Low Runtime Approach for Fault Detection for Refrigeration Systems in Smart Homes Using Wavelet Transform

This work investigates the efficiency of a fault detection system for refrigeration equipment based on Wavelet Transform. To perform the task, we used the well–known database REFIT (Personalised Retrofit Decision Support Tools for U.K. Homes using Smart Home Technology). We used data from six devices presented in three households of the database considering readings of active power as features. The results revealed an approach with high efficiency in detecting abnormal behavior of the tested appliances and presented low runtime despite large volumes of input data. Another positive point to highlight, in the proposed method, is the capacity to estimate the instants at which faults start and cease to occur. Considering the viewpoint of consumers, obtaining knowledge about the malfunctioning of household appliances enables timely repairs, resulting in financial savings and improved overall quality of life. Moreover, by setting parameters according to the characteristics of the appliances, the proposed method is suitable for different equipment, thereby establishing feasible fault detection for diverse groups of devices.