A detection method for extrusion forming of a copper part extrusion machine

Abstract

This application relates to the field of image processing technology, and particularly to a method for detecting the extrusion forming of a copper part extrusion machine. The method includes: collecting multiple video frames during the copper part extrusion process, and calculating the stable moment sets of any position points of the copper parts; initializing the initial segments of any position points, and in response to the intersection of the stable moment set of the initial segment and the stable moment set of adjacent position points of the initial segment not being empty, adding the adjacent position points to the initial segment until the intersection of the stable moment sets is empty, obtaining the stable segment of the position point; splicing the neighborhood images of each position point in the stable segment according to the stable moment set of the stable segment to obtain the extrusion image segment of the stable segment; splicing each extrusion image segment and obtaining the detection result. Through the technical solution of this application, the influence of vibration on the extrusion forming detection can be eliminated, and an accurate detection result can be obtained.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and particularly to a method for detecting the extrusion forming of a copper part extruder. Background Art

[0002] A copper part extruder forms profiles or parts with a specific cross-sectional shape by extruding copper material from the die orifice under high pressure, and is a mechanical device used to produce copper products such as copper wires, copper cables, or copper rods. During the process of using a copper part extruder to extrude and form copper materials, defects such as uneven thickness, surface cracks, and even fractures may occur in the copper parts. To ensure the quality of the extrusion forming of copper parts, it is necessary to detect the extrusion process of the copper part extruder.

[0003] Currently, the patent application document with the publication number CN118446946A discloses an intelligent control method and system for a titanium metal wire drawing process. The method includes: obtaining a grayscale image of a titanium wire to obtain edge pixel points; according to a preset similarity measurement standard, taking the number of similar pixel points of each edge pixel point as the corresponding total number of targets for each edge pixel point; taking other edge pixel points on the straight line in the gradient direction of the target point as gradient pixel points, the straight line passes through the target point, and determining the edge degree of the titanium wire according to the difference between the total number of targets of the target point and the total number of targets of the target point and the gradient pixel points, so as to obtain a target gamma value, obtaining an updated grayscale value of the target point based on gamma transformation, so as to obtain an enhanced image, thereby detecting defects and adjusting process parameters.

[0004] The above method enhances the brightness of the grayscale image and detects defects in the metal wire during the wire drawing process based on the enhanced image. However, during the extrusion forming process, the vibration of the copper part extruder will cause vibrations in copper products such as copper wires and copper cables, resulting in a large amount of noise in the grayscale image, and brightness enhancement cannot eliminate this noise generated by vibration, so the detection result of extrusion forming is inaccurate. Summary of the Invention

[0005] To solve the technical problem of inaccurate detection results of extrusion forming, this application provides a method for detecting the extrusion forming of a copper part extruder, which can eliminate the influence of vibration on the detection of extrusion forming and obtain accurate detection results.

[0006] In the first aspect of the present application, a method for detecting the extrusion molding of a copper part by an extrusion press is provided. The detection method includes: collecting multiple video frames during the extrusion process of the copper part, and intercepting the neighborhood images of any position point in each video frame according to the extrusion speed; calculating the difference images between any neighborhood image and the adjacent two neighborhood images, taking the maximum value of the average pixel values in the difference images as the vibration amplitude of the position point at the corresponding timestamp in the neighborhood image, taking the timestamps with vibration amplitudes less than the preset amplitude as stable moments, and obtaining the stable moment set of each position point; initializing the initial segment of any position point, in response to the intersection of the stable moment set of the initial segment and the stable moment set of the adjacent position points of the initial segment not being empty, adding the adjacent position points to the initial segment until the intersection of the stable moment sets is empty, obtaining the stable segment of the position point, where the stable moment set of the initial segment is the intersection of the stable moment sets of each position point in the initial segment; splicing the neighborhood images of each position point in the stable segment according to the stable moment set of the stable segment to obtain the extrusion image segment of the stable segment; splicing each extrusion image segment to obtain the extrusion image, and obtaining the detection result according to the extrusion image.

