Machining control method and device for aluminum alloy die-casting thin-wall part of new energy automobile
By real-time detection and adjustment of cutting force and deformation data of aluminum alloy die-cast thin-walled parts, the problem of low processing efficiency and precision of aluminum alloy die-cast thin-walled parts for new energy vehicles has been solved, and efficient and stable processing control has been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- WUHAN UNIV OF TECH
- Filing Date
- 2026-01-09
- Publication Date
- 2026-05-19
AI Technical Summary
The processing of thin-walled aluminum alloy die-cast parts for new energy vehicles suffers from low processing efficiency and precision. In particular, under dynamic cutting forces, chatter instability is prone to occur, affecting processing quality and machine tool efficiency.
By real-time monitoring of cutting force and deformation data of thin-walled aluminum alloy die-cast parts, the maximum deformation, peak cutting force, and cutting force fluctuation range are determined. Combined with preset thresholds, machining parameters such as spindle speed, feed rate, and depth of cut are adjusted to achieve real-time control.
This improves the processing efficiency and precision of thin-walled aluminum alloy die-cast parts for new energy vehicles, reduces chatter and instability during processing, and ensures consistent processing quality and efficiency.
Smart Images
Figure CN122064030A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of machine tool processing technology, and in particular to a processing control method and device for thin-walled aluminum alloy die-cast parts for new energy vehicles. Background Technology
[0002] With the continuous development of automobile manufacturing technology, the processing efficiency and precision of thin-walled aluminum alloy die-cast parts for new energy vehicles are constantly improving. Furthermore, due to the material properties of aluminum alloys, such as low density, high specific strength, corrosion resistance, and low cost, they have rapidly become one of the main materials for structural components in new energy vehicles. However, due to the good thermal conductivity and large coefficient of linear expansion of aluminum alloys, machining deformation is more likely to occur during processing. Aluminum alloy components for new energy vehicles generally have characteristics such as high material removal rate, large size, thin walls, and high precision requirements, leading to a deterioration in their machinability. Under the action of dynamic cutting forces, chatter instability is prone to occur at the contact point between the thin-walled workpiece and the cutting tool, directly reducing the machining accuracy and surface quality of the thin-walled workpiece and limiting the processing efficiency of the machine tool.
[0003] Machining parameters are crucial factors directly affecting the machining quality of thin-walled aluminum alloy die-cast parts for new energy vehicles. They not only influence the geometric accuracy of the workpiece but also significantly impact tool wear, workpiece surface morphology, cutting stability, and residual stress on the cutting surface. While considerable experience has been accumulated in selecting machining parameters, many empirical formulas become inapplicable as machine tool and part parameters change, significantly limiting machining efficiency and cost.
[0004] Therefore, improving the processing efficiency and precision of thin-walled aluminum alloy die-cast parts for new energy vehicles has become an urgent technical problem to be solved. Summary of the Invention
[0005] In view of this, it is necessary to provide a processing control method and device for thin-walled aluminum alloy die-cast parts for new energy vehicles, so as to solve the problems of low processing efficiency and low processing accuracy of existing thin-walled aluminum alloy die-cast parts for new energy vehicles.
[0006] To address the aforementioned problems, in a first aspect, the present invention provides a method for controlling the processing of thin-walled aluminum alloy die-cast parts for new energy vehicles, comprising: To acquire real-time cutting force data and real-time deformation data during the machining process of thin-walled aluminum alloy die-cast parts; Based on the preprocessed real-time cutting force data and real-time deformation data, the maximum deformation, peak cutting force, and cutting force fluctuation amplitude are determined. If the maximum deformation exceeds the preset deformation threshold, or the peak cutting force exceeds the preset cutting force threshold, or the cutting force fluctuation exceeds the preset cutting force fluctuation threshold, the machining parameters will be adjusted. The machining parameters include spindle speed, feed rate, and depth of cut. If it is determined that the machining parameters need to be adjusted, the adjusted machining parameters are determined based on the preset machining path and the pre-processed real-time deformation data.
[0007] In one possible implementation, the method further includes: If the maximum deformation is less than or equal to the deformation threshold, the peak cutting force is less than or equal to the cutting force threshold, and the cutting force fluctuation amplitude is less than or equal to the cutting force fluctuation threshold, then it is determined that no adjustment of the machining parameters will be made.
