Control method and system of automatic stripping and twisting machine

Abstract

The present invention relates to the field of data processing technology, and more specifically, to a control method and system for an automatic wire stripping and twisting machine, the method comprising: obtaining a thickness data set of each historical cutting surface, clustering the thickness data set of the target historical cutting surface, and clustering the data within each obtained cluster again according to the distance size to screen the target cluster, determining the various orientations of the target historical cutting surface with different thicknesses and the thickness values ​​of each orientation based on the target cluster, using the average thickness variation of adjacent historical cutting surfaces at the same orientation to predict the thickness value of the corresponding orientation of the to-be-cut surface, and adjusting the tool pressure of the corresponding orientation according to the thickness prediction value. The present invention can improve the cutting accuracy of the wire casing, prevent the wire casing from being damaged by excessive cutting, and prevent the casing from being incompletely peeled due to insufficient cutting.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and more particularly to a control method and system for an automatic wire stripping and twisting machine. Background Art

[0002] An automatic wire twisting machine is an automated device used for cutting and removing wire and cable jackets and twisting conductors. It can be used in wire processing. Its working principle is to achieve the clamping, cutting, and twisting operations of the wire through a mechanical structure and control system.

[0003] As an upgraded version of the traditional twisting machine, the induction-type automatic twisting machine introduces sensor technology. It can use laser sensors to detect data such as the thickness and diameter of the wire in a non-contact manner, thereby achieving precise processing of the wire. When using the induction-type automatic twisting machine to cut and strip the wire casing, the wire can be placed in the induction-type automatic twisting machine's detection area. The laser sensor built into the detection area then measures the thickness of the wire casing in real time, allowing the cutting depth to be automatically adjusted based on the detected thickness value, ensuring that the wire casing is accurately cut and stripped while avoiding damage to the conductor.

[0004] However, in practice, the thickness of wire jackets can be uneven at different locations due to temperature fluctuations during the manufacturing process. This unevenness limits the ability of laser sensors to measure jacket thickness at a single cross-section. The measurement data from a single or localized location captured by the laser sensor cannot accurately reflect the overall jacket thickness. Therefore, during the cutting and stripping operation, relying solely on the laser sensor's measurement data from a single or localized location can lead to overcutting and damaging the wire, or undercutting and incomplete jacket stripping, compromising wire cutting accuracy. Summary of the Invention

[0005] In order to solve the problem of poor precision when cutting and stripping electric wires, the present invention provides a control method and system for an automatic stripping and twisting machine.

[0006] According to a first aspect of the present invention, a control method for an automatic wire stripping and twisting machine is provided, comprising:

[0007] Obtain the thickness values ​​of the wire casing at multiple positions on each historical cutting surface in the automatic stripping and twisting machine to obtain a thickness data set for each historical cutting surface;

[0008] Clustering the thickness dataset of the selected target historical cutting surface to obtain multiple clusters, and clustering the data in each cluster again according to the distance to obtain the clustering results of each cluster. The cluster with the shortest average distance in the clustering results of each cluster is used as the target cluster, so as to locate the different directions of thickness on the target historical cutting surface based on each target cluster, and the mean value of all data in each target cluster is used as the thickness value of the target historical cutting surface at the corresponding direction;

[0009] The average thickness variation of all adjacent historical cutting surfaces at the same orientation is used to predict the thickness value of the corresponding orientation of the surface to be cut, so as to adjust the tool pressure at the corresponding orientation according to the thickness prediction value of each orientation of the surface to be cut.

[0010] This invention uses a secondary clustering method to accurately locate the thickness of the wire jacket at different locations. By combining this continuous thickness variation, the method predicts the thickness of the surface to be cut at each location. Based on these precise thickness predictions, tool pressure can be adjusted accordingly, effectively avoiding overcutting or incomplete cutting of the wire jacket and significantly improving the accuracy of wire cutting and stripping.

