Gear cutting tool parameter control system based on bevel angle cutting

Abstract

The invention relates to the technical field of tool control, in particular to a tooth cutting tool parameter control system based on bevel angle cutting, which comprises a tool parameter acquisition module used for acquiring the rotating speed, the axial feeding amount and the cutting depth of a tool in real time; the force-heat prediction model is used for outputting predicted cutting force and predicted cutting tool temperature; the multi-target parameter optimization model is used for receiving constraint conditions set by a user, optimizing the rotating speed, the axial feeding amount and the cutting depth of the cutter by taking the lowest cutting force, the lowest temperature of the cutting cutter and the highest machining efficiency as targets in the constraint conditions, and integrating and outputting a regulation and control strategy; and the cutter parameter control module is used for regulating and controlling the rotating speed, the axial feeding amount and the cutting depth of the cutter based on a regulation and control strategy when the predicted cutting force and the predicted temperature of the cutting cutter exceed threshold values. According to the method, by accurately regulating and controlling the parameters of the tooth cutting tool, the machining efficiency of the tooth cutting tool can be ensured, and meanwhile the abrasion speed of the tooth cutting tool is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of tool control, and particularly relates to a parameter control system for a gear shaving tool based on oblique cutting. Background Art

[0002] The gear shaving technology is a new method for machining cylindrical gears, which mainly aims at the machining problems of non-through and internal helical gears without undercuts that cannot be completed by traditional gear machining methods. This technology plays an important role in the demand for special structure gears in industries such as aviation, aerospace, automotive, and wind energy. The characteristics of gear shaving are dry, intermittent, and micro-cutting, with advantages such as continuous, high-efficiency, and high-precision.

[0003] During the gear shaving process, slight changes in cutting parameters may cause non-linear fluctuations in cutting force and cutting heat, which will affect the tool wear condition and service life. In actual production, the cutting parameters of gear shaving tools are generally controlled by experience. Due to the lack of full consideration of the workpiece situation in the actual machining process, it is easy to limit the machining efficiency of gear shaving tools and increase the wear of gear shaving tools.

[0004] In summary, it is necessary to propose a parameter control technology for gear shaving tools to ensure the machining efficiency of gear shaving tools and at the same time slow down the wear speed of gear shaving tools. Summary of the Invention

[0005] To solve the above problems, the present invention provides a parameter control system for a gear shaving tool based on oblique cutting, which is used to ensure the machining efficiency of the gear shaving tool and at the same time slow down the wear speed of the gear shaving tool.

[0006] To achieve the above object, the technical solution of the present invention is as follows: A parameter control system for a gear shaving tool based on oblique cutting, comprising: A tool parameter acquisition module, which is used to acquire the tool rotation speed, axial feed amount, and cutting depth in real time; A force-thermal prediction model, which is used to output the predicted cutting force and the predicted cutting tool temperature based on the tool rotation speed, axial feed amount, and cutting depth acquired in real time; A multi-objective parameter optimization model, which is used to receive the constraint conditions set by the user, and optimize the tool rotation speed, axial feed amount, and cutting depth with the lowest cutting force, the lowest cutting tool temperature, and the highest machining efficiency as the objectives within the constraint conditions, and integrate and output a regulation strategy; A tool parameter control module, which is used to regulate the tool rotation speed, axial feed amount, and cutting depth based on the regulation strategy; A chip collection unit, which is used to acquire the chip thickness and chip area in real time, calculate and output the actual cutting force; and is used to acquire the chip temperature in real time, calculate and output the actual cutting tool temperature; The tool parameter control module is further configured to compensate the tool rotation speed, the axial feed rate, and the cutting depth based on the actual cutting force and the actual cutting tool temperature.

[0007] Furthermore, the force-thermal prediction model is constructed as follows: Select a neural network architecture for constructing the force-thermal prediction model; Use the historical tool rotation speed, axial feed rate, and cutting depth as inputs, and the cutting force and predicted cutting tool temperature corresponding to the historical tool rotation speed, axial feed rate, and cutting depth as outputs to train the neural network; Evaluate the accuracy of the neural network prediction results using the mean absolute error, root mean square error, and mean absolute percentage error as follows: Mean absolute error:

[0008] Root mean square error:

[0009] Mean absolute percentage error: ; In the above formulas, is the original data, is the predicted value, is the number of data; Optimize the trained neural network, and use the neural network that meets the prediction accuracy after training as the force-thermal prediction model.

[0010] Furthermore, the machining efficiency is defined as the ratio of the chip volume formed during a single blade sweep process of the gear shaving tool to the sweeping time, as follows:

[0011] In the formula, is the chip volume, is the sweeping time.

