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Design and laboratory evaluation of an inexpensive noise sensor

Noise is a pervasive workplace hazard that varies spatially and temporally. Hazard mapping is a useful way to communicate intensity and distribution of noise sources in the workplace. These maps can be created using a stationary network of sensors, although the cost of noise measurement instruments has prohibited their use in such a network. The objectives for this work were to (1) develop an inexpensive noise sensor (<$100) that measures A-weighted sound pressure levels within ±2 dBA of a Type 2 sound level meter (SLM, ~$1,800); and (2) evaluate 50 noise sensors before field deployment as part of an inexpensive sensor network. The inexpensive noise sensor consists of an electret condenser microphone, an amplifier circuit, and a microcontroller with a small form factor (28mm by 47 mm by 9 mm) than can be operated as a stand-alone unit. Laboratory tests were conducted to evaluate 50 of the new sensors at 5 test levels. The testing levels were (1) ambient noise in a quiet office, (2) a pink noise test signal from 65 to 85 dBA in 10 dBA increments, and, (3) 94 dBA using a SLM calibrator. The difference between the output of the sensor and SLM were computed for each level and overall. Ninety-four percent of the noise sensors (n=46) were within ± 2 dBA of the SLM for noise levels from 65 dBA to 94 dBA. As noise level increased, bias decreased, ranging from 18.3% in the quiet office to 0.48% at 94 dBA. Overall bias of the sensors was 0.83% across the 75 dBA to 94 dBA range. These sensors are available for a variety of uses and can be customized for many applications, including incorporation into a stationary sensor network for continuously monitoring noise in manufacturing environments.

Identiferoai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-7257
Date01 August 2017
CreatorsHallett, Laura Ann
ContributorsPeters, Thomas M.
PublisherUniversity of Iowa
Source SetsUniversity of Iowa
LanguageEnglish
Detected LanguageEnglish
Typethesis
Formatapplication/pdf
SourceTheses and Dissertations
RightsCopyright © 2017 Laura Ann Hallett

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