Grooving device for casting machining

Abstract

The invention is applicable to the technical field of machining, and provides a grooving device for casting machining, which comprises a controller, the controller comprises a chip stacking risk evaluation module, a chip stacking risk evaluation model is constructed according to a metal removal rate index and a chip removal rate index by taking workpiece vibration strength and chip granularity as influence factors, and the chip stacking risk evaluation model is used for evaluating the chip stacking risk of a workpiece; a chip stacking risk index is generated; and the cooling water pressure control module builds a cooling water pressure control model according to the rated water pressure of the cooling water, the chip accumulation risk index and the current cutter temperature, and outputs a cooling water pressure adjusting quantity value to a hydraulic system for regulation and control. According to the overall technical concept, a closed-loop feedback control system is constructed, key parameters in the machining process are subjected to multi-dimensional and real-time evaluation, and technological parameters such as cooling water pressure are intelligently adjusted based on the evaluation result, so that chip accumulation is effectively prevented, the machining quality and efficiency are improved, and the service life of a tool is prolonged.

Description

Technical Field

[0001] This invention belongs to the field of machining technology, and particularly relates to a grooving device for casting processing. Background Technology

[0002] In the casting manufacturing process, the grooving process is a fundamental and critical machining step, and its execution quality and efficiency have a decisive impact on product performance, production costs, and subsequent assembly processes. Traditional grooving devices generally consist of a basic tool drive unit and a manual or primary CNC feed mechanism.

[0003] When processing typical casting materials such as cast iron and cast steel, especially in deep or continuous groove machining operations, these devices generate severe thermal effects and complex-shaped chips during the cutting process due to the uneven internal structure of the material, significant hardness fluctuations, and interference from the surface oxide layer. Chip management becomes particularly problematic.

[0004] Differences in material toughness cause chips to appear as continuous ribbons or fine granules. Combined with limitations in tool helix angle design and chip flute space constraints, these chips can easily accumulate in the machining area under high-speed cutting or high-feed conditions. This accumulation not only hinders normal contact between the tool and the workpiece, leading to excessive surface roughness and increased geometric dimensional deviations, but also exacerbates tool edge wear and may even induce chipping, causing unplanned downtime and workpiece scrap.

[0005] The risk of chip buildup is essentially the result of the combined effects of accumulated cutting heat, decreased chip removal capacity, and system dynamic instability. Monitoring a single indicator is prone to misjudgment, making it impossible to accurately pinpoint the root cause of the problem and implement targeted interventions. Under the current technological framework, the equipment struggles to achieve precise quantification and proactive control of the machining state, severely restricting the stability, efficiency, and tool life of the casting grooving process. Therefore, existing technologies urgently need improvement to address these issues. Summary of the Invention

[0006] The purpose of this invention is to provide a grooving device for casting processing, which aims to solve the above-mentioned problems.

[0007] This invention is implemented as follows: a grooving device for casting processing includes a processing table, a sliding seat slidably connected to the processing table, a threaded thrust assembly for driving the sliding seat to move horizontally on the processing table, an electric lifting seat fixedly connected to the sliding seat, and an electric drill mechanism fixedly connected to the electric lifting seat. The electric drill mechanism performs grooving operations by rotating an internal tool. The electric drill mechanism is connected to a hydraulic system, which can connect to an external water circuit and an internal spray hole of the electric drill mechanism. The device also includes a controller, which comprises:

[0008] The metal removal rate evaluation module is used to construct a metal removal rate evaluation model based on the tool cutting depth, the actual horizontal feed rate of the tool, and the tool diameter, and output the metal removal rate index.

[0009] The chip removal rate evaluation module is used to construct a chip removal rate evaluation model based on the tool helix angle, the effective cross-sectional area of ​​the chip removal groove, the cooling water flow rate, and the cooling water pressurization speed, and output the chip removal rate index.

[0010] The chip accumulation risk assessment module uses workpiece vibration intensity and chip particle size as influencing factors to construct a chip accumulation risk assessment model based on the metal removal rate index and chip removal rate index, and generates a chip accumulation risk index.

[0011] The cooling water pressure control module is used to build a cooling water pressure control model based on the rated cooling water pressure, chip accumulation risk index and current tool temperature, and output the cooling water pressure adjustment value to the hydraulic system for regulation.

[0012] Further technical solutions, in the metal removal rate evaluation model:

[0013] The metal removal rate index is equal to the product of the depth of cut index, the feed rate index, and the tool diameter index, multiplied by a positive correlation factor related to the material's unit cutting force. This enhancement factor is 1 plus the product of the material's unit cutting force index and a preset coefficient.

[0014] A further technical solution is that the depth of cut index is obtained by dividing the actual depth of cut of the tool by the maximum allowable depth of cut of the tool; the feed rate index is obtained by dividing the actual feed rate of the tool by the maximum allowable horizontal feed rate of the machine tool; the tool diameter index is obtained by dividing the actual diameter of the tool by the nominal diameter of the tool; and the material unit cutting force index is obtained by dividing the unit cutting force of the cutting material by the unit cutting force of the reference material.

[0015] Further technical solutions, in the chip removal rate evaluation model:

[0016] The chip removal rate index is equal to the product of the helix angle index and the chip removal groove area index, multiplied by the product of the cooling system flow rate index and the stamping speed index, and multiplied by an attenuation factor related to the chip bulk density, which is 1 minus a compensation term related to the chip bulk density index.

[0017] A further technical solution is as follows: the helix angle index is obtained by dividing the actual helix angle of the tool by the helix angle of the reference tool; the chip flute area index is obtained by dividing the actual chip flute area of ​​the tool by the reference chip flute area; the cooling system flow rate index is obtained by dividing the actual cooling system flow rate by the upper limit of the cooling system flow rate; the stamping speed index is obtained by dividing the actual water flow stamping speed of the cooling system by the upper limit of the water flow stamping speed; and the chip packing density index is obtained by dividing the actual chip packing density by the reference chip packing density.

[0018] A further technical solution involves obtaining the workpiece vibration intensity index by dividing the actual vibration intensity of the workpiece by the vibration intensity safety threshold; the chip morphology characteristic index is obtained by dividing the chip morphology characteristic value obtained from the vibration spectrum analysis of the casting by the reference characteristic value under ideal chip conditions; in the chip accumulation risk assessment model:

[0019] The chip accumulation risk index is the product of the metal removal rate index and the chip morphology deterioration coefficient, divided by the sum of the chip removal rate index and a very small positive number, and then multiplied by a coefficient amplified by the part of the workpiece vibration intensity index that exceeds the safety threshold. The chip morphology deterioration coefficient is inversely proportional to the chip morphology characteristic index. When the chip morphology is better than the ideal state, the coefficient is less than 1, and vice versa.

[0020] A further technical solution involves obtaining the tool temperature index by dividing the actual tool temperature by the maximum allowable operating temperature of the tool material; in the cooling water pressure control model:

[0021] The water pressure adjustment value is the rated water pressure multiplied by the proportional integral term based on the deviation between the chip stack risk index and the preset target risk index, and then multiplied by the coefficient amplified by the portion of the tool temperature index exceeding the safety threshold.

[0022] A further technical solution also includes a tool horizontal feed rate adjustment module, which is used to construct a tool horizontal feed rate adjustment model based on the chip accumulation risk index and the actual tool horizontal feed rate, output the tool horizontal feed rate adjustment amount, and adjust the tool horizontal feed rate accordingly.

[0023] A further technical solution involves a tool horizontal feed rate adjustment model where the adjustment amount is segmented based on a comparison between the chip buildup risk index and a set threshold.

