Graduate Studies

 

First Advisor

David P. Yuill

Degree Name

Doctor of Philosophy (Ph.D.)

Committee Members

Josephine Lau, Xiaoqi (Clare) Liu, Xiaoyue (Zoe) Cheng

Department

Architectural Engineering

Date of this Version

8-2024

Document Type

Dissertation

Citation

A dissertation presented to the faculty of the Graduate College at the University of nebraska in partial fulfillment of requirements for the degree of Doctor of Philosophy

Major: Architectural Engineering

Under the supervision of Professor David P. Yuill

Lincoln, Nebraska, August 2024

Comments

Copyright 2024, Yuxuan Chen. Used by permission

Abstract

In commercial buildings, fault detection and diagnosis (FDD) tools have been developed for detecting and diagnosing faults in building systems, which can provide useful information regarding fault locations and potential causes of faults, so that building operators and facility staff can be notified in time and quickly respond as problems arise. Nowadays, there are many commercial FDD tools available in the market, and these tools have been widely adopted in large- and medium-scale commercial buildings in the United States. Several studies have demonstrated the energy saving potential with the use of FDD in commercial HVAC systems, and one critical aspect of the considerations of faults is their prevalence which can indicate the commonality of faults over a course of time, and provide insights into fault prioritization. Prevalence of different fault types with respect to different systems and equipment has been reported based on FDD results in multiple studies, but limited efforts have been seen on a broad scale to validate if the FDD results are valid and the prevalence is reflective of the true frequency.

This dissertation presents the estimate of fault prevalence and field studies validating the FDD results for six FDD providers, covering a variety of faults in package rooftop units (RTUs), air-handling units (AHUs), and air terminal units (ATUs) in different buildings. Fault metrics regarding prevalence are developed, and fault prevalence in terms of fault types is calculated for all FDD tool providers. Regarding the validity of FDD tools, comparisons between the field results and the FDD results are performed. Although results show that false positives and false negatives exist, we still find that field results and FDD fault conditions are in good agreement. In addition, an essential part of this dissertation is to investigate the energy impact of the faults. By simulating selected faults in medium-scale and large-scale commercial prototype buildings through EnergyPlus software, impacts with respect to energy consumption and indoor thermal comfort are demonstrated and evaluated when HVAC system is operating under different faulty conditions.

Advisor: David P. Yuill

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