A bulldozer half shaft electronic press mounting machine control method, system, terminal and medium

Abstract

The application belongs to the technical field of bulldozer assembly, and specifically discloses a bulldozer half shaft electronic press fitting machine control method, a system, a terminal and a medium. The method comprises the following steps: controlling a telescopic rod to perform press fitting according to preset press fitting parameters, and acquiring force and depth data in a press fitting process in real time; based on the real-time data and the press fitting parameters, the adjustment amount of the press fitting speed and the force is dynamically calculated, and the control instruction is adjusted in real time according to the adjustment amount, and the press fitting is performed according to the real-time control instruction. Through real-time monitoring of the force and depth data in the press fitting process, the press fitting speed and the force can be dynamically adjusted, so that the best effect can be achieved in each press fitting operation, and the product quality is significantly improved. Meanwhile, the press fitting parameters are dynamically adjusted according to the actual situation, so that the electronic press fitting machine can better adapt to workpieces with different materials, sizes and shapes, and changes in external environment, and the adaptability and flexibility of the equipment are greatly improved.

Description

Technical Field

[0001] This invention belongs to the field of bulldozer assembly technology, specifically relating to a bulldozer half-shaft electronic press-fitting control method, system, terminal and medium. Background Technology

[0002] During the assembly of a bulldozer, the half-shaft needs to be pressed into the rear axle half-shaft hole. The fit between the half-shaft and the rear axle half-shaft hole is an interference fit with a large interference amount. Therefore, this assembly step is quite difficult and requires sufficient pressure and precision to ensure the quality of the pressing.

[0003] Traditional electronic press machines in the existing technology usually perform press-fitting operations on bulldozer half shafts according to preset parameters.

[0004] However, in actual operation, due to slight differences in the material, processing technology, post-processing aging time, outer diameter, inner diameter, surface roughness and shape of workpieces such as bulldozer half shafts and final drive boxes during production, fixed pressing parameters cannot ensure that each bulldozer half shaft can be pressed in the best condition. There is a risk that some bulldozer half shafts will be pressed too tightly or too loosely, affecting their service life and performance.

[0005] Meanwhile, the temperature inside the workshop will vary depending on the season or production period. Due to the principle of thermal expansion and contraction, the dimensions of metal parts such as bulldozer half-shafts and final drive housings will change with temperature. Fixed pressing parameters cannot compensate for this, thus affecting the pressing accuracy. Summary of the Invention

[0006] This invention addresses the problems in the prior art by providing a control method, system, terminal, and medium for an electronic pressing machine for bulldozer half-shafts. It solves the problem in the prior art where pressing of bulldozer half-shafts based on preset parameters results in half-shafts being pressed too tightly or too loosely, and compensation cannot be performed during the compression process.

[0007] The technical solution adopted in this invention is as follows: In a first aspect, this application provides a method for controlling the electronic pressing of a bulldozer half-shaft, the method comprising the following steps: Step S1: Control the servo motor according to the preset pressing parameters, and drive the telescopic rod to extend for pressing. Step S2: Obtain the pressing force and pressing depth parameters of the telescopic rod in real time; Step S3: When the pressure head of the telescopic rod contacts the workpiece, dynamically calculate the pressure speed and force adjustment amount based on the real-time pressure and depth data and pressure parameters. Step S4: Adjust the pressing speed and pressing force according to the pressing speed and force, and then update the control command. Step S5: Press-fit according to real-time control instructions.

[0008] Preferably, step S1 includes the following steps: Step S1-1: Randomly initialize a group of particles, each particle representing a set of pressing parameters, including pressure, velocity and pressing depth. Assign an initial position and velocity to each particle, and set the value range of each parameter. Step S1-2: Set the fitness function and calculate the fitness value of each particle according to the target pressing quality requirements. The pressing quality requirements include the pressing time range, pressure range, and depth error range. Steps S1-3: Based on the historical best position and global best position of the particles, update the velocity and position of the particles using the particle swarm optimization algorithm, and ensure that the parameter values ​​are within the preset boundaries; Step S1-4: Repeat steps S1-2 and S1-3 to perform iterative optimization; Steps S1-5: When the preset number of iterations is reached, stop the iteration, select the particle with the best fitness value, and extract its corresponding pressing parameters as the optimal control parameter set. Step S1-6: Control the servo motor according to the combination of control parameters obtained in step S1-5 as the preset pressing parameters.