[0024] When the risk index is above the threshold and is not in the recovery period, the amount of feed rate reduction is determined based on the ratio of the current feed rate to the degree of risk exceeding the threshold.

[0025] When the risk index is below the threshold and the safe time condition is met, the increase in feed rate is determined based on the ratio of the current feed rate to the degree to which the risk is below the threshold.

[0026] In all other cases, the feed rate adjustment is zero;

[0027] The recovery period and safety time are set based on experience or historical data.

[0028] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0029] The overall technical concept of this application lies in constructing a closed-loop feedback control system. This system performs multi-dimensional, real-time evaluation of key parameters during the machining process and intelligently adjusts process parameters such as cooling water pressure based on the evaluation results. This effectively prevents chip accumulation, improves machining quality and efficiency, and extends tool life. This adaptive control capability is not found in traditional grooving devices, demonstrating the innovation and practical value of this application in the field of casting grooving technology. The cooling water pressure control module can dynamically adjust the cooling water pressure of the hydraulic system based on the real-time generated chip accumulation risk index and tool temperature. This overcomes the limitations of constant pressure or simple on / off control in traditional cooling systems, achieving on-demand adjustment of coolant supply. When the risk increases, the system can promptly increase the water pressure to enhance chip removal capability; during stable machining periods, it avoids unnecessary energy waste. This adaptive cooling regulation mechanism significantly improves chip removal efficiency and tool life.

[0030] The inclusion of metal removal rate and chip removal rate evaluation modules allows for precise quantification of machining load and chip removal efficiency. This contrasts sharply with traditional methods that rely solely on experience or single parameters (such as spindle current) to indirectly determine machining status, providing a more scientific and comprehensive data foundation.

[0031] The chip accumulation risk assessment module comprehensively considers factors such as metal removal rate index, chip removal rate index, workpiece vibration intensity, and chip particle size to construct a multi-dimensional risk assessment model. This integrated quantitative assessment capability enables the system to provide earlier and more accurate warnings of potential chip accumulation risks, avoiding the problems of single-dimensional condition assessment and delayed warnings in traditional solutions. Attached Figure Description

[0032] Figure 1 A schematic diagram of a grooving device for casting processing;

[0033] Figure 2 This is a schematic diagram of the controller module in this invention.

[0034] In the attached diagram: 1. Machining table; 2. Sliding seat; 3. Threaded thrust assembly; 4. Electric lifting seat; 5. Electric drill mechanism; 6. Hydraulic system. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0036] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0037] like Figures 1-2 As shown, a grooving device for casting processing according to an embodiment of the present invention includes a processing table 1, a sliding seat 2 slidably connected to the processing table 1, a threaded thrust assembly 3 for driving the sliding seat 2 to move horizontally on the processing table 1, an electric lifting seat 4 fixedly connected to the sliding seat 2, and an electric drill mechanism 5 fixedly connected to the electric lifting seat 4. The electric drill mechanism 5 performs grooving operation by rotating an internal tool. The electric drill mechanism 5 is connected to a hydraulic system 6, which can connect to an external water circuit and an internal spray hole of the electric drill mechanism 5. The device also includes a controller, which includes:

[0038] The metal removal rate evaluation module is used to construct a metal removal rate evaluation model based on the tool cutting depth, the actual horizontal feed rate of the tool, and the tool diameter, and output the metal removal rate index.

[0039] The chip removal rate evaluation module is used to construct a chip removal rate evaluation model based on the tool helix angle, the effective cross-sectional area of ​​the chip removal groove, the cooling water flow rate, and the cooling water pressurization speed, and output the chip removal rate index.

[0040] The chip accumulation risk assessment module uses workpiece vibration intensity and chip particle size as influencing factors to construct a chip accumulation risk assessment model based on the metal removal rate index and chip removal rate index, and generates a chip accumulation risk index.

[0041] The cooling water pressure control module is used to build a cooling water pressure control model based on the rated cooling water pressure, chip accumulation risk index and current tool temperature, and output the cooling water pressure adjustment amount to the hydraulic system 6 for regulation.

[0042] In this embodiment, the threaded thrust assembly 3 typically consists of a screw and a drive motor, converting rotational motion into linear motion via threaded transmission, thereby driving the sliding seat 2 to move precisely horizontally on the machining table 1. The electric lifting seat 4, typically composed of a motor-driven lifting mechanism, is fixedly connected to the sliding seat 2 and is used to achieve vertical lifting motion of the electric drill mechanism 5 to adjust the cutting depth of the tool. The electric drill mechanism 5 is the core component for grooving operations, typically including a spindle, a tool clamping device, and a motor that drives the tool to rotate, cutting the casting through the high-speed rotation of the tool. The hydraulic system 6 is mainly used to provide and control the supply of coolant, typically including a water pump, pipelines, valves, and a spray device, capable of delivering coolant to the internal spray holes of the electric drill mechanism 5 to cool the cutting area and remove chips.

[0043] The controller is the intelligent control center of the entire device. It is usually composed of a microprocessor, memory, input / output interfaces, etc. It is responsible for receiving sensor data, executing evaluation models, generating control commands and sending them to the actuators to achieve real-time monitoring and adaptive adjustment of the processing process.

[0044] The metal removal rate evaluation module is a functional unit in the controller used to quantify the volume or mass of metal material removed from the workpiece per unit time. It is an important indicator for measuring processing efficiency and load.

[0045] The chip removal rate evaluation module is another functional unit in the controller. It is used to quantify the speed at which chips are effectively removed from the cutting area per unit time. It is a key indicator for evaluating chip removal efficiency and avoiding chip accumulation.

[0046] The chip accumulation risk assessment module is the core functional unit in the controller. It is used to comprehensively analyze the metal removal rate and chip removal rate, and combine them with other influencing factors to predict the likelihood and severity of chip accumulation in the processing area.

[0047] The cooling water pressure control module is an execution control unit in the controller. It is used to dynamically adjust the cooling water pressure output by the hydraulic system 6 based on the chip accumulation risk assessment results and parameters such as tool temperature, in order to optimize the cooling and chip removal effect.

[0048] This embodiment provides a grooving device for casting machining, comprising a machining table 1, a sliding seat 2, a threaded thrust assembly 3, an electric lifting seat 4, an electric drill mechanism 5, and a hydraulic system 6. The machining table 1, serving as the base platform for supporting the workpiece, can be manufactured using high-strength cast iron or steel to provide sufficient rigidity and vibration damping performance. The sliding seat 2 can be slidably connected to the machining table 1 using a combination of linear guide rails and sliders, ensuring smooth and accurate horizontal movement. The threaded thrust assembly 3 can consist of a trapezoidal screw and nut driven by a stepper motor, precisely controlling the horizontal feed position of the sliding seat 2 by controlling the rotation angle of the stepper motor. The electric lifting seat 4 can employ an electric push rod or a ball screw mechanism driven by a servo motor to achieve vertical lifting of the electric drill mechanism 5, thereby adjusting the cutting depth of the tool. The electric drill mechanism 5 can be driven by a high-speed spindle motor, and its internal components include replaceable tools, which are used to cut the casting through high-speed rotation. The hydraulic system 6 may include a constant pressure pump, a reservoir, a set of pipelines, and multiple nozzles. Coolant is drawn from the reservoir by a constant-pressure pump and delivered through pipelines to the injection port inside the electric drill mechanism 5, where it is sprayed onto the cutting area at a constant pressure and flow rate. This configuration provides basic cooling and chip removal functions.

