low cost process monitoring for polymer extrusion

low cost process monitoring for polymer extrusion Dr Jing Deng • Energy, Power and Intelligent Control • School of Electronics, Electrical Engineering and Computer Science • Queen's University Belfast • 13/08/2013 j.deng@qub.ac.uk

Content Background . Thermal energy consumption monitoring. Motor power consumption monitoring. Viscosity monitoring through ‘soft-sensoring’. Summary and future work.

1. Background Melt pressure Viscosity Feed rate Screw speed Melt temperature Barrel temperature

2. Thermal energy monitoring - the extruder 1. Background Extruder Specifications Geometrical screw parameters Killion KTS-100 laboratory single-screw extruder

2. Thermal energy monitoring - the heating and cooling 2. Thermo energy monitoring Heating and cooling elements of the single screw extruder Other circuits 0.06kw Controller circuit 0.0016kw Clamp ring heating band 0.4964kw Adapter heating band 0.106kw Cooling fan 0.04637kw Zone 1, Heating band 1.296kw Zone 2, Heating band 1.267kw Zone 3, Heating band 1.238kw

2. Thermo energy monitoring 2. Thermal energy monitoring - power supply • L1: • Controller circuits • Zone 3 heating and cooling • Motor drive power supply • L2: • Zone 1 heating and cooling • Zone 4 heating • L3: • Zone 2 heating and cooling • Zone 5 heating N L3 L1 L2

2. Thermal energy monitoring - the controller 2. Thermo energy monitoring

2. Thermo energy monitoring 2. Thermal energy monitoring - the controller Set Temperature Heating band PID Controller Temperature Extruder Barrel Zone Cooling Fan AFM215-303 DURAKOOL Mercury displacement contactor Time-proportional control

2. Thermo energy monitoring More close to the actual power consumption

2. Thermo energy monitoring 2. Thermal energy monitoring - the advantages Separate power supply • Advantage: • Additional power consumption measurement • More accurate thermal energy monitoring • Expensive power meter is not required

2. Thermo energy monitoring 2. Thermal energy monitoring - monitor separate heating zones Plot of energy consumption by different zones, screw speed at 10, cooling temperature at 25 degree Temperature settings 170-180-190, material: LDPE 2102TN32W, MFR:2.5g/10min at 190 °C and 2.16 kg

2. Thermo energy monitoring 2. Thermal energy monitoring - monitor separate heating zones Extruder Killion KTS-100Material SABIC LDPE 2100TN00W Cooling temperature setting: 25 Temperature setting: 170-180-190 Screw speed: 40 rpm Data file: 20120720C

3. Motor power consumption monitoring - the controller N L1

3. Motor power consumption monitoring - the controller Power in Power out

3. Motor power consumption monitoring - the controller Those rising edges contain high-frequency energy from harmonics of the PWM signal's frequency. Because a motor presents an inductive load to the inverter circuits, its inductance filters much of the high-frequency energy. The high frequencies do little to rotate the motor, but the energy in those frequencies must go somewhere, and the high-frequency energy dissipates as heat. Measure PWM motor efficiency

3. Motor power consumption monitoring - Apparent power consumption Power factor Screw speed Motor Apparent power consumption Screw speed Voltage current Active power current

3. Motor power consumption monitoring - the controller V_a = R_a * I + K_v * w R_a = 12.4222; K_v = 0.0038 V_a = 12.4222 * I + 0.0038 * N

4. Viscosity monitoring Viscosity measurement On-line rheometer In-line rheometer Off-line rheometer

2. Viscosity monitoring 4. Viscosity monitoring Viscosity calculation Queen's University Belfast

2. Viscosity monitoring 4. Viscosity monitoring Viscosity calculation By substituting typical values Queen's University Belfast

4. Viscosity monitoring

Forward selection method (constrained minimisation) 4. Viscosity monitoring Table 1: The comparison of forward and backward selection y X2 y e = y – X1 θ1-X2 θ2 X2 θ2 e = y – X1 θ1 X1 X1 θ 1 X1 X1 θ1

4. Viscosity monitoring 1 2 k n • Two-stage selection Selected terms Stage 1: Forward model selection Stage 2: Backward model refinement - Loop 1 …….. - Loop 2 …….. - Loop 3 …….. ……… j Candidate terms pool • Remains efficient and effective from FRA • Eliminates optimization constraint in FRA • Reduces the training error without increasing model size

4. Viscosity monitoring Consider a general nonlinear model Write in a matrix form

4. Viscosity monitoring A optimal design criterion where is known as the design matrix The new cost function becomes

4. Viscosity monitoring define Some properties of R

4. Viscosity monitoring Also define some auxiliary matrices

4. Viscosity monitoring Recursive updating Net contribution of a new term to the cost function

4. Viscosity monitoring Employing Branch and Bound

4. Viscosity monitoring The net contribution of a new term to the cost function where

5. Summary and future work • Low cost process monitoring techniques have been developed for polymer extrusion, including thermo energy monitoring, motor power consumption monitoring, and viscosity monitoring. • A-optimal design criterion and branch and bound can be employed into subset selection algorithm to further improve model compactness and computational effort. • Current and future work mainly focus on commercialisation of research outputs through an PoC project.

Questions ? Jing DENG EPIC Research Cluster j.deng@qub.ac.uk

low cost process monitoring for polymer extrusion