Vacuum adsorption control method and system applied to automatic cutting bed and electronic equipment

Abstract

The application provides a vacuum adsorption control method, system and electronic equipment applied to an automatic cutting bed. The method comprises the following steps: obtaining the distribution density and aperture of adsorption air holes, the single-layer thickness, total layer number, type and count of a fabric to be cut, and a cutting path and a cutting tool control parameter; inputting the obtained information into a vacuum adsorption force prediction model to obtain a first vacuum adsorption force and a second vacuum adsorption force; when a cutting task is performed, each adsorption air hole in the outermost circle of adsorption air holes in an adsorption area provides the first vacuum adsorption force, and each adsorption air hole in an adsorption air hole array provides the second vacuum adsorption force, wherein the adsorption air hole array comprises adsorption air hole sub-arrays covered by a contour defined by the cutting path and each adsorption air hole adjacent to the adsorption air hole sub-arrays. The system comprises various functional modules corresponding to the implementation of the above steps. The electronic equipment: when a processor executes a computer program stored in a memory, the method is realized. According to the application, the problem that the energy consumption of the vacuum adsorption operation of the fabric applied to the automatic cutting bed is large can be solved.

Description

Technical Field

[0001] This invention belongs to the field of vacuum adsorption control for automatic cutting beds, and more specifically, relates to a vacuum adsorption control method, system and electronic equipment applied to automatic cutting beds. Background Technology

[0002] An automatic cutting table is an automated device used to cut fabric into pieces. It mainly includes a cutting table, a cutting head, an operation panel, a vacuum adsorption device, and a picking table. Within the adsorption area of ​​the cutting table, multiple adsorption pores are arranged at a predetermined density. The air outlets below these pores are connected to the vacuum adsorption device via multiple conduits. During the cutting process, the vacuum adsorption device extracts air from between the multiple layers of fabric stacked in the adsorption area and the airtight plastic film covering the fabric. Atmospheric pressure compresses the fabric, causing it to adhere tightly to the cutting table. This compressed fabric, relative to the cutting table and between the fabric layers, prevents slippage or displacement due to the shearing action of the cutting blades on the cutting head during cutting, thus ensuring the accuracy of the cut pieces.

[0003] Currently, during the cutting process, in order to reduce the energy consumption of vacuum adsorption operations while ensuring the adsorption effect on the fabric, the vacuum adsorption force required by the adsorption pores is usually determined based on the specific characteristics of the fabric. For example, when the fabric is heavy and / or has high roughness, the adsorption pores only need to provide a lower vacuum adsorption force, while when the fabric is light and / or has low roughness, the adsorption pores need to provide a higher vacuum adsorption force. After determining the required vacuum adsorption force, the vacuum adsorption device is adjusted to the corresponding power. Under the action of the vacuum adsorption device, multiple adsorption pores in the adsorption zone simultaneously provide the corresponding vacuum adsorption force.

[0004] However, the applicant found that the aforementioned vacuum adsorption method for fabrics applied to automatic cutting beds could not optimize the energy consumption of the vacuum adsorption operation, and the method needs further improvement. Summary of the Invention

[0005] In view of this, the present invention provides a vacuum adsorption control method, system and electronic device for use in automatic cutting beds.

[0006] According to a first aspect of the present invention, a vacuum adsorption control method for use in an automatic cutting bed is provided, wherein a plurality of adsorption pores are distributed in the adsorption zone of the automatic cutting bed according to a predetermined density, and the vacuum adsorption control method includes the following steps:

[0007] Obtain target information, which includes the distribution density and pore size of adsorption pores, the single-layer thickness, total number of layers, type and thread count of the fabric to be cut, as well as the cutting path and cutting blade control parameters.

[0008] The target information is input into a pre-constructed vacuum adsorption force prediction model to obtain the first vacuum adsorption force and the second vacuum adsorption force.

[0009] During the cutting process, the vacuum adsorption device is controlled so that each adsorption pore in the outermost ring of adsorption pores in the adsorption zone provides the first vacuum adsorption force, and each adsorption pore in the corresponding adsorption pore array provides the second vacuum adsorption force.

