Frost Porosity Measurement Using Capacitive Sensor

Frosting is a dynamic process because of the changes in the frost-air interface temperature as the frost layer grows. The frost properties, such as frost density and frost porosity, are highly dependent on the frosting conditions and vary with time even under a constant environmental and operational conditions. Precise detection of frost properties is important for understanding frosting mechanisms and predicting frost growth, and it is also important for defrost control in many applications. So far there have been very few research reports on dynamic frost porosity measurement, and most work reports an average measurement approach, which is undertaken by measuring the mass and volume within certain frost accumulating period to estimate the averaged frost properties. Those approaches ignore the temporal variation of frost properties with an assumption that the frost buildup at a constant porosity, at least within a certain time period. As the result, there is a distinct deviation between different frost models, because as a very important input of models, most empirical frost porosity correlations were based on different time intervals of measurement. Frost, as a mixture of ice crystal and air, could have its properties estimated based on the percentage of each component. In this work, a capacitive sensor is developed to detect the capacitance variation as frost growing, which together with the dielectric constant of ice and air, could be used to determine the temporal porosity according to the Maxwell-Garnett (MG) theory. An interdigital electrode designed in this work is fabricated using photolithography technique (shown in Figure 1), together with the PCB connector and a commercial digital converter (FDC 2214) can sense the capacitance reading with a 0.0001 pF resolution. 3-D printed Polyvinyl-chloride porous structure with controlled porosity filled with/without gelatin of different concentration (shown in Figure 2) has been used to valid the sensor’s responding function. Frost porosity was measured under different conditions with known sensor function and the empirical correlation of frost porosity is provided in this work and compared with existing work. This work presents a new method to dynamically detect the frost porosity as frost growing, and it is a big contribution to the mass-based defrost strategy development and frost growth modeling