Timely
detection and elimination of surface condensation is crucial
for diverse applications in agriculture, automotive, oil and gas industries,
and respiratory monitoring. In this paper, a smart patch based on
a ZnO/aluminum (∼5 μm/50 μm thick) flexible Lamb
wave device has been proposed to detect, prevent, and eliminate condensation,
which can be realized using both of its surfaces. The patch is operated
using a machine-learning algorithm which consists of data preprocessing
(feature selection and optimization) and model training by a random
forest algorithm. It has been tested in six cases, and the results
show good detection performance with average precision = 94.40% and
average F1 score = 93.23%. The principle of accelerating
evaporation is investigated to understand the elimination and prevention
functions for surface condensation. Results show that both dielectric
heating and acoustothermal effect have their contributions, whereas
the former is found more dominant. Furthermore, the functional relationship
between the evaporation rate and the input power is calibrated, showing
a high linearity (R
2 = 97.64%) with a
slope of ∼3.6 × 10–5 1/(s·mW).
With an input power of ∼0.6 W, the flexible device has been
proven effective in the prevention of condensation.