[0049] In a preferred embodiment of the present invention, the metal removal rate evaluation model includes:

[0050] ;

[0051] in The material's unit cutting force index. The preset cutting force influence coefficient, This is the depth of cut index. For feed rate index, This is the tool diameter index. This is the metal removal rate index.

[0052] In this embodiment, the metal removal rate evaluation model aims to quantify the volume or mass of metal removed from the workpiece per unit time during the cutting process. This model forms the basis for understanding and predicting machining efficiency, cutting load, and potential machining problems such as chip buildup. Its construction can be based on empirical formulas, physical cutting theory, or data-driven methods. The metal removal rate index is a quantitative indicator output by the model, used to characterize the relative magnitude or standardized value of the metal removal rate.

[0053] Preset cutting force influence coefficient It is a weighting factor used to adjust the material's unit cutting force exponent. The degree of influence on the metal removal rate. This coefficient can be set according to tool type, cutting conditions, machining experience, or through optimization algorithms.

[0054] The solution presented in this application solves the problem of unclear model construction in traditional methods by introducing the aforementioned metal removal rate evaluation model into the controller of the grooving device 1 for casting processing, thus making the evaluation more comprehensive and accurate. This model incorporates the cutting depth index... Feed rate index and tool diameter index These parameters, as fundamental parameters, directly determine the cutting volume. Building upon this, the model further introduces the material's unit cutting force exponent. and the preset cutting force influence coefficient This approach aims to correct for the impact of differences in material properties and cutting forces on the actual metal removal rate. This combination enables... This model not only reflects cutting geometry parameters but also considers the cutting difficulty of the material itself, thus more realistically reflecting changes in the metal removal rate. By exponentializing these parameters, the model unifies physical quantities of different dimensions, facilitating comprehensive calculations in the subsequent chip accumulation risk assessment module. This model provides accurate and physically meaningful input for chip accumulation risk assessment, enabling the entire control system to more effectively predict and manage chip accumulation risks during the machining process.

[0055] In a preferred embodiment of the present invention, the depth of cut index is obtained by dividing the actual depth of cut of the tool by the maximum allowable depth of cut of the tool; the feed rate index is obtained by dividing the actual feed rate of the tool by the maximum allowable horizontal feed rate of the machine tool; the tool diameter index is obtained by dividing the actual diameter of the tool by the nominal diameter of the tool; and the material unit cutting force index is obtained by dividing the unit cutting force of the cutting material by the unit cutting force of the reference material.

[0056] In this embodiment, the depth of cut index The actual depth of cut is a standardized measure of the depth of penetration of a cutting tool into the workpiece material during the cutting process. Its function is to reflect an important aspect of the cutting load, and standardization facilitates unified evaluation under different cutting conditions. The actual depth of cut can be obtained in real time through the machine tool's CNC system, or measured using displacement sensors or laser rangefinders installed near the tool or workpiece. The maximum allowable depth of cut can be preset based on specifications provided by the tool manufacturer, material properties, and machining experience. Alternatively, the actual depth of cut can be indirectly calculated by analyzing spindle load and cutting force sensor data. The maximum depth of cut can be determined comprehensively based on factors such as tool geometry, material strength, and machine tool power limitations.

[0057] Feed rate index This is a standardized measure reflecting the horizontal speed of the cutting tool relative to the workpiece. Its function is to quantify the horizontal movement efficiency of the tool during the cutting process. Standardizing it helps to make unified evaluations across different machine tools and machining tasks. The actual feed rate of the tool can be obtained directly from the machine tool's CNC system; the maximum allowable horizontal feed rate of the machine tool can be set according to the machine tool's design parameters, drive system capabilities, and safe operating procedures. Alternatively, the actual feed rate can also be calculated by monitoring the tool's movement distance and time in real time using position sensors such as encoders or linear encoders; the maximum horizontal feed rate can be comprehensively considered based on factors such as the machine tool's transmission mechanism, motor power, and machining accuracy requirements.

[0058] Tool Diameter Index It is a standardized measure reflecting the size of cutting tools, and its purpose is to unify the representation of tool dimensions and eliminate the influence of tools of different diameters on the metal removal rate assessment model. The actual diameter of the tool can be obtained through pre-measurement or from the tool management system; the nominal diameter of the tool is usually the standard diameter marked at the factory. Alternatively, during machining, the tool diameter may change slightly due to wear, and the actual diameter can be obtained through real-time or periodic measurement using a vision inspection system or contact probe; the nominal diameter is then used as a benchmark for comparison.

[0059] Material unit cutting force index It is a standardized measure reflecting the ease of cutting a workpiece material. Its function is to make the cutting characteristics of different materials comparable, solving the problem of distortion in metal removal rate assessment models caused by material differences. The unit cutting force of the cutting material can be obtained through experimental measurement or by consulting material handbooks; the unit cutting force of the reference material can be selected as a benchmark by choosing the unit cutting force of a standard material (such as a specific grade of steel). Alternatively, the unit cutting force can also be calculated by measuring the cutting force using a force sensor during actual cutting and combining it with the cutting area; the unit cutting force of the reference material can be preset according to industry standards or specific application scenarios.

[0060] This application addresses the inaccuracy of metal removal rate assessments in traditional casting grooving devices by introducing a standardized index calculation method. This is because the calculation of key indices is often poorly defined. Specifically, the metal removal rate assessment module requires accurate input parameters when constructing the assessment model. This solution standardizes the cutting depth index by dividing the actual cutting depth by the maximum allowable cutting depth, avoiding assessment biases caused by differences in absolute depth values. Simultaneously, the feed rate index is obtained by dividing the actual feed rate by the maximum allowable horizontal feed rate of the machine tool, ensuring normalization of speed parameters and eliminating the influence of inconsistent speed units under different machine tool or machining conditions. Furthermore, the tool diameter index, obtained by dividing the actual tool diameter by the nominal tool diameter, unifies the representation of tool dimensions, preventing dimensional differences from interfering with model accuracy. Finally, the material unit cutting force index, obtained by dividing the unit cutting force of the cutting material by the unit cutting force of the reference material, makes the cutting characteristics of different materials comparable, resolving model distortion caused by material differences. The standardized calculation of these indices enables the metal removal rate assessment model to receive uniform, accurate, and physically meaningful inputs, thereby ensuring the accuracy and consistency of the metal removal rate index. This provides reliable basic data for subsequent chip removal rate assessment, chip accumulation risk assessment, and intelligent control of cooling water pressure and feed rate, significantly improving the adaptive control capability and accuracy of the entire processing process.

[0061] In a preferred embodiment of the present invention, the chip removal rate evaluation model includes:

[0062] ;

[0063] in This is the density influence coefficient. , The helix angle index, The chip removal groove area index. For cooling system flow rate index, This refers to the stamping speed index. The cutting bulk density index. This represents the chip removal rate index.

[0064] In this embodiment, the density influence coefficient This coefficient is used to quantify the negative impact of cutting bulk density on chip evacuation rate. Its value is limited to between 0 and 0.4, ensuring that cutting bulk density plays an appropriate role in the model, reflecting its hindering effect on chip evacuation while avoiding overly sensitive or unreasonable model outputs. This coefficient can be preset through experimental data fitting, expert experience setting, or based on material properties.

[0065] Helix angle index This study characterizes the effect of the tool helix angle on chip removal capability. The helix angle is one of the key parameters of tool geometry, directly affecting chip curling, flow direction, and removal efficiency.

[0066] Chip trough area index This reflects the impact of the effective cross-sectional area of ​​the chip evacuation groove on the chip removal capacity. The chip evacuation groove is the channel for chip flow, and its size directly determines the ability to accommodate and remove chips.

