Top beam body for hydraulic support and casting method of top beam body

Abstract

The invention relates to the technical field of hydraulic supports, in particular to a top beam body for a hydraulic support and a casting method thereof.The casting method comprises the steps that firstly, a preliminary casting scheme is simulated and optimized by means of the casting simulation technology, the optimal casting scheme is determined, and the smelting process and the casting process are controlled through a digital casting system; the casting speed can be accurately controlled in the casting process while the components of the molten steel meet the quality requirements, so that the whole casting process is executed according to the optimal casting scheme, the casting result is close to the simulation result as far as possible, the quality of the top beam body is guaranteed, the technological parameter optimization difficulty is reduced, and the production cost is reduced. The economic benefit of the casting process is improved. According to the casting method, the casting defects such as shrinkage cavities, shrinkage porosity and air holes are effectively reduced, the overall mechanical property of the top beam body is remarkably improved, it is ensured that the top beam body can bear large loads and impact under complex working conditions, and the service life of the top beam body is prolonged.

Description

Technical Field

[0001] This invention relates to the field of hydraulic support technology, specifically to a top beam for a hydraulic support and its casting method. Background Technology

[0002] Hydraulic supports are critical support equipment in fully mechanized coal mining faces. They use hydraulic cylinders to lift the roof to support the pre-splitting coal seam, providing a safe working area for equipment and personnel. The roof beam, as the core connecting component that transmits roof pressure to the hydraulic cylinders, directly bears the enormous pressure of the pre-splitting coal seam and must possess extremely high structural strength, rigidity, and fatigue resistance. Traditional roof beams often use thick steel plate welded structures, which suffer from welding defects, stress concentration, embrittlement of the heat-affected zone, and poor fatigue resistance. They are prone to cracking failure at the weld joints, affecting support safety and equipment lifespan.

[0003] If an integral casting process is used, the crisscrossing stiffeners within the top beam create numerous hot spots, making it highly susceptible to internal defects such as shrinkage cavities and porosity during casting. Many factors during the casting process affect the quality of the final casting. Traditional casting methods require continuous adjustments to various process parameters, consuming significant manpower, resources, and time, resulting in high trial-and-error costs. Furthermore, the process parameters determined by cost constraints are often not optimal, and the produced castings often fail to meet practical application requirements. Summary of the Invention

[0004] To address the technical problems of high defect rate and difficulty in determining optimal parameter settings during the casting process of the top beam, this application provides a top beam for a hydraulic support and its casting method, wherein the casting method includes the following steps:

[0005] Based on the casting design scheme, a preliminary design for the casting sand box is determined, and the casting process is simulated using casting simulation methods. The optimal casting scheme is then determined based on the simulation results.

[0006] The casting sand box is made according to the optimal casting scheme, and the casting sand box is baked after the surface of the casting sand box is coated with a coating material.

[0007] The molten steel, smelted under the control of the digital casting system, is allowed to stand for a preset time and then poured into a pre-baked ladle.

[0008] The casting is carried out using a digital casting system according to the optimal casting scheme, with the casting process proceeding at a steady pace followed by a faster pace and then a slower pace.

[0009] After the casting sand box is naturally cooled to below the first cooling temperature, the sand is removed from the box and the casting is heat-treated and tempered in the order of normalizing, quenching and tempering using a digital casting system.

[0010] The hydraulic support top beam provided by this invention is manufactured using the above-described casting method.

[0011] The technical effects and advantages of the invention are as follows: First, casting simulation technology is used to simulate and optimize the preliminary casting scheme to determine the optimal casting scheme. A digital casting system is then used to control the smelting and casting processes. This ensures that the composition of the molten steel meets quality requirements while precisely controlling the casting speed during the casting process. This allows the entire casting process to be executed according to the optimal casting scheme, ensuring that the casting result is as close as possible to the simulation result. This achieves both guaranteed quality of the top beam and reduced difficulty in optimizing process parameters, improving the economic efficiency of the casting process and realizing dual control over the quality and cost of the top beam during casting. The casting method provided in this application effectively reduces the generation of casting defects such as shrinkage cavities, porosity, and gas porosity, significantly improving the overall mechanical properties of the top beam, ensuring that it can withstand large loads and impacts under complex working conditions, and extending the service life of the top beam. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the overall process of the method provided by the present invention.

[0013] Figure 2 This is a flowchart illustrating the process of finding the optimal casting scheme in the method provided by this invention.

[0014] Figure 3 The design scheme of the casting sand box provided by the present invention.

[0015] Figure 4 This is a schematic diagram of the heat treatment and tempering process in the method provided by the present invention.