[0011] Preferably, the data in each cluster is clustered again according to the distance, and the clustering results of each cluster are obtained, including:

[0012] The elbow method is used to obtain the optimal number of clusters when clustering the data in each cluster, and the corresponding clusters are clustered according to the optimal number of clusters of each cluster to obtain the clustering results of each cluster.

[0013] The present invention clusters the clusters obtained by the first clustering again based on distance, and can cluster data with similar thickness values ​​and close distances into one category, thereby facilitating the subsequent positioning of locations with larger thickness and locations with smaller thickness.

[0014] Preferably, the thickness dataset of the selected target historical cutting surface is clustered to obtain multiple clusters, including:

[0015] According to the preset number of clusters, the thickness data set of the target historical cutting surface is clustered to obtain the same number of clusters as the preset number of clusters.

[0016] Preferably, the clustering algorithm used when clustering the cluster clusters and the clustering algorithm used when clustering the target historical cutting surface thickness data set are both k-means clustering algorithms.

[0017] Preferably, positioning each position of the target with different thicknesses on the historical cutting surface based on each target cluster includes:

[0018] The area between the two data points with the largest distance in any target cluster on the target historical cutting surface is taken as the area where any target cluster is located on the target historical cutting surface, and is recorded as an orientation of the target historical cutting surface to obtain all orientations of the target historical cutting surface.

[0019] The present invention can accurately locate the positions where the thickness of the wire casing is larger and smaller, so that all the positioned directions can characterize the thickness characteristics of the entire wire casing.

[0020] Preferably, the average thickness variation of all adjacent historical cutting surfaces at the same orientation is used to predict the thickness value of the corresponding orientation of the to-be-cut surface, satisfying the following relationship:

[0021] ;

[0022] Where, The surface to be cut is Predicted thickness values ​​in each direction; The historical cutting surface closest to the cutting surface is in Thickness value in each direction; 、 Respectively historical sections and The historical section is Thickness value in each direction; is the absolute value symbol; is the ordinal number of the surface to be cut.

[0023] The present invention utilizes the characteristic that the thickness of the wire casing has local continuity, and can achieve accurate prediction of the thickness value of the cutting surface.

[0024] Preferably, adjusting the tool pressure at the corresponding position according to the thickness prediction value of each position of the surface to be cut includes:

[0025] The cutting depth at any position of the surface to be cut is calculated. The cutting depth is the product of the predicted thickness value of the surface to be cut at any position and a preset coefficient. The tool pressure at any position is determined based on the cutting depth.

[0026] The present invention can combine the thickness values ​​of each positioned position and adaptively adjust the tool pressure of the corresponding position, thereby avoiding the problems of excessive cutting and incomplete cutting of the wire casing.

[0027] Preferably, the method for obtaining the thickness value of the wire casing at any position on any historical cutting surface includes:

[0028] A laser is used to emit laser light at any position of any historical cutting surface, and the thickness of the wire casing at any position is calculated by measuring the time difference of receiving the reflected light.

[0029] Preferably, all historical cutting surfaces are located between the surface to be cut and the end of the wire, and are within the detection area of ​​the automatic stripping and twisting machine.

[0030] According to a second aspect of the present invention, a control system for an automatic stripping and twisting machine is provided. The system includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the first aspect of the present invention.

[0031] The present invention has the following effects:

[0032] The present invention can accurately locate locations with greater and lesser wire jacket thickness, thereby comprehensively reflecting the overall characteristics of the wire jacket thickness. In this way, the limitations of single or localized measurements due to uneven wire jacket thickness can be effectively avoided. Furthermore, the present invention can adaptively adjust the tool pressure based on the thickness values ​​at each location, avoiding damage to the wire due to excessive cutting and the inability to completely peel the wire jacket due to incomplete cutting, thereby improving the cutting accuracy of the wire jacket. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an illustrative and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0034] Figure 1 This is a schematic flow chart of the steps of a control method for an automatic wire stripping and twisting machine according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the scope of protection of the present invention.

