Characterization and superposition regularity of aliasing signal based on the micro-three-coil sensor

Abstract

Oil condition monitoring for mechanical systems is essential for the safe and effective operation of equipment. In this paper, a micro-three-coil sensor is used to detect the aliasing signal generated by multiple particles. The output signal of this sensor has more characteristics and can reveal the superimposed signals generated when particles of different materials and sizes pass through the sensor at various distances. Simulation and experimental results show that when multiple or accumulated particles accumulate or pass through the sensor at a distance smaller than the sensor size, the position of the particles has a large effect on the magnetic field balance of the three-coil sensor. At the same time, the amplitude of the signal, the number of peaks, and troughs are closely related to the properties, size, and distance of the particles. When particles of the same material pass through the transducer at the spacing between then in the range of the two excitation coils, the amplitude of the transducer's output signal decreases because the particles act on both excitation coils simultaneously. When two particles of different materials pass through the sensor with the spacing of two excitation coils, the amplitude of the sensor output signal will increase. This research provides new ways of detecting metallic methods by using extracted signals, which provides more information about the condition of the mechanical system.