[0012] Furthermore, the objective function of the multi-objective parameter optimization model is set as follows:

[0013]

[0014]

[0015] In the formula, is the cutting tool temperature, is the cutting force; The set constraints are that the tool rotation speed is 450 - 700 r / min, the chip depth is 0.1 - 0.3 mm, and the axial feed rate is 0.1 - 0.2 mm / r; the multi-objective parameter optimization model for optimizing the tool rotation speed, axial feed rate, and cutting depth needs to satisfy the following constraints:

[0016]

[0017] In the formula, is the minimum tool rotation speed, is the maximum tool rotation speed, is the tool rotation speed variable;

[0018]

[0019] In the formula, is the minimum axial feed rate, is the maximum axial feed rate, is the axial feed rate variable;

[0020]

[0021] In the formula, is the minimum cutting depth, is the maximum cutting depth, is the cutting depth variable; The multi-objective parameter optimization model is:

[0022]

[0023] In the formula, is the Pareto optimal solution set.

[0024] Furthermore, the chip collection unit includes a fixed flange for connecting to the machine tool. A first chip channel is provided in the middle of the fixed flange. A flexible vibrating disk is fixedly connected to the top of the fixed flange. A second chip channel is provided in the middle of the flexible vibrating disk. A number of rotatable vanes are provided in the second chip channel. A first driving member for driving the vanes to rotate is provided in the side wall of the flexible vibrating disk. In the initial state, the vane combination closes the second chip channel; A detection ring groove is provided on the side wall of the flexible vibrating disk. A detection slide rail is provided in the detection ring groove. A detection slide seat is slidably connected to the detection slide rail. A light source, a CCD camera, and an infrared sensor are fixedly connected to the detection slide seat. The light source, the CCD camera, and the infrared sensor all face the axis of the second chip channel; It further includes a detection module which is used to control the operation of the flexible vibrating disk, the first driving member and the detection sliding seat. The detection module is also used to collect the chip image information on the blade plate based on the light source and the CCD camera, process and output the chip thickness and the chip area based on the chip image information, and process and output the chip temperature based on the temperature information collected by the infrared sensor.

[0025] Furthermore, the detection module is used to control the operation of the flexible vibrating disk to evenly spread the collected chips on the surface of the blade plate. Subsequently, it controls the operation of the detection sliding seat, and at the same time controls the operation of the light source, and controls the CCD camera to continuously collect the chip images on the surface of the blade plate to generate chip image information, and performs binary processing on the chip image information to obtain the bright spot area with a gray value higher than the threshold in the chip image information. The detection module is used to obtain the switching interval of the bright spot area with a medium gray value higher than the threshold in the chip image information, define the bright spot area with a switching interval less than or equal to the threshold as the chip thickness acquisition area, define the bright spot area with a switching interval greater than the threshold as the chip area acquisition area, calculate and output the chip thickness based on the chip thickness acquisition area, and calculate and output the chip area based on the chip area acquisition area.

[0026] Furthermore, calculate the actual cutting force based on the chip thickness and the chip area:

[0027] In the formula, is the unit area cutting force when the chip cross-section thickness and width are both 1 mm, which is a constant and measured through experiments; is the chip area, is the chip thickness, is a fixed value coefficient representing the influence of the chip thickness on the cutting force; is the influence coefficient of the cutting rake angle on the cutting force;

[0028] In the formula, is the shaft intersection angle, which is the angle between the axis of the face hobbing cutter and the axis of the workpiece.

[0029] Furthermore, calculate the actual cutting tool temperature based on the chip temperature:

[0030] In the formula, is the temperature rise of the face hobbing cutter caused by the friction between the face hobbing cutter and the chip, is the initial temperature of the face hobbing cutter; The temperature rise of the face hobbing cutter caused by the friction between the face hobbing cutter and the chip , and the calculation formula is as follows:

[0031] In the formula, is the chip temperature, is the chip temperature rise caused by shear deformation, is the initial temperature of the workpiece.

[0032] Furthermore, the detection module is used to control the first driving member to reciprocate once every 1 - 3 s, and control the flexible vibrating disk to continuously operate for 1 - 2 s after the reciprocating motion of the first driving member is completed.

[0033] Furthermore, a plurality of support shafts are fixedly connected to the fixed flange. A fixed ring is fixedly connected to one end of the support shaft away from the fixed flange. A protective cover is arranged between the fixed flange and the fixed ring. The protective cover is slidably matched with the support shaft. A lead screw is also arranged between the fixed ring and the fixed flange. The protective cover is in threaded cooperation with the lead screw. A second driving member for driving the lead screw to rotate is fixedly connected to the fixed ring or the fixed flange; the detection module is used to control the operation of the second driving member.

