Intelligent machining method for collet

Abstract

The present application relates to the field of automatic production, and particularly relates to a kind of intelligent processing method of collet, the method comprises: recording the cutting depth value of workpiece to be processed in the machining process and the feed angle value of tool and workpiece to be processed in the cutting process in current machining cycle, to complete the cutting of the workpiece to be processed into collet in the current machining cycle;The actual surface roughness of the collet and the actual crack distribution condition formed on the surface of the collet are detected;Whether the actual processing yield in the current machining cycle meets the processing requirement is counted;If the processing requirement is not met, the cutting depth value and the feed angle value in the next machining cycle are adjusted according to the surface roughness and the crack distribution condition;Or, the hardness screening condition of the workpiece to be processed is replaced.The present application improves the precision in the production process of collet.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automatic production, in particular to an intelligent processing method of a chuck. BACKGROUND

[0002] The chuck is a locking device for clamping tools or workpieces, usually used on drilling and milling machines and machining centers. The core of automation production technology is robot technology. Robots, as a device that can replace humans to complete repetitive and dangerous work, are widely used in industrial manufacturing. They have the characteristics of high speed, high precision, high efficiency and reliability, which has brought great changes to industrial production. At present, the development of global automation production technology presents a diversified trend. On the one hand, traditional industrial manufacturing fields such as automobile manufacturing, electronic product manufacturing, etc. have achieved highly automated production processes. On the other hand, emerging fields such as biomedicine, new energy, etc. have also begun to apply automation production technology to improve production efficiency and product quality.

[0003] The patent document with the Chinese patent publication number CN114523268A discloses a milling cutter sleeve machining method for numerical control machine tools, which comprises the following steps: step S1: preliminary preparation, the customer sends the milling cutter sleeve specifications and technical requirements to establish an order, formulates a production plan and a process scheme according to the customer's requirements, and issues a raw pipe material to the CNC lathe to prepare for workpiece machining; step S2: raw pipe rough machining, the overall surface of the raw pipe sleeve is rough machined by the CNC lathe, and the outer surface of the raw pipe sleeve is machined first with the inner surface of the raw pipe sleeve as the positioning surface, and the coaxiality of the outer surface and the inner surface of the raw pipe sleeve is ensured, and then the tapered end surface of the raw pipe sleeve is rough turned to ensure that the machining precision reaches Ra6.3-Ra10.3; step S3: raw pipe semi-finishing machining, the raw pipe is first vertically clamped on the milling machine, and the outer surface and the tapered end surface of the raw pipe sleeve are used as the positioning surface, and the raw pipe sleeve inner hole is milled by the milling cutter; then the surface of the sleeve pipe is turned by the traditional lathe to make the surface roughness reach Ra3.2-Ra5.3; step S3: heat treatment, the two ends of the raw pipe sleeve are quenched to make the hardness reach 40HRC-45HRC, which ensures the hardness of the two ends of the sleeve while keeping the middle section of the sleeve that has not been heat treated elastic; step S4: vibration grinding, the surface of the sleeve is preliminarily ground by a vibration grinding and polishing machine to further ensure the surface precision; step S5: shot blasting, the surface of the sleeve is treated by shot blasting process to further strengthen the surface hardness; step S6: grinding treatment, the outer surface and the inner surface of the sleeve are ground in sequence to make the surface roughness reach Ra1.2-Ra2.5, and the sleeve is cleaned to prepare for slotting; step S7: slotting, first, a six-equal-division slot is milled by a vertical milling cutter, and a 2mm-3mm wide connecting rib is reserved at the end surface of the slot; then a six-equal-division narrow slot for separating the pieces is milled by a sheet milling cutter, and a 3mm-4mm wide connecting rib is reserved at the end surface of the narrow slot to ensure the integrity of the sleeve; step S8: needle grinding treatment, the surface of the sleeve is ground by a coarse needle grinding process, and after cleaning, the sleeve is inspected, if the inspection is not up to standard, the sleeve is polished again until the surface quality meets the requirements; if the inspection is up to standard, the sleeve is further treated by fine needle grinding to make the surface precision reach Ra0.8-Ra1.2, and then the sleeve is processed by laser; step S9: detection and packaging, the appearance of the finished product after laser processing is detected, the finished product meeting the requirements is packaged and stored in the warehouse, and is waiting for delivery to the customer.