[0016] Figure 5 This is a casting speed curve diagram in Embodiment 1 of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Because traditional welded roof beams are prone to fatigue failure due to welding defects, a monolithic casting method was considered for production. However, when attempting to manufacture the roof beam using monolithic casting, the crisscrossing stiffeners and numerous hot spots within the beam made it highly susceptible to internal defects such as shrinkage cavities and porosity during the casting process. After repeated trials, the cast roof beam still exhibited various defects.

[0019] Example 1

[0020] To address the technical problems of high defect rates and difficulty in determining optimal parameter settings during the casting process of the top beam, reference was made to... Figure 1 This invention provides a method for casting a top beam for a hydraulic support, comprising the following steps:

[0021] S1. Determine the preliminary design of the casting sand box based on the casting design scheme, and use casting simulation methods to simulate the casting process. Determine the optimal casting scheme based on the simulation results.

[0022] S2. Prepare the casting sand box according to the optimal casting scheme, and bake it after coating the surface of the casting sand box;

[0023] S3. The molten steel, smelted under the control of the digital casting system, is allowed to stand for a preset time and then poured into a pre-baked ladle.

[0024] S4. Use a digital casting system to cast according to the optimal casting scheme, casting the top beam body at a steady pace first, then faster, then slower.

[0025] S5. After casting is completed, the casting sand box is naturally cooled to below the first cooling temperature. The sand is then removed from the box, and the digital casting system performs heat treatment and tempering on the casting in the order of normalizing, quenching, and tempering.

[0026] Specifically, in step S1, the casting simulation method is an advanced simulation method that uses the flow field-temperature field-stress field coupling method to simulate the casting process. Currently, there are several mature software programs on the market that can implement this method, such as ProCAST, COMSOL, MAGMASOFT, SuperCAST, and ANSYS Workbench. These simulation software programs can all use multiphysics coupling simulation technology to simulate the condensation process of molten steel during metal casting. For example, based on the material properties, three-dimensional model of the casting system, molten steel temperature, casting speed, and cooling conditions provided by the user, the temperature, flow rate, and shrinkage rate of the molten steel at each moment can be calculated, and the probability of shrinkage cavities (porosity) in each unit can also be calculated.

[0027] Although these software programs have greatly reduced the cost of process optimization, the process parameters still need to be determined manually during their use, and it remains quite difficult to find the optimal process parameters using these software programs.

[0028] Based on the above analysis, this application combines a deep learning model to automatically optimize process parameters in the simulation using the hot spot volume from the simulation results, in order to find the optimal casting scheme. (Refer to...) Figure 2 Specifically, it includes the following steps:

[0029] S11. Determine the preliminary plan for the casting process based on the casting design scheme, and construct the penalty function and the loss function of the deep learning model based on the thermal section volume change rate in the simulation results.

[0030] Specifically, based on the characteristics of casting simulation methods, the main parameters in the above-mentioned optimal casting scheme include: riser position, riser size, and the casting speed and casting quality corresponding to each casting stage.

[0031] Specifically, casting simulation software cannot directly provide the volume of hot spots; it can only provide the temperature and porosity of each element at different times. Therefore, the volume of hot spots needs to be calculated by the user. According to the definition of a hot spot, it is the last area in the casting to solidify, and its temperature is significantly higher than other parts during the cooling process, thus easily leading to defects such as shrinkage porosity and shrinkage cavities. Therefore, the determination of hot spots can be made jointly by a hot spot temperature threshold and a porosity acceptable threshold (generally 30%). For each element, at a specific moment during the cooling process (e.g., when the temperature of most elements drops to the solidification threshold, i.e., most areas of the casting have completed cooling), if its temperature is greater than or equal to the hot spot temperature threshold and its porosity is greater than the porosity acceptable threshold, then the element is determined to be a hot spot element. When multiple hot spot elements are interconnected (sharing nodes) and their number exceeds the normal threshold (excluding local numerical anomalies caused by geometric abrupt changes), the volume of these hot spot elements is calculated. Then, the volume of hot spots in two adjacent simulation results is calculated using the following formula (…). , Change in:

[0032]

[0033] The penalty function is used to transform the optimization objective (minimizing the hot spot volume) into a quantifiable loss value, guiding the algorithm to search for optimal process parameters. The specific form of the penalty function can be constructed based on the change in hot spot volume obtained from the above formula (i.e., the difference in hot spot volume between two simulation results), or it can be directly constructed based on the hot spot volume. For example, a penalty function can be constructed using the change in hot spot volume:

[0034]

[0035] In the formula, , For the penalty function parameters, This is used to penalize the magnitude of changes to ensure convergence stability. The objective of the penalty function is to penalize volume increases and prevent hot spot volume deterioration. Minimization causes the hot spot volume to continue to decrease.

[0036] Compared to directly constructing the penalty function based on the hot spot volume, this construction method does not require setting a target hot spot volume threshold, thus avoiding non-convergence problems caused by an unreasonable target hot spot volume threshold setting, and reducing the difficulty of system deployment and application.

