Influential factors analysis of detection accuracy for an inductive wear debris sensor

The application of oil debris monitoring technology to lubricating oil has gained substantial prominence as a diagnostic tool for identifying machinery and equipment wear-related issues. Among the various methods available for wear fault monitoring, the detection of changing electromagnetic fields using triple-coil inductive sensors are widely used because of its inherent simplicity of design and operational convenience in facilitating full-flow detection. However, the accuracy of this method is limited by several factors. In this study, an intricate simulation model of the internal magnetic field in a triple-coil inductive sensor was developed. Subsequently, the effects of the excitation signal frequency and wear particle composition on the magnetic flux density were analyzed. The simulation results show an optimal excitation frequency range of approximately 2−100 kHz for ferromagnetic particle detection, whereas nonferromagnetic metal particles require higher excitation frequencies. With an increase in the distance between adjacent wear particles, the magnetic coupling effect decreased rapidly. Moreover, the magnetic flux density changed from its maximum value to a minimum value as the rotation angle of the particles increased from 0° to 90°. A special experimental platform was constructed to verify the simulation results, and the experimental results were consistent with the simulation results.