[0004] In the prior art, there is no real-time detection and adjustment of machining parameters in the sleeve clamp production process, which results in low machining precision and unstable sleeve clamp production quality. SUMMARY

[0005] To this end, the application provides an intelligent processing method and device for a collet, which can solve the problem of low processing precision of the collet by comparing the actual surface roughness and actual crack distribution in the current cycle with the standard surface roughness and standard crack distribution to calculate an actual adjustment coefficient and adjusting the cutting depth value and the feed angle value in the next cycle.

[0006] To achieve the above object, the application provides an intelligent processing method for a collet, which comprises the following steps of:

[0007] recording the cutting depth value of a workpiece to be processed and the feed angle value of a turning tool and the workpiece to be processed in a machining process in a current processing cycle, so as to complete the cutting of the workpiece to be processed into a collet in the current processing cycle;

[0008] detecting the actual surface roughness of the collet and the actual crack distribution on the surface of the collet;

[0009] counting whether the actual processing yield in the current processing cycle meets the processing requirement;

[0010] if the processing requirement is not met, adjusting the cutting depth value and the feed angle value in the next processing cycle according to the surface roughness and the crack distribution;

[0011] or, changing the screening condition for the hardness of the workpiece to be processed.

[0012] Further, the detection of the actual surface roughness of the collet comprises the following steps of:

[0013] collecting data of the surface of the collet by a profilometer, drawing a surface profile image of the collet according to the collected data, and obtaining an actual profile image;

[0014] comparing the actual profile image with a standard profile image corresponding to the standard surface roughness to obtain a similarity value;

[0015] determining the actual surface roughness of the collet according to the similarity value and the standard surface roughness.

[0016] Further, the detection of the actual crack distribution on the surface of the collet comprises the following steps of:

[0017] collecting a surface image of the collet by an image collection device to obtain an actual surface image;

[0018] performing denoising processing on the actual surface image by an image processing software;

[0019] extracting a plurality of edge profiles in the processed actual surface image by an edge detection algorithm;

[0020] identifying a plurality of gray scale values of a plurality of regions of the edge profile;

[0021] regarding a region of the edge profile with a gray scale value less than a standard gray scale value as a crack formed by the collet surface;

[0022] marking a plurality of regions to obtain an actual crack distribution condition of the collet surface.

[0023] Further, adjusting the cutting depth value and the feed angle value in the next machining cycle according to the actual surface roughness and the actual crack distribution condition comprises:

[0024] calculating an actual adjustment coefficient according to the actual surface roughness and the actual crack distribution condition;

[0025] calculating the cutting depth value and the feed angle value in the next machining cycle according to the actual adjustment coefficient and the cutting depth value and the feed angle value in the current machining cycle.

[0026] Further, marking a plurality of regions to obtain an actual crack distribution condition of the collet surface comprises:

[0027] dividing the actual surface image into a plurality of image blocks according to a preset length and a preset width;

[0028] counting a total number of total image blocks of the actual surface image and a sub-number of image blocks in the region, and dividing the sub-number by the total number to obtain an actual crack distribution value, and regarding the actual crack distribution value as the actual crack distribution condition of the collet surface.

[0029] Further, calculating an actual adjustment coefficient according to the actual surface roughness and the actual crack distribution condition comprises:

[0030] dividing the actual surface roughness by the standard surface roughness to obtain a surface roughness adjustment coefficient;

[0031] dividing the actual crack distribution value by the standard crack distribution value to obtain a crack adjustment coefficient;

[0032] multiplying the surface roughness adjustment coefficient and the crack adjustment coefficient to obtain the actual adjustment coefficient.

[0033] Further, counting whether the actual machining yield in the current machining cycle meets the machining requirement comprises:

[0034] acquiring a current surface image of the collet machined by the current machining cycle by an image acquisition device;

[0035] denoising the current surface image;

[0036] extracting a current surface roughness and a current crack distribution value of the chuck in the current surface image;

[0037] counting an actual number of the chucks whose current surface roughness is less than or equal to the standard surface roughness and whose current crack distribution value is less than or equal to the standard crack distribution value;

[0038] dividing the actual number by a total number of chucks processed in a current processing cycle to obtain a result of the division as an actual processing yield;

[0039] comparing the actual processing yield with a preset processing yield, if the actual processing yield is greater than or equal to the preset processing yield, the processing requirement is met, and if the actual processing yield is less than the preset processing yield, the processing requirement is not met.