[0067] Cooling system flow index This is used to quantify the auxiliary role of the coolant flow rate provided by the cooling system in chip removal. The coolant not only has cooling and lubricating functions, but its flow itself also washes and carries away the chips, assisting in chip removal.

[0068] Stamping speed index This characterizes the impact of the coolant injection velocity into the cutting zone on chip removal. High-speed coolant injection generates greater momentum impact on the chips, effectively breaking them up and propelling them away from the cutting zone.

[0069] Cutting bulk density index Chip evacuation rate index is used to quantify the actual chip packing density within the cutting zone. Higher chip packing density indicates denser chips, making them more difficult to remove and creating greater obstacles to chip evacuation. This is the final output of the chip removal rate evaluation model, comprehensively reflecting the chip removal capacity of the tool itself, the chip removal capacity assisted by the coolant, and the actual chip removal efficiency under the resistance of chip accumulation. The higher the index value, the stronger the chip removal capacity and the lower the risk of chip accumulation.

[0070] The chip removal rate evaluation model proposed in this application organically combines the geometric characteristics of the tool, the dynamic parameters of the coolant, and the physical characteristics of the chips to construct a quantitative chip removal rate index. The core of this model lies in its calculation of the chip removal capability of the tool itself (based on the helix angle index). and chip removal groove area index (jointly determined) and the coolant's auxiliary chip removal capacity (determined by the cooling system flow rate index) and stamping speed index The model performs a product operation (jointly determined by both factors) to reflect the total chip removal potential under their synergistic effect. Based on this, the model further introduces the cutting bulk density index. And through density influence coefficient The chip removal rate is weighted and negatively corrected for chip removal potential, thus accurately reflecting the hindering effect of chip accumulation on chip removal. The max(0, ...) function in the formula ensures that the chip removal rate index is always non-negative, consistent with physical reality. In this way, the model can comprehensively and accurately evaluate the chip removal efficiency under the current machining state, overcoming the limitations of traditional methods that have a single evaluation dimension and insufficient quantification. For example, when the tool helix angle or chip groove area is not designed properly, even if the coolant flow rate and stamping speed are high, the chip removal rate index will be limited; conversely, when the tool has a strong chip removal capacity, appropriate adjustment of the coolant can significantly improve the chip removal efficiency. Especially in the controller of the grooving device for casting machining, this chip removal rate evaluation module can provide a key chip removal rate index for the chip accumulation risk assessment module, making the prediction of chip accumulation risk more accurate. This accurate chip removal rate evaluation enables the controller to identify potential chip accumulation risks more timely and accurately, thus providing a reliable decision basis for the subsequent coolant pressure control module and tool horizontal feed rate adjustment module, realizing adaptive optimization control of the machining process.

[0071] In a preferred embodiment of the present invention, the helix angle index is obtained by dividing the actual helix angle of the tool by the helix angle of the reference tool; the chip flute area index is obtained by dividing the actual area of ​​the tool's chip flute by the area of ​​the reference chip flute; the cooling system flow rate index is obtained by dividing the actual flow rate of the cooling system by the upper limit of the cooling system flow rate; the stamping speed index is obtained by dividing the actual water flow stamping speed of the cooling system by the upper limit of the water flow stamping speed; and the chip packing density index is obtained by dividing the actual chip packing density by the reference chip packing density.

[0072] In this embodiment, the helix angle index This is a dimensionless quantity that measures the inclination of the helical flute on a cutting tool. It is defined as the ratio of the actual helical angle of the tool to a preset reference helical angle. This index can be obtained in several ways. For example, optical measuring equipment, such as an angle meter or a video measuring instrument, can be used to accurately obtain the actual helical angle of the tool and then compare it with the optimized helical angle under industry standards or specific machining conditions as a reference. Alternatively, the nominal helical angle of the tool can be directly read from the tool design parameter database as the actual helical angle, and then the ratio can be calculated with the reference helical angle.

[0073] Chip trough area index This is a dimensionless quantity that measures the effective cross-sectional area of ​​the chip evacuation groove of a cutting tool. It is defined as the ratio of the actual chip evacuation groove area to a preset benchmark chip evacuation groove area. This index can be obtained using 3D scanning or cross-sectional analysis techniques to acquire the actual effective cross-sectional area of ​​the chip evacuation groove and then compare it with the nominal chip evacuation groove area of ​​a new tool or the average chip evacuation groove area of ​​a specific tool type as a benchmark. Alternatively, the nominal chip evacuation groove area can be retrieved from the tool manufacturer's technical manual or database based on the tool model and specifications, and then compared with the benchmark chip evacuation groove area.

[0074] Cooling system flow index This is a dimensionless quantity that measures the actual flow rate of a cooling system relative to its maximum capacity. It is defined as the ratio of the actual flow rate of the cooling system to the upper limit of the cooling system's flow rate. This index can be obtained by installing flow sensors in the coolant lines to monitor the actual flow rate of the cooling system in real time and calculating the ratio with the upper limit of the flow rate specified by the cooling system design or manufacturer; alternatively, it can be obtained by recording the operating parameters of the cooling pump, such as speed or power, combining them with the pump's performance curve to estimate the actual flow rate and then calculating the ratio with the upper limit of the flow rate.

[0075] Stamping speed index This is a dimensionless quantity that measures the turbulence velocity of cooling water relative to its maximum capacity. It is defined as the ratio of the actual turbulence velocity of the cooling system to the upper limit of the turbulence velocity. This index can be obtained by installing a velocity sensor, such as a Pitot tube or an ultrasonic Doppler velocimeter, near the coolant nozzle outlet to measure the actual turbulence velocity of the cooling system and then calculating the ratio to the upper limit of the turbulence velocity determined by the cooling system design or nozzle characteristics; alternatively, it can be obtained by measuring the pressure at the coolant nozzle and estimating the turbulence velocity using Bernoulli's equation or the nozzle flow coefficient, and then calculating the ratio to the upper limit of the turbulence velocity.

[0076] Chip Bulk Density Index It is a dimensionless quantity that measures the actual chip bulk density relative to a reference density. It is defined as the ratio of the actual chip bulk density to a preset reference chip bulk density. This index can be obtained by collecting a certain volume of chips during the machining process, weighing them, calculating the actual chip bulk density, and then comparing it with the chip bulk density produced under ideal cutting conditions or the average bulk density of a specific material as a reference. Alternatively, it can be indirectly estimated by performing image recognition and analysis of chip morphology, combined with the geometric characteristics of the chips, such as size, shape, or porosity, and then comparing it with a reference chip bulk density.

[0077] This application provides explicit and standardized calculation methods for key parameters in the chip removal rate evaluation model, namely the helix angle index, chip groove area index, cooling system flow rate index, stamping speed index, and chip bulk density index. These calculation methods all employ the method of comparing actual measured or design values ​​with preset benchmark or upper limit values, thereby converting these physical quantities into dimensionless indices. This standardization ensures the consistency and comparability of parameter values ​​under different cutting tools, different cooling system conditions, and different chip morphologies, avoiding evaluation biases caused by differences in units or dimensions. Using these standardized indices as input, the chip removal rate evaluation model can more accurately quantify chip removal capacity, thus providing a reliable data foundation for the chip accumulation risk assessment model. This enables the intelligent control system of the entire grooving device for casting processing to make decisions based on more accurate condition assessments.

