Engineering Project
Acoustic Spatiotemporal Output & Digital Image Processing
Arduino G-Code motorized speaker scanning, PWM analog conversion, and MATLAB digital video characterization.
Context & Engineering Scope
Two MATLAB hardware-in-the-loop instrumentation studies: characterizing the spatiotemporal acoustic output of a speaker using Arduino G-Code motion control (Feb 2020) and quantitative digital video/image signal analysis (Apr 2020).
Accurately characterizing acoustic and optical signals requires synchronized hardware positioning, time-domain noise reduction, digital-to-analog PWM filtering, and analysis of resolution and sampling limits.
Methodology & System Design
- 01. Arduino G-Code Motion Control (Feb 2020): Used motorized driving control with Arduino via G-Code to position the speaker relative to the acoustic sensor.
- 02. Time-Domain Averaging & PWM Filtering: Applied time-domain signal averaging to improve signal-to-noise ratio (SNR) and used pulse-width modulation (PWM) with low-pass filtering to convert digital signals to analog.
- 03. Quantitative Digital Image Processing (Apr 2020): Applied digital video measurement techniques in MATLAB to evaluate how amplitude, spatial resolution, and sampling rate affect digital imaging.
Key Results
- Characterized spatiotemporal speaker output with improved signal-to-noise ratio through time-domain averaging.
- Evaluated digital imaging resolution and sampling constraints and demonstrated PWM + low-pass digital-to-analog conversion in MATLAB.