MPS20N0040D Pressure Sensor Calibration with Arduino

Pressure is defined as an evenly distributed force acting over a surface with a given area. The accurate measurement of pressure is essential for applications ranging from material testing to weighing scales, aircraft altitude prediction, and evaluating biological functions in humans relating to respiration and blood flow In this tutorial, a digital pressure transducer and analog pressure manometer will be used to measure gauge pressure - where the analog manometer is used as the calibration tool for the digital pressure sensor. Arduino will be used to read the digital pressure transducer, an MPS20N0040D, and a 3D printed manometer will be used to measure analog pressure manually.

Force Sensitive Resistors (FSRs) with Arduino

A force sensitive resistor (FSR) is comprised of a conductive polymer material pressed between two electrode layers, giving it the ability to electrically respond to changes in stress and strain. FSRs are often used in ergonomic or rehabilitation applications where pressure is applied from human interaction and the response is recorded or translated. Force sensitive resistors are incredibly useful for human interactivity because of their slim profile, inexpensive construction, and multiplicative geometries. The sensor used in this tutorial is the RP-S40-ST, which is a 40mm x 40mm thin film FSR. An Arduino board will be used to read the analog signals outputted by the FSR in a voltage divider configuration, where the force applied to the FSR can be approximated using the sensor’s calibration curve.

Arduino + VL53L1X Time of Flight Distance Measurement

Time of flight (ToF) is an approximation of the time it takes a traveling wave to come in contact with a surface and reflect back to the source. Time of flight has applications in automotive obstacle detection, resolving geographic surface composition, and computer vision and human gesture recognition. In the application here, the VL53L1X ToF sensor will be used to track the displacement of a ping pong ball falling down a tube. We can predict the acceleration and behavior of a falling ping pong ball by balancing the forces acting on the ball, and ultimately compare the theory to the actual displacement tracked by the time of flight sensor.