itp forest products: mechatronic design and control of a waste … · 2018-06-13 · conveyor belt...
TRANSCRIPT
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Waste Paper Sorting System for Efficient Recycling
Mechatronic Design and Control of a
PI: Richard A. Venditti and M. K. (Ram) Ramasubramanian
Industry Partners: Weyerhaeuser (Tom Friberg) MSS (Michael Grubbs)
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Technology Description
The primary challenge in the recycling of paper is to obtain raw material with the highest purity. • Highly sorted paper stream will facilitate high quality end
product, and save processing chemicals and energy. • Current manual sorting techniques are not effective in
reducing landfill waste.
The project goal is to develop sensors for sorting grades of paper and board from a mixed stream automatically at high speed for more efficient recycling.
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Project Strategy� Key technical barriers. Development of stiffness measurement in
real-time on free, non-oriented samples, and inferring the type of paper based on this information is a challenging problem.
� Combination of sensing technologies in real-time, namely, lignin, stiffness, color, and adhesives to come up with the sorting scheme.
� Describe your project’s strategy for overcoming these barriers � Investigating alternative stiffness measurement methods � Developing improvements to the current stiffness
measurements � Evaluating other sensing techniques, gloss, color, IR
temperature sensor for stickies identification � Criteria for go/no-go decisions using Neural Networks.
� Sensor must be fast � Sensor must provide info on paper type � Sensor must be economical to implement � Sensor must be rugged
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Project Partners
MSS, Inc., Michael Grubbs, General Manager� Provides access to pilot facilities
� Provides feedback on progress reports
� Communicates needs of the industry
� Designs, manufactures and sells sorting equipment
Weyerhaeuser, Tom Friberg, Researcher� Provides feedback on progress reports � Communicates needs of the industry � Provides paper recycling perspective on research direction
and progress
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Commercialization� Potential Market: � Any recycling facility involved in the sorting
and/or disposal of waste paper. � Commercialization:
� As we develop prototype sensors we are testing them in acommercial environment with the industrial partner
� The review of commercial trials guide further work � We have taken this approach successfully with the lignin
sensor and have it commercialized. � We have done similar trials with the stiffness sensors and
have identified areas of improvement. � Currently working on the stiffness sensor and sensor
integration as two achievable milestones in the coming year.
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Commercialization Status� A lignin sensor has been commercialized by the industrial
partner.� MultiWave Sensor with Lignin Sensor operating at IMS Recycling
in San Diego, CA for removal of OCC, Carrier-Board, plastics and trash from newspaper.
� The Lignin Sensor set-up for Carrier-Board identification in SanDiego, CA is crucial for properly identifying the targeted materials.
� Unit shipping February 2006 to VISSER Waste Management in Udenhout, Holland.
� Two units that are being fabricated and will ship March 2006 - to Stora Enso in Cologne, Germany and to Cougle Recycling in Hamburg, PA.
� It is projected that the stiffness sensor will be commercialized in 2008.
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Energy Savings� Electricity: 10 million kWh for the US Industry. � A 5% decrease in rejected recycled pulp may occur
by recycling all sorted recovered paper rather than mixed.
� Up to 1% of the total amount of all paper and paperboard produced is rejected due to quality problems with recycled fibers.
� The rejected paper is typically re-pulped, blended at low level with fresh paper stock material and fed back to the paper machine.
� The use of higher quality pulp from recycled sorted recovered paper may decrease the 1% reject level.
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Other Benefits to using sorted paper in recycling
� Makes recycling more cost effective and efficient promotes increased recycling rates � reduce the need for virgin fibers � reduce paper waste sent to landfills
� Utilization of sorted papers in recycling processes will decrease the amount of sludge and rejects generated in recycling
� Utilization of sorted papers in recycling processes will decrease the amount of water needed to produce recycled paper
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Automated Paper Sorting SystemLignin sensor
Stiffness sensor
Gloss sensor Decision making Actuating mechanismalgorithmColor tracking
sensor
Stickies Sensor
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Lignin Sensor
� The sensor measures ligninfluorescence when excited in the visible region.
� Newsprint samples, typically containing high lignin,produce high intensity.
� Ledger printing and writinggrades with low lignin content produce low-fluorescence intensity.
� Gives normalized lignincontent in paper
� Sensor output can be usedas an input for the controlalgorithm
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Lignin sensor-Dynamic performance
� The sensor is able to identify papers moving at high speeds and is quite robust for sorting applications.
