Posts tagged Frequency Spectrum
Arduino LoRa Network Part I: Radio Basics and Range Tests

LoRa modules, such as the SX1276 used in this tutorial, are widely available and relatively inexpensive, all while being fully compatible with Arduino. LoRa modules are also modular in software and hardware: transmission power is configurable, the modules can be outfitted with antennae, and transmission speed and packet information size are both modifiable. In this tutorial, an Arduino board and SX1276 modules will be used to create a network of long range (LoRa) nodes designed to communicate and transport information. The use of antennae will also help broaden the range of the nodes, and tests in New York City will help quantify the efficiency and cone of functionality for such a node in a complex environment.

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Raspberry Pi Vibration Analysis Experiment With a Free-Free Bar

Using the Euler-Bernoulli beam theory, the resonant frequencies of a beam will be measured using a thin film piezoelectric transducer and compared to the theoretical calculations. A Raspberry Pi will be used along with a high-frequency data acquisition system (Behringer UCA202, sample rate: 44.1kHz) and the Python programming language for analysis. The fast fourier transform will allow us to translate the subtle beam deflections into meaningful frequency content. This tutorial is meant to introduce Python and Raspberry Pi as formidable tools for vibration analysis by using measurements as validation against theory.

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Audio Processing in Python Part III: Guitar String Theory and Frequency Analysis

In this continuation of the audio processing in Python series, I will be discussing the live frequency spectrum and its application to tuning a guitar. I will introduce the idea of nodes and antinodes of a stringed instrument and the physical phenomena known as harmonics. This will give us a better idea of how to tune the guitar string-by-string and also discern the notes of a given chord - all calculated using the FFT function in Python.

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Audio Processing in Python Part II: Exploring Windowing, Sound Pressure Levels, and A-Weighting Using an iPhone X

Raspberry Pi 3B+ acoustic analysis using Python. Audio recording and signal processing with Python, beginning with a discussion of windowing and sampling, which will outline the limitations of the Fourier space representation of a signal. Discussion of the frequency spectrum, and weighting phenomenon in relation to the human auditory system will also be explored. Lastly, the significance of microphone pressure units and conversion to the decibel will be briefly introduced and explained.

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