HWM is pleased to announce the next step in our continual improvement journey; the introduction of our new Electrical Noise identification function. 

Driven by AI technology and complex algorithms, PermaNET Web can now automatically identify and categorise electrical noise in leak audio recordings.  Electrical noise identification will indicate (as a percentage) the amount of noise in a single leak audio recording that can be attributed to electrical noise harmonics.

When the user-defined threshold is breached, the electrical noise calculation is displayed in PermaNET Web as a label against the PermaNET device.  Users are given the option to confirm or reject the label and to adjust the logger accordingly.

We have developed this feature for PermaNET Web to support leakage teams in more quickly identifying ‘false positives’ and to support optimisation of field resource and network performance  through evidence-based decision-making.

Using complex algorithms to identify and reduce ‘false positives’ will help to cut the wasted time and costs associated with the site visits to investigate leakage alarms.  These resources can then be more efficiently directed to reduce leaks in other areas.

By using the Electrical Noise identification tool in conjunction with our ‘new leaks’ priority report (which highlights loggers to ignore as false positives). the speed from alarm to pinpointing can be significantly increased, reducing unnecessary analyst time, whilst saving money and water.

For more information about leak detection monitoring with PermaNET please click here.