� The sensor can be successfully used as a part of a multi-sensor system to sort mixed office waste for more efficient recycling.
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Stiffness Sensor� Can be used for differentiating different grades of
paper based on their relative bending stiffness values
� Can work together with Lignin and Gloss detection sensors for better sorting
� Is more useful for sorting cardboard from mixed paper feed when compared to other sensors
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Stiffness Sensor Design Constraints
� Should be non-contact in nature � Short response time � Should be compatible with the existing conveyor
systems
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Current Techniques for Stiffness Measurement Contact Methods:� Contact transducers generate ultrasonic waves on
the surface of the paper � Excessive noise due to mechanical vibrations is a
problem � Finer grades and paper boards are difficult to
identify using this method
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Current Techniques for Stiffness Measurement Non Contact Methods:� Air coupled piezoelectric transducers, air coupled
capacitive transducers � Poor coupling of energy between the transducer and
the paper surface � Hard to implement online � Laser ultrasonic measurement technique is an
exception
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Why need different sensor design?� All the previously mentioned techniques are for
testing paper webs of almost constant thickness � These methods are aimed at calculating the exact
elastic constants � Equipment is complex � For sorting there is no need to find the elastic
constants � Unlike paper webs, the thickness of paper on a
sorting conveyor varies widely from one sample to another.
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Stiffness sensor setup
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Distance sensor� Non-contact in nature � High resolution � Output is linearly proportional to the distance � Output is not affected by target’s optical properties
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Distance sensor performance
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Microcontroller� Controls the solenoid valve timing � A/D conversion of distance sensor output � Varies the load by varying the load timing � Runs the control algorithm � Identifies the samples based on the output of the
algorithm
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Parameters which influence the deflection� Orientation of the sample with respect to the
conveyor belt (machine direction, cross machine direction)
� Thickness of the sample � Basis weight � Modulus of elasticity � Distance between the supports � Intensity of the loading � Conveyor speed � Coefficient of friction of the conveyor belt
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Static stiffness sensor
� Paper samples sitting on fixed supports are loaded pneumatically
� Samples with various elastic properties are studied � Deflection values are obtained for these samples at
a given load � Variation of the deflection with respect to various
parameters is studied
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Nozzle pressure profile
Pressure profile of the nozzle that was used for static testing of paper samples
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Static testing results
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Static testing results
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Pilot plant trials of stiffness sensor
� To better understand the problems involved during the operation of the sensor, the stiffness sensor was tested on a high speed moving conveyor
� The dynamic response of the stiffness sensor was evaluated on a moving conveyor at the MSS Inc, Nashville, TN research/manufacturing site
� Load on top of the sample was applied by the air jet from flat fan nozzle
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Pilot plant trials of stiffness sensorStatic Test Dynamic Test
Distance Sensor
Flat fan nozzle
Conveyor speed = 280 ft/min
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Dynamic test results
0
5
10
15
20
25
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Copy Paper
ow ed
Paper
ter Paper
Medium Card
Stock
Heavy Card Stock
Speciality Card Stock
Card board
Defe
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n, m
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Nozz e height=1"
Nozz e height =7"
Nozzle inlet pressure = 10 psi, Samples were loaded in MD
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Stiffness sensor characterizationStep 1:� Identifying different grades of paper which are
commonly found in the recovered paper � Testing the selected grades of paper to find the
mechanical properties Step 2: � Building an FEA ( Finite Element Analysis) model of
the system � Simulating the original loading and boundary
conditions of the system � Using the simulation output for decision making
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Paper samples material dataFour samples of different grades are picked and their mechanical properties are investigated in order to build the FEA model
Material test data for 105µm thick sample
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Paper samples test data
Copy
Medium
Stock
( 105 206 229 234
2) 75 145 200 175
l i i )
l)
Paper grade paper
card stock
Heavy card
Specialty card stock
Thickness µm)
Grammage (g/m
Modulus of e astic ty in machine d rection (GPa 3.98 1.6898 1.7935 1.6103
Modu us of elasticity in cross machine direction (Gpa
1.27 1.1143 1.090 1.1123
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FEA model� An FEA model of the system is constructed � Paper samples are modeled as orthotropic shell
elements � Material test data is used to create the material
model � Large displacement formulation is used for the
elements � The conveyor supports are modeled as rigid