[0008] In one possible implementation, determining the adjusted processing parameters based on a preset processing path and preprocessed real-time deformation data includes: Based on the preset machining path and the pre-processed real-time deformation data, the adjusted machining path and the adjusted cutting speed are determined. Based on the adjusted machining path and the adjusted cutting speed, the adjusted machining parameters are determined.
[0009] In one possible implementation, the adjusted processing path is determined based on the following formula:
[0010]
[0011] in, This indicates the adjusted processing path. This indicates the initial adjustment of the processing path. This indicates the processing path measured in real time. This is the gain coefficient. This indicates the first step in the preset processing path. One sampling point, The first step in the initial adjustment of the processing path One sampling point.
[0012] In one possible implementation, the adjusted cutting speed is determined based on the following formula:
[0013] in, This indicates the adjusted cutting speed. Indicates the original cutting speed. To adjust the coefficient, This represents the real-time deformation data after preprocessing.
[0014] In one possible implementation, determining the adjusted machining parameters based on the adjusted machining path and the adjusted cutting speed includes: The adjusted depth of cut is determined based on the adjusted machining path, and the adjusted spindle speed and feed rate are determined based on the adjusted cutting speed.
[0015] In one possible implementation, the preprocessing of the real-time cutting force data and real-time deformation data includes: The real-time cutting force data and real-time deformation data are filtered, amplified, converted from analog to digital, and time-aligned.
[0016] On the other hand, the present invention also provides a processing control device for thin-walled aluminum alloy die-cast parts for new energy vehicles, comprising: The acquisition module is used to acquire real-time cutting force data and real-time deformation data during the machining process of aluminum alloy die-cast thin-walled parts; The first determining module is used to determine the maximum deformation, peak cutting force, and cutting force fluctuation amplitude based on the preprocessed real-time cutting force data and real-time deformation data. The second determining module is used to determine to adjust the machining parameters when the maximum deformation is greater than a preset deformation threshold, or the peak cutting force is greater than a preset cutting force threshold, or the cutting force fluctuation amplitude is greater than a preset cutting force fluctuation threshold. The machining parameters include spindle speed, feed rate and depth of cut. The third determining module is used to determine the adjusted processing parameters based on the preset processing path and the pre-processed real-time deformation data when it is determined that the processing parameters need to be adjusted.
[0017] Secondly, the present invention also provides a control device, including a memory and a processor, wherein, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles as described in any of the above implementations.
[0018] Thirdly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, can implement the steps in the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles described in any of the above implementations.
[0019] The beneficial effects of this invention are as follows: The processing control method and device for thin-walled aluminum alloy die-casting parts for new energy vehicles provided by this invention detects the processing data in real time, and then determines the maximum deformation, peak cutting force, and cutting force fluctuation amplitude during the processing based on the real-time processing data. Combining the deformation threshold, cutting force threshold, and cutting force fluctuation threshold, it is determined whether to adjust the processing parameters. When it is determined that the processing parameters need to be adjusted, the adjusted processing parameters can be determined based on the preset processing path and the pre-processed real-time deformation data, thereby realizing real-time control of the processing process. No manual control of the processing process is required, which improves the processing efficiency. Furthermore, the processing accuracy can also be guaranteed by controlling the processing parameters. This invention effectively improves the processing efficiency and processing accuracy of thin-walled aluminum alloy die-casting parts for new energy vehicles. Attached Figure Description
[0020] Figure 1 A schematic flowchart of an embodiment of the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles provided by the present invention; Figure 2 A schematic flowchart illustrating an embodiment of the processing procedure for the new energy vehicle aluminum alloy die-cast thin-walled part provided by the present invention; Figure 3 A schematic flowchart illustrating an embodiment of the processing parameter adjustment process for thin-walled aluminum alloy die-cast parts for new energy vehicles provided by the present invention; Figure 4 A schematic diagram of a structural embodiment of the processing scenario for the new energy vehicle aluminum alloy die-cast thin-walled part provided by the present invention; Figure 5 A schematic diagram of an embodiment of the processing control device for thin-walled aluminum alloy die-cast parts for new energy vehicles provided by the present invention; Figure 6 A schematic diagram of an embodiment of the control device provided by the present invention. Detailed Implementation
[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.
[0022] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.
[0023] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.
[0024] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0025] This invention provides a processing control method and device for thin-walled aluminum alloy die-cast parts for new energy vehicles, which will be described below.
[0026] Figure 1 This is a schematic flowchart of an embodiment of the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles provided by the present invention, as shown below. Figure 1 As shown, the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles includes: S101. Obtain real-time cutting force data and real-time deformation data during the machining process of aluminum alloy die-cast thin-walled parts.
