A Fault Detection and Diagnostics (FDD) tool continuously identify faults and efficiency improvement opportunities through a 1-way interface to the building automation system and application of automated analytics. It is estimated that 5-30% energy saving can be achieved by employing FDD tools and implementing efficiency measures based on FDD findings. Although the potential of this technology is high, currently, an action is always required to correct the faults to generate energy savings. However, a subset of faults can potentially be addressed automatically by the system without operator intervention. Automating this fault "correction" can increase the savings generated by FDD tools. This presentation describes innovative fault auto-correction algorithms for HVAC systems. When the auto-correction routine is triggered, it overwrites control setpoints or other variables (via BACnet protocol) to implement intended changes. The presentation also showcases the field study of fault auto-correction algorithms implemented in two commercial FDD platforms and tested in four buildings.

Learning Objectives:

1. Identify the current state of the art in fault detection and diagnostics.
2. Describe the value proposition of fault detection and diagnostics.
3. Summarize the comprehensive set of fault auto-correction algorithms designed to be  integrated with commercial FDD tools.
4. Detail the performance and efficacy of automated fault correction.