[0078] In a preferred embodiment of the present invention, the workpiece vibration intensity index is obtained by dividing the actual vibration intensity of the workpiece by the vibration intensity safety threshold; the chip morphology characteristic index is obtained by dividing the chip morphology characteristic value obtained from the vibration spectrum analysis of the casting by the reference characteristic value under ideal chip conditions; in the chip accumulation risk assessment model:

[0079] ;

[0080] in The chip morphology deterioration coefficient is denoted as . , It is a detritus morphology characteristic index. , It is a very small positive number; among which This represents the metal removal rate index. The chip removal rate index, It is a very small positive number. This is the magnification intensity control factor. The vibration intensity index of the workpiece. The stockpile risk index;

[0081] When the debris morphology is finer than ideal, >1, <1 indicates that the chip morphology is conducive to chip removal;

[0082] When the debris morphology is worse than ideal... <1, >1 indicates that the chip morphology is not conducive to chip removal.

[0083] In this embodiment, the workpiece vibration intensity index This is a quantitative indicator measuring the intensity of workpiece vibration during machining. It is obtained by comparing the real-time monitored workpiece vibration intensity with a preset safety threshold. This index reflects machining stability; excessive vibration usually indicates deteriorating cutting conditions and may lead to chip accumulation. It can be implemented by installing accelerometers or vibration sensors on the machining table or workpiece fixture to collect the workpiece vibration signal in real time, processing the signal to obtain the actual vibration intensity, and then calculating the ratio with the preset safety threshold. Alternatively, it can be achieved by monitoring the vibration or acoustic characteristics of the workpiece surface or surrounding environment using a non-contact laser vibrometer or acoustic sensor, extracting the vibration intensity parameter, and then normalizing it.

[0084] Debris morphology index This index quantifies the quality of chip morphology. It extracts characteristic values ​​related to chip morphology by analyzing the vibration spectrum generated during machining and comparing them with reference values ​​under ideal conditions. Chip morphology (such as length, curl, and fracture) directly affects the smoothness of chip removal; this index assesses the ease of chip removal. It can be implemented by using vibration or acoustic emission sensors mounted on the machining table 1 or the electric drill mechanism 5 to collect vibration or acoustic emission signals during the cutting process. These signals are then subjected to spectral analysis (such as Fourier transform) to extract energy distribution, peak frequency, and harmonic characteristics within a specific frequency range as chip morphology characteristic values. These values ​​are then compared with reference characteristic values ​​obtained beforehand through experiments or simulations under ideal chip conditions. Alternatively, chip images can be captured in real-time using a visual sensor (such as a high-speed camera). Image processing techniques (such as edge detection and morphological analysis) are used to extract the geometric features of the chips (such as length, width, and curl radius), converting them into chip morphology characteristic values, which are then compared with reference values.

[0085] The chip buildup risk assessment model is a comprehensive mathematical model used to quantify the likelihood and severity of chip accumulation during machining. It combines multiple key factors such as metal removal rate, chip evacuation rate, chip morphology, and workpiece vibration. This model calculates a chip buildup risk index. This provides the controller with a unified risk quantification index for subsequent adaptive control. The chip risk assessment module in the controller can integrate a digital signal processor or microcontroller, which receives data from the metal removal rate assessment module. Chip removal rate evaluation module and the calculated workpiece vibration intensity index and debris morphology index The processor performs real-time calculations based on the above formula and outputs the chip risk index. Alternatively, the mathematical model can be implemented through programming on an industrial PC or embedded system. The system acquires the input exponents via a data bus or network interface and efficiently completes the calculation using a floating-point arithmetic unit. Calculation of values. Among them, parameters... and It can be set as e 6 or e 9 Equal to extremely small positive numbers to avoid the denominator being zero; amplification intensity control coefficient It can be calibrated based on experience or experimental data, for example, set between 0.5 and 2.0, to adjust the sensitivity of vibration to risk.

[0086] The solution proposed in this application no longer relies solely on the metal removal rate index through the chip risk assessment module in the controller. and chip removal rate index It first monitors the vibration of the workpiece in real time using sensors and quantifies it into a workpiece vibration intensity index. This index reflects the stability of the machining process. Simultaneously, by performing spectral analysis on the vibration signals generated during the cutting process, feature values ​​related to chip morphology are extracted and compared with the ideal state to obtain the chip morphology characteristic index. This index directly reflects whether the chips are fine and easy to remove or worse and difficult to remove. It is based on the chip morphology characteristics index. The chip morphology deterioration coefficient was calculated. When the chip morphology is good ( When >1), <1, reducing the risk of chip buildup; when chip morphology deteriorates ( When <1), >1, which increases the risk of debris accumulation. Subsequently, the debris risk assessment module will... , , and Substitute the formula into the new chip risk assessment model: This model cleverly uses the dynamic balance between metal removal and chip removal as its foundation, and through... The influence of factors on chip morphology is corrected, and then... Factors in workpiece vibration intensity Exceeding the safety threshold (i.e.) > 1) When this further amplifies the risk of debris accumulation. This allows for a more comprehensive and real-time reflection of the processing status. The resulting chip accumulation risk index... As a more accurate input, this information is transmitted to the cooling water pressure control module, enabling the hydraulic system 6 to more precisely adjust the cooling water pressure to prevent or address chip accumulation. This multi-dimensional, dynamically integrated evaluation method solves the problems of single and inaccurate evaluation dimensions in traditional methods, allowing the entire grooving device for casting machining to perform machining control more intelligently and adaptively.

[0087] In a preferred embodiment of the present invention, the tool temperature index is obtained by dividing the actual tool temperature by the maximum allowable operating temperature of the tool material; in the cooling water pressure control model:

[0088] ;

[0089] in The rated water pressure of the cooling system, This is the proportional gain coefficient. This is the integral gain coefficient. The stockpile risk index. The preset target risk index, This is the temperature gain coefficient. This refers to the tool temperature index. The set temperature safety threshold, This is the water pressure adjustment value.

[0090] In this embodiment, the tool temperature index is used to quantify the current thermal state of the tool. It is obtained by comparing the actual temperature of the tool with the highest operating temperature that the tool material can withstand. The actual temperature can be obtained in various ways, such as non-contact measurement of the tool's cutting area using an infrared thermometer, or real-time monitoring using contact sensors such as thermocouples embedded inside or near the tool. The highest permissible operating temperature of the tool material is typically provided by the tool manufacturer or determined through materials science experiments; it represents the upper temperature limit of the tool material without significant performance degradation or failure. The introduction of this index allows the thermal load state of the tool to be standardized and quantified, providing a crucial input parameter for subsequent cooling water pressure regulation.

[0091] The cooling water pressure control model is used to dynamically calculate the cooling water pressure regulation value. The core algorithm of the system comprehensively considers chip buildup risk and tool temperature, aiming to achieve precise and adaptive control of the cooling water pressure of the hydraulic system 6. This model incorporates the concept of proportional-integral control to quickly respond to changes in chip buildup risk and eliminate steady-state errors, while also introducing a temperature compensation mechanism to address the risk of tool overheating. The rated water pressure of the cooling system is the maximum or design water pressure that the cooling system can provide under normal operating conditions. It represents the basic capacity of the cooling system and is used to calculate water pressure regulation values. The reference is the rated water pressure. This rated water pressure is usually determined by the hardware specifications of the cooling system 6, for example, it can be the maximum output pressure of the cooling pump.