[0034] Adopting the above - mentioned scheme has the following beneficial effects: 1. In the present invention, based on the established force - heat prediction model, the predicted cutting force and the predicted cutting tool temperature under different skiving cutter parameters are predicted. Combining with the multi - objective parameter optimization model, an optimal solution set is sought near the real - time skiving cutter parameters, and the parameters of the skiving cutter are preliminarily adjusted based on this optimal solution set. At the same time, based on the real - time generated chip condition, the actual cutting force and the actual cutting tool temperature are obtained, and then the parameters of the skiving cutter are further compensated.

[0035] Compared with the prior art, through the force - heat prediction model and the multi - objective parameter optimization model, the real - time adjustment of the skiving cutter parameters is realized, so that the skiving cutter parameters can be quickly adjusted near the user - preset parameters. While initially reducing the cutting force and the cutting tool temperature, the machining efficiency is ensured. Then, considering the actual operating state of the machine tool, the parameters of the skiving cutter are compensated based on the actual cutting force and the actual cutting tool temperature, so that the operating parameters of the skiving cutter are more in line with the actual operating state of the machine tool, further reducing the cutting force and the cutting tool temperature, ensuring the machining efficiency, and effectively slowing down the wear speed of the skiving cutter.

[0036] 2. In the present invention, making full use of the dry - machining characteristics of skiving machining, the chips generated during the machining process can intuitively reflect the cutting force and the cutting temperature at the machining part between the skiving cutter and the workpiece. Based on the metal material characteristics of the chips, the chip area and thickness are accurately and efficiently obtained. The cutting force is calculated through the chip area and thickness, and the cutting temperature is calculated through the temperature after the chips fall off. Compared with the prior art, when collecting the actual cutting force and the actual cutting temperature, it is safer, more efficient, more convenient, and will not interfere with the workpiece and the skiving cutter during machining.

[0037] 3. In the present invention, the parameters of the gear shaving cutter are preliminarily adjusted in a timely manner based on the predicted cutting force and cutting temperature, and the parameters of the gear shaving cutter are compensated based on the actual cutting force and cutting temperature. The running time of the gear shaving cutter under unreasonable operating parameters is reduced, the adaptability of the operating parameters of the gear shaving cutter to the actual operating state of the machine tool is improved, it is ensured that the operating parameters of the gear shaving cutter more conform to the actual operating state of the machine tool, and the wear rate of the gear shaving cutter is slowed down.

[0038] Additional aspects and advantages of the present invention will be given in part in the following description, will become apparent in part from the following description, or will be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a schematic structural diagram of the system according to an embodiment of the present invention; Figure 2 is a three-dimensional structural diagram of the chip collection unit according to an embodiment of the present invention; Figure 3 is a top view of the chip collection unit according to an embodiment of the present invention; Figure 4 is Figure 3 the A-A cross-sectional view of

[0040] Reference numerals in the accompanying drawings of the specification include: 1. Fixed flange; 2. Support shaft; 3. Fixed ring; 4. Protective cover; 5. Flexible vibrating bowl; 6. Vane; 7. Second driving member; 8. Transparent protective plate; 9. Detection slide rail; 10. Detection slide seat. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The technical solutions of the present invention will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0042] The following will be further described in detail through specific embodiments: Embodiment 1, as shown in the Figure 1 accompanying drawings: A kind of... mainly consists of a cutter parameter acquisition module, a force-thermal prediction model, a multi-objective parameter optimization model, a cutter parameter control module, and a chip collection unit. The cutter parameter acquisition module is signal-connected to the numerical control system of the numerical control machine tool; the cutter parameter acquisition module, the force-thermal prediction model, the multi-objective parameter optimization model, and the cutter parameter control module are integrated in a terminal with data processing capabilities, and this terminal can be a programmable logic controller (PLC), a human-machine interface (HMI), an industrial PC (IPC), etc.; the chip collection unit is installed at the chip collection place of the machine tool.

[0043] The tool parameter acquisition module is used to collect the tool rotation speed, axial feed rate, and cutting depth of the current shaving tool in real time from the numerical control system of the numerically controlled machine tool. The tool rotation speed, axial feed rate, and cutting depth it collects are closely related to the cutting force and cutting tool temperature during the operation of the shaving tool. Therefore, by regulating the tool rotation speed, axial feed rate, and cutting depth of the shaving tool, the cutting force and cutting tool temperature can be effectively reduced, thereby slowing down the wear rate of the shaving tool.

[0044] The force-thermal prediction model is mainly used to predict the cutting force and cutting tool temperature under different tool rotation speeds, axial feed rates, and cutting depths. The force-thermal prediction model of this embodiment is constructed based on a neural network, and it can effectively fit the non-linear relationship between the tool rotation speed, axial feed rate, and cutting depth and the cutting force and cutting tool temperature, so as to efficiently and conveniently predict the current cutting force and cutting tool temperature during the operation of the shaving tool.