[0010] The adsorption pore array includes an adsorption pore subarray covered by the contour defined by the cutting path and individual adsorption pores adjacent to the adsorption pore array.

[0011] Alternatively, the vacuum adsorption force prediction model is established based on a neural network model;

[0012] The method for obtaining the vacuum adsorption force prediction model includes:

[0013] Select target information, first vacuum adsorption force and second vacuum adsorption force corresponding to multiple cutting tasks that have not experienced fabric shift from the production database;

[0014] The target information is used as a training sample, and the corresponding first vacuum adsorption force and second vacuum adsorption force are used as labels.

[0015] The neural network model is trained based on the training samples and the labels to obtain the vacuum adsorption force prediction model.

[0016] Optionally, the vacuum adsorption control method further includes:

[0017] During the trimming process, the average value M1 and variance N1 of the actual vacuum adsorption force provided by the outermost adsorption pores are detected. If the average value M1 is lower than the first vacuum adsorption force by 20% or the variance N1 reaches the predetermined first variance upper limit threshold, the trimming process is suspended and an alarm is triggered.

[0018] Optionally, the vacuum adsorption control method further includes:

[0019] If the average value M1 is less than 20% of the magnitude of the first vacuum adsorption force and the variance N1 does not reach the first upper limit threshold of variance, then the average value M2 and the variance N2 of the actual vacuum adsorption force provided by the adsorption pore array are obtained. If the average value M2 is less than 20% of the magnitude of the second vacuum adsorption force or the variance N2 reaches the predetermined second upper limit threshold of variance, then the trimming task is suspended and an alarm is triggered.

[0020] According to a second aspect of the present invention, a vacuum adsorption control system for an automatic cutting bed is provided, wherein a plurality of adsorption pores are distributed in the adsorption zone of the automatic cutting bed according to a predetermined density, and the vacuum adsorption control system includes the following functional modules:

[0021] The target information acquisition module is used to acquire target information, which includes the distribution density and pore size of the adsorption pores, the single-layer thickness, total number of layers, type and thread count of the fabric to be cut, as well as the cutting path and cutting blade control parameters.

[0022] The vacuum adsorption force prediction module is used to input the target information into a pre-constructed vacuum adsorption force prediction model to obtain the first vacuum adsorption force and the second vacuum adsorption force.

[0023] The vacuum adsorption control module is used to control the vacuum adsorption device during the cutting process so that each adsorption pore in the outermost ring of adsorption pores in the adsorption zone provides the first vacuum adsorption force, and each adsorption pore in the corresponding adsorption pore array provides the second vacuum adsorption force.

[0024] The adsorption pore array includes an adsorption pore subarray covered by the contour defined by the cutting path and individual adsorption pores adjacent to the adsorption pore array.

[0025] Preferably, the vacuum adsorption force prediction model is based on a neural network model;

[0026] The method for obtaining the vacuum adsorption force prediction model includes:

[0027] Select target information, first vacuum adsorption force and second vacuum adsorption force corresponding to multiple cutting tasks that have not experienced fabric shift from the production database;

[0028] The target information is used as a training sample, and the corresponding first vacuum adsorption force and second vacuum adsorption force are used as labels.

[0029] The neural network model is trained based on the training samples and the labels to obtain the vacuum adsorption force prediction model.

[0030] Preferably, the vacuum adsorption control module is also used for:

[0031] During the trimming process, the average value M1 and variance N1 of the actual vacuum adsorption force provided by the outermost adsorption pores are detected. If the average value M1 is lower than the first vacuum adsorption force by 20% or the variance N1 reaches the predetermined first variance upper limit threshold, the trimming process is suspended and an alarm is triggered.

[0032] If the average value M1 is less than 20% of the magnitude of the first vacuum adsorption force and the variance N1 does not reach the first upper limit threshold of variance, then the average value M2 and the variance N2 of the actual vacuum adsorption force provided by the adsorption pore array are obtained. If the average value M2 is less than 20% of the magnitude of the second vacuum adsorption force or the variance N2 reaches the predetermined second upper limit threshold of variance, then the trimming task is suspended and an alarm is triggered.

