Dynamic model-based fault detection and diagnosis residual considerations for vapor compression systems

This paper presents a first look at the dynamic impact of faults on vapor compression systems. Low-order control-oriented dynamic models of subcritical vapor compression cycles are used to develop sensitivity tools that enhance the residual design procedure of dynamic model-based fault detection and diagnosis algorithms. Also, experimental results are presented that confirm the sensitive outputs usefulness in an FDD algorithm. The enhanced fault information carried in the more sensitive signals of a vapor compression system will allow soft faults to be detected earlier, preventing damage to critical system components