Neural Network Winding Control for Stable Material Tension
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Solution Overview
Problem
Existing control systems for winding machines struggle to efficiently manage the tension of winding materials during discontinuous processes, leading to potential material deformation or destruction due to inadequate control over acceleration and deceleration.
Innovation Solution
A computer-implemented device using a neural network to control the winding machine's storage device and buffer system, receiving status signals and providing output signals to optimize the control of the winding process, thereby reducing stress on the mechanical parts and the material.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional PID controllers are used to control the unwinding with respect to dancer position, then the control response is fast, but the tension becomes too high causing material deformation or destruction
Solution Approach 1:
The patent implements dynamic control by continuously adjusting the unwinding motor speed based on real-time dancer position feedback and predicted future positions. The system transitions from static PID parameters to dynamic speed adjustment, allowing the control system to adapt to changing process conditions and material properties, thereby achieving fast response without excessive tension
Solution Approach 2:
The patent applies preliminary action by predicting future dancer positions and pre-adjusting the unwinding motor speed before the actual tension issue occurs. The control system uses historical data and process knowledge to anticipate tension problems and take corrective action in advance, preventing material deformation before it happens
2Device complexity
If the dancer arrangement is controlled without additional control systems, then the device complexity is low, but the tension control is insufficient leading to process interruptions
Solution Approach 1:
The patent implements feedback control by continuously monitoring the dancer position and using this information to adjust the unwinding motor speed. The system establishes a closed-loop control where the actual dancer position is measured, compared with the desired position, and the error signal is used to modify the motor command, ensuring reliable tension control
Solution Approach 2:
The control system performs self-service by automatically adjusting the unwinding parameters based on dancer position feedback without requiring manual intervention. The system monitors its own operation, detects tension issues, and corrects them autonomously, maintaining reliable tension control while reducing the need for operator involvement
3Adaptability or versatility
If the entire material roll is accelerated and deaccelerated for every process step, then the process adaptability is high, but the mechanical stress on the material and machine parts increases significantly
Solution Approach 1:
The patent applies segmentation by separating the control of the material roll from the control of the dancer arrangement. Instead of accelerating and decelerating the entire roll, the system independently controls the dancer rollers to absorb speed variations, allowing process adaptation without subjecting the material and machine parts to high mechanical stress
Solution Approach 2:
The dancer arrangement serves as an intermediary between the material roll and the processing equipment. The dancer rollers absorb speed variations and tension changes, mediating the interaction between the roll and the process, thereby enabling process adaptability while protecting the material and machine parts from excessive mechanical stress
Data Source
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AI summary
A computer-implemented device (100) for controlling a winding machine (200) for winding a winding material (M) onto a target device (T5), the winding machine (200) including a storage device (210) for storing the winding material (M) and a buffer system (220) for buffering the winding material (M) between the storage device (210) and the target device (T5), the computer-implemented device (100) comprising: a receiving unit (110) for receiving a number N of status signals (S1-S11), each of the N status signals (S1-S11) including a certain indication for a current process status of a material flow of the winding material (M), a calculating unit (120) using at least one neural network (121), said at least one neural network (121) being configured to provide a number of output signals (O1, O2) for controlling the storage device (210) and/or the buffer system (220) using the received N status signals (S1-S11) as input, and a controlling unit (130) for controlling the storage device (210) and/or the buffer system (220) using the provided output signals (01, 02). Using the at least one neural network for controlling the winding machine can produce a smoother control. This improves the energy efficiency of the winding machine and reduces the amount of stress on the mechanical parts of the winding machine and the winding material.