[0040] Further, the cutting depth of the workpiece to be processed and the feed angle of the turning tool and the workpiece to be processed during the cutting process are recorded, including:

[0041] a plurality of cutting depth values of the workpiece to be processed during the cutting process are recorded by a depth gauge;

[0042] a plurality of feed angle values of the turning tool and the workpiece to be processed during the cutting process are recorded by an angle measuring instrument.

[0043] Further, it further includes:

[0044] if the processing yield in the current processing cycle meets the processing requirement, the cutting depth and the feed angle are maintained in the next processing cycle.

[0045] Further, the screening condition of the hardness of the workpiece to be processed includes:

[0046] detecting the hardness value of the workpiece to be processed to obtain an actual hardness value;

[0047] multiplying the surface roughness adjustment coefficient and the actual hardness value to obtain a first hardness value;

[0048] multiplying the crack adjustment coefficient and the actual hardness value to obtain a second hardness value;

[0049] the screening range of the hardness of the workpiece to be processed is determined to be between the first hardness value and the second hardness value.

[0050] Compared with the prior art, the beneficial effects of the present application are that by recording the cutting depth value and the feed angle value in the current machining cycle, the parameter changes in the current machining cycle process are known in real time, thereby the cutting depth and the feed angle are adjusted in the next cycle production process, which helps to improve the production accuracy of the next machining process, improve the machining efficiency in the next cycle chuck production process, and by detecting the actual surface roughness and crack distribution of the chuck, the quality status of the chuck production is known in real time, which helps to find potential quality problems in time and ensures the stability and consistency of the quality of the chuck production, when the actual machining yield does not meet the machining requirements, the cutting depth value and the feed angle value are adjusted according to the surface roughness and crack distribution, which improves the accuracy and efficiency of the adjustment process, and further improves the machining yield of the next cycle chuck, and when the hardness of the workpiece to be machined does not meet the requirements, the hardness screening condition option can also be replaced, so that different adjustment methods are provided for the quality improvement of the next cycle chuck, and the efficiency of the next cycle chuck production is ensured.

[0051] Especially, the surface of the chuck is data collected by the profilometer, the topographic data of the surface is accurately obtained, the surface profile image is accurately drawn, accurate data basis is provided for subsequent surface roughness evaluation, the actual roughness of the chuck surface is evaluated by comparing the similarity of the actual profile image and the standard profile image corresponding to the standard surface roughness, the accuracy of the evaluation result is ensured by obtaining the similarity value, and the actual surface roughness of the chuck is determined according to the comparison of the similarity value and the standard surface roughness, which more comprehensively reflects the surface quality of the chuck and provides accurate data basis for subsequent adjustment of the cutting depth value and the feed angle value in the next cycle, thereby ensuring the production quality of the next cycle chuck.

[0052] Especially, the surface image of the chuck is collected by the image acquisition device, non-contact and non-destructive detection of the surface of the chuck is realized, the surface of the chuck is not damaged, the analysis result of the crack distribution of the surface of the chuck is accurate, and the efficiency of obtaining the distribution of the surface cracks is improved, the actual surface image is denoised, the noise and interference in the image are effectively removed, the definition and contrast of the image are improved, which helps to more accurately extract the edge profile of the crack, the edge profile in the processed actual surface image is extracted by the edge detection algorithm, the accuracy of obtaining the crack edge profile is improved, the gray value of the edge profile region is identified, the edge profile region with a gray value less than a standard gray value is marked as a crack, the crack distribution of the surface of the chuck is accurately judged, which helps to find the crack distribution of the surface of the chuck in time and provides accurate data basis for the next cycle adjustment, thereby ensuring the production quality of the next cycle chuck.

