Simulation analysis-based small lifting hook forging process optimization system and method

Abstract

The invention relates to the technical field of forging process optimization, and particularly discloses a small lifting hook forging process optimization system and method based on simulation analysis. Comprising a lifting hook three-dimensional model building module, a forging process parameter monitoring module, a lifting hook deformation state monitoring module, a lifting hook finished product quality analysis module, a casting process parameter optimization module and a lifting hook forging simulation analysis module. According to the method, the forging three-dimensional model of the target lifting hook is constructed, the forging process coincidence coefficient, the lifting hook deformation coefficient and the finished product quality evaluation coefficient are analyzed, then the lifting hook casting process is comprehensively analyzed and optimized, and finally simulation verification is conducted on an optimization scheme through finite element analysis software; by optimizing the forging process of the small and medium-sized lifting hooks and combining simulation analysis, the forging quality and the production efficiency of the lifting hooks are effectively improved, the production cost is reduced, a reliable process method is provided for production of the small-sized lifting hooks, and certain popularization and application value is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of forging process optimization, and in particular to a small hook forging process optimization system and method based on simulation analysis. BACKGROUND

[0002] In the field of industrial manufacturing, small hooks, as key components of hoisting equipment and engineering machinery, directly affect the safety and efficiency of operation. With the development of manufacturing towards high precision and intelligentization, the traditional experience-driven forging process has been difficult to meet the stringent requirements of small hooks on mechanical properties, dimensional accuracy and surface quality. Problems such as improper process parameter control, uneven deformation and stress distribution, and high defect rate of finished products frequently occur in the forging process, resulting in low product qualification rate and rising production cost, and it is urgent to realize process optimization and quality control through digital and intelligent technology.

[0003] The traditional small hook forging process optimization system has significant shortcomings. In the heating link, due to the lack of precise temperature control means, the billet is often heated unevenly, which poses a quality risk for subsequent forging; in the forming and shaping process, it is difficult to achieve high-precision control of deformation and stress distribution, which makes it easy for internal defects such as micro-cracks to occur in the billet, seriously weakening the strength and toughness of the hook. At the same time, the traditional method lacks precise simulation and real-time monitoring of the forging process, making it difficult to uncover the internal relationship between process parameters and hook quality, and making it difficult for process parameter settings to adapt to different materials and working conditions, further exacerbating internal organization and surface quality problems. In addition, relying on manual sampling and detection methods cannot achieve full-process and high-precision monitoring of hook deformation, making it difficult to detect abnormal deformation and stress, seriously affecting product consistency; the manual visual inspection combined with caliper measurement method for finished product quality evaluation not only has strong subjectivity and low efficiency, but also causes incomplete defect identification and lagging size deviation correction, making it difficult to effectively guide process optimization, ultimately resulting in low production efficiency, poor product quality stability, and resource waste and production cycle extension. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a small hook forging process optimization system and method based on simulation analysis to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme: a small hook forging process optimization system based on simulation analysis, comprising: a hook three-dimensional model establishment module, a forging process parameter monitoring module, a hook deformation state monitoring module, a hook finished product quality analysis module, a casting process parameter optimization module and a hook forging simulation analysis module.

[0006] The hook three-dimensional model establishment module is used to construct a forging three-dimensional model of the target hook through a three-dimensional design software; Forging process parameter monitoring module: Based on the forging 3D model of the target hook, it monitors the forging process parameters in real time, builds a forging process compliance model, and analyzes the forging process to obtain the forging process compliance coefficient corresponding to the target hook. The process parameters include forging temperature, forging pressure, and die movement speed. Hook deformation state monitoring module: used to monitor the hook deformation parameters of the target hook in real time during the forging process, establish a hook deformation coefficient model, and analyze and obtain the hook deformation coefficient corresponding to the target hook. The hook deformation parameters include hook deformation and stress; Finished hook quality analysis module: The industrial camera is used to capture the surface of the target hook to obtain the surface image. The quality of the target hook is analyzed based on the finished hook size to obtain the corresponding finished hook quality assessment coefficient. Casting process parameter optimization module: Based on the forging process compliance coefficient, hook deformation coefficient and finished product quality assessment coefficient corresponding to the target hook, the casting process of the target hook is comprehensively analyzed and optimized based on the comprehensive analysis results; Hook forging simulation analysis module: Use finite element analysis software to simulate the optimized forging process, and combine it with the forging 3D model to analyze the feasibility of casting process optimization and output the feasibility analysis results.