[0036] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0037] Reference Figure 1 A control method for an automatic wire stripping and twisting machine includes steps S1 to S4, specifically as follows:

[0038] S1: Obtain the thickness values ​​of the wire casing at multiple positions on each historical cutting surface in the automatic stripping and twisting machine to obtain a thickness dataset of each historical cutting surface.

[0039] In an exemplary embodiment of the present invention, all historical cutting surfaces are located between the surface to be cut and the end of the wire and are within the detection area of ​​the automatic stripping and twisting machine.

[0040] The term "wire end" refers to the end inserted into the automatic wire stripping and twisting machine; the "to-be-cut" surface refers to the area of ​​the wire where the wire casing needs to be cut off at the current moment; and the "historical cutting" surface refers to the area of ​​the wire where the wire casing needed to be cut off before the current moment. Both the "to-be-cut" surface and the "historical cutting" surface represent areas of the wire with a fixed unit length, and this embodiment does not specifically limit the fixed unit length.

[0041] It should be noted that since the detection area of ​​the automatic peeling and twisting machine is relatively short, the present invention uses the thickness data of all historical cutting surfaces within the detection area of ​​the automatic peeling and twisting machine that are simultaneously in the detection area with the surface to be cut as the basic data for subsequent analysis.

[0042] In an exemplary embodiment of the present invention, the determination of the wire jacket thickness at any location on any historical cutting surface can be achieved by the following steps:

[0043] A laser is used to emit laser light at any position of any historical cutting surface, and the thickness of the wire casing at any position is calculated by measuring the time difference of receiving the reflected light.

[0044] It should be noted that in the process of measuring the thickness of the wire casing, the laser will receive two signals, namely the signal of the light signal reflected from the surface of the wire casing and the signal of the light signal passing through the casing and reflected at the junction of the casing and the inner layer. Since the two surfaces are the plastic casing of the wire and the copper wire conductor inside the wire, the time difference between the two returns is twice that of the laser passing through the plastic casing of the conductor. Therefore, the present invention utilizes this feature to calculate the thickness value of the wire casing at any position.

[0045] Specifically, the thickness of the wire casing at any position on any historical cutting surface satisfies the following relationship:

[0046] ;

[0047] Where, is the thickness of the wire casing at any position on any historical cutting surface; is the speed of light in vacuum, =3× m / s; The dielectric coefficient is related to the material of the object to be cut. For example, when the object to be cut is plastic, =1.5, it should be noted that, The propagation speed of light signals in a vacuum is called the speed of light propagation. However, due to the presence of the medium, the propagation speed of light will be slowed down. Therefore, the dielectric coefficient needs to be set. It is the time difference between the light signal reflected from the shell surface and reflected from the shell-inner layer interface.

[0048] Among them, since the light signal needs to go back and forth twice (from the surface to the junction and then from the junction back to the surface), a This coefficient.

[0049] Furthermore, the thickness values ​​of the wire casing at multiple positions on each historical cutting surface can be calculated using a thickness calculation formula, thereby obtaining a thickness data set for each historical cutting surface.

[0050] S2: Clustering the thickness dataset of the selected target historical cutting surface to obtain multiple clusters, and clustering the data in each cluster again according to the distance size to obtain the clustering results of each cluster.

[0051] It's important to note that when sheathing wire conductors (making casings), the sheathing materials (such as PVC and PE) can easily become unevenly mixed, resulting in inconsistent thickness during extrusion. Consequently, the thickness varies across the same cross-section. Using a single sheath thickness reference cannot fully reflect the sheath thickness across the entire area, and can easily damage the sheath during cutting. Therefore, the present invention uses clustering to locate areas of greater and lesser thickness.

[0052] It should be further explained that the thickness data set of the selected target historical cutting surface is clustered according to data size in order to group thickness values ​​with similar values ​​into one category; the data within each cluster is clustered again according to distance size in order to further divide the clusters composed of thickness values ​​with similar values ​​but potentially far apart into multiple data clusters with similar values ​​and close location distances, so as to accurately locate areas with larger and smaller thicknesses.