[0009] Preferably, in step S1-2, the formula for calculating the fitness function is: ; in, , and It is weight; It is the influence factor of depth error on product quality score; and The other represents the impact factor of pressing speed on production time and the basic time consumption; These are the factors influencing production costs: intensity and time consumption. It is a fixed cost; It is the target pressing depth; It is the actual pressing depth achieved at particle position x; It is the average pressing speed at particle position x; It is the average pressing force at particle position x.

[0010] Preferably, in steps S1-3, the formula for updating the particle velocity is: ; in, ω represents the velocity of particle i at time t; ω is the inertial weight. and It is a learning factor; and It is a random number in the range [0, 1]. It is the optimal position of particle i; It is the globally optimal position of the entire particle swarm; This indicates the position of particle i at time t; It is the calculated velocity of particle i at time t+1; The formula for updating particle positions is: ; in, It is the weight of the effect of velocity on position update; It is the weight of the influence of the individual's optimal position on the current position update; It is the weight of the influence of the global optimal position on the update of the current position; It is a random perturbation weight; and These are the upper and lower bounds of the search space, respectively. is the next random number; m is the parameter of the generator.

[0011] Preferably, in step S3, the pressing speed adjustment amount is calculated using the following formula: ; The adjustment amount of the pressing force is calculated using the following formula: ; in, It is the adjustment amount for the pressing speed. It is the adjustment amount of the pressing force; , , , , , , and It is an adjustment factor; It is the preset target pressing force; It is the pressing force obtained in real time; It is the preset target pressing depth; It is the pressing depth obtained in real time; This is the maximum pressure applied. This is the maximum pressing depth achieved; It is the real-time rate of change of the pressing force; It is the real-time rate of change of the pressing depth.

[0012] Preferably, in steps S1-4, the pressing speed is calculated using the following formula: ; in, This indicates the adjusted pressing speed; This indicates the pressing speed before adjustment; Indicates the speed adjustment coefficient; Indicates the velocity damping coefficient; Indicates the target speed; The pressing force is calculated using the following formula: ; in, This indicates the adjusted pressing force; This indicates the pressing force before adjustment; Indicates the intensity adjustment coefficient; Indicates the force damping coefficient; Indicates the strength of the target; Indicates the integral coefficient of force; It represents the integral of the difference between the target force and the initial force over time.

[0013] Preferably, the method further includes the following steps: Step S6: Based on the real-time collected pressing depth and pressing force data, when it is detected that the current pressing pressure exceeds the preset safety upper limit and the pressure head displacement fails to reach the preset target displacement threshold, it is determined that a pressing abnormality has occurred, pressing is stopped, and an alarm signal is output. When the displacement of the pressure head reaches or exceeds the preset target displacement, and the applied pressure is always within the allowable range, the pressing is considered complete.

[0014] Secondly, this application provides a bulldozer half-shaft electronic press-fitting machine control system, the system comprising: The servo press-fitting execution module is used to drive the telescopic rod to extend or retract according to control commands in order to realize the press-fitting operation of the bulldozer half shaft. The pressing parameter generation module is used to dynamically generate a combination of pressing parameters including pressure, speed and pressing depth based on preset pressing quality requirements using a particle swarm optimization algorithm. The pressing quality requirements include pressing time range, pressure range and depth error range. The data acquisition module is used to collect real-time data on the pressing depth and pressing force of the telescopic rod during the pressing process; The control command calculation module is used to dynamically calculate the pressing speed adjustment amount and pressing force adjustment amount based on the real-time collected data and the current pressing parameters after the pressure head contacts the workpiece, and generate updated pressing control commands. The anomaly detection module is used to determine whether a pressing anomaly has occurred or whether pressing is complete, based on real-time acquired pressing depth and force information. Specifically, it includes: If the current pressure exceeds the preset safety threshold and the pressing depth does not reach the preset target, it is judged as abnormal and a stop pressing command and alarm signal are issued. If the current pressing depth reaches or exceeds the target value, and the pressure does not exceed the upper limit, the pressing is considered complete. The controller coordinates the operation of each module, controls the servo pressing execution module to perform real-time pressing actions according to the current control instructions, and issues a pressing end command after the completion conditions are met, causing the telescopic rod to retract to the initial standby position.