[0007] Collect video frames during the extrusion process of the copper part. For any position point in the copper part, locate the pixel point coordinates corresponding to this position point in each video frame according to the extrusion speed of the copper part and the acquisition frame rate of the video frame, and intercept the video frame according to the pixel point coordinates to obtain the neighborhood image of this position point in each video frame; further, calculate the vibration amplitude of each timestamp according to the difference images between the neighborhood image and the adjacent two neighborhood images to obtain the stable moment set of each position point; take the position point as the initial segment, and continuously expand this initial segment according to the intersection of the position point and the stable moment set of the adjacent position points until the stable segments of each position point in the copper part are obtained. Multiple position points within a stable segment can be in a stable state at the same timestamp; splice the neighborhood images of each position point in the stable segment according to the stable moment set of the stable segment to obtain the extrusion image segment of the stable segment. The extrusion image segment is the image information of the copper part in a stable state, which can eliminate the noise generated by vibration in the video frame, thereby improving the accuracy of the extrusion molding detection result; splice each extrusion image segment to obtain the extrusion image, and obtain an accurate detection result according to the extrusion image.

[0008] Preferably, the step of intercepting the neighborhood images of any position point in each video frame according to the extrusion speed includes: determining the pixel point coordinates of the position point in any video frame according to the extrusion speed, and intercepting the video frame according to the preset number of pixel points on both sides of the pixel point coordinates to obtain the neighborhood image of the position point in this video frame.

[0009] Preferably, the timestamp vibration amplitude is:

[0010] , , and are the neighborhood images of the position points at time stamp , time stamp and time stamp respectively, indicating the calculation of the average pixel value.

[0011] The larger the average pixel value in the difference image indicates that there is relative motion between two adjacent neighborhood images. The maximum value of the average pixel values in the two difference images corresponding to one neighborhood image is used as the vibration amplitude of the position point, accurately quantifying the vibration amplitude of the position point at the time stamp corresponding to the neighborhood image.

[0012] Preferably, the initial segment for initializing any position point includes: the initial segment includes the any position point.

[0013] Preferably, the extrusion image segment for obtaining the stable segment includes: obtaining the video frame at any time stamp in the stable time set of the stable segment, intercepting the video frame according to the pixel coordinates of each position point in the stable segment in the video frame to obtain the initial image segment of the stable segment; taking the mean value of all initial image segments as the extrusion image segment of the stable segment.

[0014] The stable time set of a stable segment includes at least one time stamp, and one time stamp corresponds to one initial image segment. The initial image segment is the image information of the stable segment in the copper workpiece in the stable state, which can eliminate the noise generated by vibration in the video frame.

[0015] Preferably, the step of taking the mean value of all initial image segments as the extrusion image segment of the stable segment includes: obtaining the pixel values of any position point in each initial image segment to obtain a pixel value sequence; determining the weighting coefficient of each initial image segment according to the vibration amplitude of the position point at the time stamp corresponding to the initial image segment, and the weighting coefficient is negatively correlated with the vibration amplitude; performing weighted averaging on the pixel value sequence according to the weighting coefficient to obtain the weighted pixel value of the position point, and the weighted pixel values of all position points in the stable segment constitute the extrusion image segment.

[0016] Since there are differences in the vibration amplitudes of each position point in the stable segment at different time stamps, directly taking the mean value of all initial image segments as the extrusion image segment ignores the differences in the vibration amplitudes of each position point in the stable segment at different time stamps, making the extrusion image segment greatly affected by the vibration amplitude and unable to accurately obtain the image information of the copper workpiece in the stable state. Therefore, in the process of calculating the mean value of all initial image segments, the vibration amplitudes of each position point at different time stamps, that is, in different initial image segments, can be considered to further eliminate the noise generated by vibration in the video frame.

[0017] Preferably, the position point at time stamp The weighting factor for:

[0018] , For location point In timestamp The vibration amplitude, For location point The sum of the vibration amplitudes at corresponding timestamps in all initial image segments.

[0019] Preferably, the stitching of the extruded image segments comprises: calculating a difference map of overlapping areas of any two extruded image segments, updating the translation parameters of each extruded image segment, and completing the stitching of the two extruded image segments when the average pixel value of the difference map reaches a minimum value.

[0020] Preferably, obtaining the detection result based on the extrusion image includes: dividing the extrusion image into multiple image blocks along the extrusion direction of the copper part, calculating the similarity between any image blocks to construct a similarity matrix; calculating the Euclidean distance between the similarity matrix and the unit matrix, and in response to the Euclidean distance being greater than a preset threshold, the detection result is abnormal quality, otherwise, the detection result is normal quality.