[0027] It should be noted that the processing control method for thin-walled aluminum alloy die-casting parts for new energy vehicles provided by this invention can be applied to machine tool processing scenarios, especially the processing scenarios for thin-walled aluminum alloy die-casting parts for new energy vehicles.
[0028] During machining control, the control equipment (such as a portable or desktop computer) can first acquire real-time cutting force data and real-time deformation data during the machining process of thin-walled aluminum alloy die-cast parts, providing a data foundation for subsequent machining control. Real-time cutting force data can be acquired using a three-dimensional force gauge, and real-time deformation data can be acquired using a laser displacement sensor.
[0029] S102. Based on the preprocessed real-time cutting force data and real-time deformation data, determine the maximum deformation, peak cutting force, and cutting force fluctuation amplitude.
[0030] It should be noted that after obtaining the real-time cutting force and deformation data during the machining of thin-walled aluminum alloy die-cast parts, these data can be preprocessed to improve their accuracy, thereby enhancing subsequent machining precision. Then, the maximum deformation, peak cutting force, and cutting force fluctuation amplitude can be determined using the preprocessed real-time cutting force and deformation data.
[0031] S103. If the maximum deformation is greater than the preset deformation threshold, or the peak cutting force is greater than the preset cutting force threshold, or the cutting force fluctuation is greater than the preset cutting force fluctuation threshold, determine to adjust the machining parameters, including spindle speed, feed rate and depth of cut.
[0032] It should be noted that after determining the maximum deformation, peak cutting force, and cutting force fluctuation range, the deformation threshold, cutting force threshold, and cutting force fluctuation threshold can be used to determine whether to adjust the machining parameters. This allows for timely correction in case of machining abnormalities. Machining parameters can include spindle speed, feed rate, and depth of cut. If the maximum deformation exceeds the deformation threshold, or the peak cutting force exceeds the cutting force threshold, or the cutting force fluctuation range exceeds the cutting force fluctuation threshold, then it is determined that the machining parameters need to be adjusted.
[0033] S104. If it is determined that the machining parameters need to be adjusted, the adjusted machining parameters are determined based on the preset machining path and the pre-processed real-time deformation data.
[0034] It should be noted that when it is determined to adjust the processing parameters, the adjusted processing parameters can be determined based on the preset processing path and the pre-processed real-time deformation data, so as to achieve real-time control of the processing process.
[0035] In summary, the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles provided by this invention detects processing data in real time, determines the maximum deformation, peak cutting force, and cutting force fluctuation amplitude during processing based on the real-time processing data, and determines whether to adjust processing parameters by combining deformation threshold, cutting force threshold, and cutting force fluctuation threshold. When it is determined that processing parameters need to be adjusted, the adjusted processing parameters can be determined based on the preset processing path and pre-processed real-time deformation data, thereby achieving real-time control of the processing process without the need for manual control, improving processing efficiency. Furthermore, the processing accuracy can be guaranteed by controlling the processing parameters. This invention effectively improves the processing efficiency and accuracy of thin-walled aluminum alloy die-cast parts for new energy vehicles.
[0036] In some embodiments of the present invention, the method further includes: If the maximum deformation is less than or equal to the deformation threshold, the peak cutting force is less than or equal to the cutting force threshold, and the cutting force fluctuation amplitude is less than or equal to the cutting force fluctuation threshold, then it is determined that no adjustment of the machining parameters will be made.
[0037] It should be noted that when determining whether to adjust machining parameters based on the maximum deformation, peak cutting force, and cutting force fluctuation amplitude, as well as the deformation threshold, cutting force threshold, and cutting force fluctuation threshold, if the maximum deformation is less than or equal to the deformation threshold, the peak cutting force is less than or equal to the cutting force threshold, and the cutting force fluctuation amplitude is less than or equal to the cutting force fluctuation threshold, then it can be determined that no adjustment of machining parameters is required.
[0038] In some embodiments of the present invention, determining the adjusted processing parameters based on a preset processing path and preprocessed real-time deformation data includes: Based on the preset machining path and the pre-processed real-time deformation data, the adjusted machining path and the adjusted cutting speed are determined. Based on the adjusted machining path and the adjusted cutting speed, the adjusted machining parameters are determined.
[0039] It should be noted that when determining the adjusted machining parameters based on the preset machining path and the pre-processed real-time deformation data, the adjusted machining path and the adjusted cutting speed can be determined based on the preset machining path and the pre-processed real-time deformation data, and then the adjusted machining parameters can be determined based on the adjusted machining path and the adjusted cutting speed.
