Study on fault identification rules for real refrigerant leakage in R290 room air conditioner based random forest algorithm

Authors：Yang, Jie; Wu, Jianghong^*; Yu, Xinyu; Liang, Yongbiao

Source：EXPERT SYSTEMS WITH APPLICATIONS, 2024, 238: 122126.

DOI：10.1016/j.eswa.2023.122126

• R290 room air conditioner
• Leakage
• Fault identification
• Rules

As global warming continues to cause environmental concerns, finding alternative refrigerants is a current research focus in the refrigeration industry. R290 has desirable physical properties as a refrigerant, but its flammable and explosive nature restricts its usage. In this study, the authors designed a real refrigerant leakage experiment for an R290 room air conditioner based on the latest international standard, IEC 60335-2-40-2022. The experiment system was in a professional explosion-proof enthalpy difference chamber refrigeration. Leakage experiments were conducted under minimal, rated, and maximal operating refrigeration conditions, with a maximum leakage of 30% of the rated charge. To identify refrigerant leakage faults, the authors developed a feature parameter selection method based on the random forest algorithm variable importance measures coupled with the Pearson correlation coefficient. They then used a genetic algorithm to optimize the parameters in the random forest algorithm and obtained an optimal parameter set to establish a random forest fault identification model. With 35 fault identification rules extracted, the accuracy of the test set was 91.5%. To confirm the suitability of the fault identification rules for the entire operation of the R290 room air conditioner, 23 nonmodeled experimental data sets were used, resulting in an accuracy rate of 91.3%. As a result, this study concludes that the fault identification rules proposed in this paper can be applied to the real operating conditions of the R290 room air conditioner.