Purdue University Graduate School
Thesis_WCSung.pdf (14.13 MB)

Sound Quality Evaluation of HVAC&R Equipment

Download (14.13 MB)
posted on 2020-08-04, 19:33 authored by Weonchan SungWeonchan Sung
Characteristics of heating, ventilation, air conditioning and refrigeration (HVAC&R) equipment sounds and people's responses to them were studied in order to develop models to predict annoyance from recordings of the sound. These models are intended to address shortcomings of currently used methods for HVAC&R product sound assessment. Coupled with sound prediction models, the annoyance models will be used to monitor and guide improvements to HVAC&R equipment sound quality throughout the product design process: from virtual early design, through to the prototyping and product refinement stages. Responses to residential and refrigerated truck product noise was studied; both produce broadband random noise and families of harmonics related to rotating and reciprocating components within the system. Tests were conducted to determine how people describe HVAC&R equipment sounds; how their descriptions relate to sound characteristics and overall assessments; and to develop models that relate predicted strengths of sound characteristics to the overall assessment. Annoyance models were developed for each types of product. Loudness and spectral balance metrics are included in models for both types of product. Inclusion of a tonalness metric improved models for residential units, and roughness and impulsiveness metrics improved models for refrigerated truck units. The models developed were used to predict responses in the other tests and there was good agreement between predicted and measured responses. An illustration of the use of the annoyance models, in conjunction with sound visualization and signal modification techniques, to guide improvements to product sound quality is given.


Degree Type

  • Doctor of Philosophy


  • Mechanical Engineering

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Patricia Davies

Additional Committee Member 2

J. Stuart Bolton

Additional Committee Member 3

George Chiu

Additional Committee Member 4

Kai M. Li

Additional Committee Member 5

Hong Z. Tan

Usage metrics



    Ref. manager