[0033] According to a third aspect of the present invention, an electronic device is provided, comprising a processor and a memory, wherein the processor executes a computer program stored in the memory to implement any of the above-described vacuum adsorption control methods applied to an automatic cutting bed.

[0034] The beneficial effects of this invention are as follows:

[0035] The vacuum adsorption control method of the present invention, applied to an automatic cutting bed, first acquires the distribution density and pore size of the adsorption pores, the single-layer thickness, total number of layers, type, and thread count of the fabric to be cut, as well as the cutting path and cutting blade control parameters before performing the cutting task. Then, the acquired information is input into a pre-constructed vacuum adsorption force prediction model to obtain a first vacuum adsorption force and a second vacuum adsorption force. During the cutting task, each adsorption pore in the outermost ring of the adsorption zone provides the first vacuum adsorption force to focus on adsorbing the edge areas of the fabric, while each adsorption pore in the adsorption pore array, i.e., each adsorption pore in the area of ​​the adsorption zone corresponding to the cut piece, provides the second vacuum adsorption force to focus on adsorbing the area of ​​the fabric to be cut.

[0036] The first and second vacuum adsorption forces mentioned above were obtained by predicting using a vacuum adsorption force prediction model, which was trained based on relevant data from a production database. By controlling the vacuum adsorption device so that each adsorption pore in the outermost ring of adsorption pores in the adsorption zone provides a first vacuum adsorption force and each adsorption pore in the corresponding adsorption pore array provides a second vacuum adsorption force, the energy consumption of existing vacuum adsorption operations for fabrics applied to automatic cutting beds can be reduced while ensuring the adsorption effect on the fabric. The reason is that in existing vacuum adsorption methods for fabrics applied to automatic cutting beds, all adsorption pores in the adsorption zone provide a predetermined vacuum adsorption force. However, in the vacuum adsorption control method for automatic cutting beds of the present invention, vacuum adsorption force is provided only by the outermost ring of adsorption pores in the adsorption zone and each adsorption pore in the area of ​​the adsorption zone corresponding to the cut piece. Although the actual vacuum adsorption force provided by each adsorption pore used to provide vacuum adsorption force is slightly higher, since other adsorption pores in the adsorption zone do not need to provide vacuum adsorption force, the output power of the vacuum adsorption device is lower than the output power of the vacuum adsorption device in existing vacuum adsorption methods for fabrics applied to automatic cutting beds.

[0037] As can be seen from the above, the vacuum adsorption control method of the present invention applied to automatic cutting beds can effectively solve the problem of high energy consumption in the existing vacuum adsorption operation of fabrics applied to automatic cutting beds.

[0038] The vacuum adsorption control system and electronic equipment of the present invention applied to an automatic cutting bed belong to the same general inventive concept as the vacuum adsorption control method applied to an automatic cutting bed described above, and have at least the same beneficial effects as the vacuum adsorption control method applied to an automatic cutting bed described above, the beneficial effects of which will not be repeated here.

[0039] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0040] The present invention can be better understood by referring to the following description taken in conjunction with the accompanying drawings, in which the same or similar reference numerals are used throughout the drawings to denote the same or similar parts.

[0041] Figure 1 A flowchart illustrating the implementation of a vacuum adsorption control method for an automatic cutting bed according to an embodiment of the present invention is shown.

[0042] Figure 2 A structural block diagram of a vacuum adsorption control system for an automatic cutting bed, according to an embodiment of the present invention, is shown. Detailed Implementation

[0043] To enable those skilled in the art to more fully understand the technical solutions of the present invention, exemplary embodiments of the present invention will be described more comprehensively and in detail below with reference to the accompanying drawings. Obviously, the one or more embodiments of the present invention described below are merely one or more specific ways to implement the technical solutions of the present invention, and are not exhaustive. It should be understood that other ways belonging to a general inventive concept can be used to implement the technical solutions of the present invention, and should not be limited to the embodiments described exemplary. Based on one or more embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0044] Example: Figure 1 A flowchart illustrating the implementation of a vacuum adsorption control method for an automatic cutting bed according to an embodiment of the present invention is shown. (Refer to...) Figure 1 The vacuum adsorption control method of this invention is applied to an automatic cutting bed, wherein the adsorption zone of the automatic cutting bed has multiple adsorption pores distributed at a predetermined density.

