Fault Detection and Diagnostics for Rooftop Air Conditioners

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faults, which requires tremendous data for different load levels, fault levels and types. For
complicated problems with many fault types and levels and operating conditions, it is
difficult, if not possible, to gather so much data. So recently there seems to be no research
on ANN for HVAC FDD. It should be clarified that although it is difficult to directly use
ANN to do FDD, it is very useful to use ANN to build fault-free reference models for
model-based FDD.
Finally, in the literature of HVAC FDD, some researchers (Salsbury & Diamond
2001, Liu & Dexter 2001) attempted to deal with FDD in control loop problems or use
the information from the controller to do FDD.
1.2.3 Summary of Literature Review
So far, online FDD for HVAC is primarily at the laboratory or field demonstration
stage and commercialization of FDD is a big challenge, since many practical and
economic issues should be addressed. In particular, none of the previous methods can
handle multiple simultaneous faults, which limits their applicability. The SRB FDD
method was one of the first comprehensive techniques applied to packaged air
conditioners and was the most extensively validated through experimental testing.
Significant contributions of this work included:
1. The method was validated by experimental tests and shown to have reasonably
good performance in handling individual faults.
2. The method only requires nine low-cost temperature measurements and one
humidity measurement, which is vital for practical use and commercialization.
3. This work was the first to introduce fault evaluation to HVAC&R equipment FDD
and four fault evaluation criteria were introduced.
4. A detailed simulation model was developed and used to test FDD methods.
5. The method involved the successful conversion of an infinite-classification problem
into multiple single-classification problems.
6. The work laid a blueprint for later research.