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Machine Learning

How we use machine learning techniques to interpret data.

Interested? Read on, or enter details for further info or to book a demo.

    Save time, resources and recognise patterns

    One diligent US utility was overloaded with incoming transient data and wanted a way to quickly assess event importance.

    They briefed Syrinix to create a system that could automatically classify the type of transient and alert by exception for unusual events.

    Transient alert
    Transient alert - due to closing valve

    “Shape classification allows users to see what events are produced daily, how the events change as the network activity changes, and how various transients propagate around the network.

    It’s about understanding what’s going on in a network and either mitigating it, highlighting new and uncommon events, or both. The benefit to the customer is ongoing; by keeping an eye on the classifications, it can inform the user of how changes they make to their network change the common transients"

    Alex Forbes, Hydraulic Analyst - Syrinix

    Shape Classification uses pattern recognition to compare and classify transient waveforms against an exemplar set of reference transients that are derived from that network.

    By classifying similar shapes into actions, like a pump stop or pump start, Syrinix Intelligence can identify which are everyday events and which are more important.

    This advanced level of intelligence prevents investigative time and resources from being unnecessarily spent on common network events.

    The Syrinix team run an algorithm which looks for all the transients detected in a group of PIPEMINDER devices hydraulically linked, and groups them in clusters according to their shape

    Contact us for more examples and a conversation on how we can make this work for your water utility.