Training the Asset Baseline

Click

Start Training & Monitoring

. The user will see the progress bar begin to populate as data is acquired from the variable frequency drive.

The application will create a new model at each half hertz increment of the operation speed. The model is automatically switched by reading the command frequency of the drive. Once the number of training iterations is acquired, the given frequency bucket will automatically switch from training to monitoring. Multiple frequencies can be trained in parallel depending on the variability in speed of the application. FactoryTalk Analytics GuardianAI is designed to switch automatically across frequencies between training and monitoring.

While the asset is in training, the user will not be able to edit the configuration of that asset. To make any edits, the user should click

Stop Training & Monitoring

.

Stop Training & Monitoring will stop training and monitoring the asset. Once the user stops training, any frequency bucket in progress will be reset back to 0%. Frequencies that were already fully trained are preserved and will resume monitoring once the user starts training again.

A dialogue box will prompt the user to accept the in-progress buckets reset and confirm the action.

The user should stop training to make any edits to the drive configuration.

Re-training an asset can be important if a major physical change is made to the system. An example might be replacing the motor or full re-alignment of a coupling. FactoryTalk Analytics GuardianAI starts the training process under normal conditions, but it is possible there was already existing degradation at the time the baseline was acquired. In this scenario, the application will monitor further degradation from baseline. If a user makes a major physical change without re-training, there is a possibility that FactoryTalk Analytics GuardianAI will view normal operation as anomalous behavior. If too many false positives are detected after a major maintenance event, then FactoryTalk Analytics GuardianAI should be re-trained to acquire a new baseline of the asset’s behavior.