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If the expected vibration behavior (as indicated by RMS and peak-to-peak values of acceleration and velocity) is well understood for the asset being monitored, then the Vibration Threshold Policy (LINK) provides a good solution for monitoring. However, when the expected vibration behavior is not well understood, the Motion Condition Policy can be a good tool for detecting changes in vibration state that may be indicative of a faulty condition. The machine learning algorithm utilized can be considered an anomaly detection algorithm (in the machine learning world), or a fault detection algorithm (in the condition monitoring world). The algorithm uses the time domain metrics calculated on the beacon (RMS and peak-to-peak of acceleration and velocity) to establish a baseline and produce subsequent alerts.
The following steps assume that the beacon was configured according to the standard installation instructions (LINK) (using the template: 'Default Beacon Template: Condition Monitoring AI'). It should be understood that the although the beacon needs to be configured properly to be compatible with the Motion Condition Policy, the beacon configuration itself is independent of any policies setup in Bluzone. This means that several Motion Condition Policies can be created for a single beacon, and any changes made to these policies will not affect the data that the beacon produces.
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