Sensors and Instrumentation

Notes on Sensors and Instrumentation with ipython notebooks

Andrés Marrugo, PhD

This repository is a collection of Jupyter notebooks in the form of lecture notes and engineering calculations for the course IMTR A01A Sensors and Instrumentation taught at the Universidad Tecnológica de Bolívar (Previous Sensors and Actuators course). It is largely based on the book by Nathan Ida. The lectures notes are written using the Jupyter IPython Notebook, part of the Python ecosystem for scientific computing. You can view these lectures in different ways: simply read on line by clicking on the links below; or download a single notebook or all the stuff or yet fork this entire repository using the GitHub resources and run the notebooks in your computer or in the cloud. I hope this material is useful to you and I am open to suggestions or comments.

This work was inspired by the lecture notes on Scientific Computing for Biomechanics and Motor Control by Marcos Duarte. This is a work in progress.

Introduction

We will be using Jupyter Python notebooks as a numerical computing and graphical platform for solving many problems in the course. To avoid installing Jupyter Python locally, I encourage you to use Google Colab.

• Python Tutorial
• Introduction to colab

Definitions, classifications, and general requirements

• Passive and active sensors
• Decibel measurements
• Power loss in optical fibers.

Performance Characteristics of Sensors

• Sensor selection

• A simple position sensor.

• Analytic form of transfer function.

• Errors in sensing

• Linear approximation of nonlinear transfer function.

Temperature Sensors

• A wire-spool sensor.
• Thermocouple reference tables

Mechanical Sensors

• Evaluation of a force sensor.