[0045] The vacuum adsorption control method for automatic cutting beds according to embodiments of the present invention includes the following steps:

[0046] Step S100: Obtain target information, which includes the distribution density and pore size of adsorption pores, the single-layer thickness, total number of layers, type and thread count of the fabric to be cut, as well as the cutting path and cutting blade control parameters.

[0047] Step S200: Input the target information into the pre-constructed vacuum adsorption force prediction model to obtain the first vacuum adsorption force and the second vacuum adsorption force;

[0048] Step S300: During the cutting task, the vacuum adsorption device is controlled to provide a first vacuum adsorption force to each adsorption pore in the outermost ring of adsorption pores in the adsorption zone, and to provide a second vacuum adsorption force to each adsorption pore in the corresponding adsorption pore array.

[0049] The adsorption pore array includes an adsorption pore subarray covered by a contour defined by a trimmed path, and individual adsorption pores adjacent to the adsorption pore subarray.

[0050] Specifically, in this embodiment of the invention, the type of fabric refers to the material of the fabric, such as cotton, linen, silk, wool, chemical fiber, blended fabric, and modal.

[0051] Specifically, in this embodiment of the invention, the adsorption pore sub-array is an array composed of adsorption pores completely covered by the contour defined by the trimmed path and adsorption pores partially obscured. Each adsorption pore adjacent to the adsorption pore sub-array forms an annular pore array surrounding the adsorption pore sub-array, and there are no other adsorption pores between the annular pore array and the adsorption pore sub-array.

[0052] Furthermore, in step S200 of this embodiment of the invention, the vacuum adsorption force prediction model is established based on a neural network model, and the method for obtaining the vacuum adsorption force prediction model includes:

[0053] Select target information, first vacuum adsorption force and second vacuum adsorption force corresponding to multiple cutting tasks that have not experienced fabric shift from the production database;

[0054] The target information is used as training samples, and the corresponding first vacuum adsorption force and second vacuum adsorption force are used as labels.

[0055] The neural network model is trained based on training samples and labels to obtain a vacuum adsorption force prediction model.

[0056] Specifically, in this embodiment of the invention, after inputting the target information into the vacuum adsorption force prediction model, the predicted first vacuum adsorption force and second vacuum adsorption force can be obtained; when the vacuum adsorption device is controlled so that each adsorption pore in the outermost ring of adsorption pores in the adsorption zone provides the first vacuum adsorption force and each adsorption pore in the corresponding adsorption pore array provides the second vacuum adsorption force, the compacted fabric will not slip or shift relative to the cutting table, and the fabric layers will not slip or shift due to the shearing action of the cutting blade on the cutting head during cutting, thereby ensuring the accuracy of the cut pieces.

[0057] Furthermore, the vacuum adsorption control method for automatic cutting beds according to embodiments of the present invention further includes:

[0058] During the trimming process, the average value M1 and variance N1 of the actual vacuum adsorption force provided by the outermost adsorption pores are detected. If the average value M1 is 20% lower than the first vacuum adsorption force or the variance N1 reaches the predetermined first variance upper limit threshold, the trimming process is suspended and an alarm is triggered.

[0059] Furthermore, the vacuum adsorption control method for automatic cutting beds according to embodiments of the present invention further includes:

[0060] If the average value M1 is less than 20% of the first vacuum adsorption force and the variance N1 does not reach the first upper limit threshold of variance, then the average value M2 and variance N2 of the actual vacuum adsorption force provided by the adsorption pore array are obtained. If the average value M2 is less than 20% of the second vacuum adsorption force or the variance N2 reaches the predetermined second upper limit threshold of variance, then the trimming task is suspended and an alarm is triggered.

