Systems and methods for predicting refrigerant leakage of a critically charged hvac/refrigeration system

A system for predicting a leak of a HVAC/Refrigeration system, the system comprising:

• a critically charged HVAC/Refrigeration system configured to circulate a refrigerant to cool a space;
• and
• processing circuitry configured to:
• obtain subcooling data from the critically charged HVAC/Refrigeration system;
• predict a leak event by providing the subcooling data as an input to a neural network, the neural network trained using historical data of one or more subcooling parameters of a plurality of critically charged HVAC/Refrigeration systems;
• and
• operate a display to provide a notification to a technician or a manager regarding the predicted leak event at the critically charged HVAC/Refrigeration system.

A method for leakage prognostic of a critically charged HVAC/Refrigeration unit, the method comprising:

• equipping a critically charged HVAC/Refrigeration unit with instrumentation to measure performance data and mechanical health data of the critically charged HVAC/Refrigeration unit;
• identifying leakage events of the critically charged HVAC/Refrigeration unit based on the performance data and the mechanical health data of the critically charged HVAC/Refrigeration unit;
• performing a root cause analysis of the critically charged HVAC/Refrigeration unit;
• building a root cause database using results of the root cause analysis, the root cause database comprising root causes of leakage events and associated performance data and mechanical health data;
• and
• using machine learning and the root cause database to predict if a specific critically charged HVAC/Refrigeration unit will experience a leakage event in the future based on obtained performance data and mechanical health data of the specific critically charged HVAC/Refrigeration unit;
• wherein the performance data comprises subcooling data, and the mechanical health data comprises power consumption data.