Jungle AI - Case study

Wind energy

Avoiding downtime by early detection of generator bearing imbalance

This case study outlines how Canopy helped detect and track bearing overheating until the next planned maintenance, avoiding downtime. Read the full case to find out how much was gained in increased production.

Read the full case study

Fill in the form to download the case study and
find out more on this customer case:

Thank you! Download the case here:

Download

Oops! Something went wrong while submitting the form.

Read other cases

Strengthening icing detection for enhanced solar farm performance

Canopy’s analysis uncovered significant farm-wide underperformance caused by icing.

Find out more

Maximising performance: the solution to Repsol's grid curtailment

Canopy’s performance models identified and quantified all periods of grid curtailment and losses.

Find out more

Early detection of clogged filter avoids factory downtime

Canopy identified an abnormal temperature increase caused by a clogged filter in galvanised steel production.

Find out more