closing and locking and before pouring through the parting surface sealing performance detection module, the pressure attenuation rate and an ultrasonic signal are monitored, the sealing state can be quantitatively evaluated, the flash risk can be predicted, and the follow-up cleaning workload and cost are reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of mold detection, and particularly relates to a mold detection device for an aluminum alloy tensile bar. Background Art

[0002] The inspection of aluminum alloy tensile bar molds is crucial, as it is directly related to the molding quality, production efficiency, and mold life of aluminum alloy tensile bars. During the production process of aluminum alloy tensile bars, the shape accuracy and surface condition of the mold cavity will directly affect the dimensional tolerance and surface quality of the product. If there is wear, cracks, or residue adhesion in the mold cavity, it is easy to cause defects such as burrs and dimensional deviations in the tensile bar. The health of the locking mechanism determines the reliability of the mold clamping. If the bolt threads are worn, the lubrication fails, or the holder is deformed, it may cause mold leakage, flash, and even cause production interruption. The sealing performance of the parting surface affects the risk of molten metal overflow during pouring. Poor sealing can cause flash, increasing the workload and cost of subsequent cleaning processes. However, the detection devices in the existing technology have significant defects: First, in terms of mold cavity detection, the existing devices can only perform sampling detection on the geometric dimensions of the inner cavity through contact measuring tools, and are unable to obtain surface accuracy data such as the wear degree, crack pitting degree and residue adhesion degree of the inner cavity surface, resulting in the inability to timely detect problems such as burrs on the tension rod and dimensional deviation caused by wear or residue accumulation; Second, there is a gap in the health monitoring of the locking mechanism. The existing devices lack the ability to collect dynamic data in real time during the bolt locking process, and are unable to evaluate faults such as thread wear, lubrication failure or seat deformation, making it difficult to avoid mold leakage or production interruption caused by abnormal locking mechanism; Third, the sealing detection of the parting surface relies on manual visual inspection of the fitting gap, and is unable to monitor the pressure decay rate through low-pressure gas injection or analyze microscopic leakage channels through ultrasonic signals, resulting in the inability to quantitatively evaluate the sealing status and the difficulty in predicting the risk of flash during casting, thereby increasing the workload and cost of the subsequent cleaning process. Summary of the Invention

[0003] The present invention provides a mold detection device for aluminum alloy tensile bars, which is used to solve at least one of the above-mentioned technical problems.

[0004] In order to solve the above technical problems, the present invention discloses a mold detection device for aluminum alloy tensile bars, comprising: The mold cavity online monitoring module is used to obtain the shape accuracy analysis results and surface accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold based on the point cloud data of the mold cavity and the preset standard mold cavity digital twin model; The locking mechanism health status diagnosis module is used to collect the data curve of the locking mechanism during the locking process, and compare the data curve of the locking mechanism during the locking process with the standard curve to evaluate the health status of the locking mechanism; The parting surface sealing detection module is used to inject a small amount of low-pressure gas into the closed mold cavity after the mold is closed and locked and before pouring. It monitors the pressure decay rate of the mold cavity and the detection results of the ultrasonic probe to determine the sealing status of the parting surface; The mold inspection report output module is used to obtain inspection data from the mold cavity online monitoring module, the locking mechanism health status diagnosis module, and the parting surface sealing detection module, integrate and process the data, and generate an inspection report.

[0005] Preferably, the mold cavity online monitoring module includes: A mold cavity point cloud data acquisition submodule is used to scan the mold cavity of the aluminum alloy tensile bar mold using a laser probe to obtain point cloud data of the mold cavity of the aluminum alloy tensile bar mold; The digital twin comparison submodule is used to compare the point cloud data of the mold cavity with the preset standard mold cavity digital twin model to generate a three-dimensional chromatographic deviation map of the cavity comparison; The comparison analysis submodule is used to analyze the inner cavity comparison three-dimensional chromatogram deviation map to obtain the shape accuracy analysis results and surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold; Among them, the shape accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold include the circumferential cylindricity of the inner cavity and the flatness analysis results of the top and bottom surfaces; The surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold include the wear degree, crack pitting degree and residue adhesion degree analysis results of the inner cavity surface.

[0006] Preferably, the mold cavity point cloud data acquisition submodule includes: A laser emitting unit, used for emitting a laser beam toward an inner cavity of a mold for an aluminum alloy tensile bar; A laser receiving unit is used to receive the laser beam reflected from the inner surface of the mold and obtain the reflection information of the laser beam on the inner surface of the mold; Position sensing unit, used to obtain the spatial position information of the laser probe in real time during the scanning process; The data processing unit is used to calculate the three-dimensional coordinates of each point on the mold cavity surface based on the information obtained by the laser emitting unit, the laser receiving unit and the position sensing unit, and generate point cloud data of the mold cavity of the aluminum alloy tensile bar mold.

[0007] Preferably, the digital twin comparison submodule includes: Model import unit, used to import the preset standard mold cavity digital twin model; Point cloud registration unit, used to spatially align the point cloud data of the mold cavity with the standard mold cavity digital twin model; Deviation calculation unit, used to calculate the three-dimensional spatial deviation between the mold cavity point cloud data and the corresponding points of the standard mold cavity digital twin model. The three-dimensional spatial deviation includes position deviation and normal deviation; The chromatogram generating unit is used to assign different colors according to different deviation ranges based on the position deviation and normal deviation data obtained by the deviation calculating unit, and generate a three-dimensional chromatogram deviation map of the inner cavity contrast.

[0008] Preferably, the comparative analysis submodule includes: The shape accuracy calculation unit is used to extract the coordinate data of each point on the inner cavity surface of the mold based on the inner cavity comparison three-dimensional chromatogram deviation map, and calculate the cylindricity of the inner cavity circumference and the flatness of the top and bottom surfaces; Surface accuracy calculation unit, used to analyze the wear, crack pitting and residue adhesion of the mold cavity surface. It identifies surface wear areas, cracks and residues through image recognition algorithms and calculates the wear, crack pitting and residue adhesion of the mold cavity surface. The analysis output unit is used to output the shape accuracy analysis results and surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold based on the calculation results of the cylindricity of the inner cavity circumference, the flatness of the top and bottom surfaces, the wear degree of the mold inner cavity surface, the crack pitting degree and the residue adhesion degree.