[0045] Specifically, a force-thermal prediction model is constructed based on the GA-BP neural network architecture. The GA-BP neural network combines the optimization algorithms of the genetic algorithm (GA) and the backpropagation neural network (BP). The genetic algorithm is used to optimize the weight and bias parameters of the BP neural network to improve the learning efficiency and performance of the network.

[0046] To meet the prediction requirements of cutting force and cutting tool temperature during the machining of workpieces with different materials and parts with different tooth profiles, during the shaving machining process in different scenarios, a number of tool rotation speed, axial feed rate, and cutting depth data are collected and recorded, and used as the input of the GA-BP neural network. The cutting force and cutting tool temperature under the operation of each group of tool rotation speed, axial feed rate, and cutting depth are collected and excited, and used as the output of the GA-BP neural network. The GA-BP neural network is trained to obtain the force-thermal prediction model. The specific training methods and steps are well-known existing technologies in this field and will not be elaborated here.

[0047] Subsequently, the accuracy of the prediction results of the preliminarily constructed force-thermal prediction model is evaluated to ensure that it can be used to predict the cutting force and cutting tool temperature of the shaving tool in the actual shaving machining scenario. In this embodiment, the mean absolute error, root mean square error, and mean absolute percentage error are respectively used: Mean absolute error:

[0048] Root mean square error:

[0049] Mean absolute percentage error:

[0050] In the above formulas, is the original data, is the predicted value, is the number of data.

[0051] Subsequently, the initially constructed force-thermal prediction model is optimized to ensure that the accuracy of its prediction results meets the requirements. The optimized and trained force-thermal prediction model is used to output the predicted cutting force and the predicted cutting tool temperature based on the real-time collected tool speed, axial feed rate, and cutting depth. The predicted cutting force and the predicted cutting tool temperature here are the predicted values output based on the tool speed, axial feed rate, and cutting depth, which are used to determine whether to preliminarily adjust the parameters of the gear shaving tool subsequently, so that the gear shaving tool can quickly get away from unreasonable operating parameters. Unreasonable operating parameters refer to the operating parameters that may cause significant wear to the gear shaving tool and have a greater impact on the machining efficiency. The operating parameters include the tool speed, axial feed rate, and cutting depth.

[0052] The multi-objective parameter optimization model is used to receive the constraint conditions set by the user. Here, the constraint conditions are mainly used to ensure that the solutions generated during the optimization process are feasible and avoid interference during the machining process, resulting in the inability to normally complete the workpiece machining with the parameters of the gear shaving tool. The constraint conditions set in this embodiment are the tool speed of 450 - 700 r / min, the chip depth of 0.1 - 0.3 mm, and the axial feed rate of 0.1 - 0.2 mm / r.

[0053] Subsequently, within the constraint conditions, with the lowest cutting force, the lowest cutting tool temperature, and the highest machining efficiency as the goals, the tool speed, axial feed rate, and cutting depth are optimized, and the regulation strategy is integrated and output. The regulation strategy corresponds to the Pareto optimal solution set output by the multi-objective parameter optimization model. The Pareto optimal solution set is mainly composed of the values of the decision variables and the values of the objective functions. Among them, the values of the decision variables are the optimal tool speed, axial feed rate, and cutting depth, and the values of the objective functions are the cutting force and the cutting tool temperature that the goals reach.

[0054] In this embodiment, for the optimal tool speed, axial feed rate, and cutting depth, based on the real-time collected tool speed, axial feed rate, and cutting depth, the Pareto optimal solution set close to them is sought to minimize the change in the operation of the original gear shaving tool as much as possible. Using the optimal tool speed, axial feed rate, and cutting depth to regulate the gear shaving tool can ensure that the cutting force and the cutting tool temperature are maintained near the cutting force and the cutting tool temperature that the goals reach, and have a high machining efficiency.

[0055] Specifically, the machining efficiency is defined as the ratio of the chip volume formed during a single edge sweep process of the gear shaving tool to the used sweeping time, as follows:

[0056] In the formula, is the chip volume, is the sweep time.

[0057] The objective function of the multi-objective parameter optimization model is set as follows:

[0058]

[0059]

[0060] In the formula, is the cutting tool temperature, is the cutting force; The set constraint conditions are that the tool speed is 450 - 700 r / min, the chip depth is 0.1 - 0.3 mm, and the axial feed is 0.1 - 0.2 mm / r; the multi-objective parameter optimization model needs to satisfy the following constraints when optimizing the tool speed, axial feed, and cutting depth:

[0061]

[0062] In the formula, is the minimum tool speed, is the maximum tool speed, is the tool speed variable;

[0063]

[0064] In the formula, is the minimum axial feed, is the maximum axial feed, is the axial feed variable;

[0065]

[0066] In the formula, is the minimum cutting depth, is the maximum cutting depth, is the cutting depth variable; The multi-objective parameter optimization model is:

[0067]

[0068] In the formula, is the Pareto optimal solution set.

