The noise absorption prediction of a combined and independent absorber under different conditions and at different frequencies, using the new Engineering Noise Control Software (ENC)

Abstract

Noise is one of the most harmful factors in the work environment, which is very important to control. There are various techniques to achieve this goal. One of the most important of them is the use of noise absorbers. Absorbent materials are often used to counteract the effects of reflected noise from hard surfaces and reduce their level. This is an experimental-applied study conducted in the physical factor laboratory of the Faculty of Health. The purpose was to predict the Noise absorption rate of combined and independent absorbers under different conditions and frequencies using the new ENC (engineering noise control) software. The sound absorption determination was carried out in 5 stages, including sound frequency analysis for the source, measurement of the dominant frequency, measurement of the absorption coefficient of absorbent materials in different conditions, measurement of the limit frequency (peak frequency of noise absorption) and comparison of the software results with the findings of the impedance tube in Real conditions. The best absorption mode for combined and independent absorbents is using a 5 cm rock wool absorbent with a 2 cm thick air layer behind it without a polyurethane absorbent layer and a 10 cm wide rock wool absorbent with a 1 cm air layer behind it without polyurethane layer. A polyurethane layer on the stone wool absorber decreased the amount of noise absorption for high frequencies. The results obtained from the best absorption conditions in the ENC software were consistent with the findings from the impedance tube device in real situations. The results of this study showed that suitable and optimal conditions of sound absorption could be achieved by using the ENC software, correct design, use of suitable absorbers, changes in the physical parameters of the absorber, and the use of a combined absorber.

Keywords

• Absorption coefficient
• Absorption prediction
• ENC software