Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/159243
Title: A multidimensional assessment of construction machinery noises based on perceptual attributes and psychoacoustic parameters
Authors: Hong, Joo Young
Lam, Bhan
Ong, Zhen-Ting
Ooi, Kenneth
Gan Woon-Seng 
Lee, Sungchan
Keywords: Social sciences::Psychology::Applied psychology
Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Hong, J. Y., Lam, B., Ong, Z., Ooi, K., Gan Woon-Seng & Lee, S. (2022). A multidimensional assessment of construction machinery noises based on perceptual attributes and psychoacoustic parameters. Automation in Construction, 140, 104295-. https://dx.doi.org/10.1016/j.autcon.2022.104295
Project: COT-V4-2020-1 
Journal: Automation in Construction 
Abstract: Traditional decibel-based measures in predicting annoyance from construction activities are limited to reflect high acoustic variability of construction machinery noises. Hence, a multidimensional approach based on perceptual attributes and psychoacoustic parameters is proposed. In-situ audio-visual recordings of 16 construction machinery in operation were evaluated subjectively on both perceived annoyance and a 12-item semantic differential perceptual attribute scale. The 16 machinery noises formed three clusters based on four perceptual components (Incisiveness, Strength, Intermittency, and Periodicity) derived via principal component analysis of the perceptual attributes. Notably, individual perceptual components strongly correlate with mean values of psychoacoustic parameters (loudness, sharpness, roughness, and fluctuation strength) over time, which we use to develop an annoyance model for construction noise. Both loudness and fluctuation strength were critical parameters to discriminate between clusters. The model can be used to automatically categorize construction noises by cluster and manage it based on known cluster characteristics.
URI: https://hdl.handle.net/10356/159243
ISSN: 0926-5805
DOI: 10.1016/j.autcon.2022.104295
Rights: © 2022 Elsevier B.V. All rights reserved. This paper was published in Automation in Construction and is made available with permission of Elsevier B.V.
Fulltext Permission: embargo_20240518
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

Files in This Item:
File Description SizeFormat 
Manuscript_AUTCON.pdf
  Until 2024-05-18
Accepted Manuscript1.58 MBAdobe PDFUnder embargo until May 18, 2024

SCOPUSTM   
Citations 50

1
Updated on Nov 25, 2022

Web of ScienceTM
Citations 50

1
Updated on Nov 29, 2022

Page view(s)

31
Updated on Dec 2, 2022

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.