CN117260265B - Automobile brake piston production method and system - Google Patents
Automobile brake piston production method and system Download PDFInfo
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- CN117260265B CN117260265B CN202311276746.0A CN202311276746A CN117260265B CN 117260265 B CN117260265 B CN 117260265B CN 202311276746 A CN202311276746 A CN 202311276746A CN 117260265 B CN117260265 B CN 117260265B
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- B23P—METAL-WORKING NOT OTHERWISE PROVIDED FOR; COMBINED OPERATIONS; UNIVERSAL MACHINE TOOLS
- B23P23/00—Machines or arrangements of machines for performing specified combinations of different metal-working operations not covered by a single other subclass
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23P—METAL-WORKING NOT OTHERWISE PROVIDED FOR; COMBINED OPERATIONS; UNIVERSAL MACHINE TOOLS
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Abstract
Embodiments of the present disclosure provide a method and system for producing an automotive brake piston, the method being executed on a processor, comprising: controlling a stamping device to forge raw materials in the female die according to preset forging parameters to obtain a first intermediate product; controlling the rough turning numerical control machine tool to perform rough turning on the first intermediate product according to preset rough turning parameters to obtain a second intermediate product; controlling a quenching device to carry out quenching and tempering on the second intermediate product according to the quenching and tempering parameters to obtain a third intermediate product; controlling a finish turning numerical control machine tool to finish turning the third intermediate product according to finish turning parameters to obtain a brake piston finished product; controlling an image acquisition device to acquire a first target image of a first intermediate product and/or a second target image of a second intermediate product; adjusting preset forging parameters based on the first target image; determining a tempering parameter based on the second target image; a finish turning parameter is determined based on the second target image and/or a performance parameter of the third intermediate product.
Description
Technical Field
The specification relates to the field of brake piston production, in particular to an automobile brake piston production method and system.
Background
At present, the brake piston is generally processed by the following steps: in the process of processing and manufacturing the piston, a series of operations such as slotting, cutting and the like are needed to be carried out on a semi-finished product, if the work pieces are needed to be placed on a workbench in batches manually, then the center hole of the piston is processed through a male die. However, the manual operation has problems of inconvenience and unsafe. And the existing brake piston die has the problem of low stamping stability, the product quality is easy to influence, the defective rate of the brake piston product is high, and the product quality is uneven.
Meanwhile, when the piston is coarsely used, a series of operations such as cutting and the like are needed to be carried out on a semi-finished product at present, and the cutting force generated by the large cutting amount and the large feeding amount is large, so that a workpiece is required to be clamped, and the surface of the part is clamped and deformed, so that the piston precision is affected.
Accordingly, there is a need to provide a method and system for manufacturing an automotive brake piston that achieves improved stamping stability and piston accuracy.
Disclosure of Invention
One of the embodiments of the present specification provides a brake piston production system for an automobile, comprising: the device comprises a mechanical arm, a piston processing table, a stamping device, an image acquisition device, a rough turning numerical control machine tool, a quenching device, a finish turning numerical control machine tool and a processor, wherein the processor is configured to send a control instruction to at least one of the mechanical arm, the stamping device, the image acquisition device, the rough turning numerical control machine tool, the quenching device and the finish turning numerical control machine tool; the mechanical arm is configured to transmit raw materials and intermediate products based on the control instruction; a female die is arranged on the piston processing table, and a pressure sensor is arranged on the female die; the stamping device is configured to forge the raw materials in the female die with preset forging parameters based on the control instruction to obtain a first intermediate product; the rough turning numerical control machine tool is configured to perform rough turning on the first intermediate product with preset rough turning parameters based on the control instruction to obtain a second intermediate product; the quenching device is configured to carry out quenching and tempering on the second intermediate product according to the control instruction and the quenching parameters to obtain a third intermediate product; the finish turning numerical control machine tool is configured to finish turning the third intermediate product according to the finish turning parameters based on the control instruction to obtain a brake piston finished product; the image acquisition device is configured to acquire a first target image of the first intermediate product and/or a second target image of the second intermediate product based on the control instruction; the preset forging parameters are adjusted based on the first target image; the tempering parameters are determined based on the second target image; the finish turning parameters are determined based on performance parameters of the second target image and/or the third intermediate product.
