Fault diagnostics of smart buildings (ii) - system modelling and fault detection
Due to the increase in the effects of the energy usage and depletion of resources on the environment, various countries including Singapore are increasingly focused on efforts to improve the energy efficiency of buildings. The efforts embrace the integration of energy efficient technology and resear...
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sg-ntu-dr.10356-635342023-07-07T16:49:58Z Fault diagnostics of smart buildings (ii) - system modelling and fault detection Low, Yan Ting Hu Guoqiang School of Electrical and Electronic Engineering Singapore–Berkeley Building Efficiency and Sustainability in the Tropics (SinBerBEST) DRNTU::Engineering::Electrical and electronic engineering::Electric power DRNTU::Engineering::Mechanical engineering::Alternative, renewable energy sources Due to the increase in the effects of the energy usage and depletion of resources on the environment, various countries including Singapore are increasingly focused on efforts to improve the energy efficiency of buildings. The efforts embrace the integration of energy efficient technology and research on the building services of Singapore. For this study, the research stint is exemplified by the research efforts of SinBerBest, to instill on a cyber-physical test bed conducting energy efficiency developments. In the realm of buildings and industries, it is extensively identified that the air conditioning system takes up the highest energy consumption of about 30% to 50% of a building. Hence the focus of this project will be regarding specifically into the Air Conditioning and Mechanical Ventilation (ACMV) system. The purpose is to model a simulated cyber-physical test bed in TRNSYS software. This software allows components model system of each type of constituents within a building. By understanding the test bed mechanisms, the test bed will be modelled. Parameters for modeling may include that of the building gains, ventilation, and capacity, as well as the whole of the ACMV system. The ACMV system will comprise of the test bed’s water treatment system as well as the air treatment system. The modelled test bed will be monitored and the results analyzed in energy efficiency study. This will be ready for future work of fault detection and diagnosis (FDD) using the simulated model. Bachelor of Engineering 2015-05-14T08:45:22Z 2015-05-14T08:45:22Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/63534 en Nanyang Technological University 144 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electric power DRNTU::Engineering::Mechanical engineering::Alternative, renewable energy sources Low, Yan Ting Fault diagnostics of smart buildings (ii) - system modelling and fault detection |
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Due to the increase in the effects of the energy usage and depletion of resources on the environment, various countries including Singapore are increasingly focused on efforts to improve the energy efficiency of buildings. The efforts embrace the integration of energy efficient technology and research on the building services of Singapore. For this study, the research stint is exemplified by the research efforts of SinBerBest, to instill on a cyber-physical test bed conducting energy efficiency developments. In the realm of buildings and industries, it is extensively identified that the air conditioning system takes up the highest energy consumption of about 30% to 50% of a building. Hence the focus of this project will be regarding specifically into the Air Conditioning and Mechanical Ventilation (ACMV) system. The purpose is to model a simulated cyber-physical test bed in TRNSYS software. This software allows components model system of each type of constituents within a building. By understanding the test bed mechanisms, the test bed will be modelled. Parameters for modeling may include that of the building gains, ventilation, and capacity, as well as the whole of the ACMV system. The ACMV system will comprise of the test bed’s water treatment system as well as the air treatment system. The modelled test bed will be monitored and the results analyzed in energy efficiency study. This will be ready for future work of fault detection and diagnosis (FDD) using the simulated model. |
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Hu Guoqiang |
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Hu Guoqiang Low, Yan Ting |
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Final Year Project |
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Low, Yan Ting |
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Low, Yan Ting |
title |
Fault diagnostics of smart buildings (ii) - system modelling and fault detection |
title_short |
Fault diagnostics of smart buildings (ii) - system modelling and fault detection |
title_full |
Fault diagnostics of smart buildings (ii) - system modelling and fault detection |
title_fullStr |
Fault diagnostics of smart buildings (ii) - system modelling and fault detection |
title_full_unstemmed |
Fault diagnostics of smart buildings (ii) - system modelling and fault detection |
title_sort |
fault diagnostics of smart buildings (ii) - system modelling and fault detection |
publishDate |
2015 |
url |
http://hdl.handle.net/10356/63534 |
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1772828069835309056 |