[0069] In this embodiment, let the tool speed, axial feed rate, and cutting depth collected in real time be 525 r / min, 0.15 mm / r, and 0.15 mm respectively. Using the above multi-objective parameter optimization model to solve the Pareto optimal solution set, the following solution set (partial) is output: Table 1 Output solution set of the target parameter optimization model

[0070] From it, we can obtain the required control strategy, that is, the preferred tool speed, axial feed rate, and cutting depth are 550 r / min, 0.16724 mm / r, and 0.12318 mm respectively.

[0071] When the tool parameter control module is used to predict that the cutting force and the predicted cutting tool temperature exceed the threshold, the tool speed, axial feed rate, and cutting depth are adjusted based on the control strategy. Among them, the predicted cutting force and the predicted cutting tool temperature threshold can also be obtained according to the Pareto optimal solution set solved by the multi-objective parameter optimization model. The cutting force and cutting temperature that differ from the lowest cutting force and the lowest cutting tool temperature by a certain value can be used as the threshold, so as to ensure that when the operating parameters of the gear shaving tool deviate from the reasonable value, the adjustment is carried out immediately.

[0072] After adjusting the tool speed, axial feed rate, and cutting depth according to the control strategy, ideally, the cutting force and cutting tool temperature of the gear shaving tool are low, and it has a high machining efficiency. However, affected by the environment, vibration during the machining of the machine tool itself, and the installation accuracy of the tool and workpiece, there may still be a certain gap between the cutting force and cutting tool temperature and the optimal cutting force and cutting tool temperature. Therefore, it is necessary to compensate the tool speed, axial feed rate, and cutting depth of the gear shaving tool to make the cutting force and cutting tool temperature closer to the optimal cutting force and cutting tool temperature.

[0073] In this embodiment, the chip state during the gear shaving process is collected to determine the actual cutting force and the actual cutting tool temperature. The chip thickness and chip area are collected in real time by the chip collection unit, and the actual cutting force is calculated and output; the chip temperature is collected in real time, and the actual cutting tool temperature is calculated and output.

[0074] Specifically, the actual cutting force is calculated based on the chip thickness and chip area:

[0075] In the formula, is the unit area cutting force when the chip cross-section thickness and width are each 1 mm, which is a constant and is measured through experiments; is the chip area, is the chip thickness, is a fixed coefficient, representing the chip thickness influence on the cutting force; is the influence coefficient of the cutting rake angle on the cutting force;

[0076] In the formula, is the shaft intersection angle, the angle between the axis of the face hobbing cutter and the axis of the workpiece, which can be directly obtained through the numerical control system.

[0077] Calculate the actual cutting tool temperature based on the chip temperature:

[0078] In the formula, is the temperature rise of the face hobbing cutter caused by the friction between the face hobbing cutter and the chip, is the initial temperature of the face hobbing cutter; The temperature rise of the face hobbing cutter caused by the friction between the face hobbing cutter and the chip , and the calculation formula is as follows: ; In the formula, is the chip temperature, is the temperature rise of the chip caused by shear deformation, is the initial temperature of the workpiece.

[0079]

[0080] In the formula, is the heat conversion coefficient of the plastic shear work, is the strain rate hardening coefficient, is the cutting speed on the cutting edge participating in cutting, is the equivalent cross-section shear angle, is the shear strain, is the initial shear stress in the shear deformation zone, is the thermal diffusivity of the workpiece material, is the relative slip in the shear deformation zone, is the cutting thickness.

[0081] The above-mentioned initial temperature of the workpiece and the initial temperature of the face hobbing cutter are immediately collected by conventional temperature sensors.

[0082] The tool parameter control module is also used to compensate the tool rotation speed, axial feed rate, and cutting depth according to the actual cutting force and actual cutting tool temperature obtained from the above calculations. The compensation principle is as follows: based on the solution set output by the target parameter optimization model, obtain the change trends of the cutting force and cutting tool temperature when adjusting any one of the hobbing tool parameters of the tool rotation speed, axial feed rate, and cutting depth, so as to regulate the tool rotation speed, axial feed rate, and cutting depth, making the cutting force and cutting tool temperature close to the optimal cutting force and cutting tool temperature, so that the hobbing tool operates at a lower cutting force, lower cutting temperature, and higher machining efficiency. On the one hand, it can reduce the wear of the hobbing tool, and on the other hand, it can ensure a higher machining efficiency.