One of the embodiments of the present disclosure provides a method for producing an automobile brake piston, which is executed by a processor and includes: controlling a stamping device to forge the raw materials in the female die according to preset forging parameters to obtain a first intermediate product; controlling a rough turning numerical control machine tool to perform rough turning processing on the first intermediate product according to preset rough turning parameters to obtain a second intermediate product; controlling a quenching device to carry out quenching and tempering on the second intermediate product according to quenching and tempering parameters to obtain a third intermediate product; controlling a finish turning numerical control machine to finish turning the third intermediate product according to the finish turning parameters to obtain a brake piston finished product; controlling an image acquisition device to acquire a first target image of the first intermediate product and/or a second target image of the second intermediate product; adjusting the preset forging parameters based on the first target image; determining the tempering parameters based on the second target image; determining the finish turning parameters based on the second target image and/or the performance parameters of the third intermediate product.
Drawings
The present specification will be further elucidated by way of example embodiments, which will be described in detail by means of the accompanying drawings. The embodiments are not limiting, in which like numerals represent like structures, wherein:
FIG. 1 is a schematic diagram of an automotive brake piston production system according to some embodiments of the present disclosure;
FIG. 2 is an exemplary flow chart of a method of manufacturing an automotive brake piston according to some embodiments of the present disclosure;
FIG. 3 is an exemplary schematic illustration of determining conditioning parameters according to some embodiments of the present disclosure;
FIG. 4 is an exemplary schematic diagram illustrating determining finish turning parameters according to some embodiments of the present description.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present specification, and it is possible for those of ordinary skill in the art to apply the present specification to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.
It will be appreciated that "system," "apparatus," "unit" and/or "module" as used herein is one method for distinguishing between different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.
As used in this specification and the claims, the terms "a," "an," "the," and/or "the" are not specific to a singular, but may include a plurality, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.
A flowchart is used in this specification to describe the operations performed by the system according to embodiments of the present specification. It should be appreciated that the preceding or following operations are not necessarily performed in order precisely. Rather, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to or removed from these processes.
FIG. 1 is a schematic diagram of an automotive brake piston production system according to some embodiments of the present disclosure. As shown in fig. 1, an automotive brake piston production system 100 includes: a mechanical arm 110, a piston processing table 120, a stamping device 130, an image acquisition device 140, a rough turning numerical control machine 150, a quenching device 160, a finish turning numerical control machine 170 and a processor 180.
The processor 180 refers to a functional unit for controlling the operating states of the various components of the automotive brake piston production system 100. For example, the processor may be configured to issue control instructions to at least one of a robotic arm, a stamping device, an image acquisition device, a rough turning numerically controlled machine, a quenching device, a finish turning numerically controlled machine. In some embodiments, the processor may be based on a CPU implementation.
The robot arm 110 is a functional unit for moving or transferring raw materials and intermediate products, and for example, the robot arm may be configured to transfer raw materials and intermediate products based on control instructions. In some embodiments, the robotic arm may be implemented based on a grasping robotic arm or a mobile robotic arm.
The piston machining station 120 may act as a machining station for the workpiece. For example, a female die is arranged on the piston processing table, a pressure sensor is arranged on the female die, and raw materials of the piston can be contained in the female die. In some embodiments, the piston machining station may be implemented based on a numerical control piston turning station.
The press device 130 is a functional unit for forging a raw material. For example, the stamping device may be configured to forge the raw material within the die with preset forging parameters based on the control instructions, resulting in a first intermediate product. In some embodiments, the stamping device may be implemented based on a full hydraulic stamping press.
The rough turning numerical control machine 150 is a functional unit for rough turning an intermediate product. For example, the rough turning numerically controlled machine may be configured to rough-turn the first intermediate product with preset rough turning parameters based on the control instructions to obtain the second intermediate product. In some embodiments, the rough turning numerically controlled machine may be implemented based on a multi-axis numerically controlled machine.
The quenching apparatus 160 refers to a functional unit for quenching and tempering an intermediate product. For example, the quenching apparatus may be configured to subject the second intermediate product to a quenching and tempering with a quenching and tempering parameter based on the control instruction to obtain a third intermediate product. In some embodiments, the quench may be implemented based on an oil bath quench, a water bath quench, or a salt bath quench.
The finish turning numerical control machine 170 is a functional unit for performing finish turning processing on an intermediate product. For example, the finish turning numerically controlled machine may be configured to finish turning the third intermediate product with the finish turning parameters based on the control instructions to yield a finished brake piston product. In some embodiments, the finish turning numerically controlled machine may be implemented based on a CNC machine.
The image pickup device 140 refers to a functional unit for picking up an image of an intermediate product. For example, the image acquisition device may be configured to acquire a first target image of the first intermediate product and/or a second target image of the second intermediate product based on the control instructions. In some embodiments, the image acquisition device may be implemented based on a camera.
In some embodiments, the preset forging parameters are adjusted based on the first target image, the tempering parameters are determined based on the second target image, and the finish turning parameters are determined based on the second target image and/or the performance parameters of the third intermediate product.
