Coil winding machine control method based on BP nerve network, and coil winding machine

Abstract

The invention discloses a coil winding machine control method based on a BP nerve network. The method comprises the following steps: step one, determining an input-layer vector, an intermediate-layer vector and an output-layer vector of a three-layer nerve network; step two, according to historical data, obtaining a training sample, and training the nerve network; step three, according to a certain sampling period, measuring an internal temperature T, a vibration rate U, stress F between a wire arrangement device and a coiling frame, a main shaft motor rotating speed omega a, a wire arrangement motor rotating speed omega b and a wire laying motor rotating speed omega c of a coil winding machine by use of a sensor, and normalizing the parameters to obtain the input-layer vector and the output-layer vector; step four, controlling the main shaft motor rotating speed, the wire arrangement motor rotating speed and the wire laying motor rotating speed; and step five, according to emergency shutdown signals in the intermediate-layer vector, determining an operation state of the coil winding machine. According to the invention, the coiling line breaking frequency can be reduced, the product quality is improved, the machine mean time between failures is increased, and the realistic significance is great.

Description

technical field [0001] The invention relates to the technical field of automatic control of winding machines, in particular to a control method of winding machines based on BP neural network. Background technique [0002] With the introduction of Industry 4.0 and Made in China 2025, intelligent manufacturing technology has achieved unprecedented development. Winding machine is an automatic equipment for winding coils. Commonly used electronic products such as motor coils, pin inductors, transformers, solenoid valves, ignition coils, RFID, focusing coils, etc. are all produced by winding machines. Winding technology has experienced manual, semi-automatic, and fully automatic development, and the next step will be to develop in the direction of intelligence. The key technology of the intelligent winding device is motion control, that is, the real-time control and management of the position and speed of mechanical moving parts, so that they can move according to the expected m...

AI Technical Summary

Problems solved by technology

[0011] The present invention designs and develops a winding machine control method based on BP neural network. The purpose is to overcome the shortcomings of the existing winding machine control system, such as relatively single control mode, complicated debugging, and long time-consuming defects, so that automatic adjustment can be made during the control process. Winding parameters, reducing the frequency of winding wire breakage, improving product quality and machine mean time between failures

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