[0053] Especially, the actual adjustment coefficient is calculated according to the actual surface roughness and the actual crack distribution, so that the cutting depth value and the feed angle value of the next cycle are adjusted more accurately, thereby improving the machining quality of the collet of the next cycle, the cutting depth value and the feed angle value are adjusted according to the actual adjustment coefficient, the risk of generating new cracks in the next cycle machining process is reduced, which helps to prolong the service life of the collet and the machining tool, reduce the failure and replacement frequency caused by cracks, the cutting depth value and the feed angle value are adjusted by the actual adjustment coefficient, the parameter setting in the next cycle cutting process is optimized, the cutting efficiency and the material removal rate of the next cycle are improved, thereby improving the production efficiency of the collet of the next cycle.

[0054] Especially, by dividing the actual surface image into a plurality of image blocks according to the preset length and the preset width, the actual surface image is finely divided, which helps to more accurately count the distribution of cracks in the actual surface image, provides more detailed data for subsequent processing, counts the total number of total image blocks and the number of image blocks in the region of the actual surface image, and divides the number by the total number to obtain the actual crack distribution value, objectively quantifies the crack distribution of the collet surface, more intuitively understands the crack distribution of the collet surface, and takes the actual crack distribution value as the actual crack distribution of the collet surface. The quality of the collet is more comprehensively evaluated, and the reliability and service life of the collet are more accurately reflected.

[0055] Especially, the actual adjustment coefficient is calculated by comprehensively considering the actual surface roughness and the actual crack distribution, thereby more comprehensively reflecting the quality of the collet surface, more accurately evaluating and adjusting the machining parameters, improving the overall quality of the product, and obtaining the surface roughness adjustment coefficient by dividing the actual surface roughness by the standard surface roughness, and obtaining the crack adjustment coefficient by dividing the actual crack distribution value by the standard crack distribution value, quantitatively determining the basis for adjustment, improving the accuracy and objectivity of adjustment, multiplying the surface roughness adjustment coefficient and the crack adjustment coefficient to obtain the actual adjustment coefficient, thereby simplifying the adjustment process and improving the efficiency and convenience of adjustment.

[0056] Especially, the chuck surface image in the current processing cycle is collected by the image collection device, the quality change in the processing process is monitored in real time, potential problems of the chuck are found in time, the stability and consistency of the chuck quality are ensured, the current surface image is subjected to denoising processing, interference and noise in the image are removed, the accuracy of data is improved, the surface roughness and crack distribution value in the current surface image are extracted, and the quality of the chuck is compared with the standard and preset value, the quality of the chuck is intuitively understood, the chuck quality evaluation efficiency is improved, the actual processing yield is compared with the preset processing yield, the processing effect in the current processing cycle is objectively reflected, whether the processing requirement is met is clearly judged, accurate basis is provided for subsequent adjustment and improvement, whether the actual processing yield meets the processing requirement is determined, and the processing parameter of the chuck in the next cycle is adjusted in time, so that the actual processing yield and the overall production efficiency are improved. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 The first flowchart of the intelligent processing method of the chuck provided by the embodiment of the present application is shown in the figure.

[0058] Figure 2 The second flowchart of the intelligent processing method of the chuck provided by the embodiment of the present application is shown in the figure.

[0059] Figure 3 The third flowchart of the intelligent processing method of the chuck provided by the embodiment of the present application is shown in the figure.

[0060] Figure 4 The fourth flowchart of the intelligent processing method of the chuck provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0061] In order to make the objects and advantages of the present application clearer, the present application will be further described below with reference to the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and do not limit the present application.

[0062] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application, and are not intended to limit the protection scope of the present application.

[0063] It should be noted that in the description of the present application, the terms "upper", "lower", "left", "right", "inner", "outer" and the like indicate the direction or positional relationship terms based on the direction or positional relationship shown in the drawings, which are only for the convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present application.