See fig. 2-4 and their associated description for detailed functional description of the processor 180.
FIG. 2 is an exemplary flow chart of a method of manufacturing an automotive brake piston according to some embodiments of the present disclosure. In some embodiments, the process 200 may be performed by a processor. As shown in fig. 2, the process 200 includes the steps of:
And 210, controlling the stamping device to forge the raw materials in the female die with preset forging parameters to obtain a first intermediate product.
The preset forging parameters refer to preset forging-related parameters. For example, the preset forging parameters may include punch pressure, forging temperature, amount of punch oil, and the like. In some embodiments, the preset forging parameters may be obtained based on manual settings. In some embodiments, the preset forging parameters may be adjusted based on the first target image. For more description of adjusting preset forging parameters, see step 260 and its associated description.
The first intermediate product is an intermediate product obtained by forging a raw material by a stamping device.
And 220, controlling the rough turning numerical control machine tool to perform rough turning on the first intermediate product by presetting rough turning parameters to obtain a second intermediate product.
The preset rough turning parameters refer to preset parameters related to rough turning. For example, the preset rough turning parameters may include rough turning tool parameters, rough turning cutting parameters, rough turning machining path parameters, and the like. In some embodiments, the preset rough turning parameters may be obtained based on manual settings.
The second intermediate product is an intermediate product obtained by rough turning the first intermediate product.
And 230, controlling the quenching device to carry out quenching and tempering on the second intermediate product according to the quenching and tempering parameters to obtain a third intermediate product.
The tempering parameter refers to a parameter related to tempering. For example, the tempering parameters may include quenching parameters, tempering parameters, and the like. Wherein the quenching parameters may include a quenching temperature sequence and a quenching time sequence, and the tempering parameters may include a tempering temperature sequence and a tempering time sequence. The quenching temperature sequence corresponds to the quenching time sequence, and the tempering temperature sequence corresponds to the tempering time sequence. For example, the quenching temperature sequence is (A, B, C), and the quenching time sequence is (T1, T2, T3), then it means that the temperature a is operated for T1 time, then the temperature B is operated for T2 time, and finally the temperature C is operated for T3 time.
In some embodiments, the initial conditioning parameters may be preset based on a priori knowledge and historical data. In some embodiments, the tempering parameters may be determined based on the second target image. For more description of determining the conditioning parameters, see step 270 and its associated description.
The third intermediate product is an intermediate product obtained by quenching and tempering the second intermediate product.
And 240, controlling the finish turning numerical control machine to finish turning the third intermediate product by using the finish turning parameters to obtain a brake piston finished product.
The finish turning parameter refers to a parameter related to finish turning. For example, the finish turning parameters may include cutting speed, feed rate, back draft, etc.
In some embodiments, the initial finish turning parameters may be preset based on a priori knowledge and historical data. In some embodiments, the finish turning parameters may be determined based on performance parameters of the second target image and/or the third intermediate product. For more description of determining the finish turning parameters, see step 280 and its associated description.
The brake piston finished product is a finished product obtained by finish turning the third intermediate product.
In step 250, the control image acquisition device acquires a first target image of the first intermediate product and/or a second target image of the second intermediate product.
The first target image refers to an image of the first intermediate product. In some embodiments, the first target image may be acquired based on an image acquisition device acquisition.
The second target image refers to an image of a second intermediate product. In some embodiments, the second target image may be acquired based on the image acquisition device acquisition.
Step 260 adjusts the preset forging parameters based on the first target image.
The processor may adjust the preset forging parameters in a number of ways. In some embodiments, the processor may construct a problem feature vector based on the first target image, and determine the adjusted preset forging parameters by vector matching.
In some embodiments, the numerical control system may determine, based on the problem feature vector, a reference feature vector meeting a preset condition in the vector database, and determine the reference feature vector meeting the preset condition as the associated feature vector; and determining the reference preset forging parameters corresponding to the associated feature vectors as adjusted preset forging parameters. The vector database may include a plurality of reference feature vectors and corresponding reference preset forging parameters. The reference feature vector may be constructed based on the historical first target image. The reference preset forging parameters corresponding to the reference feature vectors may be determined based on human experience. The association preset condition may refer to a judgment condition for determining the association feature vector. In some embodiments, the association preset condition may include that the vector distance is less than a distance threshold, that the vector distance is minimum, etc.
In some embodiments, the processor may extract a punch feature of the first target image; determining a press stability based on the press characteristics; and adjusting preset forging parameters in response to the stamping stability meeting preset conditions.
The stamping feature refers to a feature associated with stamping during the forging process of the first intermediate product in the first target image. For example, the punch features may include pressure features and appearance features.
