We run complex rules over your buildings data in real time to automatically detect and diagnose mechanical HVAC faults and anomalies in building conditions and energy usage. This allows our platform to alert you and your maintenance team on critical issues, where they are, what they are and how to rectify them.
The first stage of fault detection is the detection of anomalies or unwanted behaviour in real time using continuous monitoring and sophisticated algorithms.
The next stage in the process is to identify the reason for the fault and its location, this step in the process makes use of complex rule layering in order to come out with the most logical root cause.
Finally, the software quantifies and creates a priority list of items to act on. Having a priority, cause and location of the issue means the maintenance team is armed with the exact knowledge needed to fix the issue(s) as fast as possible.
FDD aims to help achieve optimum control and early fault detection (and correction) of a building's services, heating, ventilation and air conditioning systems. Such an approach can lead to a substantial reduction in unnecessary energy use, improvements in sustainability as well as overall occupant satisfaction in the conditioned environment.
BMS alarms are used for one dimensional checks against a paricular sensor or mode of operation. While they have their uses, they tend to create noise and only tell when something critical is happening. FDD is more sophisticated as it can be layered to utilise multiple checks across multiple systems to identify a developing pattern or a complex behavior and a root cause. Its value is in being able to rule in and out conditions to quantify a problem, its effect and cost.
Yes all outputs from the fault detection can be automatically ingested into various Maintenance Management software packages either via email based ticket creation or API calls (if available).
We have encountered many examples of mechanical issues, strategy issues and energy wastage across the sites we have connected to. These included passing heating valves, simultaneous heating and cooling, cycling of dampers, poor heat recovery and out of hours operations. Our case study library contains concrete examples of this in action.