Sensor fault detection and diagnosis for water loop in HVAC system
The energy consumption of HVAC has exceeded over 50% in the building sector over the past years [2]. Among all components of the HVAC system, the water chiller is the most energy-consuming component. Any fault or failure in the chiller may lead to further increase in energy consumption and inefficie...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/149259 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-149259 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1492592023-07-07T18:25:00Z Sensor fault detection and diagnosis for water loop in HVAC system Tan, Kim Xiang Cai Wenjian School of Electrical and Electronic Engineering ewjcai@ntu.edu.sg Engineering::Electrical and electronic engineering The energy consumption of HVAC has exceeded over 50% in the building sector over the past years [2]. Among all components of the HVAC system, the water chiller is the most energy-consuming component. Any fault or failure in the chiller may lead to further increase in energy consumption and inefficiency, higher O&M cost, and release more heat into the environment, thus contributing to global warming. Consequently, fault detection and diagnosis (FDD) had been proposed to detect and diagnose the possible fault types and their respective root causes. Furthermore, the implementation of FDD helps to identify the faults automatically and in a timely manner so that the user can resolve the fault as soon as possible for their HVAC system. Early detection and diagnosis using these methods prevent consequential harm and other mechanical damages on the chiller. The main focus of this project will be on using a Long Short-Term Memory (LSTM) to develop an FDD model. LSTM will target directing and diagnosing seven typical faults found in HVAC systems. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-29T06:13:38Z 2021-05-29T06:13:38Z 2021 Final Year Project (FYP) Tan, K. X. (2021). Sensor fault detection and diagnosis for water loop in HVAC system. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149259 https://hdl.handle.net/10356/149259 en A1023-201 application/pdf Nanyang Technological University |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering::Electrical and electronic engineering |
spellingShingle |
Engineering::Electrical and electronic engineering Tan, Kim Xiang Sensor fault detection and diagnosis for water loop in HVAC system |
description |
The energy consumption of HVAC has exceeded over 50% in the building sector over the past years [2]. Among all components of the HVAC system, the water chiller is the most energy-consuming component. Any fault or failure in the chiller may lead to further increase in energy consumption and inefficiency, higher O&M cost, and release more heat into the environment, thus contributing to global warming. Consequently, fault detection and diagnosis (FDD) had been proposed to detect and diagnose the possible fault types and their respective root causes. Furthermore, the implementation of FDD helps to identify the faults automatically and in a timely manner so that the user can resolve the fault as soon as possible for their HVAC system. Early detection and diagnosis using these methods prevent consequential harm and other mechanical damages on the chiller. The main focus of this project will be on using a Long Short-Term Memory (LSTM) to develop an FDD model. LSTM will target directing and diagnosing seven typical faults found in HVAC systems. |
author2 |
Cai Wenjian |
author_facet |
Cai Wenjian Tan, Kim Xiang |
format |
Final Year Project |
author |
Tan, Kim Xiang |
author_sort |
Tan, Kim Xiang |
title |
Sensor fault detection and diagnosis for water loop in HVAC system |
title_short |
Sensor fault detection and diagnosis for water loop in HVAC system |
title_full |
Sensor fault detection and diagnosis for water loop in HVAC system |
title_fullStr |
Sensor fault detection and diagnosis for water loop in HVAC system |
title_full_unstemmed |
Sensor fault detection and diagnosis for water loop in HVAC system |
title_sort |
sensor fault detection and diagnosis for water loop in hvac system |
publisher |
Nanyang Technological University |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/149259 |
_version_ |
1772826722858696704 |