Leak detection for high consequence pipelines to identify small emerging leaks and avoid significant failures which can have devastating effects
At Syrinix we understand just how important it is to manage risk on critical pipelines.
With our sophisiticated acoustic technology coupled with signal processing optimised for leak finding, we support utilities with the provision of leak detection on trunk mains.
Pairs of PIPEMINDER-T devices incorporating both a hydrophone and a geophone are deployed on the pipe performing acoustic correlation along the installed length.
Multiple sets of acoustic data are collected, reviewed and monitored via RADAR, and confidence based alerts, with built in false positive mitigation are reported.
Depending on the criticality of the monitoring site, PIPEMINDER-T systems can either be left in situ for complete 24/7 coverage or can be moved to other pipelines. The addition of pressure monitoring sensors at shorter intervals on the trunk main also enhances understanding of how the pipeline is operating.
Trunk water mains are described as the 'motorways' of the water network: large pipes of 18" diameter or larger, carrying significant volumes of water.
These pipelines present a far more challenging environment for vibro-acoustic leak finding than smaller service mains.
A burst trunk main would cause significant and likely catastrophic damage to homes and businesses, traffic disruption, and loss of water supply.
Water infrastructure is aging and it is the responsibility of each water company to look into ways to increase pipeline resilience, and therefore customer satisfaction.
Syrinix can work with you from pre-installation surveys, planning the deployment and position of sensors, to advising on levels of required analysis. Talk to us about how we can help you to manage your pipeline risk.
New and improved RADAR interface delivers intelligence and alerts
Business response update on the rapidly changing COVID-19 / Coronavirus situation
Syrinix Inc move to a permanent base in Henderson, Nevada