[0015] Thirdly, this application provides a terminal, including: The memory is used to store the control program for the electronic pressing and mounting of the bulldozer half-shaft; A processor is used to execute the steps of the bulldozer half-shaft electronic press-fitting machine control method as described in the first aspect when performing the bulldozer half-shaft electronic press-fitting machine control system.

[0016] Fourthly, this application provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the bulldozer half-shaft electronic press-fitting machine control method as described in the first aspect.

[0017] As can be seen from the above technical solutions, the advantages of the present invention are: (1) By monitoring the force and depth data during the pressing process in real time, the present invention can dynamically adjust the pressing speed and force, thereby ensuring that each pressing operation can achieve the best results and significantly improve product quality.

[0018] (2) The pressing parameters can be dynamically adjusted according to the actual situation. This invention enables the electronic pressing machine to better adapt to workpieces of different materials, sizes and shapes, as well as changes in the external environment, which greatly improves the adaptability and flexibility of the equipment.

[0019] (3) Through intelligent dynamic adjustment, the present invention reduces pressing failures or product quality problems caused by improper parameter settings, thereby improving production efficiency and reducing production costs and scrap rate.

[0020] (4) The present invention realizes the automation and intelligent control of the pressing process, simplifies the operation process, reduces the skill requirements of operators, and reduces human intervention and error. Attached Figure Description

[0021] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a bulldozer half-shaft electronic press-fitting control method provided as an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.

[0024] Please see Figure 1 As shown, the present invention provides a bulldozer half-shaft electronic press-fitting machine control method, including the following steps: Step S1: Control the servo motor according to the preset pressing parameters, and drive the telescopic rod to extend for pressing. Based on preset safety and efficiency parameters, a stable and controllable starting condition is provided. Through the precise control of the servo motor, the pressing operation can be started accurately and quickly. Step S2: Obtain the pressing force and pressing depth parameters of the telescopic rod in real time; The acquisition of real-time data allows the system to continuously monitor the pressing process, promptly detect any abnormalities, and make corresponding adjustments. In practical implementation, a force sensor, such as a pressure sensor or a force-sensitive resistor, is installed on the telescopic pole. These sensors convert the sensed pressure into an electrical signal output. The output signal of the force sensor is connected to a data acquisition device (such as a data acquisition card or controller) via a data cable. This device can read the electrical signal output by the sensor in real time and convert it into a digital signal; the digital signal is then transmitted through… Filtering is performed to obtain accurate pressing force values, where, It is the pressing force value after filtering at time point n. At a certain point in time The original pressing force value, At a certain point in time The weights of the data points are defined as follows: N is the window size of the weighted moving average filter; i is an index variable used to iterate through all samples within window N; n represents the current time point; the filtered pressing force value can be displayed to the operator in real time on the screen and simultaneously recorded in the storage device; position sensors, such as linear displacement sensors, are installed on the telescopic rod. These sensors can accurately measure the displacement of the telescopic rod, thus reflecting the pressing depth; the output signal of the position sensor is captured by the data acquisition device and converted into a digital signal for processing. The processing unit converts this data into the actual displacement or pressing depth, and the processed pressing depth data can also be displayed on the control interface in real time and recorded.

[0025] Step S3: When the pressure head of the telescopic rod contacts the workpiece, dynamically calculate the pressure speed and force adjustment amount based on the real-time pressure and depth data and pressure parameters. This step allows the pressing process to be dynamically adjusted according to real-time conditions, rather than relying on fixed preset parameters, which greatly improves the accuracy and flexibility of pressing and ensures the best pressing effect under different conditions. Step S4: Adjust the pressing speed and pressing force according to the pressing speed and force, and then update the control command. Based on previous calculations and analysis, it can generate optimal control commands, which not only improves the quality and efficiency of pressing operations, but also reduces potential risks caused by improper operation. Step S5: Press-fit according to real-time control instructions; The pressing operation was carried out according to the optimized control instructions, which ensured the accuracy and consistency of the pressing process; In the actual implementation process, the press machine receives the final control commands calculated in step S4. These commands include the adjusted press speed and press force. The press head starts to move according to the received speed and force commands. The press head moves downward at a specified speed while applying a preset pressure to begin pressing the workpiece into another workpiece. During the press process, the sensor continuously monitors the press depth and pressure to ensure that the press process is carried out according to the predetermined parameters.

