Are You Reactive or Proactive When Addressing Your Building’s HVAC Issues?

 
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The differences between Fault Detection and Diagnostics (FDD) and Building Automation Systems (BAS)

Insights by Tim Cramer | Director of Solution Consulting | Key2Act

Imagine this scenario: You are a building owner and you receive a call from a tenant that their space is too cold. It’s the middle of the winter and you need to react quickly before the comfort complaint becomes a dangerous situation. You check your building automation system and it confirms that the space is indeed cold. But what exactly is causing the problem? Is it a piece of equipment? Which one? And what other units might be affected? Who is going to call to complain next?

You call your mechanical services team, but it takes them precious time to come to your site, look for the problem, propose the fix, determine if they have the right parts, and then actually make the repair. Meanwhile, the space (and likely others) is getting colder and colder and colder…

What’s the difference between Fault Detection and Diagnostic Systems and Building Automation Systems?

Fault Detection and Diagnostics (FDD) supercharges the existing BAS with data analytics to proactively identify, diagnose and prioritize problems. FDD goes beyond mere trending and automation and utilizes the data to perform true root cause analysis and diagnostics. This allows us to not only understand what happened, but also why it happened and, more importantly, what to do next. FDD is ideal for proactive identification of maintenance issues, continuous improvement, and operational efficiency of a building’s HVAC system.

Building Automation Systems (BAS) integrate with the building systems and react to current state conditions. A BAS performs simple controls tasks as designed and provide notification when certain thresholds or triggers are met. There are limited data capture and trending capabilities, and BAS is ideal for maintaining day-to-day building operations.

How does FDD provide true diagnosis of specific issues rather than only identifying faults?

There are five ways in which a BAS fails to diagnose and provide the recommended fix when a fault occurs.

1. BAS Validation – Where the tool is objectively validating the proper operation of the BAS. The BAS tends to not be “self-aware” and therefore cannot determine when it is overridden to an improper state, programmed incorrectly or has otherwise failed in its operation, independent of the operation of the controlled systems.  With FDD, we can check the operation of the BAS and even identify problems with its sequences or settings.

2. Multi-symptom analysis – BAS alerts tend to be simple “less than”, “greater than” or “not equal to” calculations to know when values are too high or too low. They rarely layer multiple identified problems as symptoms into one comprehensive diagnosis. This is because BAS alerts are often built at the edge, and each alarm is duplicated across hundreds or thousands of devices making it difficult, or nearly impossible, to build the simple alerts into more comprehensive insights.  FDD puts these symptoms together into a complete diagnosis of the problem, supported by the individual faults.

3. Calculated Value Analysis – BAS tends to operate strictly from available data and rarely calculates predictive metrics from available data sets because it is simply not scalable.  Rewriting these calculations in all their iterations based on varying system, device, and object types is too laborious, so BAS system integrators tend to avoid them.  FDD allows us to scale calculated values from the data available to build even more comprehensive diagnostics.

4. Value Trend Analysis – BAS tends to only look at current state values to determine faults using the simple too high or too low logic. It does not evaluate the effect over time nor take trending data into consideration. FDD allows us to not only evaluate what a value is, but also how it’s been changing, giving us additional insights based on the changes over selected timeframes.

5. System-wide analysis – BAS rarely has a true semantic model to understand what comprises the elements of a system and ties them together in such a way to diagnose a system-wide problem.  This is an enhancement upon the multi-symptom problem, as system-wide analyses are often both multi-symptom and symptoms from completely separate pieces of equipment.  BAS simply doesn’t understand the relationships well enough to be able to draw these kinds of conclusions and cannot scale across sites and system types.  With FDD, we can model all assets in a similar way and write scalable rules that can work across the like assets, simplifying our setup and streamlining our operations.

What’s the next step?

If you are ready to enhance your BAS with FDD, you need a solution like BOB. 

Meet BOB, the world’s first building optimization broker. BOB is a fault detection and diagnostic solution that supercharges your existing building automation system to proactively identify and diagnose problems, and provide a recommended fix to enable your building assets to perform better, increasing the life span of your capital assets and increasing energy savings. To learn more about BOB, visit www.k2a.com/BOB


About the Author:

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Tim Cramer | Director of Solution Consulting | Key2Act

10+ years in HVAC/BAS as a Property Manager (22 buildings), and BAS Service Operations Manager (over 1,500 buildings – commercial, retail, residential)