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.

Metallic contaminants (solid) are generated by friction pair, causing wear of equipment by enters the lubricating system. This poses a great potential threat to the normal operation of such machines. The timely analysis and detection of debris can lead to the avoidance of mechanical failures. Abnormal wear in machinery may produce debris exceeding 10 μm. The traditional inductance detection method has low sensitivity and cannot meet the actual detection requirements. To boost the sensitivity of the inductance sensor, the mutual inductance of coils and the strong magnetic conductivity of permalloy was utilized to design a high sensitivity inductance sensor for the detection of debris in lubricating oil. This design was able to detect 10–15 μm iron particles and 65–70 μm copper particles in the oil. The experimental results illustrate that low-frequency excitation is the best for detecting ferromagnetic particles, while high-frequency excitation has the best effect for detecting non-ferromagnetic particles. This paper demonstrates the significant advantages of coil mutual inductance, and strong magnetic conductivity of permalloy in improving the detection sensitivity of oil debris sensors. This will provide technical support for wear detection in mechanical equipment and fault diagnosis.

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.

The safety transfer on the sea is threatened by wind, wave and surge loads. An offshore gangway ensures smooth and safe transfer by compensating the ship’s motion. In a mixed offshore gangway system, the transfer gangway is a huge asymmetric load on top of the stable platform, and the displacement of its center of gravity causes it to exert a large dynamic load on the stable platform. A dynamic model of the offshore gangway under dynamic load is established in this work. The Lagrange equation is used to establish the dynamic model of the transfer gangway; the equivalent center of gravity method is used to visualize its dynamic load. The dynamic of the stable platform is modeled by the virtual work principle. Finally, the accuracy of the mathematical model was verified by the joint simulation. Simulation results indicate that under the influence of dynamic load, the tractive force of the second drive support chain is 2–3 times greater than the tractive force of the first and third drive support chains. With the same excitation, the tractive force of the second drive support chain is 2.83 times higher than that under the static load.