[0053] In an exemplary embodiment of the present invention, the clustering algorithm used when clustering the cluster clusters and the clustering algorithm used when clustering the target historical cutting surface thickness dataset are both k-means clustering algorithms.

[0054] Optionally, other clustering algorithms, such as the DBSCAN clustering algorithm, may also be used for clustering.

[0055] In an exemplary embodiment of the present invention, clustering of the thickness dataset of the target historical cutting surface can be achieved by the following steps:

[0056] According to the preset number of clusters, the thickness data set of the target historical cutting surface is clustered to obtain the same number of clusters as the preset number of clusters.

[0057] Optionally, the preset number of clusters can be set to 4, and then the k-means clustering algorithm is used to cluster the thickness data set of the target historical cutting surface, so that thickness values ​​with similar values ​​can be clustered into one category, and finally 4 clusters are obtained. This embodiment does not specifically limit the value of the preset number of clusters.

[0058] It should be noted that the process of clustering using the k-means clustering algorithm is a prior art and will not be described in detail in this embodiment.

[0059] In an exemplary embodiment of the present invention, the following steps can be performed to cluster the data in the clusters obtained by the first clustering and clustering them again according to the distance:

[0060] The elbow method is used to obtain the optimal number of clusters when clustering the data in each cluster, and the corresponding clusters are clustered according to the optimal number of clusters of each cluster to obtain the clustering results of each cluster.

[0061] Specifically, to determine the optimal number of clusters, the clustering algorithm can be run for each cluster with different cluster numbers k (ranging from 1 to a maximum value) and the sum of squared errors (SSE) corresponding to each k value can be calculated. A curve of the SSE versus k value is then plotted, and the "elbow" location where the rate of SSE decreases significantly is observed. The k value corresponding to this location is used as the optimal number of clusters for clustering the cluster. This is the process of obtaining the optimal number of clusters using the elbow method. The calculation of the sum of squared errors is conventional and will not be described in detail in this embodiment.

[0062] Furthermore, after determining the optimal number of clusters for each cluster obtained by the first clustering, k-means clustering can be performed on the corresponding clusters based on each optimal number of clusters, thereby obtaining clustering results for each cluster.

[0063] S3: The cluster with the shortest average distance in the clustering results of each cluster is used as the target cluster, so as to locate the different directions of thickness on the target historical cutting surface based on each target cluster, and the mean of all data in each target cluster is used as the thickness value of the target historical cutting surface at the corresponding direction.

[0064] It should be noted that since each clustering result contains multiple clusters, directly locating areas (i.e., locations) with greater or lesser thickness on the target's historical cutting surface based on the clustering results of each cluster will result in excessive locations, making subsequent operations more difficult. Therefore, the present invention selects a target cluster from the clustering results of each cluster, and then locates areas with greater or lesser thickness on the target's historical cutting surface based on the selected target cluster.

[0065] Optionally, the cluster with the shortest average distance in the clustering results of each cluster can be used as the target cluster, thereby ensuring that the target cluster selected from the clustering results of any cluster can best represent the thickness characteristics of any cluster.

[0066] In an exemplary embodiment of the present invention, the determination of the positions of different thicknesses on the target historical cutting surface can be achieved by the following steps:

[0067] The area between the two data points with the largest distance in any target cluster on the target historical cutting surface is taken as the area where any target cluster is located on the target historical cutting surface, and is recorded as an orientation of the target historical cutting surface to obtain all orientations of the target historical cutting surface.

[0068] Optionally, after determining all orientations of the target historical cutting surface, the mean of all data in each target cluster can be used as the thickness value of the corresponding orientation, so that the thickness value of each orientation of the target historical cutting surface can be obtained, and then the thickness value of all historical cutting surfaces in each orientation can be determined.

[0069] It should be noted that, since the thickness data of each orientation has not been completely detected, the present invention uses the mean of all data in each target cluster as the thickness value of the corresponding orientation.

