Fault Detection and Diagnosis of Air Handling Unit in HVAC System Using Cloud-based Data Logging System

dc.contributor.advisorSong, Li
dc.contributor.authorLee, David
dc.contributor.committeeMemberCai, Jie
dc.contributor.committeeMemberMerchan-Merchan, Wilson
dc.date.accessioned2019-05-07T13:59:10Z
dc.date.available2019-05-07T13:59:10Z
dc.date.issued2019-05-10
dc.date.manuscript2019-05-06
dc.description.abstractThis project encompasses the engineering principles of design and testing of the implementation of a fault detection and diagnosis (FDD) using cloud-based data logging system on Heating, Ventilation, and Air Conditioning (HVAC) system. The data acquisition system is a compact measurement system made by Paragon Robotics that handles data from sensors, measurement hardware, and a computer with appropriate software to record four different categories of measurements: (1) temperature and humidity of outside air, (2) temperature of return, mixed, and supply air, (3) cooling oil valve operation measurements, and (4) supply air fan operation measurements. The project includes the design process of the equipment and installation of electrical and mechanical components needed for a functioning system on an Air Handling Unit (AHU) that serves a building in the University of Oklahoma. Tests of baseline operation are conducted to collect weeks of data after calibration. The system is verified with engineering fundamental Models to ensure robustness for fault detection and diagnosis. Common faults of AHU are evaluated and selected to be simulated into the system for days with faulty operation data. Qaulitative rule-based or physics-based FDD technique is used to detect and diagnose the system with data collected during operations of faults.en_US
dc.identifier.urihttps://hdl.handle.net/11244/319569
dc.languageen_USen_US
dc.subjectEnergy Efficient Building Designen_US
dc.subjectHVAC Systemen_US
dc.subjectAir Handling Uniten_US
dc.subjectFault Detection and Diagnosisen_US
dc.subjectCloud-based Data Logging Systemen_US
dc.subjectEngineering, Mechanical.en_US
dc.thesis.degreeMaster of Scienceen_US
dc.titleFault Detection and Diagnosis of Air Handling Unit in HVAC System Using Cloud-based Data Logging Systemen_US
ou.groupGallogly College of Engineering::School of Aerospace and Mechanical Engineeringen_US

Files

Original bundle
Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
2019_Lee_David_Thesis.pdf
Size:
3.74 MB
Format:
Adobe Portable Document Format
Description:
No Thumbnail Available
Name:
2019_Lee_David_Thesis.docx
Size:
20.34 MB
Format:
Microsoft Word XML
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:

Collections