EN 253: Matlab Exercise #3 Design of a Sound Level Meter
نویسنده
چکیده
The goal of this Matlab exercise is to design an A-weighted sound level meter. Although previous years have utilized multirate filtering to reduce the computational overhead, this write-up will focus on a more direct implementation using the Fast Fourier Transform (FFT). Using the Data Acquisition Toolbox in Matlab, I have implemented a basic A-weighted sound level meter. This implementation allows the user to acquire samples from the sound card in real-time at any sampling rate supported by the hardware. The FFT algorithm is used to estimate the frequency spectrum of a windowed set of samples. The frequency spectrum is weighted using a closed-form expression for the A-weighting filter. The average signal energy is estimated, in the frequency domain, using Parseval’s relation. A simple graphical user interface is provided to view real-time estimates of the signal level and the frequency spectrum. In addition, an off-line implementation is provided, as well as a simple signal generator for determining the calibration constant. In Section 2 the basic design is described, including the specific FFT length and weighting filter equation. The details of the real-time implementation are presented in Section 3. In Section 4, two examples are presented: (1) off-line calibration with training data and (2) realtime calibration using commercial sound level meters. Finally, in Section 5 the computational cost (in MADDS) is presented.
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