[0083] Embodiment 2, as shown in the attached Figures 2 - 4 figure, this embodiment provides a specific chip collection unit structure to accurately and conveniently collect parameters such as the temperature, thickness, and area of the chips. It includes a fixed flange 1 for connecting with the machine tool. A number of mounting holes are evenly distributed circumferentially on the fixed flange 1. The device can be connected to the chip collection place of the machine tool through the mounting holes using fixing bolts. A first chip channel is provided in the middle of the fixed flange 1, and a flexible vibrating disk 5 is fixedly connected to the top of the fixed flange 1. The principle of the flexible vibrating disk 5 is to achieve the efficient sorting of various irregularly shaped, micro-sized, and easily damaged parts through voice coil motor technology and flexible vibration technology. In this embodiment, it is applied to the rapid sorting of chips, and its main functions include spreading out the chips, and the spread chips have a certain regular distribution, for example, the side with greater mass faces the same direction.

[0084] A second chip channel is provided in the middle of the flexible vibrating disk 5. A number of rotatable leaf plates 6 are provided in the second chip channel. The principle of the leaf plates 6 is similar to that of an electric louver. A first driving member (servo motor) for driving the rotation of the leaf plates 6 is provided inside the side wall of the flexible vibrating disk 5. In the initial state, the combination of leaf plates 6 closes the second chip channel. When the combination of leaf plates 6 closes the second chip channel, the chips are collected on the surface of the leaf plates 6. When the leaf plates 6 rotate and do not close the second chip channel, the chips are discharged from the chip collection unit through the first chip channel and the second chip channel in sequence.

[0085] A detection ring groove is provided on the side wall of the flexible vibrating disk 5. A transparent protection plate 8 is fixedly connected to the side of the detection ring groove close to the second chip channel. A detection slide rail 9 is provided in the detection ring groove. A detection slide seat 10 is slidably connected to the detection slide rail 9. A light source (LED in this embodiment), a CCD camera, and an infrared sensor are fixedly connected to the detection slide seat 10. The light source, CCD camera, and infrared sensor all face the axis of the second chip channel.

[0086] It further includes a detection module. The detection module is used to control the operation of the flexible vibrating disk 5, the first driving member, and the detection slide 10. The detection module is also used to collect chip image information on the vane 6 based on a light source and a CCD camera, process and output the chip thickness and chip area based on the chip image information, and process and output the chip temperature based on the temperature information collected by an infrared sensor.

[0087] Specifically, the detection module is used to control the operation of the flexible vibrating disk 5 to evenly spread the collected chips on the surface of the vane 6; then control the operation of the detection slide 10, and at the same time control the light source to operate, and control the CCD camera to continuously collect the chip images on the surface of the vane 6 to generate chip image information, and perform binarization processing on the chip image information to obtain the bright spot area where the gray value in the chip image information is higher than the threshold.

[0088] The detection module is used to obtain the switching interval of the bright spot areas where the medium gray value in the chip image information is higher than the threshold, define the bright spot areas with a switching interval less than or equal to the threshold as the chip thickness acquisition area, define the bright spot areas with a switching interval greater than the threshold as the chip area acquisition area, calculate and output the chip thickness based on the chip thickness acquisition area, and calculate and output the chip area based on the chip area acquisition area.

[0089] The above processing process can be realized in cooperation with Python and the image processing software OpenCV. Among them, the principle of judging the chip thickness acquisition area and the chip area acquisition area based on the switching interval of the bright spot areas is as follows: during the synchronous rotation of the light source and the CCD camera around the chip, when the orientation of the light source and the CCD camera crosses a certain side line of the chip, the light spot reflected by the chip metal surface will switch once. Therefore, when the displacement speed of the detection slide 10 carrying the light source and the CCD camera remains unchanged, based on the switching interval of the light spots reflected by the chip metal surface, the maximum length or width of the scanning plane of the CCD camera can be indirectly obtained. Usually, the thickness of the chip is much smaller than the surface length or width of the chip. Therefore, the bright spot areas in the chip image information scanned by the CCD camera can be divided into the chip thickness acquisition area and the chip area acquisition area. Based on the corresponding acquisition areas, the corresponding chip thickness and chip area can be collected.

[0090] The continuity based on the bright area can also be used to judge the effectiveness of the chips. During the gear hobbing process, after the cutting chips fly out at high speed and land on the surface of the vane 6, a small amount of chips may break. Collecting the thickness and area of the broken chips cannot be used as the basis for compensating the parameters of the gear hobbing tool. Therefore, usually, the broken chips need to be excluded and their thickness and area are not collected. On the one hand, by setting a threshold range, the data of the chip thickness and chip area within the threshold range can be used as valid data, otherwise they are excluded. On the other hand, when the CCD camera sweeps the chips, the continuity of the chip surface can be judged. For chips with multiple breaks, their thickness and area are not collected.