[0037] S12. The optimization objective is the change rate of hot spot volume. When the change rate of hot spot volume approaches 0 from the negative range, the optimization is completed, and the process parameters at this time are output as the theoretically optimal casting scheme.

[0038] The deep learning model is built based on the penalty function constructed in step S11. It can employ a fully connected neural network or a convolutional neural network (for processing geometric data). The model structure includes:

[0039] Input layer: Process parameters, such as riser coordinates, riser size, and segmented pouring speed values. In this application, the pouring process is divided into three stages: a steady-state stage, a rapid stage, and a slow-compensation stage, with the pouring speed optimized for each stage. The pouring speed is optimized within three speed ranges for each of the three stages.

[0040] Hidden layer: Learns the complex relationship between various process parameters and hot spot volume.

[0041] Output layer: Predicting hot spot volume .

[0042] Based on the above penalty function, the following loss function is constructed:

[0043]

[0044] The MSE term calculates the mean square error between the predicted hot spot volume and the hot spot volume in the simulation results to ensure prediction accuracy. The term is used to achieve the optimization objective of minimizing the hot spot volume.

[0045] Based on the above loss function and model structure, the process parameters are automatically iteratively optimized:

[0046] Initialization: A set of process parameters (riseer location, casting speed) is randomly generated, and the hot spot volume is calculated through simulation. Alternatively, initial process parameters for the preliminary casting process can be provided based on the casting design and experience, such as... Figure 3 As shown, the ball socket location on the top beam is a major load-bearing area and a thick section during the casting process, making it highly susceptible to becoming a hot spot. Positioning the riser at this location ensures proper feeding within the socket and improves its internal quality. Simultaneously, because the top plate is a large flat plate, multiple vents are incorporated to ensure the cavity is fully filled, preventing defects such as cold shuts and incomplete filling. The initial size of the riser can be calculated using the modular method, which is the ratio of the solidified solid volume to its heat dissipation surface area.

[0047] Iteration: The model predicts the direction of parameter adjustment, minimizing the penalty function through gradient descent. For example, adjusting the riser to be closer to the hot spot region, or optimizing the pouring rhythm (pouring speed and quality at each pouring stage). For example, in this application, the pouring process is divided into three stages: steady, fast, and slow. The "steady" stage is the initial filling stage, where a low pouring speed needs to be controlled. For example, the pouring speed of a large-sized top beam is set to 20 kg / s to smoothly fill the pouring cup and sprue, avoiding splashing of molten metal and entrapment of gas. The "fast" stage is the cavity filling stage, where the pouring speed is increased to 60 kg / s to quickly fill the cavity while ensuring smooth gas discharge, reducing temperature loss of molten metal during the filling process and preventing cold shut defects. The "slow" stage is the final stage of filling, where the pouring speed is reduced to 10 kg / s when the molten metal approaches the riser or the top of the cavity for slow feeding, avoiding molten metal overflow or turbulent slag formation due to high-speed filling. By controlling the casting rhythm in this three-stage manner, the structural characteristics and filling requirements of different parts of the top beam can be effectively matched, thereby improving the overall quality of the casting.

[0048] Convergence: The optimization objective is the change rate of the hot spot volume. When the change rate of the hot spot volume approaches 0 from the negative range, the optimization is complete, and the process parameters at this time are output as the theoretically optimal casting scheme.

[0049] Furthermore, the casting scheme obtained through the above steps is merely an optimization based on simulation results. The actual casting process differs somewhat from the simulation analysis; therefore, the theoretically optimal casting scheme can be further optimized based on actual casting experiments.

[0050] S13. Conduct casting tests according to the theoretically optimal casting scheme and perform flaw detection on the cast samples. If casting defects (such as shrinkage cavities and porosity) are present in the samples, the porosity qualification threshold is lowered, iterative optimization is performed again, and the theoretically optimal casting scheme is re-determined. If there are no casting defects, the theoretically optimal casting scheme is output as the best casting scheme.

[0051] For example, if the initial porosity threshold for hot spot units was set at 30%, but shrinkage defects still appeared in the specimens during actual casting tests, it indicates that the original criteria for hot spot units were too stringent, leading to missed detections. Therefore, the porosity threshold should be lowered to increase the volume of hot spot units, and the casting process parameters should be further optimized. Conversely, if no shrinkage defects were found in the specimens during actual casting tests, it indicates that casting according to the theoretically optimal casting scheme is feasible, and the theoretically optimal casting scheme can be considered the best casting scheme.

[0052] Furthermore, in the actual casting process, a larger riser is generally more conducive to feeding, but an excessively large riser will require more molten steel during the casting process, which not only wastes materials but also increases the time required for the post-casting processing.

