The tension control system of an automatic dual-coil winding machine is a core module for ensuring winding quality. Its dynamic balancing capabilities directly impact coil forming accuracy, electrical performance, and machine operational stability. This system utilizes coordinated control of multiple parameters to achieve real-time tension adjustment under conditions such as high-speed operation, variable-diameter winding, and material switching. Its core mechanism can be summarized as a closed-loop control system combining sensor feedback, algorithm optimization, and actuator response.
At the sensor level, the tension control system typically utilizes high-precision tension detection devices, such as piezoelectric or electromagnetic sensors, to capture real-time tension fluctuations during the winding process. These sensors must achieve micronewton-level accuracy and be able to detect transient tension changes caused by variations in wire diameter, friction coefficient, or mechanical vibration. For example, when winding two coils simultaneously, if the tension of one coil deviates by 0.1N due to differences in the elastic modulus of the wire, the sensor must complete signal acquisition and transmit it to the control unit within 10ms, providing the data foundation for subsequent adjustments.
The control algorithm is the core of dynamic balancing. Modern automatic dual-coil winding machines generally employ a composite algorithm combining PID control and fuzzy control. This algorithm achieves rapid convergence of tension errors through self-tuning of the proportional, integral, and differential parameters. In the PID algorithm, the proportional component eliminates current deviations, the integral component eliminates historical accumulated errors, and the differential component predicts future trends. In dual-coil scenarios, the algorithm must independently adjust the tension of each winding head while simultaneously using coupling compensation to avoid overall tension imbalance caused by unilateral adjustment. For example, when the tension of the left coil suddenly increases due to acceleration, the algorithm must simultaneously reduce the tension output of the right coil to prevent vibration caused by uneven force on the spindle.
The response speed of the actuator directly determines the effectiveness of the adjustment. Automatic dual-coil winding machines typically use a magnetic powder clutch or a servo motor as the tension actuator. The former transmits torque through the shear stress of the magnetic powder chain, while the latter achieves high-precision torque output through current control. During dynamic adjustment, the actuator must complete the entire process from command reception to torque adjustment within 50ms. For example, when a sensor detects excessive tension, the control unit immediately sends a pulse signal to the servo motor. The motor, through a reducer, converts the rotational motion into linear force to adjust the wire's pull, ensuring that the tension returns to the set value before the next winding.
The impact of material properties on dynamic balance requires a compensation algorithm. Wires of different diameters and materials have different elastic moduli and friction coefficients. For example, the elongation of copper and aluminum wires at the same tension can differ by over 30%. The control system must have a built-in material database to automatically call preset parameters based on wire specifications and adjust the compensation values through online learning. For example, when switching to a thinner wire diameter, the system must reduce the actuator's output torque to prevent wire breakage due to insufficient wire strength.
The stability of the mechanical structure is the physical foundation of dynamic balance. Components such as the spindle, guide pulleys, and wire guides of an automatic dual-coil winding machine must possess high rigidity to minimize vibration interference with tension. For example, the spindle utilizes dynamic balancing technology to control eccentricity to within 0.01 mm, preventing periodic tension fluctuations caused by high-speed rotation. In addition, the surface of the guide wheel must be precision-polished to ensure a constant contact angle between the wire and the guide wheel, preventing tension drift caused by variations in the friction coefficient.
The impact of environmental factors on dynamic balancing must be addressed through temperature compensation and dust-proofing. Temperature fluctuations can cause changes in the magnetic permeability of the magnetic powder clutch, which in turn affects torque transmission efficiency. The control system must integrate a temperature sensor to adjust the excitation current in real time to offset environmental effects. Furthermore, the automatic dual-coil winding machine must be equipped with a sealed structure to prevent dust from intruding into the actuator and avoid tension loss caused by magnetic powder contamination or servo motor seizure.
The ultimate goal of dynamic balancing is to achieve "zero-error" control of the winding process. Through the deep collaboration of sensors, algorithms, and actuators, the automatic dual-coil winding machine can control tension fluctuations within ±1% under complex operating conditions, ensuring the consistency of electrical parameters such as coil resistance and inductance, meeting the production requirements of precision components such as transformers and inductors. This closed-loop control model not only improves equipment efficiency but also promotes the development of high-precision and high-reliability winding processes.
