A multi-head winding control system and method

Abstract

The present invention provides a multi-head winding control system and method, the system includes: a head module, a turntable module, a paint stripping module, a welding module, and a foot cutting and discharging module; wherein the head module is the key point of the entire system, and the head module is used to realize user-defined head movements to adapt to various product requirements; at the same time, the system also includes a user operation interface, a data analysis module, a data slicing module, and a data execution module. The present invention realizes asynchronous control between multiple heads, and the three heads do not interfere with each other, thereby increasing production efficiency; it realizes synchronous control of each axis in a single head, so that the products wound by each head are uniform, and the quality of the product is improved; modular control between heads can effectively control the use and non-use of any head, as well as the timing of stopping during operation, simplifying the start-stop operation; a control cycle of 1ms is adopted, so that the coil is wound more evenly, and the product quality is improved.

Description

Technical Field

[0001] The invention relates to the technical field of copper wire coil winding, and in particular to a multi-machine head winding control system and method. Background Art

[0002] Copper wire coils are widely used in inductors, motors, engines and other fields due to their stable conductivity, strong oxidation resistance, and the ability of copper wire coils to enhance magnetic fields and current passing through coils. With the advancement and development of science and technology, traditional semi-automatic winding and single-head winding equipment systems are inefficient and can no longer meet the rapidly growing market demand. Three-head winding all-in-one equipment uses three heads to wind at the same time, which greatly improves production efficiency. However, there is no complete three-head all-in-one control system on the market. The traditional PLC system has defects in the synchronous and asynchronous control of the three heads and cannot wind neatly arranged coils. A three-head all-in-one control system with simple operation and high control accuracy has become increasingly needed by the market.

[0003] That is, the current technology has the following deficiencies:

[0004] (1) Inefficient winding equipment: Traditional semi-automatic winding and single-head winding equipment systems are inefficient and can no longer meet the rapidly growing market demand;

[0005] (2) Lack of a complete three-head integrated machine control system: Although the three-head winding machine equipment can greatly improve production efficiency, there is currently no complete three-head integrated machine control system on the market;

[0006] (3) PLC system defects: The traditional PLC system has defects in the synchronous and asynchronous control of the three heads and cannot wind neatly arranged coils;

[0007] (4) Demand for high-precision control systems: There is an increasing market demand for a three-in-one control system that is easy to operate and has high control accuracy, but existing technologies have not yet been able to meet this demand.

[0008] Therefore, the prior art has deficiencies and needs further improvement. Summary of the invention

[0009] In view of the problems existing in the prior art, the present invention provides a multi-machine head winding control system and method.

[0010] To achieve the above object, the specific scheme of the present invention is as follows:

[0011] The present invention provides a multi-machine head winding control system, the system comprising:

[0012] Head module, turntable module, paint stripping module, welding module, cutting and discharging module;

[0013] The head module performs the winding operation, the turntable module controls the wire supply and the winding head position, the paint stripping module removes the insulating paint of the wire, the welding module connects the coil to other components, and the cutting and discharging module is responsible for cutting off the excess wire and removing the finished product;

[0014] The head module is the key point of the whole system. It is used to realize user-defined head movements to meet various product requirements.

[0015] At the same time, the system also includes a user operation interface, a data analysis module, a data segmentation module, and a data execution module, which are respectively used for data input, data analysis, data segmentation, and execution control.

[0016] Furthermore, the system also includes a machine learning module, which can automatically optimize the user-defined machine head movement by collecting and analyzing past operation data to improve winding efficiency and quality; the machine learning module can use various machine learning algorithms, including deep learning and reinforcement learning, to achieve self-learning and self-optimization of winding operations.

[0017] Furthermore, the user operation interface adopts a programming table to customize the machine head action, and each programming table corresponds to a machine head;

[0018] The data analysis module regards each programming table as a module, and an asynchronous control method is adopted between the three head modules to achieve independence and non-interference of each module.

