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Formalized Control Logic Fault Definition with Ontological Reasoning for Air Handling Units

Journal Article · · Automation in Construction

Control logic programs determine the behavior of Heating, Ventilation, and Air Conditioning (HVAC) systems under different operating conditions. Faults in control logic account for more than 15% of all HVAC system problems, causing energy waste and occupancy discomfort. The first step towards systematically detecting and diagnosing control logic faults is to have an unambiguous control logic fault definition so that the existence of control logic faults in an HVAC system can be discovered from its operational data. In order to have high level of fault detection accuracy, the control logic fault definition needs to be customized for different HVAC systems as they have different component information and control sequences. In this paper, we propose an object-oriented classification approach to systematically define customized control logic faults in terms of control logic input/output variable expressions. Focusing on air handling units (AHUs) systems, from their general operation objectives of energy efficiency and occupancy comfort, we elaborated four control goals and developed corresponding reasoning mechanisms to derive fault definitions. We also developed an HVAC component and control information ontology to be used in the reasoning mechanisms by extending existing HVAC information models. The prototype of the developed approach was tested with 27 common AHUs specified by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), and the results show that using the developed approach, it is possible to define a customized set of control logic faults applicable to each specific AHU with an average precision of 94.2% and average recall of 83.0%. This demonstrates the generality of our proposed approach in providing customized control logic fault definitions for different types of AHUs.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1811826
Report Number(s):
PNNL-SA-157539
Journal Information:
Automation in Construction, Vol. 129
Country of Publication:
United States
Language:
English

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