[0040] In some embodiments of the present invention, the adjusted processing path is determined based on the following formula:
[0041]
[0042] in, This indicates the adjusted processing path. This indicates the initial adjustment of the processing path. This indicates the processing path measured in real time. This is the gain coefficient. This indicates the first step in the preset processing path. One sampling point, The first step in the initial adjustment of the processing path One sampling point.
[0043] It should be noted that the adjusted processing path can be determined using the formula above.
[0044] In some embodiments of the present invention, the adjusted cutting speed is determined based on the following formula:
[0045] in, This indicates the adjusted cutting speed. Indicates the original cutting speed. To adjust the coefficient, This represents the real-time deformation data after preprocessing.
[0046] It should be noted that the adjusted cutting speed can be determined using the formula above.
[0047] In some embodiments of the present invention, determining the adjusted machining parameters based on the adjusted machining path and the adjusted cutting speed includes: The adjusted depth of cut is determined based on the adjusted machining path, and the adjusted spindle speed and feed rate are determined based on the adjusted cutting speed.
[0048] It should be noted that when determining the adjusted machining parameters based on the adjusted machining path and the adjusted cutting speed, the adjusted depth of cut can be determined based on the adjusted machining path, and the adjusted spindle speed and feed rate can be determined based on the adjusted cutting speed, thereby determining the adjusted machining parameters.
[0049] In some embodiments of the present invention, the preprocessing of the real-time cutting force data and real-time deformation data includes: The real-time cutting force data and real-time deformation data are filtered, amplified, converted from analog to digital, and time-aligned.
[0050] It should be noted that when preprocessing real-time cutting force data and real-time deformation data, filtering, amplification, analog-to-digital conversion, and time alignment can be performed on the real-time cutting force data and real-time deformation data to ensure data accuracy and thus improve subsequent machining accuracy.
[0051] This invention provides a method for controlling the deformation during the processing of thin-walled aluminum alloy die-cast parts for new energy vehicles. It integrates measurement and compensation, which can improve the control accuracy of the processing of thin-walled aluminum alloy die-cast parts for new energy vehicles and achieve high-quality and efficient processing of parts.
[0052] Combination Figure 2 The specific steps of processing control include: 1. Establish a process parameter detection platform for the processing of thin-walled aluminum alloy die-casting parts for new energy vehicles. The thin-walled aluminum alloy parts to be processed are clamped on the fixture platform, and the cutting force and deformation during the processing are detected in real time by a three-dimensional force measuring instrument and a laser displacement sensor.
[0053] Before processing, the three-dimensional force measuring instrument and the laser displacement sensor are zero-point calibrated and sensitivity calibrated by the host computer system; the sampling frequency and sampling channel of the data acquisition device are set, and a communication connection is established with the machine tool CNC system to ensure that the detection system and the machine tool control system are synchronized in time.
[0054] 2. During the milling process, the three-dimensional force measuring instrument outputs cutting force signals in the X, Y, and Z directions in real time. The laser displacement sensor moves along the tool feed direction to continuously scan the displacement changes of the machined surface in the thin-walled area, thus obtaining the deformation curve during the machining process.
[0055] During the machining process, the three-dimensional force gauge converts the force on the tool into an electric charge signal through an internal piezoelectric sensor. After being amplified and filtered by the signal conditioning circuit, the signal is input to the data acquisition unit. The laser displacement sensor is fixed on the sensor platform and driven by a servo motor to move along the lead screw guide, so that the laser spot always follows the tool machining area and continuously scans the displacement of the machining surface of the new energy vehicle aluminum alloy die-cast thin-walled part in the normal direction. The data acquisition unit synchronously samples the cutting force and displacement signals at a uniform sampling frequency and marks the time for each set of data to ensure a one-to-one correspondence between the cutting force and deformation data in the time domain.
[0056] 3. The data acquisition unit synchronously samples the above cutting force and displacement signals, and performs filtering, amplification and A / D conversion at the hardware level. After time alignment and coordinate transformation of the sampled data, it is uploaded to the host computer system.
[0057] The three-dimensional force measurement signal is subjected to coordinate transformation and decomposed into tangential force, radial force and axial force components; baseline drift compensation is performed on the displacement signal to obtain the true deformation curve; finally, the preprocessed data is transmitted to the host computer system via wired connection.