[0007] Preferably, the execution method of the hook three-dimensional model building module is as follows: Obtain the technical specification data of the target hook, create a reference plane in the 3D design software, establish a coordinate system, import the technical specification data of the target hook into the coordinate system of the 3D design software, draw the hook contour line and perform a rotation scanning operation to generate a basic entity, then add forging process features including forging allowance, flash groove and positioning groove, build a forged 3D model of the target hook, and finally convert the complete forged 3D model into a standard format and save it to the system specified path.

[0008] Preferably, the forging process parameter monitoring module is implemented as follows: Based on the forging 3D model of the target hook, the forging process parameters of the target hook are monitored in real time. The process parameters include forging temperature, forging pressure and die movement speed. Temperature sensors, pressure sensors and speed sensors are installed on the forging equipment to collect the forging temperature T, forging pressure P and die movement speed V of the target hook in real time. Obtain the standard range of forging process parameters of the target hook from the management database, wherein the standard range of forging process parameters includes the standard range of forging temperature. , Forging pressure standard range And the standard range of mold movement speed ; Based on the real-time monitoring of the forging process parameters of the target hook and the standard range of the forging process parameters, the forging process parameter deviation of the target hook is calculated. The forging process parameter deviation of the target hook includes the forging temperature deviation, the forging pressure deviation and the die movement speed deviation. Based on the forging process parameter deviation, a forging process compliance model is constructed, and the forging process is analyzed to obtain the forging process compliance coefficient corresponding to the target hook. Based on the forging process compliance coefficient corresponding to the target hook, it is judged whether the forging process meets the requirements.

[0009] Preferably, the hook deformation state monitoring module is implemented as follows: Real-time monitoring of hook deformation parameters during the forging process of the target hook to obtain the hook deformation and stress , normalize the obtained hook deformation parameters, and obtain the standard deformation of the target hook from the management database and standard stress , establish the hook deformation coefficient model, and obtain the hook deformation variables ,stress , standard deformation and standard stress Import the hook deformation coefficient model and calculate the hook deformation coefficient corresponding to the target hook.

[0010] Preferably, the execution mode of the hook finished product quality analysis module is as follows: The surface of the target hook product is photographed by an industrial camera to obtain the surface image of the target hook product, the crack rate Dr of the surface image of the target hook product is extracted, and the finished product size deviation rate Dd of the target hook product is calculated. A quality assessment model for the hook product is established, and the crack rate Dr and size deviation rate Dd of the surface image of the target hook product are respectively imported into the hook product quality assessment model, and the finished product quality assessment coefficient corresponding to the target hook is calculated. The finished product quality of the target hook is evaluated based on the finished product quality assessment coefficient, and the finished product quality assessment result of the target hook is output.

[0011] Preferably, the crack rate of the target hook finished product surface image is obtained by: importing the target hook finished product surface image into the edge detection algorithm, identifying the crack edge line in the target hook surface image, using the threshold segmentation technology to convert the target hook finished product surface image into a binary image, with the crack area being white and the background being black, and counting the number of pixels in the crack area Nc And the number of pixels in the image area of ​​the finished hook surface Nt , substitute it into the crack rate formula to obtain the crack rate of the target hook finished product surface image Dr .

[0012] Preferably, the execution mode of the casting process parameter optimization module is as follows: The forging process compliance coefficient CPC, hook deformation coefficient HDC and finished product quality evaluation coefficient QEC corresponding to the target hook are read, and by establishing a comprehensive evaluation model for the casting process of the target hook, the comprehensive evaluation index of the casting process corresponding to the target hook is calculated. Based on the comprehensive evaluation index of the casting process, a comprehensive analysis of the casting process of the target hook is performed, and the comprehensive analysis results are output. Based on the comprehensive analysis results, the corresponding optimization method is selected to optimize the casting process parameters of the target hook.