[0019] Further, the data analysis module includes data acquisition and data conversion;

[0020] Data acquisition adopts a line-by-line parsing mode, and obtains the data of each line from the user programming table in order from top to bottom. First, the cylinder instruction is obtained; then the axis movement instruction is obtained; and finally the delay instruction is obtained;

[0021] Data conversion, converting the acquired user data or instructions into parameters or instructions for mechanical movement.

[0022] Furthermore, the data slicing module performs synchronous calculations on the data parsed by each module to achieve simultaneous start and end of the actions of each axis.

[0023] Furthermore, the data slicing module calculates the time required for the main axis movement and the movement amount of other axes, calculates the speed of other axes, and then compares the speed of other axes with the maximum speed set for other axes. If the speed is greater than the maximum speed, the time is recalculated using the movement amount and maximum speed of the axis.

[0024] The present invention also provides a multi-head winding control method, which comprises the following steps:

[0025] S1, the user configures the motion parameters of each machine head on the operation interface;

[0026] S2, the data analysis module analyzes the configured parameters into parameters or instructions of mechanical movement;

[0027] S3, the data slicing module performs synchronous calculation on the parsed data to achieve simultaneous start and end of each axis action;

[0028] S4, the data execution module configures the sliced ​​data into the hardware device to realize the control of the axis.

[0029] Furthermore, the method further includes a prediction step, which uses a machine learning module to predict the motion parameters of each axis in advance so as to more accurately control the movement of each axis in actual operation; the prediction step can be performed between the data parsing step and the data segmentation step so as to achieve precise control of the axis in the data execution step.

[0030] Furthermore, the parameters configured by the user on the operation interface include cylinder instructions, axis motion instructions and delay instructions for each machine head.

[0031] Furthermore, the data analysis module regards each programming table as a module, and an asynchronous control method is adopted among the three head modules.

[0032] Furthermore, the data slicing module calculates the speed of other axes by calculating the time required for the main axis to move and the movement of other axes;

[0033] The time is set to 1ms, and the number of pulses of each axis per ms is configured into the FPGA. The FPGA sends the pulses to the servo motor on average within 1ms to achieve control of the axis.

[0034] Furthermore, the data execution module adopts the arm+fpga architecture mode and is implemented by the cooperation of cpu and fpga.

[0035] The technical solution of the present invention has the following beneficial effects:

[0036] 1. Asynchronous control among multiple machine heads is realized, and the three machine heads do not interfere with each other, which increases production efficiency;

[0037] 2. The synchronous control of each axis in a single machine head is realized, so that the products wound by each machine head are uniform and the quality of the products is improved;

[0038] 3. Modular control between machine heads can effectively control the use and non-use of any machine head, as well as the timing of stopping during operation, simplifying the start and stop operation;

[0039] 4. The 1ms control cycle makes the coil more evenly wound, improving product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a view of the mechanical body of the present invention;

[0041] Figure 2 is a flow chart of the present invention;

[0042] Figure 3 This is a product diagram of a three-head winding machine. DETAILED DESCRIPTION

[0043] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments; it can be understood that the specific embodiments described herein are only used to explain the present invention rather than to limit the present invention; it should also be noted that, for ease of description, only the parts related to the present invention rather than all are shown in the accompanying drawings.

[0044] The present invention provides a multi-head winding control system, which mainly consists of five parts: Figure 1 The following are shown: head module, turntable module, paint stripping module, welding module, cutting and discharging module.

[0045] Head module: This is the core part of the winding process; the head module usually includes one or more winding heads for winding the wire into a specific coil or other shape; each winding head can be independently controlled to wind on different coils.

[0046] Turntable module: The turntable module is used to control the supply of wire and the position of the winding head; it can rotate and move to switch between multiple winding heads or perform different winding operations inside one winding head.

[0047] Paint stripping module: During the winding process, the wire is usually coated with a layer of insulating paint; the paint stripping module is used to remove this layer of paint after the winding is completed to facilitate subsequent welding or other connection operations.

[0048] Welding module: The welding module is used to connect the wound coil to other parts, such as circuit boards or other electronic components; it can perform various types of welding, such as spot welding, laser welding, etc.