[0064] Moreover, it needs to be explained that in the description of the present application, unless explicitly defined and limited, the terms "mounting", "connecting", "connection" should be understood in a broad sense, for example, it can be fixed connection, or detachable connection, or integral connection, it can be mechanical connection, or electrical connection, it can be direct connection, or indirect connection through intermediate medium, or internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0065] Please refer to Figure 1 The present application provides an intelligent processing method of collet, which comprises the following steps:

[0066] Step S100, recording the cutting depth value of the workpiece to be processed and the feed angle value of the turning tool and the workpiece to be processed in the machining process in the current processing cycle, so as to complete the cutting of the workpiece to be processed into a collet in the current processing cycle;

[0067] Step S200, detecting the actual surface roughness of the collet and the actual crack distribution condition formed on the surface of the collet;

[0068] Step S300, counting whether the actual processing yield in the current processing cycle meets the processing requirement;

[0069] Step S400, if the processing requirement is not met, adjusting the cutting depth value and the feed angle value in the next processing cycle according to the surface roughness and the crack distribution condition;

[0070] Or, replacing the hardness screening condition of the workpiece to be processed.

[0071] Specifically, the embodiments of the present application record the cutting depth value and the feed angle value in the current processing cycle, understand the parameter change in the current processing cycle in real time, so as to adjust the cutting depth and the feed angle in the next cycle production process, which helps to improve the production precision of the next processing process, improve the processing efficiency in the collet production process of the next cycle, detect the actual surface roughness of the collet and the crack distribution condition, understand the quality condition of the collet production in real time, which helps to find potential quality problems in time, ensure the stability and consistency of the quality of the collet production, adjust the cutting depth value and the feed angle value according to the surface roughness and the crack distribution condition when the actual processing yield does not meet the processing requirement, improve the accuracy and efficiency of the adjustment process, and then improve the processing yield of the collet in the next cycle, and when the hardness of the workpiece to be processed does not meet the requirement, the hardness screening condition can also be replaced, so that different adjustment methods are provided for improving the quality of the collet in the next cycle, and the efficiency of the collet production in the next cycle is ensured.

[0072] Please refer to Figure 2As shown, detecting the actual surface roughness of the chuck comprises:

[0073] In step S210, the surface of the chuck is data-acquired by a profilometer, a surface profile image of the chuck is drawn according to the acquired data, and an actual profile image is obtained;

[0074] In step S220, the actual profile image is compared with a standard profile image corresponding to a standard surface roughness in terms of similarity, and a similarity value is obtained;

[0075] In step S230, the actual surface roughness of the chuck is determined according to the similarity value and the standard surface roughness.

[0076] Specifically, the standard surface roughness is 1.3 μm.

[0077] Specifically, the embodiment of the present application data-acquires the surface of the chuck by a profilometer, obtains the topographic data of the surface with high precision, makes the surface profile image drawn accurately, provides accurate data basis for subsequent surface roughness evaluation, compares the actual profile image with a standard profile image corresponding to a standard surface roughness in terms of similarity, evaluates the actual roughness of the surface of the chuck, ensures the accuracy of the evaluation result by obtaining the similarity value, determines the actual surface roughness of the chuck according to the comparison between the similarity value and the standard surface roughness, more comprehensively reflects the surface quality of the chuck, provides accurate data basis for subsequent adjustment of the cutting depth value and the feed angle value in the next cycle, and ensures the production quality of the chuck in the next cycle.

[0078] Specifically, detecting the actual crack distribution condition formed on the surface of the chuck comprises:

[0079] The surface image of the chuck is acquired by an image acquisition device, and an actual surface image is obtained;

[0080] The actual surface image is denoised by an image processing software;

[0081] The edge profiles in the actual surface image after processing are extracted by an edge detection algorithm;

[0082] The gray values of the regions of the edge profiles are identified;

[0083] The regions of the edge profiles with the gray values less than a standard gray value are regarded as cracks formed on the surface of the chuck;

[0084] The regions are marked, and the actual crack distribution condition formed on the surface of the chuck is obtained.

[0085] Specifically, the standard gray value is the mean value of the gray values of the regions of the edge profiles.

[0086] Specifically, the embodiment of the present application realizes non-contact and non-destructive detection of the surface of the collet by collecting the surface image of the collet through the image collection device, does not cause any damage to the surface of the collet, makes the analysis result of the crack distribution on the surface of the collet accurate, and improves the efficiency of obtaining the distribution of the surface cracks. The actual surface image is denoised to effectively remove the noise and interference in the image, improve the definition and contrast of the image, help more accurately extract the edge profile of the crack, improve the accuracy of obtaining the edge profile of the crack, identify the gray value of the edge profile region, mark the edge profile region with a gray value less than a standard gray value as a crack, accurately determine the crack distribution on the surface of the collet, help discover the crack distribution on the surface of the collet in time, provide accurate data basis for adjustment in the next cycle, and ensure the production quality of the collet in the next cycle.

