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Abstract(s)
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.
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Publisher
IGI Global