[0070] S4: using the average thickness variation of all adjacent historical cutting surfaces at the same orientation, predict the thickness value of the corresponding orientation of the surface to be cut, so as to adjust the tool pressure of the corresponding orientation according to the thickness prediction value of each orientation of the surface to be cut.

[0071] It should be noted that during the wire jacket production process, if the extruder heating temperature is too high, it can cause plastic degradation and poor fluidity, resulting in uneven thickness of the jacket over a certain distance in a certain direction. This means that the thickness of jackets in closely spaced areas at the same direction exhibits certain similarities. Therefore, based on this characteristic, the present invention uses the average thickness variation of all adjacent historically cut surfaces at the same direction to predict the thickness value of the corresponding direction of the surface to be cut.

[0072] Specifically, the predicted thickness value of any direction of the cutting surface satisfies the following relationship:

[0073] ;

[0074] Where, The surface to be cut is Predicted thickness values ​​in each direction; The historical cutting surface closest to the cutting surface is in Thickness value in each direction; 、 Respectively historical sections and The historical section is Thickness value in each direction; is the absolute value symbol; is the ordinal number of the surface to be cut.

[0075] in, Reflects all adjacent historical cutting surfaces in the The average thickness change in the direction, when the value is positive, it means The thickness of the wire casing in the direction of the first direction gradually increases along the direction close to the cutting surface; if the value is negative, it means that the first The thickness of the wire casing in each direction gradually decreases as it approaches the surface to be cut; therefore, by combining the average thickness change and the thickness data of the previous cutting surface of the surface to be cut, the thickness value of the surface to be cut in each direction can be accurately predicted.

[0076] In an exemplary embodiment of the present invention, the tool pressure can be adjusted by the following steps:

[0077] The cutting depth at any position of the surface to be cut is calculated. The cutting depth is the product of the predicted thickness value of the surface to be cut at any position and a preset coefficient. The tool pressure at any position is determined based on the cutting depth.

[0078] Specifically, the cutting depth at any direction of the surface to be cut satisfies the following relationship:

[0079] ;

[0080] Where, The first Cutting depth in each direction; The surface to be cut is Predicted thickness values ​​in each direction; is the preset coefficient. In this embodiment =0.85. It should be noted that when determining the cutting depth, The value of is the size commonly used in this field.

[0081] Furthermore, the cutting depth determination method can be used to calculate the cutting depth at each position of the surface to be cut, so that the tool pressure at the corresponding position can be determined based on the determined cutting depth at each position.

[0082] Specifically, the tool pressure at any position on the surface to be cut satisfies the following relationship:

[0083] ;

[0084] Where, The first Tool pressure in all directions; The first Cutting depth in each direction; is the machine fixed coefficient; is the contact radius of the circular tool, where Reflects the contact area of ​​the circular tool.

[0085] It should be noted that, after determining the thickness value of any cutting surface, the process of adjusting the tool pressure based on the thickness value is a prior art.

[0086] Furthermore, after determining the tool pressure at each position of the surface to be cut, the wire casing at the corresponding position can be cut and peeled off based on the determined tool pressure, thereby avoiding excessive cutting of the surface to be cut and preventing damage to the wire; at the same time, it can also avoid insufficient cutting and ensure that the wire casing at the surface to be cut can be completely peeled off.

[0087] The present invention also provides a control system for an automatic stripping and twisting machine. The system includes a memory and a processor, and a computer program is stored in the memory. The computer program integrates the functions of a control method for an automatic stripping and twisting machine. When the computer program is executed, the control method for an automatic stripping and twisting machine can improve the cutting accuracy of the wire casing, prevent excessive cutting of the wire casing from damaging the wire, and prevent insufficient cutting from causing incomplete casing stripping.

[0088] In the description of this specification, "multiple" and "several" mean at least two, such as two, three or more, etc., unless otherwise clearly defined.