[0021] In response to the Euclidean distance being greater than the preset threshold, it indicates that there are large differences in the image features of the copper parts between the image blocks, and defects such as uneven thickness, surface cracks, and even fractures appear on the surface of the copper parts. At this time, the detection result is abnormal quality, thereby realizing quality detection during the extrusion process of the copper parts.

[0022] Preferably, in response to failure to obtain the extrusion image, an early warning message indicating that the copper extruder has an abnormal operating state is issued.

[0023] If any position point is in a state of large vibration amplitude during the copper extrusion process, there will be no overlapping area between the two extrusion image segments, and splicing will be impossible, that is, the complete extrusion image cannot be obtained, indicating that the copper extruder is in a state of continuous and violent vibration, and the copper extruder is in an abnormal working state.

[0024] The technical solution of this application has the following beneficial technical effects:

[0025] Collect video frames during the extrusion process of copper parts. For any position point in the copper parts, locate the corresponding pixel point coordinates of this position point in each video frame based on the extrusion speed of the copper parts and the acquisition frame rate of the video frames. Intercept the video frames according to the pixel point coordinates to obtain the neighborhood image of this position point in each video frame. Further, calculate the vibration amplitude at each time stamp based on the difference between the neighborhood image and the difference images of two adjacent neighborhood images, and obtain the stable time set of each position point. Use the position point as the initial segment, and continuously expand this initial segment according to the intersection of the stable time sets of the position point and adjacent position points until the stable segment of each position point in the copper parts is obtained. Multiple position points within a stable segment can be in a stable state at the same time stamp. Stitch the neighborhood images of each position point in the stable segment according to the stable time set of the stable segment to obtain the extrusion image segment of the stable segment. The extrusion image segment is the image information of the copper parts in a stable state, which can eliminate the noise generated by vibration in the video frames, thereby improving the accuracy of the extrusion molding detection result. Stitch each extrusion image segment to obtain the extrusion image, and obtain an accurate detection result based on the extrusion image. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flowchart of a method for detecting the extrusion molding of a copper part extrusion machine according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Apparently, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0028] According to a first aspect of the present application, the present application provides a method for detecting the extrusion molding of a copper part extrusion machine. Figure 1 is a flowchart of a method for detecting the extrusion molding of a copper part extrusion machine according to an embodiment of the present application. As Figure 1 shown, the method for detecting the extrusion molding of the copper part extrusion machine includes steps S101 to S104, which are described in detail below.

[0029] S101, collect multiple video frames during the extrusion process of the copper parts, and intercept the neighborhood images of any position point in each video frame according to the extrusion speed; calculate the difference images between any neighborhood image and two adjacent neighborhood images, take the maximum value of the average pixel values in the difference images as the vibration amplitude of the position point at the corresponding time stamp of the neighborhood image, and take the time stamps with vibration amplitudes less than the preset amplitude as the stable times to obtain the stable time sets of each position point.

[0030] In one embodiment, a copper part extruder is used to extrude copper material placed at one end of a die orifice to the other end of the die orifice, so as to extrude the copper material into copper products such as copper wires or copper rods with a preset cross-sectional area. At the same time, at the other end of the die orifice, a traction device will traction the copper wire or copper rod to move at a preset extrusion speed to ensure that the copper wire or copper rod will be continuously extruded at the other end of the die orifice.

[0031] An image acquisition device is deployed to acquire multiple video frames during the copper part extrusion process at a fixed preset frame rate. The pose of the image acquisition device is fixed. Among them, the preset frame rate is 60 frames per second, that is, 60 image frames can be acquired per second. For any position point on the copper product, it moves away from the other end of the die orifice at a fixed extrusion speed. According to the relationship between the extrusion speed and the preset frame rate, the pixel coordinates of any position point on the copper product in each video frame can be located.

[0032] Specifically, the method of intercepting the neighborhood image of any position point in each video frame according to the extrusion speed includes: determining the pixel coordinates of the position point in any video frame according to the extrusion speed, and intercepting the video frame according to the preset number of pixels on both sides adjacent to the pixel coordinates to obtain the neighborhood image of the position point in this video frame. The preset number is 1.