[0053] Therefore, in the above-mentioned casting scheme optimization steps, the riser shrinkage cavity height is introduced to optimize the optimal casting scheme, specifically including the following steps:

[0054] S14. In step S13, in addition to performing flaw detection on the sample to detect internal defects, the actual measured value of the riser shrinkage cavity height is also recorded simultaneously to obtain the riser shrinkage cavity height of the sample with casting defects (defective riser shrinkage cavity height) and the riser shrinkage cavity height of the sample without casting defects (qualified riser shrinkage cavity height). The target shrinkage cavity height is determined based on the riser shrinkage cavity height of the two.

[0055] Specifically, determining the optimal casting scheme often requires continuous adjustment and optimization of the model through multiple casting tests. This results in multiple defective riser shrinkage cavity heights and multiple qualified riser shrinkage cavity heights. By fitting the two, a target shrinkage cavity height can be obtained. When the riser shrinkage cavity height of the sample is at this value, the sample has no casting defects. This value can be used as the optimization target for process parameters.

[0056] S15. Calculate the theoretical riser shrinkage height based on the simulation results. With the change in hot spot volume approaching 0 from the negative range as the optimization objective, construct the loss function of the dual-objective optimization problem by combining the theoretical riser shrinkage height and the target shrinkage height. Optimize the theoretically optimal casting scheme and output the theoretically optimal casting scheme.

[0057] Specifically, the theoretical riser shrinkage cavity height can be calculated based on the porosity of each unit in the simulation analysis. For example, when the porosity of a unit is greater than 80% (general experience suggests that shrinkage cavities will occur in the actual casting when the porosity is greater than 80%), the unit is identified as a shrinkage cavity unit. Shrinkage cavity determination is performed on the units near the riser, and the farthest distance between the shrinkage cavity unit and the upper surface of the riser is calculated as the theoretical riser shrinkage cavity height.

[0058] The constructed loss function takes the following form:

[0059]

[0060] In the formula, The theoretical riser shrinkage height, For the target hole height, This is an economic weighting coefficient used to balance the weight of riser and constriction hole height during the optimization process, thereby reducing the difficulty of iterative convergence.

[0061] The above steps, by introducing an economic weighting coefficient γ, optimize the riser size while ensuring the riser shrinkage cavity height is controlled within the target shrinkage cavity height H_max range. This reduces unnecessary metal consumption, thereby lowering the production cost of the top beam and achieving a good balance between safety and economy in the casting process. The optimized casting process significantly reduces the riser shrinkage cavity height while ensuring the casting is free of casting defects.

[0062] The steps described above for finding the optimal casting scheme utilize a finite number of simulation results and actual casting test results. Through multiple iterative calculations using a deep learning algorithm, the optimal casting scheme can be quickly converged. Simultaneously, the riser shrinkage height is incorporated into the loss function to optimize casting process parameters. This achieves the goal of reducing the amount of molten steel required for casting while ensuring the casting quality of the top beam, thus improving the economic efficiency of the process and realizing dual control over the quality and cost of the top beam during casting.

[0063] The quality of actual castings depends not only on the optimization of the theoretical casting scheme but also on the precision of the casting process control. By using a digital casting system to precisely control each step during the casting process, ensuring that each step strictly follows the optimal casting scheme obtained from the above steps, the final casting quality can be guaranteed.

[0064] Specifically, in step S2, the casting sand box adopts a two-box design, with the entire casting model placed in the lower box for easy demolding. The ball socket section of the top beam is the main load-bearing part, and a riser is set here to ensure internal quality. The ingate is designed to be flat and enters from the side of the top plate. Because the top plate is a large flat surface, the ingate is designed with multiple channels, and vents are added in some areas to ensure that the cavity is filled and to avoid defects such as cold shuts and incomplete filling.

[0065] The casting mold is made of plastic, which has a high surface finish, ensuring good surface quality of the casting and reducing surface defects. Furthermore, the mold allows for precise dimensional control during the molding process, meeting high dimensional accuracy requirements. In addition, plastic molds are inexpensive, lightweight, and corrosion-resistant, guaranteeing their lifespan.

[0066] The casting sand box is made by hand or machine molding using ester-hardened water glass sand or alkaline phenolic resin sand. These two types of molding sand have good collapsibility and high strength, ensuring clear molding of complex structures and reducing the difficulty of cleaning up fallen sand. For complex internal cavities, integral or segmented sand cores are fabricated. Venting channels are installed inside the sand core, which is then firmly fixed with specialized core supports to prevent drifting or floating during pouring. After completion, a refractory coating is applied to the cavity and baked, forming a dense refractory layer on the cavity surface. This prevents direct contact between the high-temperature molten steel and the sand mold, thus avoiding defects such as sand adhesion and chemical sand adhesion on the casting surface, resulting in a smooth casting surface.

[0067] In step S3, the smelting process of molten steel is controlled by a digital casting system to ensure that the composition of the melt is within the range of the target material ratio.

