Browsing by Author "Delgoshaei, Parastoo"
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Item Framework for Knowledge-Based Fault Detection and Diagnostics in Multi-Domain Systems: Application to HVAC Systems(2017-11-13) Delgoshaei, Parastoo; Austin, MarkState-of-the-art fault detection methods are equipment and domain specific and non-comprehensive. As a result, the applicability of these methods in different domains is very limited and they can achieve significant levels of performance by having knowledge of the domain and the ability to mimic human thinking in identifying the source of a fault with a comprehensive knowledge of the system and its surroundings. This technical report presents a comprehensive semantic framework for fault detection and diagnostics (FDD) in systems simulation and control. Our proposed methodology entails of implementation of the knowledge bases for FDD purposes through the utilization of ontologies and offers improved functionalities of such system through inference-based reasoning to derive knowledge about the irregularities in the operation. We exercise the proposed approach by working step by step through the setup and solution of a fault detection and diagnostics problem for a small-scale heating, ventilating and air-conditioning (HVAC) system.Item ONTOLOGY-ENABLED TRACEABILITY MODELS FOR ENGINEERING SYSTEMS DESIGN AND MANAGEMENT(2012) Delgoshaei, Parastoo; Austin, Mark A.; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis describes new models and a system for satisfying requirements, and an architectural framework for linking discipline-specific dependencies through inter- action relationships at the ontology (or meta-model) level. In a departure from state-of-the-art traceability mechanisms, we ask the question: What design concept (or family of design concepts) should be applied to satisfy this requirement? Solu- tions to this question establish links between requirements and design concepts. The implementation of these concepts leads to the design itself. These ideas, and support for design-rule checking are prototyped through a series of progressively complicated applications, culminating in a case study for rail transit systems management.Item ONTOLOGY-ENABLED TRACEABILITY MODELS FOR ENGINEERING SYSTEMS DESIGN AND MANAGEMENT(2012-12-18) Delgoshaei, Parastoo; Austin, MarkThis thesis describes new models and a system for satisfying requirements, and an architectural framework for linking discipline-specific dependencies through inter- action relationships at the ontology (or meta-model) level. In a departure from state-of-the-art traceability mechanisms, we ask the question: What design concept (or family of design concepts) should be applied to satisfy this requirement? Solu- tions to this question establish links between requirements and design concepts. The implementation of these concepts leads to the design itself. These ideas, and support for design-rule checking are prototyped through a series of progressively complicated applications, culminating in a case study for rail transit systems management.Item Semantic Models and Reasoning for Building System Operations: Focus on Knowledge-Based Control and Fault Detection for HVAC(2017) Delgoshaei, Parastoo; Austin, Mark A; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)According to the U.S. Energy Information Administration (EIA), the Building Sector consumes nearly half (47.6%) of all energy produced in the United States. Seventy-five percent (74.9%) of the electricity produced in the United States is used just to operate buildings. At the same time, decision making for building operations still heavily rely on human knowledge and practical experience and may be far from optimal. In a step toward mitigating these deficiencies, this dissertation reports on a program of research to identify opportunities for using semantic models and reason- ing in building system operations. The work focuses on knowledge-based control and fault detection for heating, ventilation and air conditioning (HVAC) systems. Decision-making procedures for building system operations are complicated by the multiplicity of participating domains (e.g., architecture, equipment, sensors, occu- pants, weather, utilities) that need to be considered. The key opportunity of this approach is a means to utilize semantic models for knowledge representation, inte- gration of heterogeneous data sources, and executable processing of semantic graph models in response to external events. The results of this dissertation are con- densed into three case-study applications; (1) Semantic-assisted model predictive control (MPC) for detection of occupant thermal comfort, (2) Semantic-based util- ity description for MPC in a chiller plant operation, and (3) Knowledge-based fault detection and diagnostics for HVAC systems.