[0091] The detection module controls the first driving member to reciprocate once every 1 - 3 s, and controls the flexible vibrating disk 5 to run continuously for 1 - 2 s after the reciprocating movement of the first driving member is completed. Thus, the chips can be regularly discharged, and the thickness and area of the chips are detected again.

[0092] A plurality of support shafts 2 are fixedly connected to the fixed flange 1. One end of the support shaft 2 far from the fixed flange 1 is fixedly connected to a fixed ring 3. A protective cover 4 is arranged between the fixed flange 1 and the fixed ring 3. The protective cover 4 is slidably matched with the support shaft 2. A lead screw is also arranged between the fixed ring 3 and the fixed flange 1. The protective cover 4 is in threaded cooperation with the lead screw. A second driving member 7 (servo motor) for driving the lead screw to rotate is fixedly connected to the fixed ring 3 or the fixed flange 1; the detection module is used to control the operation of the second driving member 7, which can not only protect the chip landing area, but also reduce the influence of external environmental light and temperature on chip detection.

[0093] Embodiment 3 is different from Embodiment 2 in that considering that it takes a certain time for the chips to land on the vane 6 after cutting, there is a certain error in directly using the temperature collected by the infrared sensor to replace the temperature during chip cutting. The temperature during chip cutting can be inversely deduced based on the temperature of the chips collected by the infrared sensor. The partial differential equation of the internal temperature of the chips changing with time during the heat conduction process:

[0094] In the formula, T is the temperature during chip cutting, is the time from chip cutting to landing on the vane 6 (which can be taken as a constant according to the actual situation, such as 0.75 s), is the density of the chip material, is the specific heat capacity of the chip material, is the thermal conductivity of the chip material, is the Laplace operator, which is used to describe the change of the temperature gradient in space.

[0095] Therefore, based on the temperature collected by the infrared sensor, the temperature during chip cutting can be inversely deduced.

[0096] Obviously, the above embodiments are merely examples given for clear illustration and not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or alterations can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. And the obvious changes or alterations derived therefrom still fall within the protection scope of this invention.

Claims

1. A parameter control system for a shaving cutter based on oblique cutting, characterized in that, Including: A tool parameter acquisition module, which is used to acquire the tool rotation speed, axial feed rate, and cutting depth in real time; A force-thermal prediction model, which is used to output the predicted cutting force and the predicted cutting tool temperature based on the tool rotation speed, axial feed rate, and cutting depth acquired in real time; A multi-objective parameter optimization model, which is used to receive the constraint conditions set by the user, and aims to minimize the cutting force, minimize the cutting tool temperature, and maximize the machining efficiency within the constraint conditions, optimize the tool rotation speed, axial feed rate, and cutting depth, and integrate and output a regulation strategy; A tool parameter control module, which is used to regulate the tool rotation speed, axial feed rate, and cutting depth based on the regulation strategy when the predicted cutting force and the predicted cutting tool temperature exceed the threshold; A chip collection unit, which is used to acquire the chip thickness and chip area in real time, and calculate and output the actual cutting force; For acquiring the chip temperature in real time, calculating and outputting the actual cutting tool temperature; The tool parameter control module is also used to compensate the tool rotation speed, axial feed rate, and cutting depth based on the actual cutting force and the actual cutting tool temperature.

2. The parameter control system of the gear shaving cutter based on oblique cutting according to claim 1, wherein The construction method of the force-thermal prediction model is as follows: Select a neural network architecture for constructing the force-thermal prediction model; Use the historical tool rotation speed, axial feed rate, and cutting depth as inputs, and the cutting force and the predicted cutting tool temperature corresponding to the historical tool rotation speed, axial feed rate, and cutting depth as outputs to train the neural network; Use the mean absolute error, root mean square error, and mean absolute percentage error to evaluate the accuracy of the neural network prediction results as follows: Mean absolute error: ; Root mean square error: ; Mean absolute percentage error: ; In the above formulas, is the original data, is the predicted value, is the number of data; Optimize the trained neural network, and use the neural network that meets the prediction accuracy after training as the force-thermal prediction model.

3. The parameter control system of the gear shaving cutter based on oblique cutting according to claim 1, wherein Define the machining efficiency as the ratio of the chip volume formed during a single blade sweep process of the shaving cutter to the sweep time used, as follows: ; In the formula, is the chip volume, is the sweep time.

4. The parameter control system of a generating shaving cutter based on angular cutting according to claim 3, wherein The setting of the objective function of the multi-objective parameter optimization model is as follows: ; ; ; Wherein, is the cutting tool temperature, is the cutting force; The set constraint conditions are that the tool rotation speed is 450 - 700 r / min, the chip depth is 0.1 - 0.3 mm, and the axial feed rate is 0.1 - 0.2 mm / r; the multi-objective parameter optimization model needs to meet the following constraint conditions when optimizing the tool rotation speed, axial feed rate, and cutting depth: ; ; In the formula, is the minimum tool rotation speed, is the maximum tool rotation speed, is the tool rotation speed variable; ; ; In the formula, is the minimum axial feed rate, is the maximum axial feed rate, is the axial feed rate variable; ; ; In the formula, is the minimum cutting depth, is the maximum cutting depth, is the cutting depth variable; The multi-objective parameter optimization model is: ; ; In the formula, is the Pareto optimal solution set.