[0068] Specifically, the digital casting system controls the steelmaking process through the following steps:

[0069] S31. Before steelmaking, the digital casting system first retrieves the preset composition database according to the material requirements of the top beam (such as ZG35CrMo or ZG20MnK) to determine the target content range and allowable deviation of key elements such as carbon, silicon, manganese, chromium, molybdenum, aluminum, barium, and calcium.

[0070] S32. During the smelting process, the system collects real-time steel temperature data in the electric arc furnace or medium-frequency furnace (recorded every 30 seconds by an infrared thermometer), and dynamically adjusts the electrode lifting height and oxygen supply intensity based on the oxygen and carbon monoxide concentrations fed back by the furnace gas analysis device. This ensures that the molten steel undergoes oxidation and reduction reactions within the optimal melting range of 1560±10℃ (approximately 150℃ above the liquidus temperature). In the LF stage (ladle refining stage), the actual content of each element in the molten steel composition is measured. Based on the deviation between the actual and target contents, the system automatically calculates the required amount of key elements to be added and feeds them proportionally using an automatic feeding device. After the newly added key elements (alloy materials) are completely melted, they are stirred evenly.

[0071] The determination of the composition of molten steel can be achieved by taking a sample from the molten steel. The sample of molten steel is poured into a mold to form a block or cake-shaped sample, which is then rapidly cooled. The prepared sample is then sent to the laboratory, where a spectrometer is typically used for rapid and accurate quantitative analysis of the chemical composition.

[0072] S33. After the preset settling time (5-8 minutes), the composition of the molten steel is detected again using a direct-reading spectrometer. If the deviation exceeds the allowable deviation (generally ±0.03%), a secondary fine-tuning procedure is initiated. Argon gas is used to purify the molten steel and control the content of harmful elements such as P and S until the composition of the melt meets the target material ratio requirements, such as O≤60ppm, N≤90PPM, and H≤4ppm.

[0073] After smelting, the molten steel needs to be poured into a ladle for the next casting step. Before pouring the molten steel into the ladle, the ladle needs to be heated to a temperature above 800°C at the bottom, so that the molten steel does not cool down too quickly in the ladle, thus improving the casting quality.

[0074] In step S4, the molten steel prepared in step S3 is poured into the casting sand box. The entire casting process is divided into three stages, starting with a steady pace, then increasing speed, and finally slowing down again. The casting speed during the casting process has a significant impact on the quality of the final casting. A digital casting system can precisely control the casting speed and casting quality (weight of molten steel) at each stage. The specific casting steps are as follows:

[0075] S41. In the initial stage of casting, a low-speed inlet is used to control the casting speed at 20 kg / s to ensure that the molten steel flows smoothly into the pouring cup and sprue in the casting sand box, avoiding defects such as sand flushing and slag entrapment caused by excessive flow rate. At the same time, observe the height of the molten steel in the pouring cup. When the liquid level rises steadily to 2 / 3 of the upper part of the sprue, proceed to the next stage.

[0076] S42. In the middle stage of casting, high-speed casting is switched to high-speed casting, and the casting speed is increased to 45 kg / s. At this time, the molten steel has filled the sprue and begins to fill the runner and ingate steadily. High-speed casting can quickly increase the liquid level in the mold cavity of the sand box, shorten the flow time of the molten steel in the mold cavity, and reduce the temperature loss and oxidation caused by long-term flow. At the same time, the weight change of molten steel is monitored in real time through a digital system. When the cumulative weight of the cast molten steel reaches 75% of the total weight of the casting, the later stage of casting is entered.

[0077] S43. In the later stages of casting, deceleration and feeding are carried out, reducing the casting speed to 15 kg / s. At this stage, the mold cavity is basically filled. Reducing the casting speed can prevent the formation of porosity due to the turbulence caused by high-speed pouring, which would prevent gas from being discharged in time. At the same time, slowing down the rise of the liquid level in the mold cavity is beneficial for sufficient feeding during the solidification process of the casting, preventing defects such as shrinkage cavities and porosity. The digital system continuously tracks the cumulative weight of the cast steel. When it reaches 95% of the total weight of the casting, the casting speed is further reduced to a low-speed dripping state of 8 kg / s until the cumulative weight of the cast steel reaches 105% of the total weight of the casting, completing the entire casting process. The excess molten steel will be removed as risers during subsequent cleaning to ensure the density of the casting body.

[0078] During the casting process described above, the digital casting system uses weighing sensors to measure the mass change of the molten steel in the ladle in real time, and controls the casting speed by adjusting the ladle's tilt angle. The specific control method is as follows:

[0079] S44. Periodically obtain the real-time molten steel quality in the ladle, and calculate the real-time casting speed based on the real-time molten steel quality;

[0080] The real-time casting rate can be calculated by subtracting the real-time molten steel mass obtained at the previous sampling time from the real-time molten steel mass obtained at the current sampling time, and then dividing by the sampling time interval.