The pressure characteristic refers to a characteristic related to the punching pressure. For example, the pressure characteristics may include a pressure maximum, a standard deviation of the pressures at a plurality of preset points, and the like. In some embodiments, the pressure signature may be obtained based on analysis of readings of pressure sensors at a plurality of preset points on the die.
Appearance characteristics refer to characteristics associated with appearance defects. For example, the appearance characteristics may include whether or not flaws (scratches, cracks, etc.) occur, and the degree of flaws. In some embodiments, the processor may obtain the flaw area and the area thereof in the first target image based on the image recognition algorithm, and take the sum of the areas of the at least one flaw area as the flaw degree. For example, the image recognition algorithm may include a feature extraction algorithm or the like.
The press stability refers to the stability of the press process. In some embodiments, the processor may calculate a degree of similarity between the punched features of the first intermediate products, and average the similarities of the punched features corresponding to the first intermediate products to obtain an average similarity; the processor can calculate standard deviations of flaw degrees of all the first intermediate products and record the standard deviations as flaw degree standard deviations; the processor can pre-store different stamping stabilities corresponding to different average similarity and different flaw degree standard difference; the stamping stability is determined by looking up a table or the like with the average similarity and the flaw degree standard deviation obtained based on the foregoing calculation. The larger the average similarity is, the smaller the standard deviation of flaw degree is, and the better the punching stability is.
The preset conditions refer to conditions that the preset forging parameters need to be adjusted to meet. In some embodiments, the preset condition may be that the press stability is less than a stability threshold. Wherein the stability threshold may be determined based on historical data.
In some embodiments, the amount of adjustment in the punch pressure in the preset forging parameters is directly related to the difference between the punch stability and the stability threshold when the preset forging parameters are adjusted.
According to some embodiments of the specification, the preset forging parameters are adjusted based on the stamping stability, so that the difference between brake pistons of different automobiles in the same batch can be reduced as much as possible, and the reject ratio of products is reduced as much as possible.
And step 270, determining tempering parameters based on the second target image.
The processor may determine the conditioning parameters in a number of ways. In some embodiments, the processor may construct a problem feature vector based on the second target image, determine the hardening and tempering parameters by vector matching. For more description of vector matching see step 260 and its associated description.
In some embodiments, the processor may extract rough turning features of the second intermediate product based on the second target image; and determining the tempering parameters of the second intermediate product through a preset algorithm based on the rough turning features.
The rough turning feature refers to a related feature of rough turning of the second intermediate product. In some embodiments, the rough turning feature comprises a degree of flash of the at least one first region, a degree of deformation of the at least one second region.
The first area is an area with burrs on the second intermediate product. In some embodiments, the first region may be determined by an image recognition algorithm based on actual fuzzing conditions.
The burr degree refers to the degree of the first intermediate product after rough turning, which is provided with burrs, bulges and the like. In some embodiments, the flash level may be determined by an image recognition algorithm.
The second area is a preset critical position area on the second intermediate product. For example, the second region may include a perforated location, a curved location, and the like. In some embodiments, the second region may be preset by a technician.
The deformation degree refers to the integral deformation degree of the plurality of key position areas after the first intermediate product is subjected to rough turning. In some embodiments, the degree of deformation may be determined by an image recognition algorithm.
In some embodiments, the processor may determine the degree of flash of the at least one first object recognition frame and each first object recognition frame, the degree of deformation of the at least one second object recognition frame and each second object recognition frame by processing the second target image of the at least one photographing perspective of the second intermediate product by the predictive model.
The predictive model may be a machine learning model. For example, convolutional neural network (Convolutional Neural Networks, CNN) models, and the like.
The input of the prediction model may be a second target image of at least one photographing view angle of the second intermediate product, for example, a plurality of second target images of the second intermediate product photographed based on a plurality of photographing view angles may be used as the input of the prediction model, and the output of the prediction model may include the degree of burrs of at least one and each of the first object recognition frames, the degree of deformations of at least one and each of the second object recognition frames.
The first object recognition frame refers to an object recognition frame for framing the first area.
The second object recognition frame refers to an object recognition frame for framing the second area.
In some embodiments, the predictive model may be trained from a first training sample with a first label. In some embodiments, the first training sample may include a second target image of at least one photographing perspective of the second intermediate product of the sample, and the first label may include a sample burr level of the at least one sample first object recognition frame and each first object recognition frame, a sample deformation level of the at least one sample second object recognition frame and each second object recognition frame. The first training sample can be obtained based on historical data, and the first label can be obtained based on labeling of an image recognition algorithm.