[0092] proportional gain coefficient Used to measure the risk index of debris accumulation. With target risk index The instantaneous response strength of the deviation between the two. The larger the deviation, the greater the contribution of the proportional term, resulting in a larger water pressure regulation value. Able to make adjustments quickly. The setting of the integral gain coefficient needs to balance the system's response speed and stability. For example, it can be determined through empirical methods, the Ziegler-Nichols tuning method, or simulation analysis based on the system's dynamic characteristics. Used to eliminate the risk index of stacked debris With target risk index The system addresses the long-term steady-state error. It gradually adjusts the water pressure by accumulating historical deviations, ensuring that the system eventually reaches the target risk level even if the proportional term cannot completely eliminate the deviation. The settings also need to consider the dynamic response of the system; for example, it can be achieved by... Similar tuning methods can be optimized.

[0093] Chip Risk Index This is a quantitative index generated by the chip accumulation risk assessment module in the controller after constructing a chip accumulation risk assessment model based on influencing factors such as metal removal rate index, chip removal rate index, workpiece vibration intensity, and chip particle size. This index reflects the potential risk level of chip accumulation during the current processing and is one of the core inputs of the cooling water pressure control model.

[0094] Preset target risk index This represents the ideal level of chip buildup risk that the system aims to maintain. It is typically set to a low safety value to ensure the stability and safety of the machining process. This value can be empirically set based on the specific machining materials, tool types, machining process requirements, and safety production standards, or determined through experimental optimization.

[0095] Temperature gain coefficient Used for tool temperature index Exceeding the set temperature safety threshold At this time, the cooling water pressure adjustment value is increased. This means that when the risk of tool overheating increases, the system will more actively increase the cooling water pressure to enhance the cooling effect. The settings determine the system's sensitivity and response intensity to tool overheating. For example, different settings can be tested experimentally. The value is selected based on its impact on tool temperature control. Tool temperature index It is a standardized index, defined earlier, obtained by comparing the actual temperature of the tool with the maximum allowable operating temperature of the tool material. It provides real-time feedback on the thermal state of the tool for the cooling water pressure control model.

[0096] Set temperature safety threshold It is a critical value of the tool temperature index; when the tool temperature index... When this threshold is exceeded, the system will consider the tool to be at risk of overheating and trigger additional cooling water pressure enhancement measures. This threshold can be set according to the heat resistance of the tool material, machining process requirements, and empirical data; for example, it can be set as a percentage of the maximum allowable operating temperature of the tool material.

[0097] Water pressure regulation value This is the adjustment amount that needs to be made to the current water pressure of the cooling system 6, calculated by the cooling water pressure control model. This value can be positive (increase water pressure) or negative (decrease water pressure), and it will be directly output to the hydraulic system 6 to achieve dynamic control of the cooling water pressure.

[0098] This application's solution introduces an advanced cooling water pressure control model, achieving intelligent and adaptive adjustment of cooling water pressure during casting processing. The core of this model lies in incorporating the chip buildup risk index... With the preset target risk index The deviation between them is used as the main control variable, combined with the tool temperature index. Compensation is then performed. Specifically, the cooling water pressure control module in the controller first acquires the real-time debris risk index generated by the debris risk assessment module. and compare it with the preset target risk index. A comparison was made. To ensure a rapid response and eliminate bias, the model employed a proportional-integral control strategy, specifically using the proportional gain coefficient... Adjust the current deviation in real time, and use the integral gain coefficient. Historical cumulative deviations are corrected to ensure that the cooling water pressure quickly and accurately approaches the pressure required to maintain the target risk level. Furthermore, to further enhance machining safety and stability, the model also incorporates a tool temperature compensation mechanism. Tool temperature index. This is obtained by standardizing the actual tool temperature with the maximum allowable operating temperature of the tool material. When this index exceeds a set temperature safety threshold... At that time, temperature gain coefficient This will activate the water pressure regulation value. This is amplified. This means that when the tool faces the risk of overheating, the system will proactively and actively increase the cooling water pressure to enhance the cooling effect, thereby effectively suppressing further increases in tool temperature and preventing accelerated tool wear or damage. The entire control process is a closed-loop feedback system. Chip Accumulation Risk Index The generation of the cooling water pressure control model relies on the outputs of the metal removal rate assessment module and the chip removal rate assessment module. These modules integrate multiple machining parameters, including tool depth of cut, feed rate, tool diameter, tool helix angle, effective cross-sectional area of ​​the chip flue, cooling water flow rate, and cooling water pressurization speed. Therefore, the cooling water pressure control model can fully utilize this multi-dimensional information to achieve comprehensive perception and precise response to the machining state. In this way, the cooling water pressure is no longer static or simply switched on and off, but dynamically adjusted according to the real-time chip accumulation risk and tool thermal load. This effectively solves the problems of traditional cooling systems, such as lagging regulation and inability to adapt to complex machining conditions, significantly improving cooling effect and chip removal efficiency.

[0099] As a preferred embodiment of the present invention, it further includes a tool horizontal feed rate adjustment module, which is used to construct a tool horizontal feed rate adjustment model based on the chip accumulation risk index and the actual tool horizontal feed rate, output the tool horizontal feed rate adjustment amount, and adjust the tool horizontal feed rate accordingly.

[0100] In this embodiment, the tool horizontal feed rate adjustment module is a functional unit of the controller. Its main responsibility is to intelligently adjust the tool's horizontal feed rate based on the real-time status during machining. This module can be implemented as a software program, running as an algorithm process within the controller; alternatively, it can be implemented using dedicated hardware circuitry, such as integration into a programmable logic controller or digital signal processor, to ensure high-speed response and stability. Its core function is to transform risk assessment results into specific feed rate adjustment commands, thereby achieving adaptive control of the machining process.

[0101] Constructing a tool horizontal feed rate adjustment model is the core algorithm for achieving intelligent adjustment. It receives the chip risk index from the chip risk assessment module and the current actual horizontal feed rate of the tool as input. Through internal logical or mathematical relationships, it calculates the necessary adjustment to the feed rate. This model can be constructed in various ways. For example, it can be based on expert experience and preset rules, proportionally reducing the feed rate when the chip risk index exceeds a certain threshold; or it can employ fuzzy logic control, reasoning based on a fuzzy set of the risk index and feed rate; or it can utilize machine learning algorithms, training on historical machining data to learn the nonlinear relationship between the risk index and the optimal feed rate adjustment.

[0102] The model calculates the tool's horizontal feed rate adjustment as an increment or decrement relative to the current tool's horizontal feed rate. This adjustment can be an absolute value, such as adjusting the feed rate to a specific value; or a relative value, such as increasing or decreasing the feed rate by a certain percentage. The output can be a digital signal, sent to the actuator via a communication interface, such as a pulse signal, analog voltage signal, or digital bus command.

[0103] Upon receiving the adjustment amount, the actuator of the device changes the horizontal movement speed of the tool accordingly. This is typically achieved by controlling the motor speed of the thread thrust assembly 3 that drives the slide 2. For example, if the adjustment amount indicates a decrease in feed rate, the controller sends a deceleration command to the drive motor of the thread thrust assembly 3, thereby slowing down the horizontal movement speed of the slide 2 and thus reducing the horizontal feed rate of the tool. Conversely, if the adjustment amount indicates an increase in feed rate, an acceleration command is sent.