[0009] Preferably, the locking mechanism health status diagnosis module includes: The locking mechanism data acquisition submodule is used to synchronously collect the torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t); The curve feature extraction submodule is used to extract the collected torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t) are preprocessed and feature extracted to obtain characteristic parameters. The characteristic parameters include the slope of the torque-angle curve in the stable stage, that is, the curve stiffness K, the time from initial preload to reaching the target pressure, that is, the pressure buildup time , torque rise rate r; The health status assessment submodule is used to compare and analyze the extracted characteristic parameters with the corresponding preset standard curve template to evaluate the health status of the locking mechanism.

[0010] Preferably, the health status assessment submodule includes: The standard curve storage unit is used to store standard curves of different types of molds, including standard torque-angle curve, standard pressure-time curve and standard torque-time curve: Deviation analysis unit, used to calculate torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t) are respectively multi-dimensional deviation indicators with the standard torque-angle curve, standard pressure-time curve and standard torque-time curve. The multi-dimensional deviation indicators include curve stiffness deviation , Pressure build-up time deviation , Torque rise rate deviation and comprehensive deviation index ; Fault diagnosis unit, used to identify the fault type based on deviation indicators: >0.3 and When <-20%, the fault type is bolt thread wear; When the value is less than -30% and the torque fluctuation is greater than 0.5, the fault type is lubrication failure; >50% and the maximum pressure in the pressure-time curve data is <0.8 , the fault type is card holder deformation.

[0011] Preferably, the parting surface sealing detection module includes: The gas path sensing unit submodule is used to install a pressure sensor and an integrated ultrasonic probe array on the dedicated gas path interface on the mold; The gas injection control submodule is used to select the type of trace low-pressure gas injected into the mold cavity, and to adjust the injected gas pressure and control the gas injection flow rate during the injection process; The mold cavity data acquisition and monitoring submodule is used to collect the gas pressure data and ultrasonic probe array signals in the mold cavity in real time; The sealing performance analysis submodule is used to calculate the gas pressure decay rate and analyze the ultrasonic signal to obtain the sealing status evaluation results of the mold parting surface.

[0012] Preferably, the sealing performance analysis submodule includes: Pressure decay analysis unit for time-based and The gas pressure value in the mold cavity collected at all times and Calculating the pressure decay rate ; An ultrasonic signal analysis unit is used to compare the collected ultrasonic signal intensity with the preset ultrasonic signal intensity to determine whether there is gas leakage on the parting surface; The sealing status evaluation unit is used to comprehensively analyze the pressure decay rate and ultrasonic signal analysis results to classify the sealing status of the mold parting surface into three levels: good, general, and poor.

[0013] Preferably, the mold inspection report output module includes: The data integration submodule is used to integrate the shape accuracy analysis results and surface accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold, the health status assessment results of the locking mechanism, and the sealing status results of the parting surface; The report output submodule is used to output the data integrated by the data integration submodule in the form of charts.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention uses a laser probe to scan and obtain point cloud data through the mold cavity online monitoring module and compares it with the standard digital twin model, which solves the problem that the existing technology can only sample and detect the geometric dimensions of the mold cavity. It can comprehensively obtain shape accuracy and surface accuracy data to avoid defects such as burrs and dimensional deviations on the tension rod. The locking mechanism health status diagnosis module uses the torque sensor, angle encoder and pressure sensor installed on the bolt and the contact surface of the limit seat and the card seat to collect the dynamic data of the locking process in real time and compare it with the standard curve, which solves the lack of dynamic data collection of the locking mechanism in the existing technology. It can accurately evaluate faults such as thread wear, lubrication failure or card seat deformation to avoid mold leakage, flash and production interruption. The parting surface sealing detection module injects a small amount of low-pressure gas after the mold is closed and locked before pouring, and monitors the pressure decay rate and ultrasonic signal, which solves the subjective problem of the existing technology relying on manual visual inspection of the sealing status of the parting surface. The sealing status can be quantitatively evaluated to predict the risk of flash and reduce the subsequent cleaning workload and cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 A schematic structural diagram of a mold for an aluminum alloy tensile bar provided in an embodiment of the present invention; Figure 2 The embodiment of the present invention provides Figure 1 A magnified schematic diagram of the structure at point A; Figure 3 Provide three views of mold 2 for the embodiment of the present invention; Figure 4 A schematic diagram of the locking mechanism structure provided by an embodiment of the present invention; Figure 5 A schematic diagram of the locking nut structure provided by an embodiment of the present invention; Figure 6 A schematic diagram of the support frame structure provided in an embodiment of the present invention.

[0016] In the figure: 1. Mold 1; 2. Mold 2; 3. Clamping seat; 4. Limiting seat; 5. Bolt; 6. Nut; 7. Stud; 8. Locking nut; 9. Positioning hole; 10. Positioning pin; 11. Support frame; 12. Retaining spring; 13. Gasket. DETAILED DESCRIPTION

[0017] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0018] In addition, in the present invention, descriptions such as "first" and "second" are only used for descriptive purposes, and do not specifically refer to the order or sequence, nor are they used to limit the present invention. They are only used to distinguish components or operations described with the same technical terms, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions and technical features between the various embodiments can be combined with each other, but this must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0019] The present invention provides the following embodiments Example 1 The embodiment of the present invention provides a mold detection device for aluminum alloy tensile bars, such as Figure 1-6 Shown, including: The mold cavity online monitoring module is used to obtain the shape accuracy analysis results and surface accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold based on the point cloud data of the mold cavity and the preset standard mold cavity digital twin model; The locking mechanism health status diagnosis module is used to collect the data curve of the locking mechanism during the locking process, and compare the data curve of the locking mechanism during the locking process with the standard curve to evaluate the health status of the locking mechanism; The parting surface sealing detection module is used to inject a small amount of low-pressure gas into the closed mold cavity after the mold is closed and locked and before pouring. It monitors the pressure decay rate of the mold cavity and the detection results of the ultrasonic probe to determine the sealing status of the parting surface; The mold inspection report output module is used to obtain inspection data from the mold cavity online monitoring module, the locking mechanism health status diagnosis module, and the parting surface sealing detection module, integrate and process the data, and generate an inspection report.