For example, the processor may obtain the first object identification frame based on an edge detection algorithm, and count a sum of lengths and/or areas of protrusions of the region in the first object identification frame for each sample, and the sample burr level of the first object identification frame in the first tag is the sum of lengths and/or areas of protrusions. For another example, the processor may obtain the second object recognition frame of the sample based on an edge detection algorithm, extract a contour of an area in the second object recognition frame, calculate a contour similarity between the contour of the second object recognition frame and a contour of a corresponding second area in a design drawing of the brake piston, and then the sample deformation degree of the second object recognition frame in the first label is a difference between 1 and the contour similarity.
According to the method and the device for determining the first region and the burr degree of the second region, the second region and the deformation degree of the second region are obtained by processing the second target image through the prediction model, rules can be found from a large number of second target images by utilizing the self-learning capability of the machine learning model, and the association relation between the first region and the burr degree of the first region, the second region and the deformation degree of the second region and the second target image is obtained, so that accuracy and efficiency of determining the first region and the burr degree of the first region and the second region and the deformation degree of the second region are improved.
The preset algorithm is an algorithm for determining a second intermediate product tempering parameter based on the rough turning feature.
In some embodiments, the processor may construct a problem feature vector based on the coarse-car features, and determine the conditioning parameters by vector matching. For more description of vector matching see step 260 and its associated description.
According to some embodiments of the specification, the rough turning feature is extracted based on the second target image, and the tempering parameters are determined through a preset algorithm, so that the tempering parameters can be more accurately adjusted, the processing process is optimized, the product defects are reduced, and the production efficiency is improved.
In some embodiments, the processor may determine the tempering parameters of the second intermediate product based on the evaluation model. For more explanation of the assessment model, see fig. 3 and its associated description.
Step 280, determining a finish turning parameter based on the second target image and/or the performance parameter of the third intermediate product.
The performance parameter refers to a parameter related to the performance of the third intermediate product. For example, the performance parameters may include strength, toughness, plasticity, and the like. In some embodiments, the processor may obtain the performance parameter of the third intermediate product via a material mechanical property testing device.
The processor may determine the finish turning parameters in a number of ways. In some embodiments, the processor may pre-record and store different finish turning parameters corresponding to different performance parameters of different second target images and/or third intermediate products based on prior knowledge or historical data, and the processor may obtain the finish turning parameters by looking up a table or the like based on the performance parameters of the second target images and/or third intermediate products.
In some embodiments, the processor may determine the finish turning parameter based on the cutting speed threshold and the initial finish turning parameter. For more description of cutting speed thresholds, see fig. 4 and its associated content.
According to some embodiments of the specification, by adjusting preset forging parameters based on the first target image and determining tempering parameters based on the second target image, forging and tempering of raw materials can be controlled more accurately, the processing process can be controlled more accurately, product defects and defective rate are reduced, and product quality is improved.
It should be noted that the above description of the flow is only for the purpose of illustration and description, and does not limit the application scope of the present specification. Various modifications and changes to the flow may be made by those skilled in the art under the guidance of this specification. However, such modifications and variations are still within the scope of the present description.
FIG. 3 is an exemplary schematic diagram illustrating determining conditioning parameters according to some embodiments of the present disclosure.
In some embodiments, the processor may generate a plurality of candidate tempering parameters 310; determining performance parameters 340 of the third intermediate product corresponding to the candidate tempering parameters 310 based on the evaluation model; based on the performance parameters 340, a conditioning parameter is determined from the plurality of candidate conditioning parameters 310.
The candidate tempering parameters 310 refer to parameters to be confirmed as final tempering parameters. In some embodiments, the processor may randomly generate a plurality of candidate tempering parameters 310 over a range based on a priori knowledge.
The assessment model 330 may be a machine learning model. For example, neural network (Neural Networks, NN) models, or the like, or any combination thereof.
In some embodiments, the inputs of the evaluation model 330 may include the rough turning feature 320, the candidate tempering parameter 310, and the outputs may include the performance parameter 340 and the first and second temperature distribution features 350, 360 of the third intermediate product corresponding to the candidate tempering parameter.
The first temperature profile 350 refers to the temperature profile of the product surface during quenching of the second intermediate product. The first temperature profile 350 may include a temperature maximum, a temperature standard deviation, of at least one first temperature region. The first temperature region refers to a region with similar temperature characteristics in the quenching process of the second intermediate product.
The second temperature profile 360 refers to the temperature profile during tempering of the second intermediate product. The second temperature profile 360 may include a temperature maximum, a temperature standard deviation, of at least one second temperature region. The second temperature region refers to a region with similar temperature characteristics during tempering of the second intermediate product.
In some embodiments, the automotive brake piston production system further comprises a thermal imaging device that can capture a first thermal image of the second intermediate product during quenching, a second thermal image of the second intermediate product during tempering; the first temperature profile 350 is determined based on the first thermal imaging map and the second temperature profile 360 is determined based on the second thermal imaging map.