[0104] This application's solution achieves adaptive control of the grooving device used for casting machining by introducing a tool horizontal feed rate adjustment module. Specifically, the chip accumulation risk assessment module in the controller continuously monitors and generates a real-time chip accumulation risk index. This chip accumulation risk index comprehensively considers multiple dimensions such as the metal removal rate index, chip removal rate index, workpiece vibration intensity index, and chip morphology characteristic index, and can comprehensively and accurately reflect the potential risk of chip accumulation during the current machining process. When the chip accumulation risk assessment module outputs the chip accumulation risk index, the tool horizontal feed rate adjustment module receives the index and combines it with the current actual horizontal feed rate of the tool. The tool horizontal feed rate adjustment model built inside this module intelligently calculates the amount of adjustment required for the tool horizontal feed rate based on these input parameters. For example, when the chip accumulation risk index increases, indicating an increased risk of chip accumulation, the adjustment model will calculate a negative adjustment amount, indicating a reduction in feed rate; conversely, when the risk index decreases, indicating a good machining condition, it may calculate a positive adjustment amount, indicating an appropriate increase in feed rate. The calculated adjustment amount of the tool's horizontal feed rate is then sent to the actuator of the thread thrust assembly 3. The thread thrust assembly 3 adjusts the horizontal movement speed of the sliding block 2 on the machining table 1 by precisely controlling the rotational speed of its drive motor, thereby achieving dynamic adjustment of the tool's horizontal feed rate. This closed-loop feedback control mechanism enables the device to automatically and promptly adjust the tool's feed rate based on real-time machining conditions, especially changes in chip accumulation risk, effectively avoiding chip accumulation risks and ensuring the stability and safety of the machining process. In this way, this solution combines multi-dimensional, real-time assessed chip accumulation risk index with dynamic adjustment of the tool feed rate, forming an intelligent adaptive control system. This not only solves the problem of ineffective utilization of assessment results in traditional devices, but more importantly, it enables the device to take preventative measures at the initial stage or before the occurrence of chip accumulation risk, proactively managing risk by adjusting the feed rate rather than passively responding, thus significantly improving machining stability and efficiency, and extending tool life.

[0105] In a preferred embodiment of the present invention, the tool horizontal feed rate adjustment model is as follows:

[0106]

[0107] in This represents the current actual feed rate. The stockpile risk index. For the set risk threshold, Within the risk saturation range, This is the maximum deceleration ratio (the ratio of the maximum deceleration value in a single operation to the current feed rate). The maximum recovery rate (the ratio of the maximum single-time growth rate to the current feed rate). The set recovery rate coefficient, This is the adjustment amount for the horizontal feed rate of the cutting tool.

[0108] In this embodiment, the current actual feed rate This refers to the current horizontal movement speed of the cutting tool during machining. This parameter is the basis for feed rate adjustment; any adjustment will be calculated and applied based on this speed to ensure the continuity and smoothness of the adjustment. Its value can be read in real time by the machine tool's CNC system or measured by sensors.

[0109] The chip accumulation risk index R is a comprehensive indicator used to quantify the risk level of chip accumulation under current machining conditions. The index calculation considers multiple factors such as metal removal rate, chip evacuation rate, workpiece vibration intensity, and chip particle size; a higher value indicates a greater chip accumulation risk. This index is generated by the chip accumulation risk assessment module and serves as the core input parameter for the tool horizontal feed rate adjustment model.

[0110] Set risk threshold It is a preset critical value used to determine whether the current debris risk has reached a level requiring deceleration measures. When the debris risk index... Exceed When this happens, the system will activate a deceleration strategy; when Below In such cases, the system may consider restoring the feed rate. This threshold can be set empirically, for example, by analyzing historical machining data under different materials, tools, and machining parameters to determine at what risk level machining anomalies begin to occur, thereby setting a safe and effective threshold. Alternatively, it can be automatically determined through machine learning methods, trained and optimized based on large amounts of machining data. .

[0111] Risk saturation range This is a parameter used to limit the deceleration rate; it defines the threshold at which the chip risk index R exceeds a certain risk threshold. After that, the risk index and The difference between them is within the effective range when calculating the deceleration ratio. and The difference exceeds At this point, the deceleration ratio will no longer increase linearly with the increase of the difference, but will reach the maximum deceleration ratio. The upper limit is set to avoid excessive deceleration due to an excessively high risk index. The settings can be based on an understanding of the dynamic response of the processing system. For example, experiments can be used to determine at what risk difference the system needs to take maximum deceleration measures to quickly avoid risks.

[0112] Maximum deceleration ratio This indicates the maximum allowable reduction in the tool's horizontal feed rate during a single adjustment. This percentage limits the extent to which the system can reduce the feed rate when the risk of chip buildup is high, preventing machining instability or a sudden drop in efficiency due to excessive deceleration. The setting needs to take into account the machine tool's dynamic response capability, the tool's durability, and the requirements of machining efficiency. For example, it can be set to 10% or 20% of the current feed rate to ensure that the deceleration process is smooth and effective.

[0113] Maximum recovery rate This indicates the maximum permissible increase in the tool's horizontal feed rate during a single adjustment. This percentage limits the system's recovery rate after the risk of chip buildup decreases, preventing the risk from recurring due to excessively rapid increases or causing machining oscillations. The settings also need to take into account the stability of the system. For example, they can be set to 5% or 10% of the current feed rate to ensure that the recovery process is gradual and safe.

[0114] Set recovery speed coefficient It is a coefficient used to adjust the feed rate recovery speed. When the chip risk index... Below the risk threshold When, this coefficient is with and The difference between these values ​​determines the rate of increase in the feed rate. The higher the value, the faster the recovery speed; The smaller the value, the slower the recovery speed. This coefficient can be adjusted based on the trade-off between processing efficiency and system stability; for example, it can be increased appropriately when higher efficiency is required. However, when high stability is required, the value can be appropriately reduced. .

[0115] Tool horizontal feed rate adjustment This refers to the adjustment required to the horizontal feed rate of the tool within the current machining cycle. This adjustment can be positive (indicating an increase in speed), negative (indicating a decrease in speed), or zero (indicating maintaining the current speed). The calculation results will be directly applied to the machine tool's feed system to achieve dynamic control of the tool's horizontal feed speed.

[0116] The recovery period refers to the mandatory waiting time from the start of the deceleration operation triggered by the chip buildup risk until the system is allowed to begin considering restoring the feed rate. The purpose of setting a recovery period is to ensure that the system does not immediately restore the feed rate when the risk has just decreased, thus giving the machining process sufficient time to stabilize and avoiding repeated risks. The recovery period can be set empirically, for example, as several seconds or tens of seconds, or it can be calculated through modeling and analyzing the physical characteristics of the machining process.

[0117] Safe time refers to the period during which the chip risk index is within the recovery period. Persistently below the risk threshold The required continuous time length. Only when the risk index... Maintain throughout the recovery period Only after the specified duration meets the safety time requirement will the system be allowed to enter the feed rate recovery phase. The safety time setting further enhances the reliability of the system's feed rate recovery, preventing premature acceleration before the risk has been fully eliminated. The safety time can also be set based on experience or determined through historical data analysis.