[0058] 4. The host computer system analyzes and processes the collected cutting force and deformation data, extracts feature quantities including maximum deformation, peak cutting force, and average load, and compares them with the preset allowable deformation range and cutting force safety threshold to achieve real-time evaluation of the current machining status.
[0059] Combination Figure 3 The host computer system processes the real-time transmitted cutting force and deformation data, calculating the following characteristic indicators: maximum deformation and its corresponding workpiece position, peak cutting force, and fluctuation amplitude. These indicators are compared with pre-set allowable deformation values and cutting force safety thresholds: when both maximum deformation and cutting force are within safe ranges, the current machining state is considered stable and marked as "normal state"; when the maximum deformation approaches the upper limit, it is marked as "warning state," and the feed rate is slightly reduced; when the deformation or cutting force exceeds the upper limit, it is marked as "over-limit state," triggering parameter adjustment and compensation algorithms, simultaneously reducing the spindle speed and feed rate, and decreasing the depth of cut.
[0060] 5. When the deformation of a certain machining section of a thin-walled part is detected to be close to or exceed the allowable deformation value, or the cutting force exceeds the safety threshold, the host computer calculates the applicable machining parameter correction and path compensation based on the pre-established adaptive compensation algorithm, and generates new cutting parameters. The cutting parameters include spindle speed, feed rate, and depth of cut.
[0061] When the detection result is determined to be "warning state" or "over-limit state", the host computer executes the following feedback control strategy: To further improve compensation accuracy, an optimization objective function based on the least squares method is designed to minimize the error between the compensated path and the theoretical path, thereby obtaining the optimal compensated path. The optimization objective function is as follows:
[0062] in, This indicates the initial adjustment of the processing path. This indicates the processing path measured in real time. This indicates the first step in the preset processing path. One sampling point, The first step in the initial adjustment of the processing path One sampling point.
[0063] Simultaneously, the cutting parameters are adjusted based on the actual deformation at each moment. Adaptive correction of the cutting rate can be achieved using the following formula:
[0064] in, This indicates the adjusted cutting speed. Indicates the original cutting speed. To adjust the coefficient, This represents the real-time deformation data after preprocessing.
[0065] To improve the accuracy of deformation compensation, a feedback-based adaptive compensation method is adopted. The workpiece deformation is monitored in real time using the new energy vehicle thin-walled part machining process parameter detection platform, and compared with the theoretical prediction of the time-varying cutting force function prediction model to dynamically correct the machining path. Adaptive compensation can adjust cutting parameters in real time, thereby achieving high-precision correction during the machining process. The feedback control model can be described by the following formula:
[0066] in, This indicates the adjusted processing path. This indicates the initial adjustment of the processing path. This indicates the processing path measured in real time. This is the gain coefficient.
[0067] 6. The corrected machining parameters and compensation path are fed back to the machine tool CNC system through the communication interface, so that the machine tool can automatically reduce the cutting load, reduce the material removal rate of local stiffness-sensitive areas, and make slight offsets to the tool path in subsequent machining to counteract the elastic deformation caused by the machining force, thereby realizing active control of the machining deformation of aluminum alloy thin-walled parts.
[0068] The corrected machining parameters are fed back to the machine tool CNC system to adjust the spindle speed, feed rate and depth of cut online, and to compensate and correct the tool machining path when necessary, so that the actual deformation of the aluminum alloy die-cast thin-walled parts for new energy vehicles is controlled within the allowable range.
[0069] 7. Throughout the entire processing, the above-mentioned detection and feedback process is repeated at a fixed sampling period to achieve closed-loop control of the processing. Processing ends when the deformation of the thin-walled part is controlled within the set range throughout the entire process. Steps 2-6 are repeated until all processing steps of the thin-walled part are completed.
[0070] Combination Figure 4 The new energy vehicle aluminum alloy die-cast thin-walled part processing parameter detection platform consists of 1 machine tool spindle, 2 processing tool, 3 laser displacement sensor, 4 three-dimensional force measuring instrument, 5 new energy vehicle thin-walled part to be measured, 6 fixture platform, 7 lead screw guide rail, 8 sensor platform, 9 servo motor, 10 data acquisition device and 11 host computer system.
