Analytical Software Prevents Sewer System Spills

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Using historical data and Seeq analytical software, Nukon calculates when sewer blockages will occur up to 13 hours in advance to prevent spills.

By Andrew May

Following a sewer spill at an environmentally significant site at Midway Point in Tasmania in August 2017, the statewide water utility sought a way to reduce the likelihood and impact of future spill events. To do this, they needed a way to predict future sewage spills, with plenty of notice so preventive measures could be taken.

The water system has 970 water and sewage pumping stations. A portion of these are high-risk sites where spills have occurred in the past. The system also has 176,000 sewer connections across the state and suffers about 2,000 sewer mains breaks and spills per year.

Having previously worked with the utility on its process historian data management system, Nukon was asked to identify and provide a proof-of-concept for an online sewer blockage detection system. Nukon aims to be the preferred partner in unlocking data for decisions that matter.

Analyzing the Data

Using Seeq to analyze data from the process historian, Nukon developed and tested a model based on data from the Midway Point spill event in August 2017. The goal was to see if the model could detect the blockage faster than current methods.

Using Seeq, it was determined that the best indicator of a blockage event (Figure 1) was the time between pump runs (time to fill). Time to fill is the time it takes for sewage to fill a wet well and alert the pump to start running to clear the well of waste.

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Figure 1: Blockages were detected and the utility notified 13 hours ahead of time.


Using historical data, Nukon identified the fill-and-pump run behavior for two different profiles: on peak and off peak, and weekends and weekdays. Normal fill and pump behavior during these periods were identified for the sewage pumping station site.

The Seeq model identifies blockages by detecting the absence of normal fill and pump behavior in real-time. For example, the absence of pump runs or extended fill time during peak times signifies an abnormality and possible blockage.

Results

The Seeq model detects blockage up to 13 hours before spillage, helping field teams avoid spill incidents by providing real-time early warning of partial or full blockages in the sewer network. The solution is integrated with the utility’s OSIsoft PI System Notifications (Figure 2) for early alerting.

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Figure 2: The Seeq software monitors pump data in real time. If it finds a problem, it tells the OSIsoft PI System software, which issues a notification.


The on-peak/off-peak model was installed as the online sewer blockage detection system for every sewage pumping station in the Midway Point region. Each site’s specific behavior, deviations and grace periods were accounted for to reduce false positives. The utility is pleased because each deployment is quick, low-cost and does not require additional monitoring equipment at sites.

Andrew May is a principal consultant for manufacturing, infrastructure and utilities at Melbourne-based Nukon, where he works with a diverse range of industry sectors and applications, enabling him to appreciate all aspects of control system engineering and pan-business optimization. He can be reached at andrew@nukon.com.au.