A Metal Abrasive Particles Classification And Identification Method Based on Dual-frequency Asymmetric Excitation Magnetic Field

Material identification of oil abrasive particles is the key to accurate diagnosis and tracing of mechanical equipment failures. Addressing the bottleneck of existing symmetrical magnetic field excitation methods in distinguishing metal types, this paper proposes a metal abrasive particle classification and identification method based on dual-frequency asymmetric magnetic field excitation. An external sensing and internal excitation nested three-coil detection structure is designed in this paper. Based on the differences in frequency response characteristics of ferromagnetic and non-ferromagnetic abrasives, a dual-frequency excitation strategy of 195kHz and 872kHz is adopted to construct an asymmetric magnetic field spatial distribution. This method can realize the detection and material differentiation of different metal abrasives. At the same time, the influence of particle size and velocity on the sensing signal are also explored. Experimental verification demonstrates that this method can effectively distinguish the magnetic properties, size, and material of iron, 440C steel, copper, and aluminum metal abrasive particles in a 6mm oil pipeline based on the multi-dimensional characteristics of the induced voltage signal, such as the number of valley peaks, amplitude difference, waveform trend, and distribution position. The theoretical of minimum detectable particle sizes reach 154μm, 114μm, 140μm, and 215μm, respectively. This method provides an effective technical means for online detection of abrasive status of mechanical equipment.