bodies� The material properties of the actual samples are
used in the model � Actual Loading and boundary conditions are
simulated
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FEA model
Conveyor-2
Conveyor-1
Paper sample
Gap = 40mm
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Paper Orientations on Conveyor
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Finite Element SimulationsConveyor Speed Orientation Nozzle Pressure
MD
300 ft/min
CD
MD-30Degrees
MD-60Degrees
10psi
20psi
25psi
30psi
10psi
20psi
25psi
30psi
10psi
20psi
25psi
30psi10psi
20psi
25psi
30psi
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Conveyor Speed = 300 ft/min, MD
Response of 105µm paper sample to applied load; conveyor speed =300 ft/min, load = 20psi
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Conveyor Speed = 300 ft/min, MD
Response of 229µm paper sample to applied load; conveyor speed =300 ft/min, load = 20psi
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Conveyor Speed= 300 ft/min, MD
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Conveyor Speed = 300 ft/min, MD 30
Response of 105µm paper sample to applied load; conveyor speed =300 ft/min, load = 20psi
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Conveyor Speed = 300 ft/min, MD 30
Response of 229µm paper sample to applied load; conveyor speed =300 ft/min, load = 20psi
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Conveyor Speed = 300 ft/min, MD 30
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Conveyor Speed = 300 ft/min, CD
Response of 105µm paper sample to applied load; conveyor speed =300 ft/min, load = 10psi
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Conveyor Speed = 300 ft/min, CD
Response of 229µm paper sample to applied load; conveyor speed =300 ft/min, load = 10psi
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Conveyor Speed = 300 ft/min, CD
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Time Response Curves, MD-300ft/min
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Conveyor Speed = 1200 ft/min, MD
Response of 105µm paper sample to applied load; conveyor speed =1200 ft/min, load = 10psi
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Conveyor Speed = 1200 ft/min, MD
Response of 229µm paper sample to applied load; conveyor speed =1200 ft/min, load = 10psi
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Conveyor Speed = 1200 ft/min, MD
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Damping caused by the surrounding air
Response of the paper when there is no viscous pressure acting on top of it
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Damping caused by the surrounding air
Response of the paper when there is viscous pressure acting on top of it
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Response of the sample to pneumatic load
Applied pneumatic load is equal to the load applied by the cylindrical nozzle operating at 5 psi and held 1” above the conveyor surface, conveyor speed=1200ft/min
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Time Response Curves, MD-1200ft/min
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Comparison of Response Curves
20psi-MD-300 20psi-MD-1200
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Future Work� Stiffness sensor development completion� Use of RF sensors for fast response and
higher speed sorting � Commercialization of stiffness sensor to
identify carrier boards and other stiffmaterials
� IR imaging based sensors for stickiesidentification
� Neural network control algorithmimplementation
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Flutter of paper
Flutter can be defined as the dynamic instability of an elastic body in an air stream
� The vibration modes of the samples subjected to lateral load depend on the elastic constants of the samples
� For a given value of tangential load, stiff samples vibrate at a much lower frequency whereas flexible thin samples vibrate with larger amplitudes and higher frequencies
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Flutter based sorting setup
Tangential load
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Stiffness sensor performance enhancement
� The use of frequency domain analysis (web flutter in a fluid flow) to compliment the results obtained from the deflection data.
� Results from the classic “Flag Flutter” problem show that the flutter frequency is related to the bending stiffness as shown.
� This method also eliminates the requirement for the paper samples to be at a constant height from the sensor, thereby making it more robust
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Stiffness Sensor - Performance Enhancements� Potential Sensors for frequency analysis
� Laser Distance Sensor from LMI Technologies (USA), Inc � Resolutions down to 0.001mm � Standardized with optical filters to reduce the influence
of ambient light � High speed, Analog outputs (V), up to 100 kHz � Optional modulated version (-M) to exclude any
influence from external light � Fast laser intensity control for object color changes
� LK-G series from Keyence (USA), Inc � Resolutions down to 0.01micrometer � High speed, Analog outputs (V), up to 50 kHz � Resistant to ambient lighting conditions
� Flutter frequency measurements which can then be used to correlate to the stiffness measured from the displacement data.
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Future Needs� Development of the stiffness sensor can be
completed by June 2007 and commercialization can be accomplished by January 2008.
� Exploration and development of the IR sensor is very useful and can be a new project for potential support.
� Funding runs out end of 2006.� Additional support for one year can significantly
influence the outcome of this research.
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Acknowledgement
This research was supported by the U.S. Department of Energy under the Industries for the Future Program, Forest Products Industry Agenda 2020; project number DE-FC07-00ID13880