[0020] In this embodiment, the mold for the aluminum alloy tensile rod includes mold 1 and mold 2, which are hinged at the ends close to each other, and a holder 3 is fixedly installed on the side wall of the end of mold 1 away from mold 22, and a locking mechanism is provided on the side wall of the end of mold 22 away from mold 1.

[0021] Optionally, the locking mechanism includes: a limit seat 4, the bottom end of the limit seat 4 is installed on the side wall of the mold 2, and a bolt 5 is rotatably connected to the limit seat 4, a nut 6 is threadedly connected to the bolt 5 between the limit seats 4, a stud 7 is fixed on the nut 6, and a locking nut 8 is rotatably connected to the stud 7.

[0022] Optionally, a plurality of positioning holes 9 are provided on the mold 1 , and positioning pins 10 matching the positioning holes 9 are fixedly mounted on the mold 2 2 .

[0023] Optionally, a support frame 11 is welded to the bottom side of each end of the mold 1 and the mold 2 2 that are away from each other.

[0024] Optionally, the ends of the mold 1 and the mold 2 2 that are close to each other are hingedly connected, and a retaining spring 12 and a gasket 13 are provided at the hinge connection.

[0025] In this embodiment, the shape accuracy analysis results of the inner cavity of the current aluminum alloy tensile bar mold include the circumferential cylindricity of the inner cavity and the flatness analysis results of the top and bottom surfaces.

[0026] In this embodiment, the surface accuracy analysis results of the inner cavity of the current aluminum alloy tensile bar mold include analysis results of the wear degree, crack pitting degree, and residue adhesion degree of the inner cavity surface.

[0027] In this embodiment, the data curve of the locking mechanism during the locking process includes the torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t).

[0028] In this embodiment, the standard curve includes a standard torque-angle curve, a standard pressure-time curve, and a standard torque-time curve.

[0029] In this embodiment, the parting surface refers to the contact surface where mold 1 1 and mold 2 2 fit together when the mold is closed. It is the boundary of the mold cavity, and its sealing performance directly affects whether the molten metal will overflow from the mold gap during the pouring process, thereby affecting the molding quality of the aluminum alloy tensile bar and the service life of the mold.

[0030] The working principle and beneficial effects of the above technical solution are as follows: during operation, the mold cavity online monitoring module performs analysis based on the point cloud data of the mold cavity of the aluminum alloy tensile bar mold and the preset standard mold cavity digital twin model; the locking mechanism health status diagnosis module collects the data curve during the locking process through the torque sensor and angle encoder installed on the bolt 5 and the pressure sensor installed on the contact surface between the limit seat 4 and the clamping seat 3 and compares it with the standard curve; the parting surface sealing detection module injects a trace amount of low-pressure gas into the closed mold cavity after the mold is closed and locked and before pouring, and monitors the pressure decay rate of the mold cavity and the detection results of the ultrasonic probe; the mold inspection report output module obtains the inspection data from the above modules and generates an inspection report after integration and processing; By hinge-connecting the mold 1 and the mold 2, the clamping seat 3 and the limit seat 4 are in contact, and the locking nut 8 is rotated at the same time, and then the locking nut 8 is clamped on the clamping seat 3, so that the mold 1 and the mold 2 are fully in contact, and finally the aluminum alloy melt is poured through the upper opening. After it is fully cooled, the locking mechanism is opened to remove the prepared aluminum alloy tensile bar; The aluminum alloy tensile bar mold is provided with a mold 1 and a mold 2, and connected by a locking mechanism, thereby realizing the opening and closing of the mold; the provision of a support frame 11 is conducive to achieving effective support for the mold 1 and the mold 2; the provision of a locking mechanism is conducive to realizing the opening and closing of the mold 1 and the mold 2; the provision of a positioning hole 9 and a positioning pin 10 is conducive to improving the positioning of the mold 1 and the mold 2, thereby solving the problem that the locking mechanism of the traditional tensile bar mold is not only complicated in locking mechanism but also in locking process, which easily causes the locking mechanism to fail during use of the mold; The present invention uses a laser probe to scan and obtain point cloud data through the mold cavity online monitoring module and compares it with the standard digital twin model, which solves the problem that the existing technology can only sample and detect the geometric dimensions of the mold cavity. It can comprehensively obtain shape accuracy and surface accuracy data to avoid defects such as burrs and dimensional deviations on the tension rod. The locking mechanism health status diagnosis module uses the torque sensor, angle encoder and pressure sensor installed on the bolt 5 and the contact surface of the limit seat 4 and the holder 3 to collect the dynamic data of the locking process in real time and compare it with the standard curve, which solves the gap in the existing technology of lacking dynamic data collection of the locking mechanism. It can accurately evaluate faults such as thread wear, lubrication failure or deformation of the holder 3 to avoid mold leakage, flash and production interruption. The parting surface sealing detection module injects a small amount of low-pressure gas after the mold is closed and locked before pouring, and monitors the pressure decay rate and ultrasonic signal, which solves the subjective problem of the existing technology relying on manual visual inspection of the sealing status of the parting surface. The sealing status can be quantitatively evaluated to predict the risk of flash and reduce the subsequent cleaning workload and cost.

[0031] Example 2 Based on Example 1, the mold cavity online monitoring module includes: A mold cavity point cloud data acquisition submodule is used to scan the mold cavity of the aluminum alloy tensile bar mold using a laser probe to obtain point cloud data of the mold cavity of the aluminum alloy tensile bar mold; The digital twin comparison submodule is used to compare the point cloud data of the mold cavity with the preset standard mold cavity digital twin model to generate a three-dimensional chromatographic deviation map of the cavity comparison; The comparison analysis submodule is used to analyze the inner cavity comparison three-dimensional chromatogram deviation map to obtain the shape accuracy analysis results and surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold; Among them, the shape accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold include the circumferential cylindricity of the inner cavity and the flatness analysis results of the top and bottom surfaces; The surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold include the wear degree, crack pitting degree and residue adhesion degree analysis results of the inner cavity surface.