[0081] S45. Calculate the difference between the real-time casting speed and the target casting speed (casting speed deviation). Based on the casting speed deviation and the relationship between the ladle tilt angle and the casting speed, dynamically adjust the ladle tilt angle so that the deviation between the real-time casting speed and the target casting speed is within the allowable deviation range of the casting speed.

[0082] During steel ladle casting, the casting speed is related not only to the inclination angle but also to the rate of change of the inclination angle. The relationship between the casting speed and the inclination angle (the angle between the upper surface of the ladle and the horizontal plane) and the rate of change of the inclination angle differs for different ladle specifications. This relationship can be determined through pre-calibration, specifically including the following steps:

[0083] S451. Simulate actual casting conditions under laboratory conditions, control the ladle to cast at different constant inclination angles, and record the stable casting speed at the corresponding inclination angle.

[0084] S452. Control the ladle to perform dynamic casting at different rates of change of inclination angle (such as uniformly increasing or decreasing the inclination angle), and record the inclination angle, rate of change of inclination angle, and corresponding instantaneous casting speed data at each moment;

[0085] S453. Data fitting is performed on the stable casting speed, instantaneous tilt angle, tilt angle change rate, and instantaneous casting speed to obtain the theoretical flow rate-tilt angle function relationship.

[0086] We can assume that the theoretical flow velocity has the following functional relationship with the inclination angle and the rate of change of the inclination angle:

[0087]

[0088] In the formula, The casting speed is defined as follows: when the inclination angle is stable, it is the steady-state casting speed; when the inclination angle changes, it is the instantaneous casting speed. The instantaneous tilt angle at the current moment. The rate of change of the tilt angle at the current moment. The sampling time interval, , , , represents the corresponding fitting coefficients.

[0089] This is a constant term, related to the theoretical volume of the ladle and the actual volume of molten steel. During the casting process, the volume of molten steel in the ladle cannot be exactly equal to its theoretical volume; a certain safety margin must be maintained. This means that molten steel can only flow out of the ladle when the ladle's angle is greater than a certain angle. Furthermore, since different castings have different weights, the volume of molten steel required for casting also varies. This results in different volumes of molten steel in the ladle when casting different castings, hence the constant term. It also needs to be changed depending on the project.

[0090] For example, assuming the volume of molten steel in a certain type of ladle is 80% of the ladle's theoretical volume, the theoretical flow rate-inclination angle function relationship, calibrated through experiments, is as follows:

[0091]

[0092] The digital casting system can dynamically adjust the ladle tilt angle in real time based on the theoretical flow rate-tilt angle function relationship fitted by pre-tests, thereby ensuring that the actual casting speed is consistent with the casting speed required in the optimal casting scheme, and can be changed in time when it is necessary to change the casting speed, thus ensuring the control accuracy of the entire casting process.

[0093] After casting, the casting is allowed to cool naturally in the casting sand box to prevent excessive internal stress or even cracking caused by excessively rapid cooling. Preferably, the sand is removed from the casting box when the temperature is below 400°C.

[0094] After unpacking, the surface of the casting is treated to remove molding sand, risers, and burrs.

[0095] Because the internal structure of cast parts is usually uneven, with coarse grains and casting stress, their strength, toughness, and other properties often fail to meet technical requirements. Therefore, heat treatment is used to modify the microstructure of the material.

[0096] refer to Figure 4 Specifically, it includes the following steps:

[0097] S51. First, normalizing is performed to refine the grains and homogenize the microstructure. The casting is reheated to the austenitizing temperature (890±10℃), held at that temperature for a sufficient time (3.0-4.5h), and then cooled in air. This process can eliminate coarse dendrites and compositional segregation in the as-cast microstructure, significantly refine the grains, and homogenize the microstructure, thereby improving the strength and toughness of the casting and preparing a good microstructure foundation for subsequent quenching and tempering treatment.

[0098] S52. A combined quenching and high-temperature tempering process is used to improve the overall mechanical properties of the casting. The quenching temperature is controlled at 900±10℃, held for 3.0-4.5 hours, and then water-cooled. The tempering temperature is 540±40℃, held for 4.5-6.0 hours, and then water-cooled. Quenching gives the casting a high-strength martensitic structure, but this also results in significant brittleness and internal stress. The subsequent high-temperature tempering decomposes the martensite into a high-strength, high-toughness tempered sorbite structure. This structure gives the casting high strength while also providing good plasticity and toughness, achieving a good balance of strength and toughness, which is crucial for the top beam structure that bears impact loads.

[0099] Through the above-mentioned heat treatment processes of normalizing, quenching, and tempering, the grains inside the casting are refined, residual stress on the inner wall is eliminated, and the mechanical properties of the casting are effectively improved.

