Improvements in data logging technology for the past 10 years have significantly improved water companies’ awareness of pressure transients on their network. However, as an industry we are still understanding their causes, how best to monitor for them and the impact that they can have on asset life.
Whilst significant transients can cause immediate bursts on water networks, we also need to be conscious of the impact that smaller, more frequent transients have to damage our assets.
What's the solution?
Our approach includes using a variety of data sources to identify both the causes of transients and the effects these transients can have on water networks. By correlating these two types of data, we can identify areas of a client’s water network most likely to be affected by transients and direct field teams to investigate areas where we have a high confidence of finding the causes of transients.
Our data science led analysis of transient data allows us to identify where the same transients are occurring on water networks across a wider time range, for example where the same customer behaviour occurs on a regular schedule or a PRV consistently fails to perform at low flow. By categorising transients in this manner, their causes can be identified, understood, and prioritised for resolution.
As our analysis continues, we are building an ever-greater understanding of transient types and a standard library of shapes, allowing us to identify root causes based on the transients created. This allows us to deliver faster insight for our clients and prioritise transients based on the risk they pose to our clients assets.
Our analysis tools allow clients who are looking to reduce bursts on their network to proactively identify and understand the causes of those bursts. By resolving these causes through transient investigation, clients can achieve a meaningful reduction in leakage in the areas affected.
We are working with our clients to understand the impact that transients have on their networks and the most cost-effective approach for the long-term monitoring of transients, allowing them to achieve and maintain calm networks without breaking the bank.