The first thermal imaging image refers to a thermal imaging image of the second intermediate product acquired by the thermal imaging device during quenching of the second intermediate product.
The second thermal imaging diagram refers to a thermal imaging diagram of the second intermediate product acquired by the thermal imaging device in the tempering process of the second intermediate product.
In some embodiments, the processor may divide the first thermal imaging map into a plurality of sub-regions according to a preset size and shape, cluster the plurality of sub-regions of the first thermal imaging map based on the temperatures of the sub-regions, and obtain a plurality of first temperature regions and temperatures corresponding to the first temperature regions based on the result of the clustering, for example, the processor may determine the sub-region included in one cluster as one first temperature region, and the temperature of the sub-region corresponding to the center of each cluster is taken as the temperature of the first temperature region, so that the processor may calculate the temperature maximum value and the temperature standard deviation of the plurality of first temperature regions to determine the first temperature distribution feature 350.
The determination of the second temperature profile 360 is similar to the determination of the first temperature profile, see in particular above.
In some embodiments of the present disclosure, by capturing a thermal imaging image, the temperature distribution of the second intermediate product may be captured more accurately, thereby improving the accuracy of the first temperature distribution feature and the second temperature distribution feature.
In some embodiments, the inputs to the evaluation model 330 further include preset forging parameters. The preset forging parameters can be preset or adjusted.
For a more explanation of preset forging parameters and their adjustments, see FIG. 2 and its associated content.
According to some embodiments of the specification, the performance parameters, the first temperature distribution characteristics and the second temperature distribution characteristics of the third intermediate product corresponding to the candidate tempering parameters are determined by adding the preset forging parameters, and the influence of the forging processing process on the performance parameters is considered, so that the determined performance parameters are more comprehensive and accurate.
According to some embodiments of the specification, the performance parameters, the first temperature distribution characteristics and the second temperature distribution characteristics of the third intermediate product corresponding to the candidate tempering parameters are determined through the evaluation model, so that the candidate tempering parameters corresponding to the optimal performance parameters can be found, the production process is controlled better, and the product quality is improved.
In some embodiments, the assessment model may be trained by a second training sample with a second tag. In some embodiments, the second training sample may include a sample rough turning feature, a sample tempering parameter, and the second label may include a performance parameter of the third intermediate product corresponding to the sample tempering parameter, and the first temperature distribution feature, the second temperature distribution feature. Wherein the second training sample and the second tag may be obtained based on historical data.
In some embodiments, the processor may determine the candidate conditioning parameters 310 corresponding to the optimal performance parameters 340 as the final conditioning parameters.
Because the thickness and shape of the second intermediate product at different positions are different, the heating degree is different, and the strength/hardness of different areas can be obviously different after quenching and tempering in the tempering process. In some embodiments of the present disclosure, based on the performance parameter, a suitable conditioning parameter is determined from the plurality of candidate conditioning parameters, such that the performance parameter meets a requirement and performance at different locations is as consistent as possible after conditioning the second intermediate product.
FIG. 4 is an exemplary schematic diagram illustrating determining finish turning parameters according to some embodiments of the present description.
In some embodiments, the processor may divide the third intermediate product into a plurality of areas to be finish turned 410 based on the rough turning features 320; determining a cutting speed threshold 420 when cutting out the machining allowance of the region 410 to be finished based on the rough turning feature 320 and the performance parameter 340 of the third intermediate product; based on the cutting speed threshold 420, the initial finish turning parameters 430, finish turning parameters 440 of the area to be finish turned are determined.
The area to be finish turned 410 refers to an area where finish turning is required. In some embodiments, the processor may divide the surface area of the third intermediate product into a plurality of sub-areas according to a preset size and shape based on a plurality of third target images captured in different directions, calculate a comprehensive index for each sub-area, cluster the plurality of sub-areas based on the comprehensive index, and obtain a plurality of regions 410 to be finished and a comprehensive index of each region 410 to be finished based on a result of the clustering. The comprehensive index reflects the difference of different finish turning areas.
In some embodiments, the composite index may be calculated based on the rough turning features 320. For example, the composite index of the sub-region is a weighted sum of the thickness of the sub-region, the burr level of the sub-region, and the deformation level of the sub-region.
In some embodiments, the processor may obtain the thickness of the different sub-regions based on a design drawing of the brake piston; taking the burr degree of the first area as the burr degree of at least one sub-area corresponding to the first area; and taking the deformation degree of the second area as the deformation degree of at least one sub-area corresponding to the second area. For more description of the first region, the flash level, the second region and the deformation level, see fig. 2 and its associated description.