[0033] Among them, when any position point enters the field of view of the image acquisition device, the neighborhood image of the position point can be acquired, and until the position point moves out of the field of view of the image acquisition device, multiple neighborhood images of the position point can be acquired.

[0034] In this way, during the extrusion forming process of the copper part extruder, multiple neighborhood images of any position point on the copper product are acquired, and one neighborhood image corresponds to one timestamp.

[0035] For the position point , the vibration amplitude satisfies the relational expression:

[0036] , , and are the neighborhood images of the position point at the timestamp , the timestamp and the timestamp respectively. represents calculating the average pixel value.

[0037] It can be understood that is the difference image between the neighborhood image at the timestamp and the previous adjacent neighborhood image; is the timestamp The difference map between the neighborhood image and the next adjacent neighborhood image; the larger the average pixel value in the difference map, the more relative motion occurs between the two adjacent neighborhood images. Therefore, the maximum value of the average pixel values in the two difference maps corresponding to one neighborhood image is used as the vibration amplitude of the position point, and the vibration amplitude of the position point at the time stamp corresponding to the neighborhood image is accurately quantified.

[0038] For any position point, if the vibration amplitude at a time stamp is less than the preset amplitude, it means that the position point does not have a large vibration at this time stamp and is in a stable state. This time stamp is a stable moment, where the preset amplitude is 1; thus, all the stable moments of the position point are used as the stable moment set of the position point.

[0039] S102, initialize the initial segment of any position point. In response to the intersection of the stable moment set of the initial segment and the stable moment set of the adjacent position points of the initial segment not being empty, add the adjacent position points to the initial segment until the intersection of the stable moment sets is empty, and obtain the stable segment of the position point. The stable moment set of the initial segment is the intersection of the stable moment sets of each position point within the initial segment.

[0040] In one embodiment, after obtaining the stable moment set of any position point on the copper product, multiple stable segments can be obtained based on the stable moment set of the position point. One stable segment includes at least one stable moment.

[0041] For the position point , the method for obtaining the stable segment of the position point is described in detail. First, initialize the initial segment of the position point . The initial segment includes the position point . At this time, the stable moment set of the initial segment is the stable moment set of the position point . The adjacent position points of the initial segment include the position points adjacent to both sides of the position point , including the position point and the position point . Here, the position point is used as an example for illustration; when the intersection of the stable moment set of the initial segment and the stable moment set of the adjacent position points of the initial segment is not empty, it means that the initial segment and the adjacent position points are both in stable moments at the same time stamp. Therefore, the adjacent position points can be added to the initial segment of the position point to update the initial segment of the position point . The initial segment of the position point includes the position point and the position point . .

[0042] At this time, the set of stable moments of the initial segment is the position points and the position points the intersection of the sets of stable moments. The adjacent position points of the initial segment are the position points and the position points the position points adjacent to both sides of the position segment composed of, including the position points and the position points ; thus, continuously add the adjacent position points of the initial segment to the initial segment until the intersection of the set of stable moments of the initial segment and the set of stable moments of the adjacent position points of the initial segment is empty, indicating that the adjacent position points of the initial segment cannot maintain a stable state with each position point in the initial segment at the same time stamp.

[0043] It can be understood that if the intersection of the set of stable moments of the initial segment and the set of stable moments of the adjacent position points of the initial segment includes 10 time stamps, it means that all the position points in the initial segment and the adjacent position points of the initial segment are in a stable state at these 10 time stamps.

[0044] In this way, multiple stable segments are obtained. A stable segment includes multiple position points, and the multiple position points in a stable segment can be in a stable state at the same time stamp.

[0045] S103, splice the neighborhood images of each position point in the stable segment according to the set of stable moments of the stable segment to obtain the extrusion image segment of the stable segment.

[0046] In one embodiment, obtaining the extrusion image segment of the stable segment includes: obtaining a video frame at any time stamp in the set of stable moments of the stable segment, intercepting the video frame according to the pixel point coordinates of each position point in the stable segment in the video frame to obtain the initial image segment of the stable segment; taking the mean value of all the initial image segments as the extrusion image segment of the stable segment.

