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Article

Acoustic Sensing and Noise Identification of a Heating, Ventilation and Air Conditioning Unit: Industrial Case Study

by
Stephen Grigg
1,
Zeyad Yousif Abdoon Al-Shibaany
1,2,*,
Matthew Robert Pearson
1,
Rhys Pullin
1 and
Paul Calderbank
3
1
Cardiff School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
2
Biomedical Engineering Department, University of Technology-Iraq, Baghdad 10066, Iraq
3
Bergstrom (Europe) Ltd., 41 Sycamore Close, Dyffryn Business Park, Ystrad Mynach, Hengoed CF82 7RJ, UK
*
Author to whom correspondence should be addressed.
Appl. Sci. 2021, 11(21), 9811; https://doi.org/10.3390/app11219811
Submission received: 4 March 2021 / Revised: 6 October 2021 / Accepted: 12 October 2021 / Published: 20 October 2021
(This article belongs to the Section Acoustics and Vibrations)

Abstract

Reducing the noise and improving the sound quality of vehicles’ interior space is one of the challenges to enhance passengers’ experience. This is an ever-growing issue as entirely electric cars are becoming commonplace, making previously unnoticed noise a significant problem. Heating, Ventilation and Air Conditioning (HVAC) units are a major noise source in a vehicle’s interior space, yet automotive manufacturers only give a maximum dB specification to HVAC unit manufactures. Problematic noise is only typically identified once the unit is within the vehicle at the late stages of a project. Psychoacoustics is the study of human perception to sound, allowing unpleasant noise to be identified within recorded data. Within this study, an industrial prototype HVAC unit was analysed using a 96-channel acoustic camera capable of isolating and locating noise sources from the unit using beamforming. In addition to identifying the location of noise sources, several psychoacoustic metrics were used, such as sharpness and loudness, to identify undesirable noise within an extensive data set due to the vast range of test configurations. Testing was conducted to analyse the unit. Within the initial testing, an ‘annoying’ sound was identified at a particular motor RPM, and this was located using the camera to an area which indicated that it was a result of structural resonance. In addition, present was a high-frequency source which could not be located accurately. The results of this testing enable modifications to the unit to be made early in its’ development, either structurally to alter the resonance of the unit or within the settings to ensure certain RPMs are avoided.
Keywords: acoustic camera; HVAC; noise identification acoustic camera; HVAC; noise identification

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MDPI and ACS Style

Grigg, S.; Al-Shibaany, Z.Y.A.; Pearson, M.R.; Pullin, R.; Calderbank, P. Acoustic Sensing and Noise Identification of a Heating, Ventilation and Air Conditioning Unit: Industrial Case Study. Appl. Sci. 2021, 11, 9811. https://doi.org/10.3390/app11219811

AMA Style

Grigg S, Al-Shibaany ZYA, Pearson MR, Pullin R, Calderbank P. Acoustic Sensing and Noise Identification of a Heating, Ventilation and Air Conditioning Unit: Industrial Case Study. Applied Sciences. 2021; 11(21):9811. https://doi.org/10.3390/app11219811

Chicago/Turabian Style

Grigg, Stephen, Zeyad Yousif Abdoon Al-Shibaany, Matthew Robert Pearson, Rhys Pullin, and Paul Calderbank. 2021. "Acoustic Sensing and Noise Identification of a Heating, Ventilation and Air Conditioning Unit: Industrial Case Study" Applied Sciences 11, no. 21: 9811. https://doi.org/10.3390/app11219811

APA Style

Grigg, S., Al-Shibaany, Z. Y. A., Pearson, M. R., Pullin, R., & Calderbank, P. (2021). Acoustic Sensing and Noise Identification of a Heating, Ventilation and Air Conditioning Unit: Industrial Case Study. Applied Sciences, 11(21), 9811. https://doi.org/10.3390/app11219811

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