[0061] Specifically, in this embodiment of the invention, on the one hand, the average value M1 and variance N1 of the actual vacuum adsorption force provided by the outermost adsorption pores are used to evaluate whether the actual vacuum adsorption force provided by the outermost adsorption pores meets expectations. If the average value M1 is 20% lower than the first vacuum adsorption force or the variance N1 reaches the first variance upper limit threshold, it indicates that the actual vacuum adsorption force provided by the outermost adsorption pores does not meet expectations, and the trimming task needs to be suspended and an alarm needs to be triggered. On the other hand, the average value M2 and variance N2 of the actual vacuum adsorption force provided by the adsorption pore array are used to evaluate whether the actual vacuum adsorption force provided by the adsorption pore array meets expectations. If the average value M2 is 20% lower than the second vacuum adsorption force or the variance N2 reaches the second variance upper limit threshold, it indicates that the actual vacuum adsorption force provided by the adsorption pore array does not meet expectations, and the trimming task needs to be suspended and an alarm needs to be triggered.

[0062] Accordingly, based on the vacuum adsorption control method applied to an automatic cutting bed in the embodiments of the present invention, the embodiments of the present invention also propose a vacuum adsorption control system applied to an automatic cutting bed.

[0063] Figure 2 A structural block diagram of a vacuum adsorption control system applied to an automatic cutting bed according to an embodiment of the present invention is shown. (Refer to...) Figure 2 The vacuum adsorption control system of this invention is applied to an automatic cutting bed, wherein the adsorption zone of the automatic cutting bed has multiple adsorption pores distributed at a predetermined density.

[0064] The vacuum adsorption control system for an automatic cutting bed according to embodiments of the present invention includes the following functional modules:

[0065] The target information acquisition module is used to acquire target information, including the distribution density and pore size of adsorption pores, the single-layer thickness, total number of layers, type and thread count of the fabric to be cut, as well as the cutting path and cutting blade control parameters.

[0066] The vacuum adsorption force prediction module is used to input target information into a pre-constructed vacuum adsorption force prediction model to obtain the first vacuum adsorption force and the second vacuum adsorption force.

[0067] The vacuum adsorption control module is used to control the vacuum adsorption device during the cutting process so that each adsorption pore in the outermost ring of adsorption pores in the adsorption zone provides a first vacuum adsorption force, and each adsorption pore in the corresponding adsorption pore array provides a second vacuum adsorption force.

[0068] The adsorption pore array includes an adsorption pore subarray covered by a contour defined by a trimmed path, and individual adsorption pores adjacent to the adsorption pore subarray.

[0069] Accordingly, based on the vacuum adsorption control method for automatic cutting beds in the embodiments of the present invention, the embodiments of the present invention also propose an electronic device, which includes a processor and a memory. When the processor executes the computer program stored in the memory, it implements the vacuum adsorption control method for automatic cutting beds in the embodiments of the present invention.

[0070] While one or more embodiments of the present invention have been described above, those skilled in the art will recognize that the present invention can be implemented in any other form without departing from its spirit and scope. Therefore, the embodiments described above are illustrative and not restrictive, and many modifications and substitutions will be apparent to those skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. A vacuum adsorption control method applied to an automatic cutting bed, wherein the adsorption zone of the automatic cutting bed has a plurality of adsorption pores distributed at a predetermined density, characterized in that, The vacuum adsorption control method includes: Obtain target information, which includes the distribution density and pore size of adsorption pores, the single-layer thickness, total number of layers, type and thread count of the fabric to be cut, as well as the cutting path and cutting blade control parameters. The target information is input into a pre-constructed vacuum adsorption force prediction model to obtain the first vacuum adsorption force and the second vacuum adsorption force. During the cutting process, the vacuum adsorption device is controlled so that each adsorption pore in the outermost ring of adsorption pores in the adsorption zone provides the first vacuum adsorption force, and each adsorption pore in the corresponding adsorption pore array provides the second vacuum adsorption force. The adsorption pore array includes an adsorption pore sub-array covered by the contour defined by the cutting path and individual adsorption pores adjacent to the adsorption pore array. The vacuum adsorption control method further includes: During the trimming process, the average value M1 and variance N1 of the actual vacuum adsorption force provided by the outermost adsorption pores are detected. If the average value M1 is lower than the first vacuum adsorption force by 20% or the variance N1 reaches the predetermined first variance upper limit threshold, the trimming process is suspended and an alarm is triggered. If the average value M1 is less than 20% of the magnitude of the first vacuum adsorption force and the variance N1 does not reach the first upper limit threshold of variance, then the average value M2 and the variance N2 of the actual vacuum adsorption force provided by the adsorption pore array are obtained. If the average value M2 is less than 20% of the magnitude of the second vacuum adsorption force or the variance N2 reaches the predetermined second upper limit threshold of variance, then the trimming task is suspended and an alarm is triggered.