[0032] In this embodiment, the point cloud data of the mold cavity of the mold for aluminum alloy tensile rods is a set of three-dimensional coordinates of each point on the surface of the mold cavity. These three-dimensional coordinate data record the specific position of each sampling point on the surface of the mold cavity in space, thereby constructing the shape contour of the mold cavity in the form of points.

[0033] In this embodiment, the preset standard mold cavity digital twin model is a pre-set digital model that contains information such as the ideal geometric shape, dimensional parameters, and surface features of the mold cavity. This model serves as a standard reference for the mold cavity and represents the ideal state that the mold cavity for aluminum alloy tensile bars should achieve in design. It is used for comparison and analysis with the actual collected mold cavity point cloud data. The preset standard mold cavity digital twin model contains information such as the ideal geometric shape, dimensional parameters, and surface features of the mold cavity.

[0034] In this embodiment, the three-dimensional chromatographic deviation diagram of the inner cavity comparison is generated by the chromatographic generation unit in the digital twin comparison submodule, based on the three-dimensional spatial deviation data between the mold inner cavity point cloud data obtained by the deviation calculation unit and the corresponding points of the standard mold inner cavity digital twin model. Different colors are assigned according to different deviation ranges to generate a three-dimensional image. This diagram can intuitively display the difference between the actual state of the mold inner cavity and the ideal standard model, and different colors correspond to different degrees of deviation.

[0035] The working principle and beneficial effects of the above technical solution are as follows: During operation, the mold cavity point cloud data acquisition submodule uses a laser probe to scan the mold cavity of the aluminum alloy tensile bar mold to obtain point cloud data. The digital twin comparison submodule compares the point cloud data with a preset standard mold cavity digital twin model to generate a cavity comparison three-dimensional chromatogram deviation map. The comparison analysis submodule analyzes the deviation map to obtain analysis results of the mold cavity's shape accuracy (circumferential cylindricity, top and bottom surface flatness) and surface accuracy (wear, crack pitting, and residue adhesion). The present invention obtains point cloud data of the three-dimensional coordinates of each point on the mold cavity surface through laser probe scanning, providing an accurate data basis for subsequent analysis, and uses the digital twin comparison submodule to compare the point cloud data with the standard model. The three-dimensional chromatogram deviation map is generated through deviation calculation to intuitively display the difference between the actual state and the ideal state of the mold cavity. The comparative analysis submodule extracts coordinate data based on the deviation map, calculates shape accuracy indicators such as cylindricity and flatness, identifies wear areas, cracks and residues through image recognition algorithms, and calculates surface accuracy indicators such as wear degree, crack pitting degree and residue adhesion degree, providing a detailed technical basis for mold repair and maintenance, and improving mold detection accuracy and efficiency.

[0036] Example 3 Based on Example 2, the mold cavity point cloud data acquisition submodule includes: A laser emitting unit, used for emitting a laser beam toward an inner cavity of a mold for an aluminum alloy tensile bar; A laser receiving unit is used to receive the laser beam reflected from the inner surface of the mold and obtain the reflection information of the laser beam on the inner surface of the mold; Position sensing unit, used to obtain the spatial position information of the laser probe in real time during the scanning process; The data processing unit is used to calculate the three-dimensional coordinates of each point on the mold cavity surface based on the information obtained by the laser emitting unit, the laser receiving unit and the position sensing unit, and generate point cloud data of the mold cavity of the aluminum alloy tensile bar mold.

[0037] In this embodiment, the laser beam is used as a scanning light source, and its parameters such as wavelength and intensity can be adjusted according to the mold material and the surface characteristics of the inner cavity.

[0038] In this embodiment, the spatial position information of the laser probe includes the three-dimensional coordinates (x, y, z) of the laser probe and the attitude angle ( ), where (x, y, z) represents the specific position of the laser probe in space, ( ) represents the rotation angle of the laser probe around the three coordinate axes.

[0039] In this embodiment, the three-dimensional coordinates of each point on the inner surface of the mold cavity are calculated using the triangulation principle. The triangulation principle formula is: ;in, is the distance from the measured point to the laser probe, is the baseline distance between the laser emitting unit and the laser receiving unit, f is the focal length of the laser receiving unit, and s is the offset of the laser beam on the imaging surface of the laser receiving unit.

[0040] The working principle and beneficial effects of the above technical solution are as follows: during operation, the laser emitting unit emits a laser beam into the mold cavity, the laser receiving unit receives the laser beam reflected by the mold cavity surface and obtains reflection information, the position sensing unit obtains the spatial position information (3D coordinates and attitude angle) during the laser probe scanning process in real time, and the data processing unit calculates the 3D coordinates of each point on the mold cavity surface based on the above information using the principle of triangulation to generate point cloud data; Based on the triangulation principle formula, the present invention uses the laser emission and receiving units and the position sensing unit to work together to accurately calculate the three-dimensional coordinates of each point on the mold cavity surface, generate high-resolution point cloud data, ensure the accuracy and reliability of the point cloud data, provide high-quality data support for digital twin comparison and subsequent analysis, and improve the detection accuracy of the mold cavity.

[0041] Example 4 Based on Example 2, the digital twin comparison submodule includes: Model import unit, used to import the preset standard mold cavity digital twin model; Point cloud registration unit, used to spatially align the point cloud data of the mold cavity with the standard mold cavity digital twin model; Deviation calculation unit, used to calculate the three-dimensional spatial deviation between the mold cavity point cloud data and the corresponding points of the standard mold cavity digital twin model. The three-dimensional spatial deviation includes position deviation and normal deviation; The chromatogram generating unit is used to assign different colors according to different deviation ranges based on the position deviation and normal deviation data obtained by the deviation calculating unit, and generate a three-dimensional chromatogram deviation map of the inner cavity contrast.