[0047] Among them, the set of stable moments of the stable segment includes at least one time stamp. Obtain the pixel point coordinates of each position point in the stable segment in the video frame corresponding to this time stamp, and record the width of the video frame as , and the height is recorded as . After intercepting the video frame corresponding to this time stamp according to the pixel point coordinates, an initial image segment with a width of and a height of is obtained, where is the number of position points in the stable segment; the number of the initial image segments is the same as the number of time stamps in the set of stable moments of the stable segment.

[0048] In another embodiment, since multiple initial image segments corresponding to multiple timestamps can be collected in a stable segment, and there are differences in the vibration amplitudes of each position point in the stable segment at different timestamps, directly taking the mean of all the initial image segments as the extruded image segment ignores the differences in the vibration amplitudes of each position point in the stable segment at different timestamps, making the extruded image segment highly affected by the vibration amplitude and unable to accurately obtain the image information of the copper workpiece in the stable state. Therefore, during the process of calculating the mean of all the initial image segments, the vibration amplitudes of each position point in different initial image segments (i.e., at different timestamps) can be considered.

[0049] Specifically, the step of taking the mean of all the initial image segments as the extruded image segment of the stable segment includes:

[0050] Obtain the pixel values of any position point in each initial image segment to get a pixel value sequence; determine the weighting coefficient of each initial image segment according to the vibration amplitude of the position point at the corresponding timestamp of the initial image segment, where the weighting coefficient is negatively correlated with the vibration amplitude; perform weighted averaging on the pixel value sequence according to the weighting coefficient to obtain the weighted pixel value of the position point, and the weighted pixel values of all the position points in the stable segment constitute the extruded image segment.

[0051] Among them, the weighting coefficient of the position point at the timestamp

[0052] is: where is the vibration amplitude of the position point at the timestamp and is the sum of the vibration amplitudes of the position point

[0053] at the corresponding timestamps of all the initial image segments.

[0054] S104. Stitch all the extruded image segments to obtain an extruded image, and obtain a detection result based on the extruded image.

[0055] In one embodiment, an extruded image segment includes the pixel values of multiple position points in the stable state. After stitching all the extruded image segments, an extruded image can be obtained, and the extruded image includes the pixel values of all the position points on the copper workpiece in the stable state.

[0056] Specifically, the splicing of each extruded image segment includes: calculating the difference map of the overlapping region between any two extruded image segments, and updating the translation parameters of each extruded image segment until the average pixel value of the difference map reaches the minimum value, at which point the splicing of the two extruded image segments is completed.

[0057] Among them, the overlapping region of the two extruded image segments can be accurately located according to the position points included in the extruded image segment. If the area of the overlapping region is equal to 0, it means that the two extruded image segments cannot be spliced. On the contrary, the two extruded image segments can be spliced based on the overlapping region until a complete extruded image is obtained.

[0058] Among them, since the overlapping region has been determined, the translation parameter only includes the up and down translation parameter.

[0059] It can be understood that if any position point is in a state of large vibration amplitude during the copper part extrusion process, there will be no overlapping region between the two extruded image segments, and thus splicing cannot be performed, that is, a complete extruded image cannot be obtained. At this time, it indicates that the copper part extruder is in a continuous and relatively violent vibration, and the copper part extruder is in an abnormal working state, and a warning message of abnormal operation state of the copper part extruder is sent.

[0060] In one embodiment, obtaining the detection result based on the extruded image includes: equally dividing the extruded image into multiple image blocks along the copper part extrusion direction, calculating the similarity between any two image blocks to construct a similarity matrix; calculating the Euclidean distance between the similarity matrix and the identity matrix, and in response to the Euclidean distance being greater than a preset threshold, the detection result is quality abnormality, otherwise, the detection result is quality normal.

[0061] Among them, the identity matrix is a matrix with the same size as the similarity matrix and all values being 1. The size of the similarity matrix is related to the number of image blocks. If the number of image blocks is 5, the size of the similarity matrix is a 5x5 square matrix.

[0062] The preset threshold is 0.5. It can be understood that in response to the Euclidean distance being greater than the preset threshold, it indicates that there are large differences in the image features of the copper parts between the image blocks, and there are defects such as uneven thickness, surface cracks or even fractures on the surface of the copper parts. At this time, the detection result is quality abnormality, realizing quality detection during the copper part extrusion process.