[0013] Preferably, the specific content of the comprehensive analysis of the target hook casting process based on the casting process comprehensive evaluation index is: comparing the casting process comprehensive evaluation index with the preset casting process comprehensive evaluation index threshold; if the casting process comprehensive evaluation index is greater than the preset casting process comprehensive evaluation index threshold, the target hook casting process is judged to be normal; otherwise, the target hook casting process is judged to be abnormal, and it is necessary to screen the corresponding optimization method to optimize the casting process parameters of the target hook.

[0014] To achieve the above objectives, the present invention provides the following technical solutions: a method for optimizing the forging process of a small hook based on simulation analysis, and implementing the above-mentioned system for optimizing the forging process of a small hook based on simulation analysis, comprising the following steps: S1: Establishing a 3D model of the hook: Constructing a forging 3D model of the target hook using 3D design software; S2: Monitoring forging process parameters: Based on the forging 3D model of the target hook, the forging process parameters are monitored in real time, a forging process compliance model is constructed, and the forging process is analyzed to obtain the forging process compliance coefficient corresponding to the target hook. The process parameters include forging temperature, forging pressure, and die movement speed. S3: Hook deformation state monitoring: real-time monitoring of the hook deformation parameters during the forging process of the target hook, establishment of a hook deformation coefficient model, and analysis to obtain the hook deformation coefficient corresponding to the target hook. The hook deformation parameters include hook deformation and stress. S4: Finished hook quality analysis: The surface of the target hook is photographed by an industrial camera to obtain the surface image of the target hook. The quality of the target hook is analyzed based on the finished hook size to obtain the finished product quality assessment coefficient corresponding to the target hook. S5: Casting process parameter optimization: Based on the forging process compliance coefficient, hook deformation coefficient and finished product quality assessment coefficient corresponding to the target hook, the casting process of the target hook is comprehensively analyzed and the casting process of the target hook is optimized based on the comprehensive analysis results; S6: Hook forging simulation analysis: Use finite element analysis software to simulate the optimized forging process, and combine it with the forging 3D model to analyze the feasibility of casting process optimization and output the feasibility analysis results.

[0015] As described above, the present invention provides a small hook forging process optimization system and method based on simulation analysis, which has at least the following beneficial effects: The present invention provides a small hook forging process optimization system and method based on simulation analysis. The system constructs a three-dimensional forging model of a target hook, monitors the forging process parameters in real time based on the three-dimensional forging model of the target hook, constructs a forging process compliance model, analyzes the forging process to obtain the forging process compliance coefficient corresponding to the target hook, and establishes a hook deformation coefficient model by real-time monitoring of the hook deformation parameters during the forging process of the target hook, and analyzes and obtains the hook deformation coefficient corresponding to the target hook; then, an industrial camera is used to photograph the surface of the target hook product to obtain the surface image of the target hook, and the quality of the target hook product is analyzed in combination with the size of the hook product to obtain the finished product quality evaluation coefficient corresponding to the target hook; based on the forging process compliance coefficient, hook deformation coefficient and finished product quality evaluation coefficient corresponding to the target hook, a comprehensive analysis is performed on the casting process of the target hook, and then the casting process is optimized; finally, the optimization scheme is simulated and verified using finite element analysis software to ensure the feasibility and effectiveness of the process adjustment. This invention breaks through the limitations of traditional experience-dependent process optimization. By optimizing the forging process of small and medium-sized hooks and combining it with simulation analysis, it effectively improves the forging quality and production efficiency of the hooks, significantly improves the forging quality stability and production efficiency of small hooks, reduces the scrap rate and production costs, and provides a reliable process method for the production of small hooks, which has certain promotion and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without inventive effort.

[0017] Figure 1 This is a structural schematic diagram of a small hook forging process optimization system based on simulation analysis in the present invention.