[0042] In this embodiment, the point cloud data of the mold cavity is spatially aligned with the standard mold cavity digital twin model, and the iterative closest point algorithm is used for point cloud registration. The objective function is: ;in, is the registration error, n is the number of points in the point cloud data, is the i-th point in the mold cavity point cloud data, For the standard mold cavity digital twin model The corresponding nearest point.

[0043] In this embodiment, the point in the mold cavity point cloud data is ( ), the corresponding point in the digital twin model of the standard mold cavity is , and Position deviation The calculation formula is as follows: ;in, are the x, y, and z coordinates of the i-th point in the mold cavity point cloud data in three-dimensional space, They are the points in the digital twin model of the standard mold cavity and The corresponding x, y, and z coordinates of the i-th point in three-dimensional space, Represents the position deviation of the i-th point, which reflects the difference in spatial distance between the actual mold cavity point and the corresponding point of the standard model.

[0044] In this embodiment, ( ) corresponds to the normal vector ; The corresponding normal vector ; and Normal deviation The calculation formula is: ;in, , represents the dot product of two normal vectors, , , respectively represent the modulus lengths of the two normal vectors, Represents the normal vector deviation of the i-th point. The value range is between [0,2]. The closer the value is to 0, the closer the directions of the two normal vectors are, that is, the smaller the normal deviation is. The closer the value is to 2, the greater the difference in the directions of the two normal vectors is, and the larger the normal deviation is.

[0045] The working principle and beneficial effects of the above technical solution are as follows: During operation, the model import unit imports a preset digital twin model of the standard mold cavity, the point cloud registration unit uses an iterative closest point algorithm to align the mold cavity point cloud data with the standard model space, the deviation calculation unit calculates the three-dimensional spatial deviation (including position deviation and normal deviation) between the point cloud data and the corresponding points of the standard model, and the chromatogram generation unit assigns colors according to different deviation ranges based on the deviation data to generate a three-dimensional chromatogram deviation map of the cavity comparison; The present invention achieves high-precision registration of point cloud data with the standard model through an iterative nearest point algorithm. The deviation between the point cloud and the standard model is comprehensively calculated through the position deviation formula and the normal deviation formula. The three-dimensional chromatogram deviation diagram intuitively displays the degree of deviation through color, facilitating the rapid identification of abnormal areas such as mold cavity wear and deformation, thereby improving the efficiency and intuitiveness of mold detection.

[0046] Example 5 Based on Example 2, the comparative analysis submodule includes: The shape accuracy calculation unit is used to extract the coordinate data of each point on the inner cavity surface of the mold based on the inner cavity comparison three-dimensional chromatogram deviation map, and calculate the cylindricity of the inner cavity circumference and the flatness of the top and bottom surfaces; Surface accuracy calculation unit, used to analyze the wear, crack pitting and residue adhesion of the mold cavity surface. It identifies surface wear areas, cracks and residues through image recognition algorithms and calculates the wear, crack pitting and residue adhesion of the mold cavity surface. The analysis output unit is used to output the shape accuracy analysis results and surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold based on the calculation results of the cylindricity of the inner cavity circumference, the flatness of the top and bottom surfaces, the wear degree of the mold inner cavity surface, the crack pitting degree and the residue adhesion degree.

[0047] In this embodiment, the least squares method is used to fit the cylindrical surface and the plane to calculate the cylindricity of the inner cavity in the circumferential direction and the flatness of the top and bottom surfaces, including: ;in, is the cylindricity of the inner cavity circumference, is the distance from the i-th point on the mold cavity surface to the axis of the fitted cylindrical surface, The maximum distance from the point to the axis of the fitted cylinder calculated for all parameters, The minimum value of the distance to the axis of the fitted cylinder among the points calculated for all parameters; ; is the flatness of the top or bottom surface of the inner cavity. is the distance from the i-th point on the top or bottom surface of the mold cavity to the fitting plane, The maximum value of the distance to the fitted plane among the points calculated for all parameters, The minimum of the distances to the fitted plane among the points calculated for all parameters.

[0048] In this embodiment, methods such as area ratio and length statistics are used to quantify the degree of wear, crack pitting, and residue adhesion, including: ;in, is the wear degree of the mold inner cavity surface, that is, the percentage of the mold inner cavity surface wear area to the entire inner cavity surface. It represents the area of ​​the wear area on the inner cavity surface of the mold identified from the inner cavity contrast 3D chromatogram deviation map by the image recognition algorithm. Represents the total surface area of ​​the mold cavity; ;in, The crack pitting degree of the mold inner cavity surface is used to measure the degree of cracks and pitting on the mold inner cavity surface. represents the total length of cracks and pitting areas identified from the inner cavity contrast 3D chromatographic deviation map by the image recognition algorithm, Indicates the total length of the corresponding part of the mold cavity surface under ideal conditions; ;in, The percentage of residue adhesion area on the mold cavity surface to the entire cavity surface is It represents the area of ​​the residue attachment region on the mold inner cavity surface identified by the image recognition algorithm from the inner cavity contrast 3D chromatogram deviation map. Represents the total surface area of ​​the mold cavity.

[0049] In this embodiment, based on the calculation results of the circumferential cylindricity of the inner cavity, the flatness of the top and bottom surfaces, the wear of the mold inner cavity surface, the crack pitting degree and the residue adhesion degree, the shape accuracy analysis results and surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile rod mold are output, that is, the calculation results of the circumferential cylindricity of the inner cavity, the flatness of the top and bottom surfaces, the wear of the mold inner cavity surface, the crack pitting degree and the residue adhesion degree are compared with their corresponding preset values, and whether the circumferential cylindricity of the inner cavity, the flatness of the top and bottom surfaces, the wear of the mold inner cavity surface, the crack pitting degree and the residue adhesion degree are qualified are output.

