Symbolic AI for External Magnetic Interference Classification in Magnetostrictive Position Sensors

Magnetostrictive Position Sensors (MPS) are used for high-precision distance and velocity measurements. These sensors work on the basis of Time-of-Flight (ToF) calculation for a structure-borne sound wave generated through magnetic fields within the sensor systems. The accuracy of these sensors is affected by stray external electromagnetic interference (EMI) which can interact with the structure-borne sound wave they generate. This study presents a novel solution using symbolic AI to classify the intensity of EMI and help improve measurement accuracy in industrial environments with multiple sources of EMI. Thus, it is of significance for measurement in industrial environments where multiple sources of external electromagnetic interference can be present.