[0026] Step S6: Based on the real-time collected pressing depth and pressing force data, when it is detected that the current pressing pressure exceeds the preset safety upper limit and the pressure head displacement fails to reach the preset target displacement threshold, it is determined that a pressing abnormality has occurred, pressing is stopped, and an alarm signal is output. When the displacement of the pressure head reaches or exceeds the preset target displacement, and the applied pressure is always within the allowable range, the pressing is considered complete. By setting preset values, the system can automatically determine whether the pressing meets the expected standards, thereby avoiding excessive or insufficient pressing. In the actual implementation process, before the pressing begins, the required pressing depth and pressure preset values ​​are set. During the pressing process, the control system will continuously compare the real-time pressing depth or pressure data with the preset values.

[0027] Step S7: After pressing is completed, the controller will send a command to the pressing head to start retracting. After receiving the retraction command, the pressing head will start retracting at a preset speed and trajectory. The pressing head will continue to retract until it returns to its initial position, preparing for the next pressing operation.

[0028] In one embodiment of half-shaft pressing in bulldozer manufacturing, a half-shaft needs to be pressed into the bulldozer's final drive housing. Based on previously calculated control commands, the pressing head begins pressing at a moderate speed and with appropriate force, slowly pressing the half-shaft into the final drive housing. Throughout the process, sensors on the pressing machine continuously monitor the pressing depth and applied pressure. Before pressing, preset values ​​for the required pressing depth and pressure are set according to the specifications of the half-shaft and final drive housing. When the pressing head presses the half-shaft into the final drive housing and reaches these preset values, the control system recognizes that pressing is complete. Once pressing is complete, the controller immediately sends a command to the pressing head to retract to its initial position. Upon receiving the command, the pressing head smoothly retracts, eventually returning to its position before pressing began, ready for the next pressing operation.

[0029] In some embodiments, step S1 includes the following steps: Step S1-1: Randomly initialize a group of particles, each particle representing a set of pressing parameters, including pressure, velocity and pressing depth. Assign an initial position and velocity to each particle, and set the value range of each parameter. By randomly initializing the particle swarm, the globally optimal combination of pressing parameters can be found. Step S1-2: Set the fitness function and calculate the fitness value of each particle according to the target pressing quality requirements. The pressing quality requirements include the pressing time range, pressure range, and depth error range. The fitness function can evaluate the quality of each set of press-fitting parameters. Through the fitness value, the performance of different parameter combinations can be quantitatively compared. Steps S1-3: Based on the historical best position and global best position of the particles, update the velocity and position of the particles using the particle swarm optimization algorithm, and ensure that the parameter values ​​are within the preset boundaries; By updating the particle's velocity and position, parameters can be dynamically adjusted, making the search process more flexible and efficient, and helping to escape local optima and find the global optimum. Step S1-4: Repeat steps S1-2 and S1-3 to perform iterative optimization; Through multiple iterations, the optimal combination of pressing parameters can be gradually approximated, improving the optimization and stability of the pressing operation. Steps S1-5: When the preset number of iterations is reached, stop the iteration, select the particle with the best fitness value, and extract its corresponding pressing parameters as the optimal control parameter set. By setting the number of iterations, the computational cost and time of the optimization process can be controlled, ensuring that a relatively optimized combination of press fitting parameters is obtained within a reasonable time. Step S1-6: Control the servo motor according to the combination of control parameters obtained in step S1-5 as the preset pressing parameters; Using optimized pressing parameters in actual operation can improve the quality and efficiency of pressing operations, reduce trial and error costs, and enhance the overall performance of the production line.

