Paper web winding: roll quality improvement through the maximization of coupling between drive rolls and driven built paper roll
View Patent ↗A System and Method for Adaptive Paper Web Winding that adjusts Operational Parameters, including torque, pressure, tension, acceleration, Jerk Rate, and sheet speed, in response to Operational Data and feedback. The system, in one embodiment, comprises a Front Drum with adjustable torque control, a Rider Roll with variable pressure regulation, an Unwind Section with tension control, and a Control Unit configured to maximize coupling between drive rolls and driven built paper roll. The method involves detecting the Coefficient of Friction of a Paper Web, then adjusting Operational Parameters in response to Operational Data and feedback. This invention improves efficiency and reliability in paper winding operations by automating adjustments to accommodate variations in the Coefficient of Friction of a Paper Web.
1 . An adaptive winding system comprising: one or more drive rolls; one or more sensors configured to detect actual web speed; and a control unit configured to detect slippage by comparing the actual web speed to the speed of the one or more drive rolls, and to adjust one or more operational parameters based on real-time feedback from the one or more sensors to restore frictional engagement.
2 . The adaptive winding system of claim 1 , wherein the one or more operational parameters include torque, pressure, tension, web speed, acceleration rate, jerk rate, or a combination thereof.
3 . The adaptive winding system of claim 1 , further comprising a rider roll configured to apply variable pressure on a built roll to maintain frictional engagement.
4 . The adaptive winding system of claim 1 , wherein the one or more sensors include a non-contact web speed sensor, a tension sensor, or a combination thereof.
5 . The adaptive winding system of claim 1 , wherein the one or more operational parameters are adjusted in response to one or more machine learning algorithms.
6 . The adaptive winding system of claim 1 , further comprising a communication system configured to provide real-time visualizations of system performance metrics, predictive alerts, or a combination thereof, for potential slippage, misalignment, or a combination thereof.
7 . A method for an adaptive winding system comprising: detecting slippage between a web and one or more drive rolls by comparing data from one or more sensors; and dynamically adjusting one or more operational parameters to restore frictional engagement between the web and the one or more drive rolls.
8 . The adaptive winding system of claim 1 , wherein slippage conditions between a web and a rotating component are detected by comparing operational data from one or more sensors monitoring actual web speed to operational data from one or more sensors monitoring drum speed, and adjustments to operational parameters are performed in real time.
9 . The adaptive winding system of claim 1 , further comprising an unwind section configured to regulate web tension upstream of a built roll using feedback from tension sensors and unwind motor speed sensors.
10 . The adaptive winding system of claim 1 , wherein adjustments include recalibrating acceleration rate, jerk rate, or a combination thereof, to prevent slippage.
11 . The method of claim 7 , wherein the adjusting uses one or more machine learning algorithms to analyze one or more patterns in operational data and adjust one or more operational parameters in response to the operational data.
12 . The method of claim 7 , further comprising logging operational data for creation, optimization, or a combination thereof, of winding recipes.
13 . The method of claim 7 , further comprising modifying rider roll pressure based on feedback from one or more sensors.
14 . The method of claim 7 , wherein detecting slippage includes identifying when a front drum speed exceeds a back drum speed, and dynamically adjusting includes adjusting front drum torque to restore frictional engagement.
15 . The method of claim 7 , wherein detecting slippage includes identifying when a back drum speed exceeds the actual web speed, and dynamically adjusting includes reducing unwind tension to restore frictional engagement.
16 . The method of claim 7 , further comprising using one or more machine learning algorithms to predict adjustments to operational parameters based on historical operational data for different paper types, environmental conditions, or a combination thereof.
17 . A system comprising: a drive roll; a sensor configured to measure web speed; and a control unit to detect slippage based on a discrepancy between the measured web speed and the drive roll speed, and to adjust a parameter accordingly.
18 . The adaptive winding system of claim 1 , wherein the control unit uses one or more machine learning algorithms to analyze patterns in operational data and adjust one or more operational parameters to restore frictional engagement.
19 . The adaptive winding system of claim 1 , further comprising a memory configured to log operational data for creation, optimization, or a combination thereof, of winding recipes.
20 . The adaptive winding system of claim 1 , wherein the control unit is configured to detect vibrations, interweaving, or a combination thereof, based on real-time feedback from one or more sensors.