[0089] While several embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Numerous modifications, variations, and alternatives will occur to those skilled in the art without departing from the concept and spirit of the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein may be employed in practicing the present invention.

Claims

1. A control method for an automatic wire stripping and twisting machine, characterized in that: include: Obtain the thickness values ​​of the wire casing at multiple positions on each historical cutting surface in the automatic stripping and twisting machine to obtain a thickness data set for each historical cutting surface; Clustering the thickness dataset of the selected target historical cutting surface to obtain multiple clusters, and clustering the data in each cluster again according to the distance to obtain the clustering results of each cluster. The cluster with the shortest average distance in the clustering results of each cluster is used as the target cluster, so as to locate the different directions of thickness on the target historical cutting surface based on each target cluster, and the mean value of all data in each target cluster is used as the thickness value of the target historical cutting surface at the corresponding direction; Locating various orientations of different thicknesses on the target historical cutting surface based on each target cluster, including: taking the area between the two data points with the largest distance in any target cluster on the target historical cutting surface as the area where the any target cluster is located on the target historical cutting surface, and recording it as an orientation of the target historical cutting surface, so as to obtain all orientations of the target historical cutting surface; The average thickness variation of all adjacent historical cutting surfaces in the same direction is used to predict the thickness value of the corresponding direction of the surface to be cut. According to the thickness prediction value of each direction of the surface to be cut, the tool pressure of the corresponding direction is adjusted. The average thickness variation of all adjacent historical cutting surfaces in the same direction is used to predict the thickness value of the corresponding direction of the surface to be cut, satisfying the following: ； The surface to be cut is Predicted thickness values ​​in each direction; The historical cutting surface closest to the cutting surface is in Thickness value in each direction; 、 Respectively historical sections and The historical section is Thickness value in each direction; is the absolute value symbol; is the ordinal number of the surface to be cut; According to the thickness prediction value of each orientation of the surface to be cut, the tool pressure in the corresponding orientation is adjusted, including: calculating the cutting depth of any orientation of the surface to be cut, the cutting depth being the product of the thickness prediction value of the surface to be cut at that orientation and a preset coefficient, so as to determine the tool pressure at that orientation based on the cutting depth.

2. The control method of an automatic wire stripping and twisting machine according to claim 1, characterized in that: The data in each cluster is clustered again according to the distance to obtain the clustering results of each cluster, including: The elbow method is used to obtain the optimal number of clusters when clustering the data in each cluster, and the corresponding clusters are clustered according to the optimal number of clusters of each cluster to obtain the clustering results of each cluster.

3. The control method of an automatic wire stripping and twisting machine according to claim 1, characterized in that: The thickness dataset of the selected target historical cutting surface is clustered to obtain multiple clusters, including: According to a preset number of clusters, the thickness data set of the target historical cutting surface is clustered to obtain a number of clusters that is the same as the preset number of clusters.

4. The control method of an automatic wire stripping and twisting machine according to claim 2 or 3, characterized in that: The clustering algorithm used when clustering the cluster clusters and the clustering algorithm used when clustering the thickness dataset of the target historical cutting surface are both the k-means clustering algorithm.

5. The control method of an automatic wire stripping and twisting machine according to claim 1, characterized in that: A method for obtaining the thickness value of the wire casing at any position on any historical cutting surface includes: A laser is used to emit laser light at any position of any historical cutting surface, and the thickness of the wire casing at any position is calculated by measuring the time difference of receiving the reflected light.

6. The control method of an automatic wire stripping and twisting machine according to claim 1, characterized in that: All historical cutting surfaces are located between the surface to be cut and the end of the wire and are within the detection area of ​​the automatic stripping and twisting machine.

7. A control system for an automatic wire stripping and twisting machine, characterized in that: The control system of the automatic stripping and twisting machine includes a memory and a processor, wherein a computer program is stored in the memory, and the processor executes the computer program to implement the steps of the control method of the automatic stripping and twisting machine as described in any one of claims 1-6.

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