2. The vacuum adsorption control method for an automatic cutting bed according to claim 1, characterized in that, The vacuum adsorption force prediction model is based on a neural network model. The method for obtaining the vacuum adsorption force prediction model includes: Select target information, first vacuum adsorption force and second vacuum adsorption force corresponding to multiple cutting tasks that have not experienced fabric shift from the production database; The target information is used as a training sample, and the corresponding first vacuum adsorption force and second vacuum adsorption force are used as labels. The neural network model is trained based on the training samples and the labels to obtain the vacuum adsorption force prediction model.

3. A vacuum adsorption control system for an automatic cutting bed, wherein the adsorption zone of the automatic cutting bed has a plurality of adsorption pores distributed at a predetermined density, characterized in that, The vacuum adsorption control system includes: The target information acquisition module is used to acquire target information, which includes the distribution density and pore size of the adsorption pores, the single-layer thickness, total number of layers, type and thread count of the fabric to be cut, as well as the cutting path and cutting blade control parameters. The vacuum adsorption force prediction module is used to input the target information into a pre-constructed vacuum adsorption force prediction model to obtain the first vacuum adsorption force and the second vacuum adsorption force. The vacuum adsorption control module is used to control the vacuum adsorption device during the cutting process so that each adsorption pore in the outermost ring of adsorption pores in the adsorption zone provides the first vacuum adsorption force, and each adsorption pore in the corresponding adsorption pore array provides the second vacuum adsorption force. The adsorption pore array includes an adsorption pore sub-array covered by the contour defined by the cutting path and individual adsorption pores adjacent to the adsorption pore array. The vacuum adsorption control module is also used for: During the trimming process, the average value M1 and variance N1 of the actual vacuum adsorption force provided by the outermost adsorption pores are detected. If the average value M1 is lower than the first vacuum adsorption force by 20% or the variance N1 reaches the predetermined first variance upper limit threshold, the trimming process is suspended and an alarm is triggered. If the average value M1 is less than 20% of the magnitude of the first vacuum adsorption force and the variance N1 does not reach the first upper limit threshold of variance, then the average value M2 and the variance N2 of the actual vacuum adsorption force provided by the adsorption pore array are obtained. If the average value M2 is less than 20% of the magnitude of the second vacuum adsorption force or the variance N2 reaches the predetermined second upper limit threshold of variance, then the trimming task is suspended and an alarm is triggered.

4. The vacuum adsorption control system for an automatic cutting bed according to claim 3, characterized in that, The vacuum adsorption force prediction model is based on a neural network model. The method for obtaining the vacuum adsorption force prediction model includes: Select target information, first vacuum adsorption force and second vacuum adsorption force corresponding to multiple cutting tasks that have not experienced fabric shift from the production database; The target information is used as a training sample, and the corresponding first vacuum adsorption force and second vacuum adsorption force are used as labels. The neural network model is trained based on the training samples and the labels to obtain the vacuum adsorption force prediction model.

5. An electronic device, characterized in that, It includes a processor and a memory, wherein the processor executes a computer program stored in the memory to implement the vacuum adsorption control method for an automatic cutting bed as described in claim 1 or 2.

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