[0050] The working principle and beneficial effects of the above technical solution are as follows: during operation, the shape accuracy calculation unit extracts the coordinate data of each point on the mold inner cavity surface based on the inner cavity comparison three-dimensional chromatographic deviation map, fits the cylindrical surface and the plane through the least squares method, and calculates the circumferential cylindricity and the top and bottom surface flatness. The surface accuracy calculation unit identifies surface wear areas, cracks and residues through an image recognition algorithm, and calculates the wear degree, crack pitting degree and residue adhesion degree using methods such as area ratio and length statistics. The analysis output unit compares the calculation results with preset values ​​and outputs the shape accuracy and surface accuracy analysis results. The present invention uses the least squares method to fit cylindrical surfaces and planes, and accurately quantifies the shape accuracy of the mold cavity through the cylindricity formula and the flatness formula; accurately evaluates the surface accuracy through the wear degree formula, the crack pitting degree formula, and the residue adhesion degree formula, and compares the calculated results with the preset values ​​to output a conclusion on whether the test is qualified, providing a clear basis for mold maintenance and replacement, and improving the scientific nature of the detection.

[0051] Example 6 Based on Example 1, the locking mechanism health status diagnosis module includes: The locking mechanism data acquisition submodule is used to synchronously collect the torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t); The curve feature extraction submodule is used to extract the collected torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t) are preprocessed and feature extracted to obtain characteristic parameters. The characteristic parameters include the slope of the torque-angle curve in the stable stage, that is, the curve stiffness K, the time from initial preload to reaching the target pressure, that is, the pressure buildup time , torque rise rate r; The health status assessment submodule is used to compare and analyze the extracted characteristic parameters with the corresponding preset standard curve template to evaluate the health status of the locking mechanism.

[0052] In this embodiment, the torque-angle curve data T( ) reflects the relationship between the rotation angle of bolt 5 and the torque; The pressure-time curve data P(t) reflects the change of the contact pressure between the limit seat 4 and the clamping seat 3 over time during the locking process; The torque-time curve data T(t) reflects the relationship between the torque of bolt 5 and time, and assists in analyzing the torque change trend.

[0053] The working principle and beneficial effects of the above technical solution are as follows: when working, the data acquisition submodule collects the torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t), the curve feature extraction submodule preprocesses the data and extracts feature parameters, and the health status assessment submodule compares and analyzes the feature parameters with the preset standard curve template to assess the health status of the locking mechanism; Through real-time synchronous acquisition of the locking process data curve by multiple sensors, the relationship between the rotation angle and torque of the bolt 5, the change in contact pressure between the limit seat 4 and the holder 3 over time, and the trend of torque change over time are comprehensively recorded. The curve stiffness, pressure buildup time, and torque rise rate are extracted to provide key indicators for health status assessment. The extracted characteristic parameters are compared and analyzed with the corresponding preset standard curve template to promptly detect faults such as bolt 5 thread wear, lubrication failure, or holder 3 deformation, thereby ensuring the normal operation of the mold.

[0054] Example 7 Based on Example 6, the health status assessment submodule includes: Standard curve storage unit, used to store standard curves of different types of molds, including standard torque-angle curve, standard pressure-time curve and standard torque-time curve; Deviation analysis unit, used to calculate torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t) are respectively multi-dimensional deviation indicators with the standard torque-angle curve, standard pressure-time curve and standard torque-time curve. The multi-dimensional deviation indicators include curve stiffness deviation , Pressure build-up time deviation , Torque rise rate deviation and comprehensive deviation index ; Fault diagnosis unit, used to identify the fault type based on deviation indicators: >0.3 and When <-20%, the fault type is thread wear of bolt 5; When the value is less than -30% and the torque fluctuation is greater than 0.5, the fault type is lubrication failure; >50% and the maximum pressure in the pressure-time curve data is <0.8 When , the fault type is deformation of card seat 3.

[0055] In this embodiment, the standard torque-angle curve is: ; Standard pressure-time curve: ; Standard torque-time curve: ;in, is the independent variable of the standard torque-angle curve, , b and c are the binomial coefficient, the number of words in a single formula and the constant term of the standard torque-angle curve, which respectively represent the nonlinearity of the standard torque-angle curve, the slope of the linear section of the curve and the initial contact torque compensation value. is the standard maximum pressure, e is a natural number, and its value is 2.71. The rate constant is established for pressure, t in the standard pressure-time curve is the independent variable of the standard pressure-time curve, and t in the standard torque-time curve is the independent variable of the standard torque-time curve. is the standard maximum torque, is the time scale parameter, which controls the rising rate of the standard torque-time curve. is a shape parameter that controls the inflection point position of the standard torque-time curve.

[0056] In this embodiment, the curve stiffness deviation ;in, is the standard curve stiffness corresponding to the standard torque-angle curve; Pressure build-up time deviation ;in, The standard pressure establishment time corresponding to the standard pressure-time curve; Torque rise rate deviation ;in is the standard torque rising rate corresponding to the standard torque-time curve; Comprehensive Deviation Index ;in, 、 and They correspond to the weight values ​​of curve stiffness deviation, pressure buildup time deviation and torque rise rate deviation respectively.

[0057] The working principle and beneficial effects of the above technical solution are as follows: through the standard torque-angle curve, standard pressure-time curve and standard torque-time curve, a standard reference is provided for deviation analysis, the difference between the measured curve and the standard curve is quantified through the deviation calculation formula, the comprehensive deviation index integrates multi-dimensional deviations to improve the evaluation accuracy, and fault diagnosis rules are established based on the deviation index. Combined with the working characteristics of components such as the bolt 5, the limit seat 4, and the clamping seat 3, the fault type is accurately identified, precise guidance is provided for repair and maintenance, and the intelligent level of mold fault diagnosis is improved.

[0058] Example 8 Based on Example 1, the parting surface sealing detection module includes: The gas path sensing unit submodule is used to install a pressure sensor and an integrated ultrasonic probe array on the dedicated gas path interface on the mold; The gas injection control submodule is used to select the type of trace low-pressure gas injected into the mold cavity, and to adjust the injected gas pressure and control the gas injection flow rate during the injection process; The mold cavity data acquisition and monitoring submodule is used to collect the gas pressure data and ultrasonic probe array signals in the mold cavity in real time; The sealing performance analysis submodule is used to calculate the gas pressure decay rate and analyze the ultrasonic signal to obtain the sealing status evaluation results of the mold parting surface.