[0087] Referring to Figure 3 Adjusting the cutting depth value and the feed angle value in the next machining cycle according to the actual surface roughness and the actual crack distribution includes:

[0088] Step S410, calculating an actual adjustment coefficient according to the actual surface roughness and the actual crack distribution;

[0089] Step S420, calculating the cutting depth value and the feed angle value in the next machining cycle according to the actual adjustment coefficient and the cutting depth value and the feed angle value in the current machining cycle.

[0090] Specifically, the embodiment of the present application calculates an actual adjustment coefficient according to the actual surface roughness and the actual crack distribution, makes the adjustment of the cutting depth value and the feed angle value in the next cycle more accurate, thereby improving the machining quality of the collet in the next cycle, adjusts the cutting depth value and the feed angle value according to the actual adjustment coefficient, reduces the risk of generating new cracks in the next cycle, helps prolong the service life of the collet and the machining tool, reduces the failure and replacement frequency caused by cracks, adjusts the cutting depth value and the feed angle value through the actual adjustment coefficient, optimizes the parameter setting in the cutting process in the next cycle, improves the cutting efficiency and material removal rate in the next cycle, and thereby improves the production efficiency of the collet in the next cycle.

[0091] Specifically, marking a plurality of the regions to obtain the actual crack distribution formed on the surface of the collet includes:

[0092] Dividing the actual surface image according to a preset length and a preset width to obtain a plurality of image blocks;

[0093] The total number of total image blocks of the actual surface image and the sub-number of image blocks in the region are counted, and the sub-number is divided by the total number to obtain an actual crack distribution value, which is taken as the actual crack distribution condition formed by the collet surface.

[0094] Specifically, the preset length is one-twentieth of the length of the actual surface image, and the preset width is one-twentieth of the width of the actual surface image.

[0095] Specifically, the actual surface image is divided according to the preset length and the preset width to obtain a plurality of image blocks, so as to realize fine division of the actual surface image, help to more accurately count the distribution of cracks in the actual surface image, provide more detailed data for subsequent processing, count the total number of total image blocks of the actual surface image and the sub-number of image blocks in the region, divide the sub-number by the total number to obtain an actual crack distribution value, objectively quantify the crack distribution condition of the collet surface, more intuitively understand the crack distribution condition of the collet surface, take the actual crack distribution value as the actual crack distribution condition formed by the collet surface, more comprehensively evaluate the quality of the collet, and more accurately reflect the reliability and service life of the collet.

[0096] Specifically, calculating the actual adjustment coefficient according to the actual surface roughness and the actual crack distribution condition comprises:

[0097] obtaining a surface roughness adjustment coefficient by dividing the actual surface roughness by the standard surface roughness;

[0098] obtaining a crack adjustment coefficient by dividing the actual crack distribution value by the standard crack distribution value;

[0099] multiplying the surface roughness adjustment coefficient and the crack adjustment coefficient to obtain the actual adjustment coefficient.

[0100] Specifically, the standard crack distribution value is 0.2.

[0101] Specifically, the actual adjustment coefficient is calculated by comprehensively considering the actual surface roughness and the actual crack distribution condition, so as to more comprehensively reflect the quality condition of the collet surface, more accurately evaluate and adjust the processing parameter, improve the overall quality of the product, obtain the surface roughness adjustment coefficient by dividing the actual surface roughness by the standard surface roughness, obtain the crack adjustment coefficient by dividing the actual crack distribution value by the standard crack distribution value, quantitatively determine the basis for adjustment, improve the accuracy and objectivity of adjustment, multiply the surface roughness adjustment coefficient and the crack adjustment coefficient to obtain the actual adjustment coefficient, so as to simplify the adjustment process and improve the efficiency and convenience of adjustment.

[0102] Referring to Figure 4 As shown, the statistics of whether the actual processing yield in the current processing cycle meets the processing requirements includes:

[0103] In step S310, the current surface image of the chuck processed in the current processing cycle is collected by an image collection device.

