Leaks in Gippsland Water (GW) have historically been complicated to detect using existing flow data models. GW was looking to trial a different, real-time method of detecting common failure modes, utilizing their existing remote telemetry system, data stored in the PI System and time-series analytics provided by Seeq Workbench.
While exploring this use case on defined assets, leak events were classified by Nukon into two main categories:
Short term leaks with high step-change in flows due to main breaks
Long-term leaks, which were slow leaks due to cracks in pipes
This session will cover the approach and challenges of reliable, early detection of anomalies to create a real-time, asset-specific leak detection model which can be applied at scale.
Speaker
Andrew May
Andrew May, Principal Consultant - Utilities
Andrew has more than 15 years experience in Systems Engineering, MI/MES design, control system design, historians, time-series analytics, machine learning and commissioning within the utilities, process, mining, oil and gas, automotive, food & beverage, critical infrastructure and manufacturing sectors.
Andrew specialises in Business Optimisation as part of the Nukon Senior Leadership team, helping businesses understand and implement their strategic vision using technology, delivering innovative and awesome projects for customers.