[0030] In specific applications, this includes: Determine the size of the particle swarm (i.e. the number of particles). For each particle, randomly generate its initial position and velocity. Here, the position represents a set of pressing parameters (pressure, velocity, and pressing depth), and the velocity represents the direction and step size of parameter adjustment. Ensure that the generated parameter values ​​are within a reasonable range to avoid safety hazards in actual operation. Define a fitness function, taking the position of each particle (i.e., the pressing parameters) as input, and calculate its fitness value. The higher the fitness value, the better the set of parameters. Based on the current velocity and position of each particle, and its fitness value, use the velocity and position update formulas in the particle swarm optimization algorithm to adjust the particle's state. The updated particle will represent the new pressing parameter combination for the next round of evaluation. Repeat the steps, that is, continuously calculate and update the particle's fitness value and state. After each iteration, record the current best particle (i.e., the particle with the highest fitness value). When the preset number of iterations is reached, stop the iteration process and output the position of the currently recorded best particle, that is, the final pressing parameter combination. Convert the output final pressing parameter combination into control commands for the servo motor. Based on these commands, precisely control the operation of the servo motor, thereby driving the telescopic rod to perform the pressing operation according to the optimized parameters.

[0031] In some embodiments, in step S1-2, the formula for calculating the fitness function is: ; in, , and It is weight; It is the influence factor of depth error on product quality score; and The other represents the impact factor of pressing speed on production time and the basic time consumption; These are the factors influencing production costs: intensity and time consumption. It is a fixed cost; It is the target pressing depth; It is the actual pressing depth achieved at particle position x; It is the average pressing speed at particle position x; It is the average pressing force at particle position x.

[0032] This fitness function ensures a balance between product quality, production efficiency, and production costs during the optimization process, resulting in a more comprehensive optimization outcome. This is achieved by adjusting the weighting coefficients (…). , and ) and various influencing factors ( , , , , This function allows for flexible adjustment of optimization objectives to adapt to different production needs and product characteristics. It precisely quantifies the performance of each particle (i.e., each set of pressing parameters), reflecting the quality, efficiency, and cost of the pressing operation through specific numerical values. By optimizing the pressing depth (…),… Approaching This can reduce quality problems caused by insufficient or excessive pressing, thereby improving the overall quality of the product. The pressing speed function... Regarding the impact on production time, optimizing the pressing speed can reduce the production cycle and improve production efficiency. Optimizing the pressing force (…) The combination of speed and efficiency can reduce the additional costs incurred due to over-pressing or low-speed pressing while ensuring product quality and production efficiency, thereby achieving effective control of production costs.

[0033] In some embodiments, the formula for updating the particle velocity in steps S1-3 is: ; in, ω represents the velocity of particle i at time t; ω is the inertial weight. and It is a learning factor; and It is a random number in the range [0, 1]. It is the optimal position of particle i; It is the globally optimal position of the entire particle swarm; This indicates the position of particle i at time t; It is the calculated velocity of particle i at time t+1; This velocity update formula allows particles to dynamically adjust based on historical velocities, individual optimalities, and global optimalities. This dynamism enables particles to effectively explore and develop the search space, finding better solutions. (Through learning factors...) and and random numbers and This increases the randomness and diversity of the search process, helping to avoid getting trapped in local optima and improving global search capabilities. In the formula... The first position represents the individual's optimal position, encouraging particles to move closer to their historical best position; while the second position represents the global optimal position, guiding particles to move towards the optimal position of the entire swarm. This mechanism finds a balance between individual optimization and collective intelligence.

[0034] The formula for updating particle positions is: ; in, It is the weight of the effect of velocity on position update; It is the weight of the influence of the individual's optimal position on the current position update; It is the weight of the influence of the global optimal position on the update of the current position; It is a random perturbation weight; and These are the upper and lower bounds of the search space, respectively. This is the next random number; m is the parameter of the generator; This position update formula considers the particle's current position and velocity, as well as the influence of the individual optimal position and the global optimal position. This allows the particle to comprehensively consider multiple pieces of information when updating its position, improving the accuracy and efficiency of the search. This is achieved by adjusting the influencing weights. , , and This allows for flexible control over the influence of different factors on particle position updates. The formula includes an upper bound on the search space. and the lower realm This ensures that particles do not exceed the predetermined search range when updating their positions, thus guaranteeing the effectiveness and feasibility of the search. Through the influence of the global optimal position g, this formula encourages particles to move closer to the global optimal solution, enhancing the algorithm's global search capability. The individual optimal position pi helps particles converge quickly to their historical best position, thereby improving the algorithm's convergence speed to some extent.

