Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4991285 | Applied Thermal Engineering | 2017 | 11 Pages |
Abstract
The enhancement of fault detection and diagnosis (FDD) strategy for air-conditioning system is always a complex difficulty. In previous studies, the virtual refrigerant charge (VRC) sensor method and principal component analysis (PCA) based exponentially-weighted moving average (EWMA) method were proposed to identify refrigerant charge faults for variable refrigerant flow (VRF) systems, respectively. However, both methods had defects in some cases. On the basis of complementary advantages, this study employs the VRC model to detect the undercharge faults as it shown outstanding efficiency on identifying undercharge cases. Similarity, the PCA-EWMA model is used to detect the overcharge faults, since it is very sensitive to the little variation in the overcharge situations. Further, a novel online refrigerant charge fault diagnosis strategy is proposed based on two fault detection methods, i.e. VRC method and PCA-EWMA method. The new hybrid model overcomes the defects of two previous methods appropriately and well inherits the advantages of both. Finally, the robustness of the proposed refrigerant charge fault diagnosis strategy is verified using the experimental data and online data collected from different type of VRF systems.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Fluid Flow and Transfer Processes
Authors
Jiangyan Liu, Guannan Li, Huanxin Chen, Jiangyu Wang, Yabin Guo, Jiong Li,