[0100] After heat treatment, the castings are finished by precision grinding and shot blasting to remove oxide scale and minor defects on the surface, ensuring the surface quality of the castings and improving the adhesion of anti-corrosion paint in subsequent spraying processes.

[0101] Example 1

[0102] The casting process of the top beam of the hydraulic support used in a certain project is as follows:

[0103] (1) Determine the preliminary plan for casting sand box based on the design plan of top beam body, and optimize the casting plan.

[0104] (2) The casting sand box adopts a two-box design. For specific design scheme, please refer to the following. Figure 3 The entire cavity of the top beam is placed in the lower box, and the riser is set on the top plate at the position corresponding to the ball socket of the top beam. Multiple ingates of the casting system enter from the side of the top plate. The ingates are designed to be flat, forming a smooth flow channel with the side of the top plate. Multiple vent holes are set on the top plate to ensure that the cavity is filled and to avoid defects such as cold shut and insufficient pouring.

[0105] (3) The proportion and type of raw materials are strictly controlled through a digital casting system to ensure proper control of the molten steel composition. Simultaneously, during the ladle refining process, silicon, aluminum, barium, calcium, etc., are added, and argon is used to purify the molten steel, controlling the content of harmful elements such as P and S. The control parameters are O≤60ppm, N≤90PPM, and H≤4ppm to ensure casting quality. After melting, the ladle is allowed to stand for 5-8 minutes to allow gases and impurities to rise to the surface. Before pouring the molten steel into the ladle, the ladle is preheated to a bottom temperature above 800℃.

[0106] (4) The digital casting system casts according to the pre-optimized casting scheme, and the casting speeds for the three casting stages are as follows:

[0107] Stable phase: 20±3 kg / s

[0108] Fast phase: 45±5kg / s

[0109] Slow speed phase: 15±2kg / s

[0110] The casting speed curve during the rapid casting stage is as follows: Figure 5 As shown in the figure, the fluctuation of the casting speed is basically evenly distributed on both sides of the average speed (the vertical axis in the figure is 0), and the final average casting speed is 60.98 kg / s.

[0111] (5) After casting, keep the sand mold in the mold and cool it to below 400°C before opening the mold and removing the sand, mold sand, risers and burrs from the surface of the casting.

[0112] (6) Heat treatment and tempering are performed through the following steps:

[0113] Normalizing: 890±10℃, hold for 3.0-4.5 hours, then air cool;

[0114] Quenching: 900±10℃, hold for 3.0-4.5h, then cool down with water;

[0115] Tempering: 540±40℃, hold for 4.5-6.0h, then cool down with water.

[0116] The mechanical properties of the tensile test specimens (after the same heat treatment process) cast from the same batch of molten steel are as follows:

[0117]

[0118] The impact test results of the impact test specimens cast in the same batch (underwent the same heat treatment process) are shown in the table below:

[0119]

[0120] The tensile test specimens cast from the same batch of molten steel used for the hydraulic support beam in this project exhibited a yield strength of 744 MPa, a tensile strength of 894 MPa, an elongation of 14.5%, and a reduction of area of ​​50%, demonstrating a good balance of strength and toughness. Impact test results showed an average impact energy of 50.2 J at room temperature, and even at -20℃, the average impact energy remained at 27.8 J, indicating that the beam produced using the above method possesses excellent low-temperature impact toughness, meeting the stringent requirements for material mechanical properties under complex working conditions. Based on this, it can be concluded that the metallurgical quality of this batch of molten steel is good, possessing the material basis for casting the hydraulic support beam.

[0121] The cast sample top beam body was finished by precision grinding and shot blasting to remove surface oxide scale and surface defects. Then, ultrasonic non-destructive testing was used to check for casting defects inside. The feedback from the ultrasonic waves showed no obvious abnormal peaks, indicating that there were no casting defects inside the top beam body sample and that it met the quality requirements.

[0122] In summary, the advantages of the top beam casting method provided in this application are as follows: First, by using casting simulation technology to simulate and optimize the preliminary casting plan, the optimal casting scheme is determined, ensuring the scientific nature and predictability of the casting process. The use of plastic molds to create the casting sand box, followed by coating and baking treatment, improves the stability and surface quality of the sand mold, laying the foundation for obtaining excellent castings. During the steel preparation stage, the smelting is controlled by a digital casting system, and a preset settling time is performed to ensure the purity and fluidity of the molten steel. During the casting process, a strict adherence to the "steady first, then fast, then slow" rhythm helps to ensure smooth filling, reduce slag entrapment and oxidation, and improve the density of the casting. After the casting cools to a specific temperature, it is removed from the mold and subjected to sequential heat treatment (normalizing, quenching, and tempering) using a digital casting system. This allows for precise control of the metallographic structure and mechanical properties of the casting, ensuring that the top beam possesses excellent strength, toughness, and wear resistance, thereby significantly improving the overall operational reliability and service life of the hydraulic support.

