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Formalized control logic fault definition with ontological reasoning for air handling units
Abstract 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 components 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 unit (AHU) systems, and 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 these 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 overall precision of 94.2% and recall of 83.0%. This demonstrates the generality of our proposed approach in providing customized control logic fault definitions for different types of AHUs.
Highlights HVAC control logic fault definition needs to be customized for different systems. An ontological reasoning approach is proposed to systematically derive customized control logic fault definition for AHUs. A new HVAC component and control information ontology is developed to support the proposed ontological reasoning approach. A prototype implementation demonstrates the accuracy of the proposed approach with 27 different AHU systems. A complete real-world example is presented to demonstrate the use of the proposed approach.
Formalized control logic fault definition with ontological reasoning for air handling units
Abstract 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 components 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 unit (AHU) systems, and 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 these 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 overall precision of 94.2% and recall of 83.0%. This demonstrates the generality of our proposed approach in providing customized control logic fault definitions for different types of AHUs.
Highlights HVAC control logic fault definition needs to be customized for different systems. An ontological reasoning approach is proposed to systematically derive customized control logic fault definition for AHUs. A new HVAC component and control information ontology is developed to support the proposed ontological reasoning approach. A prototype implementation demonstrates the accuracy of the proposed approach with 27 different AHU systems. A complete real-world example is presented to demonstrate the use of the proposed approach.
Formalized control logic fault definition with ontological reasoning for air handling units
Lei, Xuechen (Autor:in) / Chen, Yan (Autor:in) / Bergés, Mario (Autor:in) / Akinci, Burcu (Autor:in)
19.05.2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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