MMEA (The Measurement, Monitoring and Environmental Efficiency Assessment) research program final seminar presentation by Dr. Esko Juuso, University of Oulu

1. MMEA Final Seminar
Helsinki 26 November 2015
Intelligent Analysers for Control
and Optimisation of Wastewater
Treatment Plants
Esko Juuso
Control Engineering Group, Faculty of Technology
University of Oulu, Finland

2. MMEA Final Seminar
Helsinki 26 November 2015
Measurements  Applications
• Basis: Measurements
– Microwave, image analysis, LED, ...
– Sampling, dilution, cleaning, uncertainty
– Towards online and process
• Pipelined data analysis
– Scaling functions, recursive updates
• Intelligent analysers (soft sensors)
 Decision support & operating conditions
 Modelling with specific submodels
• Integration to automation & risk analysis
• Smart services
0 10 20 30 40 50 60 70 80 90 100
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
Suspendedsolids
Measured
k-fold cv

3. MMEA Final Seminar
Helsinki 26 November 2015
Monitoring and control
• Image analysis of floc morphology
• Data analysis: nonlinear scaling  indices, limits
• Intelligent indicators
– Scaled values [-2, 2]
– Trend indices
• Plant performance: long windows
• Control + DSS: short windows
• Traffic lights
– Levels &Trends
• Cases: wastewater treatment (WWT) plants
– Pulp mill WWT (Stora Enso, Oulu)
– Municipal WWT (HSY),
• Automation systems  Online (Valmet)
UEF

4. MMEA Final Seminar
Helsinki 26 November 2015
Measurements  Control
• Data analysis
– Limits
• Trend analysis
– Changes
– Trajectories
• Uncertainty
Detection of operating conditions
- system adaptation
- fault diagnosis, maintenance,
- performance, quality
Dynamic simulation
- controller design, prediction
Intelligent analysers
- sensor fusion
- software sensors
- trends
Intelligent control
- adaptation
- model-based
Measurements
- on-line analysers
- DSP
Intelligent actuators
- model-based
Intelligent analyser
(Software sensor)
Controller
Stricter requirements
Capacity increase
Fluctuations
Intelligent + MPC

5. MMEA Final Seminar
Helsinki 26 November 2015
• A generalised norm
• Special cases. Min ... Max
– p=1, Arithmetic mean
– p=2, Standard deviation, rms value
• Variable specific  Pipelined analysis
• Recursive updates
Data analysis: generalised norms
p is a real numberSeparately for each variable x j

6. MMEA Final Seminar
Helsinki 26 November 2015
Generalised moments  Limits
• Skewness (k=3)
– Positive
– Symmetric
– Negative
• Generalised moment
03 
03 
03   
k
X
k
p
p
k
MXE







 

)(
Define orders p for central values
- Linguistic levels
translated into numbers
- Levels represented by
natural language
Levels of adaptation
with time:
- Recalculate norms
- Update orders of the
norms
Scaled values [-2, 2]

7. MMEA Final Seminar
Helsinki 26 November 2015
Shortage of nutrients
Too much nutrients
High oxygen
Low oxygen
High temperature
Low temperature
High flow
Low flow
Very good
Low reduction
Settling problems
Very good
Warnings
Process states & Limits Traffic lights
All variables with
scaled values [-2, 2]

8. MMEA Final Seminar
Helsinki 26 November 2015
Trends calculated from scaled values [-2, 2]
  



k
nki
j
L
k
nki
j
S
T
j
LS
kX
n
kX
n
kI )(
1
1
)(
1
1
)(
Change of trend index
Trend index

9. MMEA Final Seminar
Helsinki 26 November 2015
Trends in treatment results  Traffic lights
Low
reduction
Settling
problems
Very good
Very good

10. MMEA Final Seminar
Helsinki 26 November 2015
Dynamic models
Water treatment
Fuzzy LE blocks
BioMass
Load
- Load
- Nutrients
- Oxygen
- Temperature
Condition of
the biomass
All variables with
scaled values [-2, 2]

11. MMEA Final Seminar
Helsinki 26 November 2015
Measurements  Automation
 Risk Management
Measurements
Intelligent
analysers
Risk
Management
Environment
Weather
Hydrological forecasts
Processes
Data processing chain
• Data quality
• Uncertainty handling
• Anomaly detection
Open data (weather)

12. MMEA Final Seminar
Helsinki 26 November 2015
Wastewater Treatment
Control
Decision making
Control
Decision making
Process control
Decision making
Modelling
Risk identification
Risk analysis
High-level control
Diagnostics
Performance analysis
Enviromental measurements
Adaptation
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Measurement
technology
Process
Measurements
Modelling
Open data
Data Management
- Data Sources
- Processing
- Testbed
Weather observations &
forecasting
Quality control & anomaly
detections
Data operator & data sources
EE Services
Concepts
Monitoring and management framework
for early risk management
EE Management
- Monitoring methods
- Decision Support
Environmental management
Monitoring methods and tools
Decision support systems
Remote Sensing
- Radar
- Lidar
- Airborne
Measurements
•- Solution studies
•- High performance
• on-line monitoring Fouling and
contamination
Wastewater
measurements
Atmospheric boundary
layer sensing with radar,
lidar & airborne
instruments
Low-cost sensors in
water analytics
Probabilistic nowcasting
Process insight, weather, water balance
Intelligent analysers: traffic lights, trends
New measurements
Global
markets
Situation awareness

13. MMEA Final Seminar
Helsinki 26 November 2015
Smart Applications in Industrial Internet
Thing
Thing
Thing
Act!
Store,
analyse,
refine,
etc.
Local integrated applications!
Utilise!
Local processing
Efficient local use
Less data transfer
Digitalisation & Clouds
Things
Services
Control
Decision making
Control
Decision making
Process control
Decision making
Modelling
Risk identification
Risk analysis
High-level control
Diagnostics
Performance analysis
Enviromental measurementsAdaptation
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Intelligent analyser
(Software sensor)
Measurement
technology
Process
Measurements
Modelling
Open data
GSPC & Trends
I2oS3IoT
Experts

14. MMEA Final Seminar
Helsinki 26 November 2015
Conclusions
• Measurements  real-time use
– Sampling  Laboratory analysis (uncertainty)
• Compact solutions for intelligent analysers
• Combine measurements + trend analysis + GSPC
• Monitoring  Control & Optimisation
• Forecasting + Risk identification
• Situation awareness
• Smart services
Environment
WWTP
Active sludge
Open data
Participatory
observations