[0071] The positional connections between them are as follows: 5. The aluminum alloy die-cast thin-walled part of the new energy vehicle to be measured is clamped on the 6 fixture platform; 4. One end of the three-dimensional force measuring instrument is connected to the 1 machine tool spindle, and the other end is connected to the 2 machining tool; 10. The data acquisition device is connected to the 4 three-dimensional force measuring instrument and also to the 11 host computer system; 7. The lead screw guide rail is fixed on the 6 fixture platform; 8. The sensor platform is fixed on the 7 lead screw guide rail; 3. The laser displacement sensor is fixed on the 8 sensor platform; 9. The servo motor is connected to the 8 lead screw guide rail; 3. The laser displacement sensor is connected to the 10 data acquisition device, and the 10 data acquisition device is connected to the 11 host computer system.
[0072] The laser displacement sensor is cuboid in shape, with a resolution of ±0.004mm and a measurement range of ±10mm. It is used to measure the deformation of the workpiece surface during processing. The model of this laser displacement sensor is LK-H050.
[0073] 4. The three-dimensional force gauge is cylindrical, with a resolution of 1N in the X and Y directions and 4N in the Z direction. Its measurement range in the X and Y directions is ±5KN, and its measurement range in the Z direction is ±20KN. Its sampling frequency is 2KHz. It is used to measure the load of cutting forces on the workpiece in various directions during the machining process. Its model is 9132C.
[0074] The data acquisition unit 10 is cuboid in shape. It is used to collect, process, and upload the acquired data to the host computer for further analysis. The collected data includes machining cutting force data measured by the three-dimensional force gauge and machining deformation data measured by the laser displacement sensor.
[0075] 6. The clamping platform is disc-shaped, with dimensions of approximately 500mm × 500mm × 48mm. It has threaded holes for fixing various devices and 5. The aluminum alloy die-cast thin-walled parts of the new energy vehicle to be tested are fixed on the experimental table. Its material is 45 steel.
[0076] 5. The aluminum alloy die-cast thin-walled part to be tested for new energy vehicles is a shell-type part used for sealing the motor end cover of new energy vehicles.
[0077] The 9 servo motors are cuboid in shape and fixed on the 7 lead screw guide rails to provide power for the 3 laser displacement sensors to perform accompanying movements during tool processing.
[0078] The host computer system is a WIN11 computer, which is connected to the data acquisition unit 10 via a data cable. Its main function is to store the detection data uploaded by the data acquisition unit 10 and analyze the results of the detection data.
[0079] The workflow of this testing platform is mainly divided into two parts, as detailed below: 1. To measure the cutting force during the machining process of the thin-walled aluminum alloy die-casting part for new energy vehicles (5), a three-dimensional force gauge (4) is connected at one end to the machine tool spindle (1) via an interface, and at the other end to the machining tool (2). During machining, the three-dimensional force gauge (3) converts the force on the machining tool (2) into an electrical charge signal through its built-in piezoelectric sensor. The original signal is demodulated by the signal conditioning circuit in the signal acquisition unit (10) to obtain the real-time cutting force of the thin-walled aluminum alloy die-casting part for new energy vehicles (5) during machining. The collected data is then transmitted to the host computer system (11) via a data transmission line for further analysis.
[0080] 2. To measure the deformation of the thin-walled aluminum alloy die-casting part for new energy vehicles during processing (5), a laser displacement sensor (3) is fixed on a sensor platform (8), which is in turn fixed on a lead screw guide rail (7). A servo motor (9) provides power to move synchronously with the machining tool (2), ensuring continuous detection of the machining plane. Simultaneously, the laser displacement sensor (3), based on optical triangulation, emits a highly focused and collimated laser beam through an internal laser diode. After being focused by a lens, a tiny spot illuminates the surface of the thin-walled aluminum alloy die-casting part (5). After reflection, the beam is imaged onto a photodetector on its focal plane using a receiving lens. Using trigonometric relationships, the real-time deformation of the surface of the thin-walled aluminum alloy die-casting part during processing is calculated. The data is then processed by a signal acquisition device (10) and finally transmitted to a host computer system (11) to obtain the deformation data during processing.
[0081] This invention establishes a machining process parameter detection platform to simultaneously monitor three-dimensional cutting forces and displacements in critical thin-walled areas during milling. Displacement sensors move along the feed direction and continuously scan, obtaining deformation curves and spatial distribution information during machining. Simultaneously, a data acquisition unit samples and preprocesses the force-displacement signals, and a host computer further extracts features such as maximum deformation and peak cutting force for condition evaluation. Therefore, compared to experience-based post-processing methods, this invention makes the machining deformation process explicit, enabling earlier and more accurate identification of thin-walled parts entering deformation-sensitive or unstable regions. The host computer compares real-time features with preset allowable deformation values and cutting force safety thresholds. Once the detected values approach or exceed the thresholds, machining parameter corrections are calculated and fed back to the CNC system. This allows for online adjustments to the spindle speed, feed rate, and depth of cut, and, if necessary, compensation corrections to the tool path, thereby suppressing load fluctuations and reducing the risk of thin-walled part deformation.
