• Silva, Pedro
• Aguiar, Martim Lima De
• Gaspar, Pedro Dinis

Abstract

It is widely known that the defrosting operation of evaporators of commercial refrigeration equipment is one of the main causes of inefficiency on these systems. Several defrosting methods are used nowadays, but the most commonly used are still time-controlled defrosting systems, usually by either electric resistive heating or reverse cycle. This happens because most demand defrost methods are still considered complex, expensive, or unreliable. Demand defrost can work by either predicting frost formation by processing measured conditions (fin surface temperature, air humidity, and air velocity), operative symptoms of frost accumulation (pressure drop and refrigerant properties), or directly measuring the frost formation using sensors (photoelectric, piezoelectric, capacitive, resistive, etc.). The data measured by the sensors can be directly used by the system but can also be processed either by simple algorithms or more complex systems that use artificial intelligence and predictive methods. This chapter approaches frost sensing and prediction for command of demand defrost systems.

Topics

• impedance spectroscopy
• surface