[0035] In some embodiments, the pressing speed adjustment amount in step S3 is calculated using the following formula: ; The adjustment amount of the pressing force is calculated using the following formula: ; in, It is the adjustment amount for the pressing speed. It is the adjustment amount of the pressing force; , , , , , , and It is an adjustment factor; It is the preset target pressing force; It is the pressing force obtained in real time; It is the preset target pressing depth; It is the pressing depth obtained in real time; This is the maximum pressure applied. This is the maximum pressing depth achieved; It is the real-time rate of change of the pressing force; It is the real-time rate of change of the pressing depth; This step dynamically calculates adjustments to pressing speed and force using real-time data on pressing force and depth. This real-time feedback and adjustment mechanism ensures the pressing process remains optimal, improving product quality and production efficiency. The adjustment calculation comprehensively considers multiple dimensions, including pressing force, pressing depth, and their rate of change, resulting in more comprehensive and precise adjustments. Multiple adjustment coefficients provide high flexibility and configurability for the pressing process. By monitoring changes in pressing force and depth in real time and adjusting pressing speed and force accordingly, equipment damage or product quality issues caused by overload can be effectively prevented. Precise control of pressing speed and force shortens the pressing cycle, reduces unnecessary downtime, and improves production efficiency. Furthermore, the optimized pressing parameters also help reduce energy consumption.

[0036] In some embodiments, the pressing speed is calculated in steps S1-4 using the following formula: ; in, This indicates the adjusted pressing speed, which is the result of the formula calculation and will be used as the speed setting value in the final control command. This indicates the pressing speed before adjustment, also known as the initial speed or current speed; The speed adjustment factor is a positive number. This represents the velocity damping coefficient, a non-negative number used to reduce the impact of the difference between the initial velocity and the target velocity on the final velocity. When the initial velocity is far from the target velocity, this term increases, thereby reducing the adjustment range of the final velocity to avoid excessive velocity changes. Indicates the target speed; The pressing force is calculated using the following formula: ; in, This indicates the adjusted pressing force, which is the result of the formula calculation and will be used as the force setting value in the final control command. This indicates the pressing force before adjustment, also known as the initial force or current force. This represents the intensity adjustment coefficient, which is a positive number. This represents the force damping coefficient, a non-negative number used to reduce the impact of the difference between the initial force and the target force on the final force. When the initial force is far from the target force, this term will increase, thereby reducing the adjustment range of the final force to avoid excessive force changes. The target force is the desired pressing force, which can be a preset value or dynamically determined according to process requirements. This represents the force integral coefficient, which is a positive number used to consider the impact of the difference between the target force and the initial force over a period of time on the final force adjustment. This term helps to reduce the force deviation that exists over a long period of time. It represents the integral of the difference between the target force and the initial force over time, reflecting the cumulative effect of the force deviation over a period of time.

[0037] By employing speed adjustment coefficients, speed damping coefficients, force adjustment coefficients, force damping coefficients, and force integral coefficients, the pressing speed and force can be controlled more precisely, bringing them closer to the preset target values. This precise control helps improve product quality and production efficiency. The damping coefficient helps reduce the impact of the difference between the initial and target values ​​on the final adjustment result. When the pressing speed or force deviates from the target value, the damping term increases, thus smoothly adjusting these parameters and avoiding excessive fluctuations, helping to protect the mechanical system from sudden impacts and stresses. By considering the difference between the target and initial values ​​over a period of time, it can better address long-term deviations, thereby improving the stability of the pressing process. This invention can dynamically adjust based on real-time pressing data and preset target parameters, allowing the system to flexibly adapt to different production environments and process requirements.

