Building management system with machine learning for detecting anomalies in vibration data sets

A method for correcting abnormal operation of equipment, the method comprising:

• obtaining a vibration data set comprising vibration measurements recorded by one or more vibration sensors while operating the equipment during a time period;
• analyzing the vibration data set using one or more machine learning models to identify the operation of the equipment as normal or abnormal;
• generating model reasoning indicating a reason why the operation of the equipment is identified as normal or abnormal by the one or more machine learning models;
• and
• initiating a corrective action responsive to identifying the operation of the equipment as abnormal, the corrective action based on the model reasoning.

A controller for correcting abnormal operation of equipment, the controller comprising one or more processing circuits configured to:

• obtain an operating data set comprising measurements recorded by one or more sensors while operating the equipment during a time period;
• obtain operator comments comprising observations from an operator characterizing operation of the equipment during the time period;
• analyze the data set and the operator comments using one or more machine learning models to identify the operation of the equipment as normal or abnormal;
• and
• initiate a corrective action responsive to identifying the operation of the equipment as abnormal.