An ultrasensitive debris sensor based on microfluidic technology is introduced in this article. The microsensor not only achieves the traditional inductance detection, but also proposes a resistance detection method based on coil. The magnetic field distribution in the detection region was obtained by simulation, and the magnetization and eddy current effects of metal particles in harmonic magnetic field were simulated. The frequency characteristics and signal characteristics of inductance and resistance detection were studied through experiments. High-frequency excitation can enhance the eddy current effect inside the metal particles, thereby helping to improve the resistance detection sensitivity, enhance the inductance detection effect of nonferromagnetic metal particles, and reduce the inductance detection effect of ferromagnetic metal particles. The research results showed that inductance parameter has stronger detection ability for ferromagnetic metals, and resistance parameter has stronger detection ability for nonferromagnetic metals. According to the characteristics of inductance and resistance signals, the accurate distinction of metal debris property and size can be realized. And the size measurement error caused by the debris shape can be reduced by the judgment method based on two parameters. This impedance detection based on inductance and resistance parameters provides a new method for high-sensitivity monitoring of metal debris. The debris microsensor can be used as a sensing element of portable oil monitoring devices, and provide technical support for health assessment, state warning, and fault diagnosis of mechanical equipment.

A capacitive–inductive magnetic plug sensor for online condition monitoring is proposed in this article, which can achieve particle counting, debris measurement, and wear rate estimation. The sensor can detect capacitance and inductance parameters, the coil is the outer electrode to detect the dielectric change in capacitance mode, and the coil directly induces magnetic field disturbance in inductance mode. Through introducing a reference unit, Wheatstone bridge circuits are constructed to enhance the response to debris and reduce the interference of oil temperature and viscosity. A postprocessing circuit with filtering and amplifying functions is adopted to improve accuracy. The sensor output characteristics and debris position effect are studied through the experiment. The comprehensive analysis of the detection results in two modes can improve sensor adaptability and overcome the deficiency of low reliability based on a single detection method. This sensor can provide more accurate debris information for the fault diagnosis of hydraulic equipment and is of great significance for intelligent maintenance.

An inductive oil pollutant detection sensor based on a high-gradient magnetic field structure is designed in this paper, which is mainly used for online detection and fault analysis of pollutants in hydraulic and lubricating oil systems. The innovation of the sensor is based on the inductance detection method. Permalloy is embedded in the sensing region of the sensor, so that the detection area generates a high gradient magnetic field to enhance the detection accuracy of the sensor. Compared with traditional inductive sensors, the sensor has a significant improvement in detection accuracy, and the addition of permalloy greatly improves the stability of the sensor’s detection unit structure. The article theoretically analyzes the working principle of the sensor, optimizes the design parameters and structure of the sensor through simulation, determines the best permalloy parameters, and establishes an experimental system for verification. Experimental results show that when a piece of permalloy is added to the sensing unit, the signal-to-noise ratio (SNR) of iron particles is increased by more than 20%, and the signal-to-noise ratio of copper particles is increased by more than 70%. When two pieces of permalloy are added, the signal-to-noise ratio for iron particles is increased by more than 70%, and the SNR for copper particles is increased several times. This method raises the lower limit of detection for ferromagnetic metal particles to 20 μm, and the lower limit for detection of non-ferromagnetic metal particles to 80 μm, which is the higher detection accuracy of the planar coil sensors. This paper provides a new and faster online method for pollutant detection in oil, which is of great significance for diagnosing and monitoring the health of oil in mechanical systems.