a real time event detection system for wwtp protection · 10/16/2009 · a real time event...
TRANSCRIPT
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A Real Time Event Detection System for WWTP Protection
Roger O’HalloranWater Quality Information Collection System Project
17 August 2009
Urban Water Security Research Alliance
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Overview of this presentation
• Brief introduction to requirements for real- time monitoring in PRW system
• Describe development of a novel system to reliably detect contamination events in real-time in a range of effluents
• Show some interesting results• Outline future directions
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PRW Monitoring Requirements
• To ensure safe operation of the PRW system, reliable monitoring is essential– Within each barrier
• To ensure process control and optimal performance
– Between each barrier• To ensure treated effluent meets requirements for
the subsequent barrier
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Desired outcomes by end-users
• Advanced water quality monitoring technologies– provide continuous water quality information
in real-time– enable operators/grid managers to manage
potential risks at the earliest possible barrier/control point
– further improve the level of control, thereby better safeguarding treatment plant operation
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PRW Monitoring Requirements
• The monitoring system must: – detect potentially harmful events with a low error rate
(false +/-)– respond in near real-time– have minimal calibration and maintenance, and low
ongoing costs– be user friendly
• automated data analysis/event alerts• self-diagnosis of faults• suited for use by non-scientific staff (blue overalls rather than
white coats!)
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Typical online WQ monitoring systems
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Technical Challenges
• Most existing online sensors/sensing systems perform well in the laboratory environment for pre-treated samples
• A limited number have demonstrated satisfactory performance in field environments
• None has demonstrated satisfactory performance in a difficult sample matrix such as raw sewage
• Wastewater sources are highly diversified – Compositions/matrix are complex, consisting of countless
inorganic, organic and biological compounds– Real-time quantitative detection of even a small fraction of these
compounds is practically impossible due to both technological and economic reasons
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Monitoring Requirements
• Commercial online systems are all based on sensors designed for operation in a strictly controlled matrix– pH, ionic strength, purity, etc– with continuous field measurements it is impractical to artificially
manipulate sample matrix: an intrinsic flaw in the methodology
• Sewage is a highly fouling and variable medium which is far removed from the designed operating conditions of chemical sensors
• To our knowledge, no commercially available water quality monitoring system currently in operation is capable of effectively and reliably detecting significant sewer discharge events.
• What, then?
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Research Plan: Approach and Methodology
• Traditional approach is to collect and analyse individual samples to determine the quantity of a known substance– results must be known precisely to allow comparison with other
samples– compare results to predetermined criteria to determine
performance compliance • For end users, the measured value allows decisions to
be made about the system that was sampled, e.g. for the final effluent of a WWTP:– Does the effluent meet regulatory requirements? – Can it be discharged? – Is the plant functional and operating within desired control limits?
• For end users the ultimate purpose of an analytical measurement is to determine performance compliance of their system
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Performance monitoring using event prediction
• We propose a different approach– Use a number of online sensors that each give a
different picture of the sample– Look at overall sample matrix rather than individual
components– Record the results continuously– The time trace gives a picture of the state of the
system– Normal system behaviour becomes evident by
observation for a significant time – Abnormal events can be easily recognised by
comparison to the baseline
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Online flow-through sensor system
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Online sensor baseline patterns
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Performance monitoring using event prediction
• System characterisation is now determined by the detection of events
• Because we are looking for changes, the absolute value of the sensor readings is not so important
• We determine if the system is subject to ‘abnormal’ conditions that have significantly changed the sample matrix
• We detect these events using several off-the-shelf sensors in combination to give an overall picture of the sample matrix
• Using this approach, we can characterise a sample without the need to fully rely on the accuracy of the measured sensing signal
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Performance monitoring using event prediction
• The essential system requirements are:– A sensing platform incorporating multiple sensors, i.e., primary
(PS), secondary (SS) and indicative (IS) sensors– Sensors must be able to
• physically tolerate the sample matrix conditions• Ideally, should be self-contained, requiring no added reagents • should respond to one or more physicochemical aspects of sample
matrix change – Matrix change information required for sample characterisation
can be collectively represented by the analytical signals obtained from the selected sensors
– The analytical signals from all sensors must be acquired continuously and simultaneously in real-time
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Analytical signal correction
Matrix Recognition Sensors Indicative Sensor
Sample
Data Collection and Processing
Setup ReferenceValue
Matrix Correction
Ana
lytic
al S
igna
l
Concentration
?
Ideal signal
Measured Signal
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Development of event detection system
• Focus on the first 2 barriers, which are responsible for most of the waste removal:– Sewer discharge / catchment– Wastewater Treatment Plant
• Major discharges must be detected before they can compromise treatment plant performance
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Current System Configuration
• 6 self-contained sensing probes (temperature, pH, conductivity, DO, ORP, turbidity)
• Temperature sensor is used as a PS to calibrate other sensors
• pH, conductivity, DO, ORP, turbidity sensors are SS/IS
• Sensing signal baseline can be used as the reference
• Allows inter-sensor calibration/correlation
• Installed at Bundamba WWTP (Ipswich)
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Diurnal patterns and baseline stability
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A significant discharge event
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Sudden matrix change
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Tem p °CD OC ondu ctivity m SpHTurb id ity NTU
Sudden matrix change
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Zoom in to the discharge event
Sudden matrix changeSudden matrix change
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Another (industrial?) discharge event
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Effect of the event on effluent quality at Barrier 2
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Effect of heavy rainfall and catchment overflow
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Work in progress
This FY (09/10):– Development of mathematics module
• Detect events using baseline, slope, magnitude and duration
– Refinement of flow manifold• Optimised cleaning using wall jet flow
– Source new sensors
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Future directions
Phase 2:• Development of real-time
event detection system• Further development and
applications to other barriers
• Real-time event detection network.
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Acknowledgements
• Ipswich Water• Research Team• Support from the UWSRA and the Queensland
State Government
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Thank you
www.urbanwateralliance.org.au