[0018] Figure 2 The figure is a flow chart of a method for optimizing the forging process of a small hook based on simulation analysis according to the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention. Example 1

[0020] See also Figure 1 As shown, the present invention provides a small hook forging process optimization system based on simulation analysis, including a hook three-dimensional model building module, a forging process parameter monitoring module, a hook deformation state monitoring module, a hook finished product quality analysis module, a casting process parameter optimization module and a hook forging simulation analysis module; Hook 3D model building module: used to build a forging 3D model of the target hook through 3D design software; In this embodiment, it should be specifically explained that the execution method of the hook three-dimensional model building module is as follows: Obtain technical specification data of the target hook, including but not limited to the standard model of the hook, external dimension data, material type code, and load-bearing grade value; create a reference plane in the 3D design software, establish a coordinate system, import the technical specification data of the target hook into the coordinate system of the 3D design software, draw the hook contour line and perform a rotation scanning operation to generate a basic entity; then add forging process features including forging allowance, flash groove and positioning groove, and construct a forged 3D model of the target hook; finally, convert the complete forged 3D model into the standard STEP format and save it to the system-specified path to provide a basic data model for subsequent process analysis.

[0021] Forging process parameter monitoring module: Based on the forging 3D model of the target hook, it monitors the forging process parameters in real time, builds a forging process compliance model, and analyzes the forging process to obtain the forging process compliance coefficient corresponding to the target hook. The process parameters include forging temperature, forging pressure, and die movement speed. In this embodiment, it should be specifically explained that the execution method of the forging process parameter monitoring module is as follows: Based on the forging 3D model of the target hook, the forging process parameters of the target hook are monitored in real time. The process parameters include forging temperature, forging pressure and die movement speed. Temperature sensors, pressure sensors and speed sensors are installed on the forging equipment to collect the forging temperature T, forging pressure P and die movement speed V of the target hook in real time. Obtain the standard range of forging process parameters of the target hook from the management database, wherein the standard range of forging process parameters includes the standard range of forging temperature. forging pressure standard range and die movement speed standard range ; Based on the real-time monitoring of the target hook forging process parameters and the forging process parameter standard range, the forging process parameter deviation of the target hook is calculated, including the forging temperature deviation, the forging pressure deviation and the die movement speed deviation, based on the forging process parameter deviation, the forging process compliance model is constructed, the forging process is analyzed to obtain the forging process compliance coefficient corresponding to the target hook, and whether the forging process meets the requirements is judged based on the forging process compliance coefficient corresponding to the target hook.

[0022] In this embodiment, it needs to be specifically pointed out that the specific content of judging whether the forging process meets the requirements based on the forging process compliance coefficient corresponding to the target hook is: reading the forging process compliance coefficient corresponding to the target hook, comparing the forging process compliance coefficient with the preset process compliance coefficient threshold, if the forging process compliance coefficient is greater than or equal to the preset process compliance coefficient threshold, it is judged that the forging process corresponding to the target hook meets the requirements; if the forging process compliance coefficient is less than the preset process compliance coefficient threshold, it is judged that the forging process corresponding to the target hook does not meet the requirements, the forging process corresponding to the target hook which does not meet the requirements is marked as the forging process judgment result, and the warning information is sent to the mobile device of the corresponding production management personnel.

[0023] The calculation formula of the forging temperature deviation is: Wherein, Td represents the forging temperature deviation of the target hook. The calculation formula of the forging pressure deviation is: Wherein, Pd represents the forging pressure deviation of the target hook. The calculation formula of the die movement speed deviation is: Wherein, Vd represents the forging temperature deviation of the target hook. The calculation formula of the forging process compliance model is: Wherein, CPC represents the forging process compliance coefficient corresponding to the target hook, respectively represent the preset maximum allowable forging temperature deviation, the maximum allowable forging pressure deviation and the maximum allowable die movement speed deviation.

[0024] In this embodiment, it needs to be specifically pointed out that the greater the forging temperature deviation of the target hook in the formula Td The greater 、 The greater the forging pressure deviation Pd The greater the die movement speed deviation Vd The smaller the forging process compliance coefficient of the target hook CPC The greater, indicating that the forging process of the target hook does not meet the requirements.

[0025] Hook deformation state monitoring module: used to monitor the hook deformation parameters of the target hook in real time during the forging process, establish a hook deformation coefficient model, and analyze and obtain the hook deformation coefficient corresponding to the target hook. The hook deformation parameters include hook deformation and stress; In this embodiment, it should be specifically explained that the execution method of the hook deformation state monitoring module is as follows: Real-time monitoring of hook deformation parameters during the forging process of the target hook to obtain the hook deformation and stress , normalize the obtained hook deformation parameters to eliminate the influence of dimension, and obtain the standard deformation of the target hook from the management database and standard stress , establish the hook deformation coefficient model, and obtain the hook deformation variables ,stress , standard deformation and standard stress Import the hook deformation coefficient model and calculate the hook deformation coefficient corresponding to the target hook.

