Water Metering with the WaWiCo USB Kit and Raspberry Pi

For this project, we will be comparing the WaWiCo sensor with a conventional hall-effect mechanical flow meter. The WaWiCo sensor introduces a novel method for water metering, with non-invasive acoustic analysis. The benefit of the WaWiCo method is evident during the mechanical flow meter analysis, where we need to match pipe diameters and fittings and ensure that the flow terminates at a point. Otherwise, mechanical meters require cutting in piping — which is not an option for many users. Using a Raspberry Pi computer and a WaWiCo USB water meter kit, the frequency content of water flow for a given pipe is analyzed. Additionally, this frequency response will be used to correlate to the flow rate (in L/s) approximated by the mechanical flow meter. This brings us one step closer to being able to non-invasively measure water flow using the WaWiCo method.

Calibration of a Magnetometer with Raspberry Pi

In this tutorial, methods for calibrating a magnetometer aboard the MPU9250 is explored using our Calibration Block. The magnetometer is calibrated by rotating the IMU 360° around each axis and calculating offsets for hard iron effects. Python is again used as the coding language on the Raspberry Pi computer in order to communicate and record data from the IMU via the I2C bus. The second half of this tutorial gives a full calibration routine for the IMU's accelerometer, gyroscope, and magnetometer. The final implementation will allow for moderate (first-order) calibration of the MPU9250 under reasonable conditions, requiring only the calibration block and IMU. Finally, the complete final code will save the coefficients for each sensor for future use in direct applications without the need for constant calibration. The use of the calibration coefficients will allow for improved estimates of orientation, displacement, vibration, and other relevant control and measurement analyses.

Gyroscope and Accelerometer Calibration with Raspberry Pi

This is the second entry into the series entitled "Calibration of an Inertial Measurement Unit (IMU) with Raspberry Pi" where the gyroscope and accelerometer are calibrated using our Calibration Block. Python is used as the coding language on the Raspberry Pi to find the calibration coefficients for the two sensors. Validation methods are also used to integrate the IMU variables to test the calibration of each sensor. The gyroscope shows a fairly accurate response when calibrated and integrated, and found to be within a degree of the actual rotation test. The accelerometer was slightly less accurate, likely due to the double integration required to approximate displacement and the unbalanced table upon which the IMU was calibrated. Filtering methods are also introduced to smooth the accelerometer data for integration. The final sensor, the magnetometer (AK8963), will be calibration in the next iteration of this series.

Calibration of an Inertial Measurement Unit (IMU) with Raspberry Pi - Part I

Inertial measurement units (IMUs) can consist of a single sensor or collection of sensors that capture data meant to measure inertial movements in a given reference frame. Acceleration, speed of rotation, and magnetic field strength are examples of sensors contained in an IMU. IMUs can be found in applications ranging smart devices, medical rehabilitation, general robotics, manufacturing control, aviation and navigation, sports learning, and augmented and virtual reality systems. Inertial measurement units have become increasingly popular as their form factors shrink and computational power increases. The ability to use IMUs for indoor/outdoor tracking, motion detection, force estimation, orientation detection, among others has caused the use and availability of inertial sensors to become nearly widespread in smart phones, smart watches, drones, and other common electronic devices. The internet is full of projects involving accelerometers, gyroscopes, and magnetometers, but few cover the full calibration of all three sensors. In this project, the manual calibration of a nine degree-of-freedom (9-DoF) IMU is explored. A common MPU9250 IMU is attached to a cube to manually find the calibration coefficients of the three sensors contained within the IMU: accelerometer, gyroscope, and magnetometer. The IMU is wired to a Raspberry Pi - which will allow for high-speed data acquisition rates of all nine components of the IMU.

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.

Infrared Thermometry Theory and Applications with Arduino and Python

In this tutorial, I will explore black body radiation, infrared detectors, and the relationship between temperature and emissivity - all with the intention of exploring how infrared (IR) detectors measure temperature from a distance. Arduino will be used, along with an MLX90614 IR thermometer, and a thermocouple for true-temperature approximation of each object. Planck’s discovery of energy quanta and their relationship to thermodynamics is the basis for radiation detectors and infrared temperature sensors. We will use Planck’s law to derive a usable equation that can relate the radiation measured by an infrared sensor to the temperature of a radiative object.

Smartphone Arduino Weighing Scale with Load Cell and HX711

In this tutorial, I introduce an Arduino-based weighing scale that uses a load cell, analog-to-digital converter, and calibrated mass. I introduce calibration with known masses to create a powerful and accurate weighing system that can be used for highly accurate measurement purpose such as: chemistry, horticulture, cooking, and much more!

Arduino Weighing Scale with Load Cell and HX711

In this tutorial, I introduce an Arduino-based weighing scale that uses a load cell, analog-to-digital converter, and calibrated mass. I introduce calibration with known masses to create a powerful and accurate weighing system that can be used for highly accurate measurement purpose such as: chemistry, horticulture, cooking, and much more!