[0049] Cutting and unloading module: After the winding and welding process is completed, the cutting and unloading module is used to cut off the excess wire and move the finished product out of the machine; this module includes a set of cutting equipment and a set of conveying equipment.

[0050] The head module is the key point of the whole system;

[0051] The software part includes: user operation interface, data analysis module, data segmentation module, and data execution module, which are used for data input, data analysis, data segmentation, and execution control respectively.

[0052] The software also includes a machine learning module that can automatically optimize user-defined machine head movements to improve winding efficiency and quality by collecting and analyzing past operation data; the machine learning module can use various machine learning algorithms, including deep learning and reinforcement learning, to achieve self-learning and self-optimization of winding operations.

[0053] like Figure 2 As shown, a control method corresponding to multi-head synchronous / asynchronous winding is also proposed.

[0054] Under the premise of satisfying the simultaneous operation of the three heads, the product accuracy is improved and the operation is simplified. This method is mainly divided into four parts:

[0055] 1. User operation part (user operation interface).

[0056] This part adopts a table-based custom programming method, which allows users to customize the machine head movements to meet the needs of various products. For the three-head winding machine system, three programming tables are provided as follows, which are used to control the three machine heads respectively.

[0057] The programming table is as follows:

[0058]

[0059] 2. Data analysis part.

[0060] This part regards each programming table as a module, and adopts asynchronous control method among the three head modules to realize the independence and non-interference of each module.

[0061] a) Data acquisition: This method adopts a line-by-line parsing mode to obtain the data of each line from the user programming table in order from top to bottom. First, the cylinder instruction is obtained; then the axis motion instruction is obtained; and finally the delay instruction is obtained.

[0062] b) Data conversion: converting the acquired user data or instructions into parameters or instructions for mechanical motion.

[0063] 3. Data sharding part.

[0064] This part performs synchronous calculations on the data parsed by each module, realizing the simultaneous start and end of each axis action. The synchronization steps are as follows:

[0065] a) Calculate the time t required for the spindle to move.

[0066] b) Based on the time t and the movement of the other axes, calculate the speed v of the other axes.

[0067] c) Compare the speed v of other axes with the maximum speed vMax set for other axes. If v>vMax, recalculate the time t using the movement s and vMax of the axis, that is, t=s / vMax.

[0068] d) Record the time t and the speed v required for each axis to complete its own movement according to the time t, and the segmentation is completed.

[0069] 4. Data execution part.

[0070] This part adopts the arm+fpga architecture mode. The above three parts are calculated by the cpu, and this part is implemented by the cpu and fpga.

[0071] a) After testing the effect of the time slice size on the product, set the time slice to 1ms, and then obtain the number of pulses to be sent per ms based on the slice data calculated in step 3.

[0072] b) The number of pulses of each axis per ms is configured into the FPGA, which sends the pulses to the servo motor on average within 1ms to achieve control of the axis.

[0073] The method further includes a prediction step, which uses a machine learning module to predict the motion parameters of each axis in advance so as to more accurately control the motion of each axis in actual operation; the prediction step can be performed between the data parsing step and the data slicing step so as to achieve precise control of the axis in the data execution step.

[0074] Application of deep learning in multi-machine winding control system:

[0075] In this scenario, deep learning can be used to analyze and understand past operation data to optimize user-defined machine head movements. This optimization may include identifying which movements can improve winding efficiency and which movements may cause quality problems. Deep learning models can learn from a large amount of historical data and understand the complex patterns and relationships in these data to predict future results or make optimization suggestions.

[0076] Application of reinforcement learning in multi-machine winding control system:

[0077] Reinforcement learning can be used to self-optimize the control system. In each winding operation, the reinforcement learning model will try to take different actions, and then get rewards or penalties based on the results (such as winding efficiency and quality). Through continuous trial and error and learning, the model can find the best strategy, that is, how to adjust the head action to maximize winding efficiency and quality.

[0078] In the prediction step of the multi-head winding control method, the machine learning module can use deep learning or reinforcement learning to predict the motion parameters of each axis. This prediction can help the system control the motion of each axis more accurately in actual operation, thereby improving the efficiency and quality of winding. For example, the deep learning model can predict future axis motion parameters by analyzing historical data; while the reinforcement learning model can find the optimal axis motion parameters through continuous trial and error and learning.

