Tracking the Health of City Utility Assets

Sydney Water is the largest water utility in Australia, supplying water and treating sewage for the four million residents of Sydney, the Illawarra and the Blue Mountains. One of the facilities that Sydney Water Corporation (SWC) operates is responsible for processing nearly half of the city's sewage.

Five raw sewage pumps (RSPs) keep the facility running. Large, two-story pumps, with one-megawatt (MW) motors, drive the sewage through the plant. After raw sewage is subjected to screening and grit removal, the RSPs lift the flow into chemically assisted sedimentation tanks, which remove smaller particles by “flocculation”. The final treated wastewater then gravitates to a deep-water ocean outfall, roughly four kilometres from the shore.

Previously, condition monitoring of the facility’s plant was carried out manually on a periodic basis — until they installed an online condition surveillance system and tested the concept of online condition monitoring as a maintenance tool.

Accelerometers were connected to five RSPs and three centrifuges at the plant. Surveillance monitors were used to automate data collection. Links between the central control room network server and the running equipment were achieved through the use of Ethernet hubs and fibre-optic cable for the pumps, and a wireless link to the more distant centrifuges.

To pass the monitoring information from the plant control room to Sydney Water’s asset management database server — located 40 minutes away — a transfer station, responsible for storing the collected vibration data, was configured to send vibration data via the corporate wide-area network to the live database every 10 minutes. A user-friendly interface provides a graphical representation of the health of all machinery being monitored online.

Greater visibility of the health of the RSPs and centrifuges, and regular analysis performed online are the immediate benefits. By having the online monitoring 24 hours a day, 365 days a year, they are able to detect changes that may be a trigger for a potential failure.

The greater effectiveness in maintenance planning could translate into a 10 percent to 15 percent overall saving in maintenance costs for these units.

- A A. Bhaduri