[0026] The calculation formula of the hook deformation coefficient model is: , where HDC represents the hook deformation coefficient corresponding to the target hook, denote the weight coefficients of hook deformation and stress respectively, and .

[0027] It should be specifically noted that, in a specific embodiment, It can be set to 0.6, It can be set to 0.4. During the forging process of small hooks, deformation plays a key role in the hook's final dimensional accuracy and assembly adaptability. Dimensional deviations may cause the hook to fail to function properly, affecting its functionality, so a higher weight of 0.6 is assigned. While stress is also important, excessively high or low stress can affect the hook's mechanical properties and fatigue life. However, compared to the direct impact of deformation on dimensional accuracy, its importance is slightly less, so the weight is set to 0.4. This weight setting can highlight key influencing factors, more accurately evaluate the deformation state during the hook forging process, and provide an effective basis for process optimization.

[0028] Finished hook quality analysis module: The industrial camera is used to capture the surface of the target hook to obtain the surface image. The quality of the target hook is analyzed based on the finished hook size to obtain the corresponding finished hook quality assessment coefficient. In this embodiment, it should be specifically explained that the execution method of the hook finished product quality analysis module is as follows: The surface of the target hook product is photographed by an industrial camera to obtain the surface image of the target hook product, the crack rate Dr of the surface image of the target hook product is extracted, and the finished product size deviation rate Dd of the target hook product is calculated. A quality assessment model for the hook product is established, and the crack rate Dr and size deviation rate Dd of the surface image of the target hook product are respectively imported into the hook product quality assessment model, and the finished product quality assessment coefficient corresponding to the target hook is calculated. The finished product quality of the target hook is evaluated based on the finished product quality assessment coefficient, and the finished product quality assessment result of the target hook is output.

[0029] The calculation formula of the hook finished product quality assessment model is: , where QEC represents the finished product quality evaluation coefficient corresponding to the target hook, They represent the preset maximum allowable crack rate and the maximum finished product size deviation rate, respectively. Represents the exponential function.

[0030] In this embodiment, it should be specifically noted that the greater the crack rate Dr of the target hook finished product surface image in the formula, the greater the crack rate Dr 、 The larger the finished product size deviation rate Dd, the smaller the finished product quality evaluation coefficient QEC corresponding to the target hook, indicating that the finished product quality of the target hook is unqualified.

[0031] In this embodiment, it should be specifically explained that the method for obtaining the crack rate of the target hook finished product surface image is as follows: the target hook finished product surface image is imported into the edge detection algorithm, the crack edge line in the target hook surface image is identified, and the target hook finished product surface image is converted into a binary image using the threshold segmentation technology, with the crack area being white and the background being black, and the number of pixels in the crack area is counted. Nc And the number of pixels in the image area of ​​the finished hook surface Nt , substitute it into the crack rate formula Get the crack rate of the target hook finished product surface image Dr。

[0032] Casting process parameter optimization module: Based on the forging process compliance coefficient, hook deformation coefficient and finished product quality assessment coefficient corresponding to the target hook, the casting process of the target hook is comprehensively analyzed and optimized based on the comprehensive analysis results; In this embodiment, it should be specifically explained that the execution method of the casting process parameter optimization module is as follows: The forging process compliance coefficient CPC, hook deformation coefficient HDC, and finished product quality evaluation coefficient QEC corresponding to the target hook are read. By establishing a comprehensive casting process evaluation model for the target hook, the corresponding casting process comprehensive evaluation index of the target hook is calculated. Based on the casting process comprehensive evaluation index, a comprehensive analysis of the casting process of the target hook is conducted and the comprehensive analysis results are output. Based on the comprehensive analysis results, the corresponding optimization method is selected to optimize the casting process parameters of the target hook. The calculation formula of the casting process comprehensive evaluation model is: , where CEI represents the comprehensive evaluation index of the casting process corresponding to the target hook, They represent the weight coefficients of forging process compliance coefficient, hook deformation coefficient and finished product quality assessment coefficient respectively, and .