[0038] In some embodiments, this application provides a bulldozer half-shaft electronic press-fitting machine control system, the system comprising: The servo press-fitting execution module is used to drive the telescopic rod to extend or retract according to control commands in order to realize the press-fitting operation of the bulldozer half shaft. The pressing parameter generation module is used to dynamically generate a combination of pressing parameters including pressure, speed and pressing depth based on preset pressing quality requirements using a particle swarm optimization algorithm. The pressing quality requirements include pressing time range, pressure range and depth error range. The data acquisition module is used to collect real-time data on the pressing depth and pressing force of the telescopic rod during the pressing process; The control command calculation module is used to dynamically calculate the pressing speed adjustment amount and pressing force adjustment amount based on the real-time collected data and the current pressing parameters after the pressure head contacts the workpiece, and generate updated pressing control commands. The anomaly detection module is used to determine whether a pressing anomaly has occurred or whether pressing is complete, based on real-time acquired pressing depth and force information. Specifically, it includes: If the current pressure exceeds the preset safety threshold and the pressing depth does not reach the preset target, it is judged as abnormal and a stop pressing command and alarm signal are issued. If the current pressing depth reaches or exceeds the target value, and the pressure does not exceed the upper limit, the pressing is considered complete. The controller coordinates the operation of each module, controls the servo pressing execution module to perform real-time pressing actions according to the current control instructions, and issues a pressing end command after the completion conditions are met, causing the telescopic rod to retract to the initial standby position.

[0039] In some embodiments, this application provides a terminal, including: The memory is used to store the control program for the electronic pressing and mounting of the bulldozer half-shaft; A processor is used to execute the steps of the bulldozer half-shaft electronic press-fitting machine control method when performing the bulldozer half-shaft electronic press-fitting machine control system.

[0040] In some embodiments, this application provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the bulldozer half-shaft electronic press-fitting machine control method.

[0041] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A control method for an electronic press-fitting machine of a bulldozer half-shaft, characterized in that, Includes the following steps: Step S1: Control the servo motor according to the preset pressing parameters, and drive the telescopic rod to extend for pressing. Step S1-1: Randomly initialize a group of particles, each particle representing a set of pressing parameters, including pressure, velocity and pressing depth. Assign an initial position and velocity to each particle, and set the value range of each parameter. Step S1-2: Set the fitness function and calculate the fitness value of each particle according to the target pressing quality requirements. The pressing quality requirements include the pressing time range, pressure range, and depth error range. In step S1-2, the formula for calculating the fitness function is: ； in, , and It is weight; It is the influence factor of depth error on product quality score; and These represent the impact factor of pressing speed on production time and the basic production time, respectively; These are the factors influencing production costs: intensity and time consumption. It is a fixed cost; It is the target pressing depth; It is the actual pressing depth achieved at particle position x; It is the average pressing speed at particle position x; It is the average pressing force at particle position x; Steps S1-3: Based on the historical best position and global best position of the particles, update the velocity and position of the particles using the particle swarm optimization algorithm, and ensure that the parameter values ​​are within the preset boundaries; In steps S1-3, the formula for updating the particle velocity is: ； in, ω represents the velocity of particle i at time t; ω is the inertial weight. and It is a learning factor; and It is a random number in the range [0, 1]. It is the optimal position of particle i; It is the globally optimal position of the entire particle swarm; This indicates the position of particle i at time t; It is the calculated velocity of particle i at time t+1; The formula for updating particle positions is: ； in, It is the weight of the effect of velocity on position update; It is the weight of the influence of the individual's optimal position on the current position update; It is the weight of the influence of the global optimal position on the update of the current position; It is a random perturbation weight; and These are the upper and lower bounds of the search space, respectively. This is the next random number; m is the parameter of the generator; Step S1-4: Repeat steps S1-2 and S1-3 to perform iterative optimization; Steps S1-5: When the preset number of iterations is reached, stop the iteration, select the particle with the best fitness value, and extract its corresponding pressing parameters as the optimal control parameter set. Step S1-6: Control the servo motor according to the combination of control parameters obtained in step S1-5 as the preset pressing parameters; Step S2: Obtain the pressing force and pressing depth parameters of the telescopic rod in real time; Step S3: When the pressure head of the telescopic rod contacts the workpiece, dynamically calculate the pressure speed and force adjustment amount based on the real-time pressure and depth data and pressure parameters. Step S4: Adjust the pressing speed and pressing force according to the pressing speed and force, and then update the control command. Step S5: Press-fit according to real-time control instructions.