[0104] In step S320, the current surface image is denoised.

[0105] In step S330, the current surface roughness and the current crack distribution value of the chuck in the current surface image are extracted.

[0106] In step S340, the actual number of chucks with the current surface roughness less than or equal to the standard surface roughness and the current crack distribution value less than or equal to the standard crack distribution value is counted.

[0107] In step S350, the actual number is divided by the total number of chucks processed in the current processing cycle to obtain a division result as an actual processing yield.

[0108] In step S360, the actual processing yield is compared with a preset processing yield. If the actual processing yield is greater than or equal to the preset processing yield, the processing requirements are met. If the actual processing yield is less than the preset processing yield, the processing requirements are not met.

[0109] Specifically, the preset processing yield is 90%.

[0110] Specifically, the chuck surface image in the current processing cycle is collected by the image collection device, the quality change in the processing process is monitored in real time, potential problems of the chuck are found in time, the stability and consistency of the chuck quality are ensured, the current surface image is denoised to remove interference and noise in the image and improve the accuracy of the data, the surface roughness and the crack distribution value in the current surface image are extracted and compared with the standard and preset values, the quality of the chuck is intuitively understood, the quality evaluation efficiency of the chuck is improved, the actual processing yield is compared with the preset processing yield, the processing effect in the current processing cycle is objectively reflected, whether the processing requirements are met is clearly judged, accurate basis is provided for subsequent adjustment and improvement, the processing parameters of the chuck in the next cycle are adjusted in time according to whether the actual processing yield meets the processing requirements, the actual processing yield and the overall production efficiency are improved.

[0111] Specifically, the cutting depth of the workpiece to be processed in the processing process and the feed angle of the turning tool and the workpiece to be processed in the cutting process are recorded.

[0112] record a plurality of cutting depth values of the workpiece during the cutting process by a depth gauge;

[0113] record a plurality of feed angle values of the turning tool and the workpiece during the cutting process by an angle measuring instrument.

[0114] Specifically, further comprising:

[0115] If the processing yield in the current processing cycle meets the processing requirements, maintain the cutting depth and the feed angle in the next processing cycle.

[0116] Specifically, the replacement of the screening condition of the hardness of the workpiece comprises:

[0117] detect the hardness value of the workpiece to obtain an actual hardness value;

[0118] multiply the surface roughness adjustment coefficient by the actual hardness value to obtain a first hardness value;

[0119] multiply the crack adjustment coefficient by the actual hardness value to obtain a second hardness value;

[0120] determine the screening range of the hardness of the workpiece to be between the first hardness value and the second hardness value.

[0121] Specifically, the embodiment of the present application detects the hardness value of the workpiece and obtains an actual hardness value, thereby providing accurate data basis for subsequent adjustment of the hardness value screening of the chuck in the next cycle, improving the accuracy and effect of the chuck processing, multiplying the surface roughness adjustment coefficient and the crack adjustment coefficient by the actual hardness value to obtain a first hardness value and a second hardness value, comprehensively considering the influence of the surface roughness, the crack distribution and the hardness factor on the workpiece, more comprehensively evaluating the applicability of the workpiece, increasing the accuracy and reliability of the screening, determining the screening range of the hardness of the workpiece to be between the first hardness value and the second hardness value, improving the flexibility and efficiency of the screening, replacing the screening condition of the hardness of the workpiece, selecting the workpiece more suitable for processing, thereby optimizing the processing process, reducing the processing difficulties and risks caused by the unsuitable hardness, and improving the overall processing efficiency and product quality.

[0122] The technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will all fall within the protection scope of the present application.