[0079] Figure 3 This is a product diagram of a three-head winding machine;

[0080] The three heads complete the winding, and then determine whether the station on the turntable is idle. If it is idle, put the coil in. After the turntable rotates, the system Figure 1 The clockwise sequence completes the upper laser stripping, lower laser stripping, laser welding, foot cutting, and material discharging to produce Figure 3 For the product shown, after the product is welded to the material strip, the workstation is cleared and then checked to see if it is idle before entering into the production of the next coil.

[0081] The specific numerical values ​​described in the present invention are all examples to illustrate the logic of the present invention, and are not intended to limit the scope of the patent of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly used in the technical field related to multi-head winding coils, are also included in the patent protection scope of the present invention.

Claims

1. A multi-head winding control system, characterized in that: The system includes: Head module, turntable module, paint stripping module, welding module, cutting and discharging module; The head module performs the winding operation, the turntable module controls the wire supply and the winding head position, the paint stripping module removes the insulating paint of the wire, the welding module connects the coil to other components, and the cutting and discharging module is responsible for cutting off the excess wire and removing the finished product; At the same time, the system also includes a user operation interface, a data analysis module, a data segmentation module, and a data execution module, which are used for data input, data analysis, data segmentation, and execution control respectively; The system also includes a machine learning module that automatically optimizes user-defined machine head movements to improve winding efficiency and quality by collecting and analyzing past operation data; the machine learning module uses machine learning algorithms to achieve self-learning and self-optimization of winding operations; The user operation interface adopts a programming table to customize the machine head action, and each programming table corresponds to a machine head; The data analysis module regards each programming table as a module, and the three head modules adopt an asynchronous control method to achieve independence and non-interference of each module; The data analysis module includes data acquisition and data conversion; Data acquisition adopts a line-by-line parsing mode, and obtains the data of each line from the user programming table in order from top to bottom. First, the cylinder instruction is obtained; then the axis movement instruction is obtained; and finally the delay instruction is obtained; Data conversion, converting the acquired user data or instructions into parameters or instructions for mechanical motion; The data slicing module performs synchronous calculations on the data parsed by each module to achieve simultaneous start and end of the actions of each axis; The data slicing module calculates the time required for the main axis movement and the movement amount of other axes, calculates the speed of other axes, and then compares the speed of other axes with the maximum speed set for other axes. If the speed is greater than the maximum speed, the time is recalculated using the movement amount and maximum speed of the axis.

2. A multi-head winding control method, using the system of claim 1, characterized in that: The method comprises the following steps: S1, the user configures the motion parameters of each machine head on the operation interface; S2, the data analysis module analyzes the configured parameters into parameters or instructions of mechanical movement; S3, the data slicing module performs synchronous calculation on the parsed data to achieve simultaneous start and end of each axis action; S4, the data execution module configures the sliced ​​data into the hardware device to realize the control of the axis.

3. The multi-head winding control method according to claim 2, characterized in that: The method further includes a prediction step, which uses a machine learning module to predict the motion parameters of each axis in advance so as to more accurately control the motion of each axis in actual operation; the prediction step can be performed between the data parsing step and the data slicing step so as to achieve precise control of the axis in the data execution step.

4. The multi-head winding control method according to claim 2, characterized in that: The parameters configured by the user on the operation interface include the cylinder instructions, axis motion instructions and delay instructions of each machine head.

5. The multi-head winding control method according to claim 2, characterized in that: The data parsing module regards each programming table as a module, and the asynchronous control method is adopted between the three head modules; The data slicing module calculates the speed of other axes by calculating the time required for the main axis to move and the movement of other axes; The time is set to 1ms, and the number of pulses of each axis per ms is configured into the FPGA. The FPGA sends the pulses to the servo motor on average within 1ms to achieve control of the axis.

6. The multi-head winding control method according to claim 2, characterized in that: The data execution module adopts the arm+fpga architecture mode and is implemented by the cooperation of cpu and fpga.

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