[0082] This invention repeats the process of detection-evaluation-correction-re-detection with a fixed sampling cycle, forming a closed-loop control until the deformation of the thin-walled part is controlled within a set range throughout the entire process before ending the processing. Because the detection-correction process is iteratively executed with a fixed sampling cycle, processing deformation can be controlled within the set range, thereby improving the consistency of dimensional accuracy and surface quality, reducing the scrap rate during processing, and facilitating the achievement of the goal of high-quality and high-efficiency processing of thin-walled parts.
[0083] To better implement the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles in this embodiment of the invention, based on the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles, correspondingly, as follows: Figure 5 As shown, this embodiment of the invention also provides a processing control device for thin-walled aluminum alloy die-cast parts for new energy vehicles. The processing control device 500 for thin-walled aluminum alloy die-cast parts for new energy vehicles includes: The acquisition module 501 is used to acquire real-time cutting force data and real-time deformation data during the machining process of aluminum alloy die-cast thin-walled parts; The first determining module 502 is used to determine the maximum deformation, the peak cutting force, and the cutting force fluctuation amplitude based on the preprocessed real-time cutting force data and real-time deformation data. The second determining module 503 is used to determine to adjust the machining parameters when the maximum deformation is greater than a preset deformation threshold, or the peak value of the cutting force is greater than a preset cutting force threshold, or the fluctuation range of the cutting force is greater than a preset cutting force fluctuation threshold. The machining parameters include spindle speed, feed rate and depth of cut. The third determining module 504 is used to determine the adjusted processing parameters based on the preset processing path and the pre-processed real-time deformation data when it is determined that the processing parameters need to be adjusted.
[0084] The processing control device 500 for thin-walled aluminum alloy die-casting parts for new energy vehicles provided in the above embodiments can realize the technical solutions described in the above embodiments of the processing control method for thin-walled aluminum alloy die-casting parts for new energy vehicles. The specific implementation principles of each module or unit can be found in the corresponding content in the above embodiments of the processing control method for thin-walled aluminum alloy die-casting parts for new energy vehicles, and will not be repeated here.
[0085] like Figure 6 As shown, the present invention also provides a control device 600. The control device 600 includes a processor 601, a memory 602, and a display 603. Figure 6 Only some components of the control device 600 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.
[0086] In some embodiments, processor 601 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 602 or process data, such as the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles in this invention.
[0087] In some embodiments, processor 601 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 601 may be local or remote. In some embodiments, processor 601 may be implemented on a cloud platform. In one embodiment, the cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-cloud, etc., or any combination thereof.
[0088] In some embodiments, memory 602 may be an internal storage unit of control device 600, such as a hard disk or memory of control device 600. In other embodiments, memory 602 may also be an external storage device of control device 600, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on control device 600.
[0089] Furthermore, the memory 602 may include both internal storage units of the control device 600 and external storage devices. The memory 602 is used to store application software and various types of data for which the control device 600 is installed.
[0090] In some embodiments, display 603 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an organic light-emitting diode (OLED) touchscreen. Display 603 is used to display information from control device 600 and to display a visual user interface. Components 601-603 of control device 600 communicate with each other via a system bus.
[0091] In one embodiment, when the processor 601 executes the processing control program for the thin-walled aluminum alloy die-casting part for new energy vehicles stored in the memory 602, the following steps can be implemented: To acquire real-time cutting force data and real-time deformation data during the machining process of thin-walled aluminum alloy die-cast parts; Based on the preprocessed real-time cutting force data and real-time deformation data, the maximum deformation, peak cutting force, and cutting force fluctuation amplitude are determined. If the maximum deformation exceeds the preset deformation threshold, or the peak cutting force exceeds the preset cutting force threshold, or the cutting force fluctuation exceeds the preset cutting force fluctuation threshold, the machining parameters will be adjusted. The machining parameters include spindle speed, feed rate, and depth of cut. If it is determined that the machining parameters need to be adjusted, the adjusted machining parameters are determined based on the preset machining path and the pre-processed real-time deformation data.