[0123] The above method is not only applicable to the top beam of hydraulic support, but can also be extended to the casting production of other large, complex, and high-requirement engineering machinery structural components.

[0124] In conclusion, 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 within the protection scope of the present invention.

Claims

1. A method for casting a top beam for a hydraulic support, characterized in that, Includes the following steps: Based on the casting design scheme, a preliminary design for the casting sand box is determined, and the casting process is simulated using casting simulation methods. The optimal casting scheme is then determined based on the simulation results. The casting sand box is made according to the optimal casting scheme, and the casting sand box is baked after the surface of the casting sand box is coated with a coating material. The molten steel, smelted under the control of the digital casting system, is allowed to stand for a preset time and then poured into a pre-baked ladle. The casting is carried out using a digital casting system according to the optimal casting scheme, with the casting process proceeding at a steady pace followed by a faster pace and then a slower pace. After the casting sand box is naturally cooled to below the first cooling temperature, the sand is removed from the box and the casting is heat-treated and tempered in the order of normalizing, quenching and tempering using a digital casting system.

2. The method according to claim 1, characterized in that, The casting sand box is molded using ester-cured water glass sand or alkaline phenolic resin sand. The casting sand box is a two-box molding process. The casting model used to prepare the casting sand box is placed in the lower box to facilitate demolding. The casting model is a plastic mold.

3. The method according to claim 1, characterized in that, The steel smelting steps include: Based on the material requirements, retrieve the composition database to determine the target content and allowable deviation of each key element; Periodically collect molten steel samples, determine the actual content of each key element in the molten steel samples, automatically calculate the required amount of key elements to be added based on the deviation between the actual content and the target content, and automatically adjust the content of key elements. After the preset settling time, the actual content of each key element in the molten steel sample is measured again. If the deviation between the actual content and the target content exceeds the allowable deviation, the secondary fine-tuning procedure is initiated to adjust the content of the required key elements again.

4. The method according to claim 3, characterized in that, The steel smelting steps also include: purifying the steel with argon gas to ensure that the content of harmful elements in the steel meets quality requirements. The quality requirements are as follows: O≤60ppm, N≤90PPM, H≤4ppm.

5. The method according to claim 1, characterized in that, The bottom temperature of the ladle after baking is greater than 800°C.

6. The method according to claim 1, characterized in that, The steps for casting the casting include: The real-time quality of molten steel in the ladle is periodically obtained, and the real-time casting speed is calculated based on the real-time quality of molten steel. Calculate the casting speed deviation between the real-time casting speed and the target casting speed. Based on the casting speed difference and the relationship between the ladle tilt angle and the casting speed, dynamically adjust the ladle tilt angle to ensure that the casting speed deviation is less than the allowable casting speed deviation.

7. The method according to claim 1, characterized in that, The heat treatment and tempering steps include: Normalizing treatment: Hold at 890±10℃ for 3-4.5 hours, then air cool; Quenching treatment: Hold at 900±10℃ for 3-4.5h, then water-cooled; Tempering treatment: Hold at 540±40℃ for 4.5-6 hours, then water-cool.

8. The method according to claim 1, characterized in that, The steps for determining the optimal casting scheme include: Based on the casting design scheme, a preliminary plan for the casting process is determined. A penalty function and a loss function of the deep learning model are constructed using the hot spot volume change rate in the simulation results. The hot spot volume is the total volume of spatially continuous units with porosity greater than the qualified threshold. The hot spot volume change is the difference between the hot spot volumes of two adjacent simulation results. The optimization objective is the change rate of the hot spot volume. When the change rate of the hot spot volume approaches 0 from the negative range, the optimization is completed, and the process parameters at this time are output as the theoretically optimal casting scheme. Casting tests were conducted according to the theoretically optimal casting scheme, and the cast samples were inspected for defects. If casting defects were found in the samples, the porosity qualification threshold was lowered, and iterative optimization was performed again to redetermine the theoretically optimal casting scheme. If no defects were found, the theoretically optimal casting scheme was output as the best casting scheme.

9. The method according to claim 8, characterized in that, The step of determining the optimal casting scheme also includes: During the casting test, the shrinkage cavity height of the defective riser and the shrinkage cavity height of the qualified riser are obtained, and the target shrinkage cavity height is determined based on the shrinkage cavity height of the two risers. The theoretical riser shrinkage height is calculated based on the simulation results. The optimization objective is to reduce the volume change of the hot spot from the negative range to 0. A loss function for a dual-objective optimization problem is constructed by combining the theoretical riser shrinkage height and the target shrinkage height. The theoretically optimal casting scheme is then optimized, and the theoretically optimal casting scheme is output.

10. A top beam for a hydraulic support, characterized in that, It is prepared by the method described in any one of claims 1-9.

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