IConIC learns the ‘signature’ of what a healthy system looks like in a specific environment, with the potential to pinpoint specific faults depending on how the signature changes.
IConIC’s health score is based on analysing how close the system is to a healthy/unhealthy boundary, generated during a brief training phase. A score of zero represents this boundary, with a positive score indicating good health, and a negative score indicating poor health.
This can then be portrayed visually to engineers so they can quickly determine the health of specific cylinders, pumps or drive-trains.