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

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

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

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

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!)

Typical online WQ monitoring systems

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

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?

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

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

Online flow-through sensor system

Online sensor baseline patterns

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

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

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

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

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)

Diurnal patterns and baseline stability

A significant discharge event

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Sudden matrix change

Zoom in to the discharge event

Sudden matrix changeSudden matrix change

Another (industrial?) discharge event

Effect of the event on effluent quality at Barrier 2

Effect of heavy rainfall and catchment overflow

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

Future directions

Phase 2:• Development of real-time

event detection system• Further development and

applications to other barriers

• Real-time event detection network.

Acknowledgements

• Ipswich Water• Research Team• Support from the UWSRA and the Queensland

State Government

Thank you

www.urbanwateralliance.org.au