[0033] In this embodiment, it needs to be specifically explained that the specific content of the comprehensive analysis of the target hook casting process based on the casting process comprehensive evaluation index is: comparing the casting process comprehensive evaluation index with the preset casting process comprehensive evaluation index threshold. If the casting process comprehensive evaluation index is greater than the preset casting process comprehensive evaluation index threshold, the target hook casting process is judged to be normal; otherwise, the target hook casting process is judged to be abnormal, and it is necessary to screen the corresponding optimization method to optimize the casting process parameters of the target hook.

[0034] In this embodiment, it should be specifically explained that the optimization of the casting process parameters of the target hook includes material cutting optimization, heating process optimization, forging process optimization and heat treatment process optimization; The blanking optimization specifically includes: using high-precision cutting equipment to accurately calculate the blanking length and weight according to the size and weight requirements of the hook, thereby ensuring the size accuracy of the blank and reducing material waste; The specific optimization of the heating process involves the introduction of an intelligent heating system that uses thermocouples and temperature sensors to monitor and provide feedback on the billet temperature in real time, accurately controlling the temperature and heating time of the heating furnace. The heating temperature is controlled within an appropriate range, such as an initial forging temperature of 420°C to 460°C and a final forging temperature of no less than 440°C, ensuring uniform heating of the billet and improving the plasticity and fluidity of the material. The forging process optimization specifically involves utilizing advanced forging equipment and dies to control the deformation during the pre-forging phase to between 30% and 40% to avoid stress concentration caused by excessive single deformation. During the forming process, the press tonnage ratio is rationally adjusted, and appropriate reduction is employed to ensure a more balanced flow of metal fibers and enhance the mechanical properties of the hook.

[0035] The heat treatment process optimization specifically involves optimizing heat treatment parameters and employing a combination of quenching and tempering. The quenching temperature is controlled at 507±5°C and the tempering temperature is controlled at 170±5°C. Through precise temperature control and holding time settings, grain refinement is achieved, forging stress is eliminated, and the hardness, strength, and toughness of the hook are improved.

[0036] Hook forging simulation analysis module: Use finite element analysis software to simulate the optimized forging process, and combine it with the forging 3D model to analyze the feasibility of casting process optimization and output the feasibility analysis results.

[0037] In this embodiment, it should be specifically explained that the execution method of the hook forging simulation analysis module is as follows: Import the optimized process parameters and forging 3D model into finite element analysis software, set material properties, boundary conditions and contact parameters, generate high-quality meshes and densify them in key areas, use explicit dynamics solvers to perform forging process simulation calculations, record stress, strain and temperature distribution data, analyze material flow and possible defects, compare simulation results with preset process standards to calculate feasibility scores, and finally generate a feasibility analysis report containing key data, charts and conclusions, providing a scientific basis for process optimization.

[0038] Finite element analysis software was used to simulate the optimized forging process. A three-dimensional model of the hook forging was constructed, and parameters such as material properties, boundary conditions, and loads were set. By simulating metal flow and stress-strain distribution at different forging stages, potential defects and problems were predicted. For example, the simulations demonstrated uniform metal flow and significantly reduced stress concentration. Simulations of the entire forging process revealed that the optimized process resulted in a more reasonable distribution of equivalent stress and strain within the hook, meeting design requirements, verifying the feasibility and effectiveness of the process optimization. Example 2

[0039] See also Figure 2 As shown, the present invention provides a small hook forging process optimization method based on simulation analysis, comprising the following steps: S1: Establishing a 3D model of the hook: Constructing a forging 3D model of the target hook using 3D design software; S2: Monitoring forging process parameters: Based on the forging 3D model of the target hook, the forging process parameters are monitored in real time, a forging process compliance model is constructed, and the forging process is analyzed to obtain the forging process compliance coefficient corresponding to the target hook. The process parameters include forging temperature, forging pressure, and die movement speed. S3: Hook deformation state monitoring: real-time monitoring of the hook deformation parameters during the forging process of the target hook, establishment of a hook deformation coefficient model, and analysis to obtain the hook deformation coefficient corresponding to the target hook. The hook deformation parameters include hook deformation and stress. S4: Finished hook quality analysis: The surface of the target hook is photographed by an industrial camera to obtain the surface image of the target hook. The quality of the target hook is analyzed based on the finished hook size to obtain the finished product quality assessment coefficient corresponding to the target hook. S5: Casting process parameter optimization: Based on the forging process compliance coefficient, hook deformation coefficient and finished product quality assessment coefficient corresponding to the target hook, the casting process of the target hook is comprehensively analyzed and the casting process of the target hook is optimized based on the comprehensive analysis results; S6: Hook forging simulation analysis: Use finite element analysis software to simulate the optimized forging process, and combine it with the forging 3D model to analyze the feasibility of casting process optimization and output the feasibility analysis results.