[0118] The tool horizontal feed rate adjustment model proposed in this application adjusts the chip buildup risk index. Current actual feed rate By comprehensively judging and calculating a series of preset parameters, the horizontal feed rate of the tool is controlled. The model employs adaptive adjustment. Its core lies in its segmented adjustment strategy. First, the system continuously monitors the chip risk index generated by the chip risk assessment module. When the chip risk index Exceeding the set risk threshold If the system is not currently in a forced wait recovery period, the model will calculate a negative adjustment. This means performing a deceleration operation. The magnitude of the deceleration is not constant, but rather depends on... and The difference between them is dynamically adjusted, and the risk saturation range is used as a guide. and maximum deceleration ratio Limitations are imposed to ensure that deceleration effectively addresses risks without causing excessive deceleration that could impact processing efficiency. This proportional deceleration mechanism, based on risk level, allows the system to precisely respond to the severity of risks, avoiding the one-size-fits-all deceleration strategies of traditional methods. Secondly, when the chip stack risk index... Reduced and below the risk threshold Once the system has met the safety time requirement, the model will calculate a positive adjustment. This means performing an increase in growth rate. The magnitude of the increase is also dynamic, depending on... and The difference between them and the set recovery rate coefficient Calculations are performed, and the maximum recovery ratio is used. Limitations are imposed. This gradual increase strategy, combining a recovery period and a safety time, effectively avoids prematurely resuming high-speed feed before the risk is fully mitigated or the system is fully stable, thus preventing repeated risks and processing oscillations. The introduction of a recovery period and a safety time provides the system with necessary buffering and verification mechanisms, ensuring the robustness of the recovery process. In other cases, i.e., when the chip risk index... Not exceeding And not lower than When the model reaches a point where recovery is needed, or when it is in the recovery phase but the safety time has not yet been met, the model will output zero adjustment. The system maintains the current feed rate. This ensures that the system does not make unnecessary frequent adjustments when the machining state is stable or in a transitional phase, thus maintaining the smoothness of the machining process. This solution is closely integrated with the aforementioned tool horizontal feed rate adjustment module and chip accumulation risk assessment module to form a complete closed-loop control system. The chip accumulation risk assessment module provides quantitative risk information in real time, and this model intelligently adjusts the tool's horizontal feed rate based on this information and the current feed rate. This collaborative working mechanism enables the device to shift from passively responding to risks to actively preventing risks. By precisely controlling the feed rate, the device can effectively avoid chip accumulation, reduce tool wear, and improve machining quality and efficiency. For example, when the chip accumulation risk index... When the feed rate increases due to changes in cutting conditions, the system can quickly and smoothly reduce it, thereby reducing the metal removal rate, alleviating chip removal pressure, and effectively preventing chip buildup. Once the risk is eliminated, the system can gradually restore the feed rate in a timely manner to ensure machining efficiency. This adaptive feed rate adjustment capability significantly improves the intelligence level and machining stability of the grooving device for casting machining.

[0119] 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, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A grooving device for casting processing, comprising a processing table (1), wherein a sliding seat (2) is slidably connected to the processing table (1), a threaded thrust assembly (3) for driving the sliding seat (2) to move horizontally is provided on the processing table (1), an electric lifting seat (4) is fixedly connected to the sliding seat (2), and an electric drill mechanism (5) is fixedly connected to the electric lifting seat (4), the electric drill mechanism (5) performs grooving operation by rotating an internal tool, the electric drill mechanism (5) is connected to a hydraulic system (6), the hydraulic system (6) being able to connect to an external water channel and an internal spray hole of the electric drill mechanism (5), characterized in that, It also includes a controller, which includes: The metal removal rate evaluation module is used to construct a metal removal rate evaluation model based on the tool cutting depth, the actual horizontal feed rate of the tool, and the tool diameter, and output the metal removal rate index. The chip removal rate evaluation module is used to construct a chip removal rate evaluation model based on the tool helix angle, the effective cross-sectional area of ​​the chip removal groove, the cooling water flow rate, and the cooling water pressurization speed, and output the chip removal rate index. The chip accumulation risk assessment module uses workpiece vibration intensity and chip particle size as influencing factors to construct a chip accumulation risk assessment model based on the metal removal rate index and chip removal rate index, and generates a chip accumulation risk index. The cooling water pressure control module is used to build a cooling water pressure control model based on the rated cooling water pressure, chip accumulation risk index and current tool temperature, and output the cooling water pressure adjustment value to the hydraulic system (6) for regulation.

2. The grooving device for casting processing according to claim 1, characterized in that, In the metal removal rate evaluation model: The metal removal rate index is equal to the product of the depth of cut index, the feed rate index, and the tool diameter index, multiplied by a positive correlation factor related to the material's unit cutting force. This enhancement factor is 1 plus the product of the material's unit cutting force index and a preset coefficient.

3. The grooving device for casting processing according to claim 2, characterized in that, The depth of cut index is obtained by dividing the actual depth of cut by the tool by the maximum allowable depth of cut; the feed rate index is obtained by dividing the actual feed rate by the maximum allowable horizontal feed rate of the machine tool; the tool diameter index is obtained by dividing the actual diameter by the nominal diameter; and the material unit cutting force index is obtained by dividing the unit cutting force of the cutting material by the unit cutting force of the reference material.

4. The grooving device for casting processing according to claim 1, characterized in that, In the chip removal rate evaluation model: The chip removal rate index is equal to the product of the helix angle index and the chip removal groove area index, multiplied by the product of the cooling system flow rate index and the stamping speed index, and multiplied by an attenuation factor related to the chip bulk density, which is 1 minus a compensation term related to the chip bulk density index.

5. The grooving device for casting processing according to claim 4, characterized in that, The helix angle index is obtained by dividing the actual helix angle of the tool by the helix angle of the reference tool; the chip flute area index is obtained by dividing the actual chip flute area of ​​the tool by the reference chip flute area. The cooling system flow rate index is obtained by dividing the actual cooling system flow rate by the upper limit of the cooling system flow rate. The stamping speed index is obtained by dividing the actual water flow stamping speed of the cooling system by the upper limit of the water flow stamping speed; the chip packing density index is obtained by dividing the actual chip packing density by the reference chip packing density.

6. The grooving device for casting processing according to claim 1, characterized in that, The workpiece vibration intensity index is obtained by dividing the actual vibration intensity of the workpiece by the vibration intensity safety threshold; the chip morphology characteristic index is obtained by dividing the chip morphology characteristic value obtained from the vibration spectrum analysis of the casting by the reference characteristic value under ideal chip conditions; in the chip accumulation risk assessment model: The chip accumulation risk index is the product of the metal removal rate index and the chip morphology deterioration coefficient, divided by the sum of the chip removal rate index and a very small positive number, and then multiplied by a coefficient amplified by the part of the workpiece vibration intensity index that exceeds the safety threshold. The chip morphology deterioration coefficient is inversely proportional to the chip morphology characteristic index. When the chip morphology is better than the ideal state, the coefficient is less than 1, and vice versa.

7. The grooving device for casting processing according to claim 1, characterized in that, The tool temperature index is obtained by dividing the actual tool temperature by the maximum allowable operating temperature of the tool material; in the cooling water pressure control model: The water pressure adjustment value is the rated water pressure multiplied by the proportional integral term based on the deviation between the chip stack risk index and the preset target risk index, and then multiplied by the coefficient amplified by the portion of the tool temperature index exceeding the safety threshold.

8. The grooving device for casting processing according to claim 1, characterized in that, It also includes a tool horizontal feed rate adjustment module, which is used to construct a tool horizontal feed rate adjustment model based on the chip accumulation risk index and the actual tool horizontal feed rate, output the tool horizontal feed rate adjustment amount, and adjust the tool horizontal feed rate accordingly.

9. The grooving device for casting processing according to claim 8, characterized in that, In the tool horizontal feed rate adjustment model, the adjustment amount of the tool horizontal feed rate is controlled in segments based on the comparison result between the chip accumulation risk index and the set threshold: When the risk index is above the threshold and is not in the recovery period, the amount of feed rate reduction is determined based on the ratio of the current feed rate to the degree of risk exceeding the threshold. When the risk index is below the threshold and the safe time condition is met, the increase in feed rate is determined based on the ratio of the current feed rate to the degree to which the risk is below the threshold. In all other cases, the feed rate adjustment is zero; The recovery period and safety time are set based on experience or historical data.

Images