Statistical scheme for fault detection using Arduino and MPU 6050

Unmanned Aerial Vehicles (UAVs) are widely used for various civilian, security and military applications. UAVs are equipped with a number of sensors such as accelerometers and gyroscopes, the measured data reliability of these sensors is critical and data obtained from these sensors must be accurate. Sometimes, sensors are prone to damage because of various electric/communication problems. This paper proposes a statistical scheme for catering real-time experimental results of fault detection for inertial measurement unit sensors (accelerometer and gyroscope) by using statistical analysis measures. The objective is to detect sensor bias fault, total sensor failure and drift or additive type fault in gyroscope and accelerometer measurements by processing their data via statistical measures. The scheme of processing the sensor data aims to suggest best statistical measures for fault detection in a multiple-sensor setting, after graphical signal analysis (comparison of the graphs of signal overture of all sensors) has been completed. This scheme can be helpful in diagnosis and subsequent isolation of sensors with fault in high-reliability applications where accuracy of data is critical.