[0040] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0041] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A small hook forging process optimization system based on simulation analysis, characterized in that: include: Hook 3D model building module: used to build a forging 3D model of the target hook through 3D design software; Forging process parameter monitoring module: Based on the forging 3D model of the target hook, it monitors the forging process parameters in real time, builds a forging process compliance model, and analyzes the forging process to obtain the forging process compliance coefficient corresponding to the target hook. The process parameters include forging temperature, forging pressure, and die movement speed. Hook deformation state monitoring module: used to monitor the hook deformation parameters of the target hook in real time during the forging process, establish a hook deformation coefficient model, and analyze and obtain the hook deformation coefficient corresponding to the target hook. The hook deformation parameters include hook deformation and stress; Finished hook quality analysis module: The industrial camera is used to capture the surface of the target hook to obtain the surface image. The quality of the target hook is analyzed based on the finished hook size to obtain the corresponding finished hook quality assessment coefficient. Casting process parameter optimization module: Based on the forging process compliance coefficient, hook deformation coefficient and finished product quality assessment coefficient corresponding to the target hook, the casting process of the target hook is comprehensively analyzed and optimized based on the comprehensive analysis results; Hook forging simulation analysis module: Use finite element analysis software to simulate the optimized forging process, and combine it with the forging 3D model to analyze the feasibility of casting process optimization and output the feasibility analysis results.

2. The small hook forging process optimization system based on simulation analysis according to claim 1 is characterized in that: The execution method of the hook three-dimensional model building module is as follows: Obtain the technical specification data of the target hook, create a reference plane in the 3D design software, establish a coordinate system, import the technical specification data of the target hook into the coordinate system of the 3D design software, draw the hook contour line and perform a rotation scanning operation to generate a basic entity, then add forging process features including forging allowance, flash groove and positioning groove, build a forged 3D model of the target hook, and finally convert the complete forged 3D model into a standard format and save it to the system specified path.

3. The small hook forging process optimization system based on simulation analysis according to claim 1 is characterized in that: The execution mode of the forging process parameter monitoring module is as follows: Based on the forging 3D model of the target hook, the forging process parameters of the target hook are monitored in real time. The process parameters include forging temperature, forging pressure and die movement speed. Temperature sensors, pressure sensors and speed sensors are installed on the forging equipment to collect the forging temperature T, forging pressure P and die movement speed V of the target hook in real time. Obtain the standard range of forging process parameters of the target hook from the management database, wherein the standard range of forging process parameters includes the standard range of forging temperature. , Forging pressure standard range And the standard range of mold movement speed ; Based on the real-time monitoring of the forging process parameters of the target hook and the standard range of the forging process parameters, the forging process parameter deviation of the target hook is calculated. The forging process parameter deviation of the target hook includes the forging temperature deviation, the forging pressure deviation and the die movement speed deviation. Based on the forging process parameter deviation, a forging process compliance model is constructed, and the forging process is analyzed to obtain the forging process compliance coefficient corresponding to the target hook. Based on the forging process compliance coefficient corresponding to the target hook, it is judged whether the forging process meets the requirements.

4. The small hook forging process optimization system based on simulation analysis according to claim 1 is characterized in that: The execution mode of the hook deformation state monitoring module is as follows: Real-time monitoring of hook deformation parameters during the forging process of the target hook to obtain the hook deformation and stress , normalize the obtained hook deformation parameters, and obtain the standard deformation of the target hook from the management database and standard stress , establish the hook deformation coefficient model, and obtain the hook deformation variables ,stress , standard deformation and standard stress Import the hook deformation coefficient model and calculate the hook deformation coefficient corresponding to the target hook.

