On using ‘‘loudness-weighted’’ SEL, LEQ, and DNL to assess noise environments
Paul D. Schomer
Abstract
Paul D. Schomer
Abstract
LEQ and DNL are commonly used to assess the long-term noise environments around airports, roads, etc. The fundamental building block to these assessments is the A-weighted sound level or SEL. These are used to compute LEQ or DNL. But many problems have surfaced over the simple use of A-weighting. The A-weighting has been shown to be deficient in assessing sound with strong low-frequency content, and other characteristics, like impulsiveness, are not properly accounted for by the A-weighting. However, no other simple filter has been shown to be superior to the A-weighting filter. One can consider building a more complicated filter that dynamically changes with level and frequency to better reflect human response than does the A-weighting. The equal loudness contours expressed in phons offers a set of curves that can be used to design such a filter. Like A-weighted sound level or A-weighted SEL, signals processed with such a new ‘‘filter’’ would be termed ‘‘loudness-weighted’’ sound level or ‘‘loudness-weighted’’ SEL. This author has analyzed many sounds to illustrate, test, and evaluate the concept of loudness-weighted SEL. This paper discusses the concept of using ‘‘loudness-weighting’’ in place of A-weighting and the results indicated by the analysis of many common sounds.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
LEQ and DNL are commonly used to assess the long-term noise environments around airports, roads, etc. The fundamental building block to these assessments is the A-weighted sound level or SEL. These are used to compute LEQ or DNL. But many problems have surfaced over the simple use of A-weighting. The A-weighting has been shown to be deficient in assessing sound with strong low-frequency content, and other characteristics, like impulsiveness, are not properly accounted for by the A-weighting. However, no other simple filter has been shown to be superior to the A-weighting filter. One can consider building a more complicated filter that dynamically changes with level and frequency to better reflect human response than does the A-weighting. The equal loudness contours expressed in phons offers a set of curves that can be used to design such a filter. Like A-weighted sound level or A-weighted SEL, signals processed with such a new ‘‘filter’’ would be termed ‘‘loudness-weighted’’ sound level or ‘‘loudness-weighted’’ SEL. This author has analyzed many sounds to illustrate, test, and evaluate the concept of loudness-weighted SEL. This paper discusses the concept of using ‘‘loudness-weighting’’ in place of A-weighting and the results indicated by the analysis of many common sounds.
Key concepts: Loudness, Weighting, A-weighting, Filter (signal processing), Noise (video), Mathematics, Acoustics, Computer science