[0059] The working principle and beneficial effects of the above technical solution are as follows: during operation, the gas path sensing unit submodule installs a pressure sensor and an integrated ultrasonic probe array on the mold's dedicated gas path interface; the gas injection control submodule selects compressed air or inert gas as a trace low-pressure gas, adjusts the injection pressure and controls the flow; the data acquisition and monitoring submodule collects gas pressure data and ultrasonic probe array signals in the mold cavity in real time; and the sealing performance analysis submodule calculates the pressure decay rate and analyzes the ultrasonic signal to obtain the sealing status evaluation result of the parting surface; By integrating an ultrasonic probe array and installing a pressure sensor near the mold parting surface, real-time monitoring of gas escape signals and pressure changes in the cavity is achieved. A trace amount of low-pressure gas is selected and the injection flow is controlled to ensure that the detection process is safe and does not affect the mold structure. Through pressure decay rate calculation and ultrasonic signal analysis, microscopic leakage channels caused by deformation, wear or insufficient locking of the parting surface are determined, and the risk of flash during casting is predicted. The pressure decay rate reflects the sealing performance. When the ultrasonic signal intensity is greater than the preset value, it is determined that there is a leak, thereby improving the sensitivity of parting surface sealing detection and reducing the production of defective products.

[0060] Example 9 Based on Example 8, the sealing performance analysis submodule includes: Pressure decay analysis unit for time-based and The gas pressure value in the mold cavity collected at all times and Calculating the pressure decay rate ; An ultrasonic signal analysis unit is used to compare the collected ultrasonic signal intensity with the preset ultrasonic signal intensity to determine whether there is gas leakage on the parting surface; The sealing status evaluation unit is used to comprehensively analyze the pressure decay rate and ultrasonic signal analysis results to classify the sealing status of the mold parting surface into three levels: good, general, and poor.

[0061] In this embodiment, the pressure decay rate .

[0062] In this embodiment, the collected ultrasonic signal intensity is compared with the preset ultrasonic signal intensity to determine whether gas escape exists on the parting surface. Specifically, when the collected ultrasonic signal intensity is greater than the preset ultrasonic signal intensity, it is determined that gas escape exists on the parting surface near the probe.

[0063] In this embodiment, the sealing status of the mold parting surface is divided into three levels: good, fair, and poor, based on the comprehensive analysis results of the pressure decay rate and the ultrasonic signal. Specifically: If the pressure decay rate is less than the first preset pressure decay rate and there is no abnormality in the ultrasonic signal, the assessment is good; If the pressure decay rate is between the first preset pressure decay rate and the second preset pressure decay rate or there is a slight ultrasonic signal abnormality, the assessment is fair; If the pressure decay rate is greater than a second preset pressure decay rate or the ultrasonic signal is obviously abnormal, the evaluation is poor.

[0064] The working principle and beneficial effects of the above technical solution are as follows: the present invention quantifies the degree of gas pressure attenuation through the pressure decay rate formula, intuitively reflects the sealing performance of the parting surface, and ultrasonic signal analysis accurately locates the gas escape position by comparing the signal intensity with the preset threshold. The sealing status is evaluated according to the preset grade standard based on the combined results of the two, providing a clear basis for mold maintenance. For example, when the pressure decay rate is too fast or the ultrasonic signal is abnormal, the mold locking mechanism can be adjusted in time or the parting surface can be repaired to avoid the generation of flash during casting, thereby improving product quality and production efficiency.

[0065] Example 10 Based on Example 1, the mold inspection report output module includes: The data integration submodule is used to integrate the shape accuracy analysis results and surface accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold, the health status assessment results of the locking mechanism, and the sealing status results of the parting surface; The report output submodule is used to output the data integrated by the data integration submodule in the form of charts.

[0066] The working principle and beneficial effects of the above technical solution are as follows: by integrating the test results of the mold cavity online monitoring, locking mechanism health diagnosis and parting surface sealing detection module, the mold status data can be centrally managed, and the data can be converted into graphical output to improve the intuitiveness and readability of the test results, so that operators can quickly grasp the overall status of the mold, and provide comprehensive data support for mold maintenance plan formulation, repair strategy optimization and scrapping decision-making. For example, mold grinding or replacement can be arranged according to the degree of wear and crack pitting, the lubrication plan can be adjusted according to the type of locking mechanism failure, and whether to re-lock the mold can be decided based on the parting surface sealing status assessment results, thereby improving the efficiency of mold management throughout its life cycle.

[0067] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A mold detection device for aluminum alloy tensile bars, characterized by: include: The mold cavity online monitoring module is used to obtain the shape accuracy analysis results and surface accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold based on the point cloud data of the mold cavity and the preset standard mold cavity digital twin model; The locking mechanism health status diagnosis module is used to collect the data curve of the locking mechanism during the locking process, and compare the data curve of the locking mechanism during the locking process with the standard curve to evaluate the health status of the locking mechanism; The parting surface sealing detection module is used to inject a small amount of low-pressure gas into the closed mold cavity after the mold is closed and locked and before pouring. It monitors the pressure decay rate of the mold cavity and the detection results of the ultrasonic probe to determine the sealing status of the parting surface; The mold inspection report output module is used to obtain inspection data from the mold cavity online monitoring module, the locking mechanism health status diagnosis module, and the parting surface sealing detection module, integrate and process the data, and generate an inspection report.

2. The mold detection device for aluminum alloy tensile bars according to claim 1, characterized in that: The mold cavity online monitoring module includes: A mold cavity point cloud data acquisition submodule is used to scan the mold cavity of the aluminum alloy tensile bar mold using a laser probe to obtain point cloud data of the mold cavity of the aluminum alloy tensile bar mold; The digital twin comparison submodule is used to compare the point cloud data of the mold cavity with the preset standard mold cavity digital twin model to generate a three-dimensional chromatographic deviation map of the cavity comparison; The comparison analysis submodule is used to analyze the inner cavity comparison three-dimensional chromatogram deviation map to obtain the shape accuracy analysis results and surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold; Among them, the shape accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold include the circumferential cylindricity of the inner cavity and the flatness analysis results of the top and bottom surfaces; The surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold include the wear degree, crack pitting degree and residue adhesion degree analysis results of the inner cavity surface.

