Systems and Methods for Detecting Malfunctions in Refrigerant Based Systems based on Changes in Measured System Metrics

A system, comprising:

• a temperature sensor externally mounted to a line, of a refrigerant loop, that couples components of a refrigeration device;
• and
• a monitoring device, in communication with the temperature sensor, including one or more processors for performing functions of (i) sampling the temperature sensor and generating temperature readings of the line, (ii) analyzing the temperature readings, over time, at start and stop instances of operation of the refrigeration device;
• and (iii) outputting an indicator of a refrigerant leak or malfunction of the refrigeration device based on analyzing the temperature readings at start and stop instances of operation of the refrigeration device.

A method, comprising:

• sampling a temperature sensor that is externally mounted to a line, of a refrigerant loop, that couples components of a refrigeration device and generating temperature readings of the line;
• analyzing the temperature readings, over time, at start and stop instances of operation of the refrigeration device;
• and
• outputting an indicator of a refrigerant leak of the refrigeration device based on analyzing the temperature readings at start and stop instances of operation of the refrigeration device.

A method, comprising:

• sampling a temperature sensor that is externally mounted to a line, of a refrigerant loop, that couples components of a refrigeration device and generating temperature readings of the line;
• sampling current and voltage monitors attached to the refrigerant device to collect continuous power consumption data;
• combining data from the temperature sensor, power consumption data and retrieved outdoor air temperature data in a machine learning algorithm to identify anomalous behavior;
• utilizing frequency analysis on the power consumption data, when computed directly on the device;
• and
• using the data from the temperature sensor and the power consumption data to diagnose the anomalous behavior before reporting a leak or failure.