2. The bulldozer half-shaft electronic press-fitting control method according to claim 1, characterized in that, In step S3, the pressing speed adjustment amount is calculated using the following formula: ； The adjustment amount of the pressing force is calculated using the following formula: ； in, It is the adjustment amount for the pressing speed. It is the adjustment amount of the pressing force; , , , , , , and It is an adjustment factor; It is the preset target pressing force; It is the pressing force obtained in real time; It is the preset target pressing depth; It is the pressing depth obtained in real time; This is the maximum pressure applied. This is the maximum pressing depth achieved; It is the real-time rate of change of the pressing force; It is the real-time rate of change of the pressing depth.

3. The bulldozer half-shaft electronic press-fitting control method according to claim 2, characterized in that, In steps S1-S4, the pressing speed is calculated using the following formula: ； in, This indicates the adjusted pressing speed; This indicates the pressing speed before adjustment; Indicates the speed adjustment coefficient; Indicates the velocity damping coefficient; Indicates the target speed; The pressing force is calculated using the following formula: ； in, This indicates the adjusted pressing force; This indicates the pressing force before adjustment; Indicates the intensity adjustment coefficient; Indicates the force damping coefficient; Indicates the strength of the target; Indicates the integral coefficient of force; It represents the integral of the difference between the target force and the initial force over time.

4. The bulldozer half-shaft electronic press-fitting control method according to claim 1, characterized in that, The method also includes the following steps: Step S6: Based on the real-time collected pressing depth and pressing force data, when it is detected that the current pressing pressure exceeds the preset safety upper limit and the pressure head displacement fails to reach the preset target displacement threshold, it is determined that a pressing abnormality has occurred, pressing is stopped, and an alarm signal is output. When the displacement of the pressure head reaches or exceeds the preset target displacement, and the applied pressure is always within the allowable range, the pressing is considered complete.

5. A bulldozer half-shaft electronic pressing machine control system, used to execute the bulldozer half-shaft electronic pressing machine control method as described in claim 1, characterized in that, The system includes: The servo press-fitting execution module is used to drive the telescopic rod to extend or retract according to control commands in order to realize the press-fitting operation of the bulldozer half shaft; The pressing parameter generation module is used to dynamically generate a combination of pressing parameters including pressure, speed and pressing depth based on preset pressing quality requirements using a particle swarm optimization algorithm. The pressing quality requirements include pressing time range, pressure range and depth error range. The data acquisition module is used to collect real-time data on the pressing depth and pressing force of the telescopic rod during the pressing process; The control command calculation module is used to dynamically calculate the pressing speed adjustment amount and pressing force adjustment amount based on the real-time collected data and the current pressing parameters after the pressure head contacts the workpiece, and generate updated pressing control commands. The anomaly detection module is used to determine whether a pressing anomaly has occurred or whether pressing is complete, based on real-time acquired pressing depth and force information. Specifically, it includes: If the current pressure exceeds the preset safety threshold and the pressing depth does not reach the preset target, it is judged as abnormal and a stop pressing command and alarm signal are issued. If the current pressing depth reaches or exceeds the target value, and the pressure does not exceed the upper limit, the pressing is considered complete. The controller coordinates the operation of each module, controls the servo pressing execution module to perform real-time pressing actions according to the current control instructions, and issues a pressing end command after the completion conditions are met, causing the telescopic rod to retract to the initial standby position.

6. A terminal, characterized in that, include: The memory is used to store the control program for the electronic pressing and mounting of the bulldozer half-shaft; A processor is used to implement the steps of the bulldozer half-shaft electronic press-fitting machine control method as described in claim 1 when executing the bulldozer half-shaft electronic press-fitting machine control program.

7. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions. When the computer reads the computer instructions from the storage medium, the computer executes the bulldozer half-shaft electronic press-fitting machine control method as described in claim 1.

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