5. The small hook forging process optimization system based on simulation analysis according to claim 1 is characterized in that: The execution method of the hook finished product quality analysis module is as follows: The surface of the target hook product is photographed by an industrial camera to obtain the surface image of the target hook product, the crack rate Dr of the surface image of the target hook product is extracted, and the finished product size deviation rate Dd of the target hook product is calculated. A quality assessment model for the hook product is established, and the crack rate Dr and size deviation rate Dd of the surface image of the target hook product are respectively imported into the hook product quality assessment model, and the finished product quality assessment coefficient corresponding to the target hook is calculated. The finished product quality of the target hook is evaluated based on the finished product quality assessment coefficient, and the finished product quality assessment result of the target hook is output.

6. The small hook forging process optimization system based on simulation analysis according to claim 5 is characterized in that: The crack rate of the target hook finished product surface image is obtained by: importing the target hook finished product surface image into the edge detection algorithm, identifying the crack edge line in the target hook surface image, using the threshold segmentation technology to convert the target hook finished product surface image into a binary image, with the crack area being white and the background being black, and counting the number of pixels in the crack area Nc And the number of pixels in the image area of ​​the finished hook surface Nt , substitute it into the crack rate formula to obtain the crack rate of the target hook finished product surface image Dr .

7. The small hook forging process optimization system based on simulation analysis according to claim 1 is characterized in that: The execution mode of the casting process parameter optimization module is as follows: The forging process compliance coefficient CPC, hook deformation coefficient HDC and finished product quality evaluation coefficient QEC corresponding to the target hook are read, and by establishing a comprehensive evaluation model for the casting process of the target hook, the comprehensive evaluation index of the casting process corresponding to the target hook is calculated. Based on the comprehensive evaluation index of the casting process, a comprehensive analysis of the casting process of the target hook is performed, and the comprehensive analysis results are output. Based on the comprehensive analysis results, the corresponding optimization method is selected to optimize the casting process parameters of the target hook.

8. The small hook forging process optimization system based on simulation analysis according to claim 7 is characterized in that: The specific content of the comprehensive analysis of the target hook casting process based on the casting process comprehensive evaluation index is: comparing the casting process comprehensive evaluation index with the preset casting process comprehensive evaluation index threshold. If the casting process comprehensive evaluation index is greater than the preset casting process comprehensive evaluation index threshold, the target hook casting process is judged to be normal; otherwise, the target hook casting process is judged to be abnormal, and it is necessary to screen the corresponding optimization method to optimize the casting process parameters of the target hook.

9. A method for optimizing the forging process of a small hook based on simulation analysis, which is used to use the system for optimizing the forging process of a small hook based on simulation analysis as described in any one of claims 1 to 8, characterized in that: The following steps are involved: S1: Establishing a 3D model of the hook: Constructing a forging 3D model of the target hook using 3D design software; S2: Monitoring forging process parameters: Based on the forging 3D model of the target hook, the forging process parameters are monitored in real time, a forging process compliance model is constructed, and the forging process is analyzed to obtain the forging process compliance coefficient corresponding to the target hook. The process parameters include forging temperature, forging pressure, and die movement speed. S3: Hook deformation state monitoring: real-time monitoring of the hook deformation parameters during the forging process of the target hook, establishment of a hook deformation coefficient model, and analysis to obtain the hook deformation coefficient corresponding to the target hook. The hook deformation parameters include hook deformation and stress. S4: Finished hook quality analysis: The surface of the target hook is photographed by an industrial camera to obtain the surface image of the target hook. The quality of the target hook is analyzed based on the finished hook size to obtain the finished product quality assessment coefficient corresponding to the target hook. S5: Casting process parameter optimization: Based on the forging process compliance coefficient, hook deformation coefficient and finished product quality assessment coefficient corresponding to the target hook, the casting process of the target hook is comprehensively analyzed and the casting process of the target hook is optimized based on the comprehensive analysis results; S6: Hook forging simulation analysis: Use finite element analysis software to simulate the optimized forging process, and combine it with the forging 3D model to analyze the feasibility of casting process optimization and output the feasibility analysis results.

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