The machining allowance refers to the thickness of a metal layer reserved (to be cut off) on the surface of the part in the machining process. In some embodiments, the tooling allowance is determined from historical experience.
The cutting speed threshold 420 is a speed threshold set to prevent the cutting speed from becoming too high, resulting in excessive frictional heating and deformation.
In some embodiments, the processor may determine the cutting speed threshold 420 corresponding to the composite index by vector matching based on the composite index of the region to be finish turned 410, the performance parameter 340 of the third intermediate product.
For example, the processor may construct a current feature vector based on the composite index of the region to be finish turned 410 of the third intermediate product, the performance parameter 340 of the third intermediate product, and determine at least one reference cutting speed threshold stored in association with the at least one reference feature vector in the vector database based on the current feature vector querying the vector database for at least one reference feature vector having a vector distance from the feature vector less than a distance threshold; when the number of the reference cutting speed thresholds is plural, the respective reference cutting speed thresholds are weighted and summed, and the sum value is taken as a cutting speed threshold 420, and when the weighted sum is performed, the weight of each reference cutting speed threshold is related to the vector distance, the smaller the vector distance, the larger the weight. The reference feature vector may be constructed based on a comprehensive index of the to-be-finely-turned region of the historical third intermediate product and a performance parameter of the historical third intermediate product, and the reference cutting speed threshold corresponding to the reference feature vector may be obtained based on the historical cutting speed.
In some embodiments, the cut speed threshold 420 is a dynamic value, the cut speed threshold 420 being inversely related to the machining allowance. As the machining allowance decreases, the processor may increase the corresponding cutting speed threshold 420.
The smaller the machining allowance, the more the finish turning of the product is finished, and attention is paid to the surface quality of the product. According to some embodiments of the specification, the cutting speed threshold value is inversely related to the machining allowance, so that the appearance quality of the surface of a finished product is better, the generation of phosphorus thorns and accumulated cutting burrs is reduced, and the machining precision and the finish degree are improved.
The initial finish turning parameter 430 is a preliminary determined finish turning parameter. In some embodiments, the initial fine parameters 430 may be preset based on a priori knowledge and historical experience.
In some embodiments, the processor may determine finish turning parameters 440 for the area to be finish turned based on the cutting speed threshold 420, the initial finish turning parameters 430. For example, the feed amount and the back draft amount in the finish turning parameters follow the initial finish turning parameters, and the cutting speed is set to run at the cutting speed threshold.
According to some embodiments of the specification, based on the cutting speed threshold and the initial finish turning parameters, the finish turning parameters of a plurality of areas to be finish turned of the third intermediate product are determined, the areas with different shapes/thicknesses/hardness are different in deformation resistance, different cutting speeds can be adopted, deformation of the product is reduced, and accuracy is improved.
While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing detailed disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements, and adaptations to the present disclosure may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within this specification, and therefore, such modifications, improvements, and modifications are intended to be included within the spirit and scope of the exemplary embodiments of the present invention.
Meanwhile, the specification uses specific words to describe the embodiments of the specification. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the present description. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the present description may be combined as suitable.
Furthermore, the order in which the elements and sequences are processed, the use of numerical letters, or other designations in the description are not intended to limit the order in which the processes and methods of the description are performed unless explicitly recited in the claims. While certain presently useful inventive embodiments have been discussed in the foregoing disclosure, by way of various examples, it is to be understood that such details are merely illustrative and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements included within the spirit and scope of the embodiments of the present disclosure. For example, while the system components described above may be implemented by hardware devices, they may also be implemented solely by software solutions, such as installing the described system on an existing server or mobile device.
Likewise, it should be noted that in order to simplify the presentation disclosed in this specification and thereby aid in understanding one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure does not imply that the subject matter of the present description requires more features than are set forth in the claims. Indeed, less than all of the features of a single embodiment disclosed above.
In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially. Unless otherwise indicated, "about," "approximately," or "substantially" indicate that the number allows for a 20% variation. Accordingly, in some embodiments, numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and employ a method for preserving the general number of digits. Although the numerical ranges and parameters set forth herein are approximations that may be employed in some embodiments to confirm the breadth of the range, in particular embodiments, the setting of such numerical values is as precise as possible.
Each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., referred to in this specification is incorporated herein by reference in its entirety. Except for application history documents that are inconsistent or conflicting with the content of this specification, documents that are currently or later attached to this specification in which the broadest scope of the claims to this specification is limited are also. It is noted that, if the description, definition, and/or use of a term in an attached material in this specification does not conform to or conflict with what is described in this specification, the description, definition, and/or use of the term in this specification controls.
Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments of this specification. Other variations are possible within the scope of this description. Thus, by way of example, and not limitation, alternative configurations of embodiments of the present specification may be considered as consistent with the teachings of the present specification. Accordingly, the embodiments of the present specification are not limited to only the embodiments explicitly described and depicted in the present specification.
Claims (4)
1. An automotive brake piston production system, comprising: a mechanical arm, a piston processing table, a stamping device, an image acquisition device, a rough turning numerical control machine tool, a quenching device, a finish turning numerical control machine tool and a processor,
The processor is configured to send a control instruction to at least one of the mechanical arm, the stamping device, the image acquisition device, the rough turning numerical control machine tool, the quenching device and the finish turning numerical control machine tool;
The mechanical arm is configured to transmit raw materials and intermediate products based on the control instruction;
a female die is arranged on the piston processing table, and a pressure sensor is arranged on the female die;
The stamping device is configured to forge the raw materials in the female die with preset forging parameters based on the control instruction to obtain a first intermediate product;
The rough turning numerical control machine tool is configured to perform rough turning on the first intermediate product with preset rough turning parameters based on the control instruction to obtain a second intermediate product;
The quenching device is configured to carry out quenching and tempering on the second intermediate product according to the control instruction and the quenching parameters to obtain a third intermediate product;
the finish turning numerical control machine tool is configured to finish turning the third intermediate product with finish turning parameters based on the control instruction to obtain a brake piston finished product;
The image acquisition device is configured to acquire a first target image of the first intermediate product and/or a second target image of the second intermediate product based on the control instruction; the preset forging parameters are adjusted based on the first target image; the tempering parameters are determined based on the second target image; the finish turning parameters are determined based on performance parameters of the second target image and/or the third intermediate product;
extracting stamping characteristics of the first target image;
Determining a press stability based on the press characteristic;
Adjusting the preset forging parameters in response to the stamping stability meeting a preset condition;
extracting rough turning features of the second intermediate product based on the second target image;
determining hardening and tempering parameters of the second intermediate product through a preset algorithm based on the rough turning features;
Dividing the third intermediate product into a plurality of areas to be finish-turned based on the rough turning features;
Determining a cutting speed threshold value when cutting off the machining allowance of the area to be finished on the basis of the rough turning characteristics and the performance parameters of the third intermediate product;
And determining the finish turning parameters of the region to be finish turned based on the cutting speed threshold and the initial finish turning parameters.
2. The system of claim 1, wherein the processor is further configured to:
Generating a plurality of candidate tempering parameters;
Determining performance parameters of the third intermediate product corresponding to the candidate tempering parameters based on an evaluation model; the evaluation model is a machine learning model;
determining the quality parameter from a plurality of the candidate quality parameters based on the performance parameter.
3. A method for producing an automotive brake piston based on processor execution, comprising:
Controlling a stamping device to forge raw materials in the female die according to preset forging parameters to obtain a first intermediate product;
controlling a rough turning numerical control machine tool to perform rough turning processing on the first intermediate product according to preset rough turning parameters to obtain a second intermediate product;
controlling a quenching device to carry out quenching and tempering on the second intermediate product according to quenching and tempering parameters to obtain a third intermediate product;
controlling a finish turning numerical control machine tool to finish turning the third intermediate product according to finish turning parameters to obtain a brake piston finished product;
Controlling an image acquisition device to acquire a first target image of the first intermediate product and/or a second target image of the second intermediate product;
adjusting the preset forging parameters based on the first target image;
determining the tempering parameters based on the second target image;
Determining the finish turning parameters based on the second target image and/or the performance parameters of the third intermediate product;
extracting stamping characteristics of the first target image;
Determining a press stability based on the press characteristic;
Adjusting the preset forging parameters in response to the stamping stability meeting a preset condition;
extracting rough turning features of the second intermediate product based on the second target image;
determining hardening and tempering parameters of the second intermediate product through a preset algorithm based on the rough turning features;
Dividing the third intermediate product into a plurality of areas to be finish-turned based on the rough turning features;
Determining a cutting speed threshold value when cutting off the machining allowance of the area to be finished on the basis of the rough turning characteristics and the performance parameters of the third intermediate product;
And determining the finish turning parameters of the region to be finish turned based on the cutting speed threshold and the initial finish turning parameters.
4. A method according to claim 3, wherein said determining, by means of a preset algorithm, the tempering parameters of said second intermediate product comprises:
Generating a plurality of candidate tempering parameters;
Determining performance parameters of the third intermediate product corresponding to the candidate tempering parameters based on an evaluation model; the evaluation model is a machine learning model;
determining the quality parameter from a plurality of the candidate quality parameters based on the performance parameter.
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