5. The parameter control system of the shaving cutter based on oblique cutting according to claim 1, characterized in that The chip collection unit includes a fixed flange (1) for connecting to the machine tool. A first chip channel is arranged in the middle of the fixed flange (1). A flexible vibrating disc (5) is fixedly connected to the top of the fixed flange (1). A second chip channel is arranged in the middle of the flexible vibrating disc (5). A number of rotatable blades (6) are arranged in the second chip channel. A first driving member for driving the blades (6) to rotate is arranged inside the side wall of the flexible vibrating disc (5). In the initial state, the combination of the blades (6) closes the second chip channel; A detection ring groove is arranged on the side wall of the flexible vibrating disc (5). A detection slide rail (9) is arranged in the detection ring groove. A detection slide seat (10) is slidably connected to the detection slide rail (9). A light source, a CCD camera, and an infrared sensor are fixedly connected to the detection slide seat (10). The light source, the CCD camera, and the infrared sensor all face the axis of the second chip channel; It further includes a detection module. The detection module is used to control the operation of the flexible vibrating disk (5), the first driving member and the detection slide (10). The detection module is also used to collect chip image information on the vane (6) based on a light source and a CCD camera, process and output the chip thickness and chip area based on the chip image information, and process and output the chip temperature based on the temperature information collected by the infrared sensor.

6. The parameter control system of a shaving cutter based on angular cutting according to claim 5, wherein The detection module is used to control the operation of the flexible vibrating disk (5) to evenly spread the collected chips on the surface of the vane (6); then control the operation of the detection slide (10), and at the same time control the operation of the light source, and control the CCD camera to continuously collect the chip images on the surface of the vane (6) to generate chip image information, and perform binary processing on the chip image information to obtain the bright spot area with a gray value higher than the threshold in the chip image information; The detection module is used to obtain the switching interval of the bright spot areas with a medium gray value higher than the threshold in the chip image information, define the bright spot areas with a switching interval less than or equal to the threshold as the chip thickness acquisition area, define the bright spot areas with a switching interval greater than the threshold as the chip area acquisition area, calculate and output the chip thickness based on the chip thickness acquisition area, and calculate and output the chip area based on the chip area acquisition area.

7. The parameter control system of the gear shaving cutter based on oblique cutting according to claim 6, characterized in that, Calculate the actual cutting force based on the chip thickness and the chip area: ; In the formula, is the cutting force per unit area when the chip cross-section thickness and width are both 1 mm, which is a constant and measured through experiments; is the chip area, is the chip thickness, is a fixed value coefficient representing the influence of the chip thickness on the cutting force; is the influence coefficient of the cutting rake angle on the cutting force; ; In the formula, is the shaft intersection angle, i.e., the angle between the axis of the face hobbing cutter and the axis of the workpiece.

8. The parameter control system of the gear shaving cutter based on oblique angle cutting according to claim 6, wherein, Calculate the actual cutting tool temperature based on the chip temperature: ; In the formula, is the tool temperature rise caused by the friction between the generating shaving tool and the chip, is the initial temperature of the generating shaving tool; Tool temperature rise caused by friction between the skiving tool and the chip , and the calculation formula is as follows: ; In the formula, is the chip temperature, is the chip temperature rise caused by shear deformation, is the initial workpiece temperature.

9. The parameter control system of a gear shaving cutter based on oblique cutting according to claim 5, characterized in that, The detection module is used to control the first driving member to reciprocate once every 1 - 3 s, and control the flexible vibrating disk (5) to continuously operate for 1 - 2 s after the reciprocating motion of the first driving member is completed.

10. The parameter control system of a gear shaving cutter based on oblique cutting according to claim 5, characterized in that, A plurality of support shafts (2) are fixedly connected to the fixed flange (1). One end of the support shaft (2) far from the fixed flange (1) is fixedly connected with a fixed ring (3). A protective cover (4) is arranged between the fixed flange (1) and the fixed ring (3). The protective cover (4) is slidably matched with the support shaft (2). A lead screw is also arranged between the fixed ring (3) and the fixed flange (1). The protective cover (4) is in threaded cooperation with the lead screw. A second driving member (7) for driving the lead screw to rotate is fixedly connected to the fixed ring (3) or the fixed flange (1); the detection module is used to control the operation of the second driving member (7).

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