[0092] It should be understood that when the processor 601 executes the processing control program for the thin-walled aluminum alloy die-casting parts for new energy vehicles stored in the memory 602, in addition to the functions mentioned above, it can also perform other functions, as detailed in the description of the corresponding method embodiments above.
[0093] Furthermore, this embodiment of the invention does not specifically limit the type of control device 600 mentioned. Control device 600 can be a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, laptop computer, or other portable electronic device. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices running iOS, Android, Microsoft, or other operating systems. The aforementioned portable electronic device can also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the invention, control device 600 may not be a portable electronic device, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).
[0094] Accordingly, this application also provides a computer-readable storage medium for storing computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can realize the steps or functions in the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles provided in the above-described method embodiments.
[0095] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.
[0096] The above provides a detailed description of the processing control method and device for thin-walled aluminum alloy die-cast parts for new energy vehicles provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.
Claims
1. A method for controlling the processing of thin-walled aluminum alloy die-cast parts for new energy vehicles, characterized in that, include: To acquire real-time cutting force data and real-time deformation data during the machining process of thin-walled aluminum alloy die-cast parts; Based on the preprocessed real-time cutting force data and real-time deformation data, the maximum deformation, peak cutting force, and cutting force fluctuation amplitude are determined. If the maximum deformation exceeds the preset deformation threshold, or the peak cutting force exceeds the preset cutting force threshold, or the cutting force fluctuation exceeds the preset cutting force fluctuation threshold, the machining parameters will be adjusted. The machining parameters include spindle speed, feed rate, and depth of cut. If it is determined that the machining parameters need to be adjusted, the adjusted machining parameters are determined based on the preset machining path and the pre-processed real-time deformation data.
2. The processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles according to claim 1, characterized in that, The method further includes: If the maximum deformation is less than or equal to the deformation threshold, the peak cutting force is less than or equal to the cutting force threshold, and the cutting force fluctuation amplitude is less than or equal to the cutting force fluctuation threshold, then it is determined that no adjustment of the machining parameters will be made.
3. The processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles according to claim 1, characterized in that, The process of determining adjusted processing parameters based on a preset processing path and pre-processed real-time deformation data includes: Based on the preset machining path and the pre-processed real-time deformation data, the adjusted machining path and the adjusted cutting speed are determined. Based on the adjusted machining path and the adjusted cutting speed, the adjusted machining parameters are determined.
4. The processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles according to claim 3, characterized in that, The adjusted processing path is determined based on the following formula: in, This indicates the adjusted processing path. This indicates the initial adjustment of the processing path. This indicates the processing path measured in real time. This is the gain coefficient. This indicates the first step in the preset processing path. One sampling point, The first step in the initial adjustment of the processing path One sampling point.
5. The processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles according to claim 3, characterized in that, The adjusted cutting speed is determined based on the following formula: in, This indicates the adjusted cutting speed. Indicates the original cutting speed. To adjust the coefficient, This represents the real-time deformation data after preprocessing.
6. The processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles according to claim 3, characterized in that, The process of determining the adjusted machining parameters based on the adjusted machining path and adjusted cutting speed includes: The adjusted depth of cut is determined based on the adjusted machining path, and the adjusted spindle speed and feed rate are determined based on the adjusted cutting speed.
7. The processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles according to claim 1, characterized in that, The preprocessing of the real-time cutting force data and real-time deformation data includes: The real-time cutting force data and real-time deformation data are filtered, amplified, converted from analog to digital, and time-aligned.
8. A processing control device for thin-walled aluminum alloy die-cast parts for new energy vehicles, characterized in that, include: The acquisition module is used to acquire real-time cutting force data and real-time deformation data during the machining process of aluminum alloy die-cast thin-walled parts; The first determining module is used to determine the maximum deformation, peak cutting force, and cutting force fluctuation amplitude based on the preprocessed real-time cutting force data and real-time deformation data. The second determining module is used to determine to adjust the machining parameters when the maximum deformation is greater than a preset deformation threshold, or the peak cutting force is greater than a preset cutting force threshold, or the cutting force fluctuation amplitude is greater than a preset cutting force fluctuation threshold. The machining parameters include spindle speed, feed rate and depth of cut. The third determining module is used to determine the adjusted processing parameters based on the preset processing path and the pre-processed real-time deformation data when it is determined that the processing parameters need to be adjusted.
9. A control device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the processing control method for aluminum alloy die-cast thin-walled parts for new energy vehicles as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the processing control method for thin-walled aluminum alloy die-cast parts for new energy vehicles as described in any one of claims 1 to 7.