3. The mold detection device for aluminum alloy tensile bars according to claim 2, characterized in that: The mold cavity point cloud data acquisition submodule includes: A laser emitting unit, used for emitting a laser beam toward an inner cavity of a mold for an aluminum alloy tensile bar; A laser receiving unit is used to receive the laser beam reflected from the inner surface of the mold and obtain the reflection information of the laser beam on the inner surface of the mold; Position sensing unit, used to obtain the spatial position information of the laser probe in real time during the scanning process; The data processing unit is used to calculate the three-dimensional coordinates of each point on the mold cavity surface based on the information obtained by the laser emitting unit, the laser receiving unit and the position sensing unit, and generate point cloud data of the mold cavity of the aluminum alloy tensile bar mold.

4. The mold detection device for aluminum alloy tensile bars according to claim 2, characterized in that: Digital twin comparison submodule, including: Model import unit, used to import the preset standard mold cavity digital twin model; Point cloud registration unit, used to spatially align the point cloud data of the mold cavity with the standard mold cavity digital twin model; Deviation calculation unit, used to calculate the three-dimensional spatial deviation between the mold cavity point cloud data and the corresponding points of the standard mold cavity digital twin model. The three-dimensional spatial deviation includes position deviation and normal deviation; The chromatogram generating unit is used to assign different colors according to different deviation ranges based on the position deviation and normal deviation data obtained by the deviation calculating unit, and generate a three-dimensional chromatogram deviation map of the inner cavity contrast.

5. The mold detection device for aluminum alloy tensile bars according to claim 2, characterized in that: Comparative analysis submodule, including: The shape accuracy calculation unit is used to extract the coordinate data of each point on the inner cavity surface of the mold based on the inner cavity comparison three-dimensional chromatographic deviation map, and calculate the cylindricity of the inner cavity circumference and the flatness of the top and bottom surfaces; Surface accuracy calculation unit, used to analyze the wear, crack pitting and residue adhesion of the mold cavity surface. It identifies surface wear areas, cracks and residues through image recognition algorithms and calculates the wear, crack pitting and residue adhesion of the mold cavity surface. The analysis output unit is used to output the shape accuracy analysis results and surface accuracy analysis results of the mold inner cavity of the current aluminum alloy tensile bar mold based on the calculation results of the cylindricity of the inner cavity circumference, the flatness of the top and bottom surfaces, the wear degree of the mold inner cavity surface, the crack pitting degree and the residue adhesion degree.

6. The mold detection device for aluminum alloy tensile bars according to claim 1, characterized in that: The locking mechanism health status diagnosis module includes: The locking mechanism data acquisition submodule is used to synchronously collect torque-angle curve data T( ), pressure-time curve data P(t) and torque-time curve data T(t); The curve feature extraction submodule is used to extract the collected torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t) are preprocessed and feature extracted to obtain characteristic parameters. The characteristic parameters include the slope of the torque-angle curve in the stable stage, that is, the curve stiffness K, the time from initial preload to reaching the target pressure, that is, the pressure buildup time , torque rise rate r; The health status assessment submodule is used to compare and analyze the extracted characteristic parameters with the corresponding preset standard curve template to evaluate the health status of the locking mechanism.

7. The mold detection device for aluminum alloy tensile bars according to claim 6, characterized in that: The health status assessment submodule includes: The standard curve storage unit is used to store standard curves of different types of molds, including standard torque-angle curve, standard pressure-time curve and standard torque-time curve: Deviation analysis unit, used to calculate torque-angle curve data T ( ), pressure-time curve data P(t) and torque-time curve data T(t) are respectively multi-dimensional deviation indicators with the standard torque-angle curve, standard pressure-time curve and standard torque-time curve. The multi-dimensional deviation indicators include curve stiffness deviation , Pressure build-up time deviation , Torque rise rate deviation and comprehensive deviation index ; Fault diagnosis unit, used to identify the fault type based on deviation indicators: >0.3 and When <-20%, the fault type is bolt (5) thread wear; When the value is less than -30% and the torque fluctuation is greater than 0.5, the fault type is lubrication failure; >50% and the maximum pressure in the pressure-time curve data is <0.8 When , the fault type is the deformation of the card seat (3), where This is the standard maximum pressure.

8. The mold detection device for aluminum alloy tensile bars according to claim 1, characterized in that: Parting surface sealing detection module includes: The gas path sensing unit submodule is used to install a pressure sensor and an integrated ultrasonic probe array on the dedicated gas path interface on the mold; The gas injection control submodule is used to select the type of trace low-pressure gas injected into the mold cavity, and to adjust the injected gas pressure and control the gas injection flow rate during the injection process; The mold cavity data acquisition and monitoring submodule is used to collect the gas pressure data and ultrasonic probe array signals in the mold cavity in real time; The sealing performance analysis submodule is used to calculate the gas pressure decay rate and analyze the ultrasonic signal to obtain the sealing status evaluation results of the mold parting surface.

9. The mold detection device for aluminum alloy tensile bars according to claim 8, characterized in that: The sealing performance analysis submodule includes: Pressure decay analysis unit for time-based and The gas pressure value in the mold cavity collected at all times and Calculating the pressure decay rate ; An ultrasonic signal analysis unit is used to compare the collected ultrasonic signal intensity with the preset ultrasonic signal intensity to determine whether there is gas leakage on the parting surface; The sealing status evaluation unit is used to comprehensively analyze the pressure decay rate and ultrasonic signal analysis results to classify the sealing status of the mold parting surface into three levels: good, general, and poor.

10. The mold detection device for aluminum alloy tensile bars according to claim 1, characterized in that: The mold inspection report output module includes: The data integration submodule is used to integrate the shape accuracy analysis results and surface accuracy analysis results of the mold cavity of the current aluminum alloy tensile bar mold, the health status assessment results of the locking mechanism, and the sealing status results of the parting surface; The report output submodule is used to output the data integrated by the data integration submodule in the form of charts.

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