[0063] It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several deformations and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for detecting the extrusion forming of a copper part extruder, characterized in that, The detection method includes: Collect multiple video frames during the copper part extrusion process, and intercept the neighborhood images of any position point in each video frame according to the extrusion speed, where the any position point refers to any position point on the copper product; calculate the difference images between any neighborhood image and the adjacent two neighborhood images, and take the maximum value of the average pixel values in the difference images as the vibration amplitude of the any position point at the corresponding timestamp of the neighborhood image, and take the timestamps with vibration amplitudes less than the preset amplitude as stable moments to obtain the stable moment set of each position point; Initialize the initial segment of any position point, where the initial segment includes the any position point. In response to the intersection of the stable moment set of the initial segment and the stable moment set of the adjacent position points of the initial segment not being empty, add the adjacent position points to the initial segment. In this way, continuously add the adjacent position points of the initial segment to the initial segment until the intersection of the stable moment set of the initial segment and the stable moment set of the adjacent position points of the initial segment is empty, then obtain the stable segment of the position point. The stable moment set of the initial segment is the intersection of the stable moment sets of each position point within the initial segment; Stitch the neighborhood images of each position point in the stable segment according to the stable moment set of the stable segment to obtain the extrusion image segment of the stable segment; Stitch each extrusion image segment to obtain the extrusion image, and obtain the detection result according to the extrusion image; Obtaining the extrusion image segment of the stable segment includes: Obtain the video frame of any timestamp in the stable moment set of the stable segment, and intercept the video frame according to the pixel coordinates of each position point in the stable segment in the video frame to obtain the initial image segment of the stable segment; Take the mean value of all initial image segments as the extrusion image segment of the stable segment; Obtaining the detection result according to the extrusion image includes: Divide the extrusion image into multiple image blocks equally along the copper part extrusion direction, and calculate the similarity between any two image blocks to construct a similarity matrix; Calculate the Euclidean distance between the similarity matrix and the identity matrix. In response to the Euclidean distance being greater than the preset threshold, the detection result is abnormal quality, otherwise, the detection result is normal quality.

2. The extrusion forming detection method of a copper part extruder according to claim 1, characterized in that The intercepting the neighborhood images of any position point in each video frame according to the extrusion speed includes: Determine the pixel coordinates of any position point in any video frame according to the extrusion speed, and intercept the video frame according to the preset number of pixels on both sides of the pixel coordinates to obtain the neighborhood image of the any position point in the video frame.

3. A method for detecting the extrusion forming of a copper part extrusion machine according to claim 1, characterized in that, Position point Timestamp The vibration amplitude is as follows: , , and are the neighborhood images of the position point at timestamp , timestamp and timestamp respectively, and represents calculating the average pixel value.

4. A method for detecting the extrusion forming of a copper part by an extrusion press according to claim 1, characterized in that, The taking the mean value of all initial image segments as the extrusion image segment of the stable segment includes: Obtain the pixel values of any position point in each initial image segment to obtain a pixel value sequence; Determine the weighting coefficient of each initial image segment according to the vibration amplitude of the position point at the corresponding timestamp of the initial image segment, and the weighting coefficient is positively correlated with the vibration amplitude; Perform weighted averaging on the pixel value sequence according to the weighting coefficient to obtain the weighted pixel value of the position point, and the weighted pixel values of all position points in the stable segment constitute the extrusion image segment.

5. A method for detecting the extrusion forming of a copper part extrusion press according to claim 4, characterized in that, Position point at the timestamp weighting factor is: , is the position point at the timestamp of the vibration amplitude, is the position point which is the sum of the vibration amplitudes at the timestamps corresponding to all initial image segments.

6. A method for detecting the extrusion forming of a copper part extrusion machine according to claim 1, characterized in that The stitching each extrusion image segment includes: Calculate the difference image of the overlapping area of any two extrusion image segments, and update the translation parameters of each extrusion image segment until the average pixel value of the difference image reaches the minimum value, then complete the stitching of the two extrusion image segments.

7. A method for detecting the extrusion forming of a copper part extruder according to claim 1, characterized in that, In response to being unable to obtain the extrusion image, issue a warning message about the abnormal operating state of the copper part extruder.

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