An impedance debris sensor capable of simultaneously detecting inductance and resistance parameters is presented, which mainly consists of two planar coils in parallel, two excitation silicon steel strips inserted in the inner hole of coils and a built-in silicon steel strip located in the center of channel. The excitation silicon steel strips and the built-in silicon steel strip establish a detection region with a high-gradient magnetic field to improve the sensitivity of the sensor. And the square channel makes full use of the sensitive detection region, thereby further increasing the detection throughput. Experiments have shown that the amplitudes of the inductance and resistance pulses generated by the same particle many times through the detection region are different. The uncertainty of the sensor can be reduced for an accurate size information by combining the detection results of the inductance and resistance parameters. By comparing and analyzing the inductance parameter detection result and the resistance parameter detection result, the impedance debris sensor can distinguish and measure 25μm iron particle and 85μm copper particle. With its high sensitivity, high throughput and capability of multi-parameter detection, this sensor can potentially be used for health monitoring of hydraulic equipment.

Oil condition monitoring is an important way to achieve mechanical equipment health assessment, condition early warning, fault diagnosis, and intelligent maintenance. A microsensor integrated with inductance-resistance and capacitance sensing units is presented, which can comprehensively detect metal debris, air bubbles, and moisture in oil based on impedance analysis. The inductance-resistance sensing unit not only detects traditional inductance parameter, but also proposes a resistance detection method based on coil to further improve the detection sensitivity for nonferromagnetic metal debris. The capacitance sensing unit can detect air bubbles, and a new moisture measurement method is also proposed. Based on the signal characteristics of inductance, resistance and capacitance detection results, the microsensor can effectively distinguish 16–500 μ m iron debris, 60–500 μ m copper debris, >170 μ m air bubbles and moisture in oil. The ultrasensitive microsensor can obtain more oil status information, which has important value and wide engineering application prospect for modern fault diagnosis and prediction theory based on information fusion.

A bridge-type inductance sensor with a two-stage filter circuit for high-precision detection of metal debris in the oil is proposed. The sensor mainly consists of a bridge-structure sensing unit and a two-stage filter circuit. The sensing unit consists of two double-wire solenoid coils (as the detection unit and the reference unit, respectively) and a Wheatstone bridge -structure. This structure enhances the response of the detection unit to the magnetic field disturbance generated by the wear debris and can improve the detection accuracy of the sensor. Furthermore, a circuit with rectification, amplitude modulation, and amplification functions is introduced to eliminate the noise interference from the environment and the system, and to accurately extract the weak abrasive signals that are submerged in the noise. Meanwhile, by adjusting the passband gain of the two-stage filter circuit, the measurement range of the sensor voltage value is improved. Experimental results show that adding a two-stage filter circuit can improve the resolution of the sensor, and can effectively detect $45~\mu \text{m}$ iron particles. The sensor provides technical support for the modularity and portability of the testing instrument, which is essential for fault diagnosis and prevention of the hydraulic systems.

A microfluidic sensor based on the inductive-capacitive Coulter counting principle to detect multi-contaminants in hydraulic oil is presented. The sensor consists of a silicon steel plate and a planar coil. The silicon steel plate makes the distribution of the magnetic flux more dense and uniform, thereby effectively improving the dection sensitivity. The experimental results show that the low-frequency alternating current should be used to detect ferromagnetic particles, and the high-frequency alternating current should be used to detect non-ferromagnetic particles. In inductance mode, the high-frequency excitation should be selected to identify smaller copper particles for comprehensive accuracy, and 30lm iron particles and 110lm copper particles were detected at 2.0MHz. In capacitance mode, the signal amplitude decreases with frequency, but the signal-to-noise ratio increases first with frequency and then decreases. There is the best capacitance detection sensitivity at 0.7MHz, and 100lm water droplets and 160lm air bubbles were detected. As the core component of the portable oil detection device, this sensor can be used for health monitoring of mechanical equipment to prevent hydraulic system failure.

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.