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.
Read MoreA Raspberry Pi will be used to read the MPU9250 3-axis acceleration, 3-axis angular rotation speed, and 3-axis magnetic flux (MPU9250 product page can be found here). The output and limitations of the MPU9250 will be explored, which will help define the limitations of applications for each sensor. This is only the first entry into the MPU9250 IMU series, where in the breadth of the articles we will apply advanced techniques in Python to analyze each of the 9-axes of the IMU and develop real-world applications for the sensor, which may be useful to engineers interested in vibration analysis, navigation, vehicle control, and many other areas.
Read MoreThe pitot tube is a device used to approximate the speed of vehicles traveling by air and water. An in-depth article on NASA's website is dedicated to pitot tubes (also called pitot-static tubes, Prandtl tubes), where it cites the primary application as airspeed indicator on aircraft. For more information on design and limitations of the instrument, I recommend perusing that page. For this tutorial, only the basic theory is explored using Bernoulli's equation and a practical application. An inexpensive pitot tube and a digital differential pressure sensor are used to measure pressure, which is converted to a digital signal using an Arduino board.
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