[0123] The above merely illustrates the preferred embodiments of the present application, and is not used to limit the present application; for those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A smart machining method for collets, characterized in that, include: Record the depth of cut of the workpiece and the feed angle between the cutting tool and the workpiece during the current machining cycle, so as to complete the cutting of the workpiece into a collet within the current machining cycle; The actual surface roughness of the collet and the actual crack distribution on the collet surface are detected. To determine whether the actual processing yield within the current processing cycle meets the processing requirements; If the processing requirements are not met, the cutting depth and feed angle values ​​in the next processing cycle are adjusted according to the actual surface roughness and the actual crack distribution. Alternatively, the screening criteria for the hardness of the workpiece to be processed may be changed; Adjusting the cutting depth and feed angle values ​​for the next machining cycle based on the actual surface roughness and the actual crack distribution includes: Calculate the actual adjustment coefficient based on the actual surface roughness and the actual crack distribution. The cutting depth and infeed angle values ​​for the next machining cycle are calculated based on the actual adjustment coefficient and the cutting depth and infeed angle values ​​in the current machining cycle. The actual adjustment coefficient is calculated based on the actual surface roughness and the actual crack distribution, including: The surface roughness adjustment coefficient is obtained by dividing the actual surface roughness by the standard surface roughness; The crack adjustment coefficient is obtained by dividing the actual crack distribution value by the standard crack distribution value. The actual adjustment coefficient is obtained by multiplying the surface roughness adjustment coefficient by the crack adjustment coefficient.

2. The intelligent processing method for collets according to claim 1, characterized in that, Detecting the actual surface roughness of the collet includes: Data is collected from the surface of the collet using a profilometer, and a surface profile image of the collet is drawn based on the collected data to obtain the actual profile image. The actual contour image is compared with the standard contour image corresponding to the standard surface roughness to obtain a similarity value; The actual surface roughness of the collet is determined based on the similarity value and the standard surface roughness.

3. The intelligent machining method for collets according to claim 2, characterized in that, Detecting the actual crack distribution on the surface of the collet includes: The surface image of the collet is acquired using an image acquisition device to obtain the actual surface image; The actual surface image is denoised using image processing software; Several edge contours are extracted from the processed actual surface image using an edge detection algorithm; Identify several grayscale values ​​of regions with several edge contours; The region of the edge contour that is less than the standard gray value among the aforementioned gray values ​​is regarded as the crack formed on the surface of the collet; Several regions are marked to obtain the actual crack distribution on the surface of the collet.

4. The intelligent machining method for collets according to claim 3, characterized in that, Marking several of the aforementioned regions to obtain the actual crack distribution on the surface of the collet includes: The actual surface image is divided into several image blocks according to a preset length and a preset width; The total number of image blocks in the actual surface image and the fractional number of image blocks in the region are counted, and the fractional number is divided by the total number to obtain the actual crack distribution value. The actual crack distribution value is used as the actual crack distribution status formed on the collet surface.

5. The intelligent machining method for collets according to claim 1, characterized in that, Whether the actual processing yield within the current processing cycle meets the processing requirements includes: The current surface image of the collet, processed during the current processing cycle, is acquired using an image acquisition device; The current surface image is denoised. Extract the current surface roughness and current crack distribution values ​​of the collet from the current surface image; The actual number of collets whose current surface roughness is less than or equal to the standard surface roughness and whose current crack distribution value is less than or equal to the standard crack distribution value is counted. Divide the actual quantity by the total number of collets processed in the current processing cycle, and obtain the result as the actual processing yield. The actual processing yield is compared with the preset processing yield. If the actual processing yield is greater than or equal to the preset processing yield, the processing requirements are met. If the actual processing yield is less than the preset processing yield, the processing requirements are not met.

6. The intelligent machining method for collets according to claim 5, characterized in that, Record the depth of cut on the workpiece during machining, as well as the feed angles between the cutting tool and the workpiece during the cutting process, including: Several cutting depth values ​​of the workpiece during the cutting process were recorded using depth calipers. Several feed angle values ​​between the cutting tool and the workpiece are recorded using an angle measuring instrument during the cutting process.

7. The intelligent machining method for collets according to claim 6, characterized in that, Also includes: If the machining yield in the current machining cycle meets the machining requirements, the cutting depth and feed angle will be maintained in the next machining cycle.

8. The intelligent machining method for collets according to claim 7, characterized in that, Changing the screening criteria for the hardness of the workpiece to be processed includes: The hardness value of the workpiece to be processed is detected to obtain the actual hardness value; The first hardness value is obtained by multiplying the surface roughness adjustment coefficient by the actual hardness value; The second hardness value is obtained by multiplying the crack adjustment coefficient by the actual hardness value; The hardness range of the workpiece to be processed is determined to be between the first hardness value and the second hardness value.

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