A high-precision wear particle monitoring instrument based on numerical simulation, machine vision, multi-target tracking algorithm, and microfluidic technology is designed and developed in this paper. The instrument not only performs the traditional particle number and size detection, but also proposes a particle density detection model based on motion velocity. Firstly, an on-line visual microfluidic chip for oil particles motion was specially designed. Then a mathematical model relationship between particles velocity and particles diameter, particles density, oil viscosity, oil density was established by force analysis and solving the equation, which was used to explain the working principle of the instrument. Meanwhile, a multi-target tracking algorithm incorporating the characteristics of wear particles based on YOLOv5-Deepsort was custom-developed to detect the number, size, and motion characteristics of particles under the optical field of view of the image sensor. Secondly, the oil flow field distribution and the four factors affecting the particle motion characteristics in the self-developed chamber, particle size, particle material, particle radial position, and oil velocity were analyzed by using the finite element analysis in COMSOL. Finally, a pin-disk wear experimental validation results demonstrated this approach has excellent suitability to monitor the number, size, and density of wear particles with diameters above 20μm and densities above 2000 kg/m3 simultaneously. This portable oil particle monitoring instrument provides technical support for condition monitoring, fault diagnosis, and intelligent maintenance of rotating mechanical equipment.

Since inline monitoring method has the advantages of no sampling, being real-time, no human intervention, and low error, this paper innovatively proposes to study the inline monitoring of wear particles in an oil pipeline, from the perspective of the different motion characteristics of the particles. In this paper, an inline optical sensor was designed and developed by studying the velocity characteristics of different particles through theoretical calculations, numerical simulations, and experimental analysis. First, an equation for particle motion was statistically established, based on the forces acting on wear particles in an oil-filled vertical tube. Then a finite element model of particle motion in a full-flow oil pipeline was created, to simulate particle motion with various diameters, densities, locations, and shapes. Finally, the results of the theoretical study were effectively applied to design an inline optical monitoring sensor, and the experimental validation results demonstrated that the inline sensor has excellent suitability for monitoring wear particles. This study has significance for the safe operation of large rotating machinery.

With the improvement of modern aviation equipment manufacturing technology, there are relatively few failures due to the unreliability of the aircraft. However, human factors which resulted in air crashes and unsafe events are raised. In this paper, for many typical accident scenarios of a particular plane, the flight simulation verifications of the pilot’s workload and behavior are carried out on the certain transport category airplane, namely the six-degrees-of-freedom full-motion flight simulator. The subjective and physiological evaluation methods combine to analyze the human factors of pilots in the sudden typical accident scene during a flight mission. The study uses eye trackers, professional heart rate monitors, cameras, and other equipment to collect the pilot’s physiological information during the flight mission, and allows the pilots to fill in the subjective evaluation scale, establishing a subjective and objective evaluation index system. Thus, the human factors of pilots in typical fault situations are analyzed. The analysis shows the combined personal and accurate evaluation method, with the test equipment and environment proposed by this paper being feasible for the human factor evaluation in the accident or incident of transport category airplanes. It will benefit aviation stakeholders in determining the proper action to decrease the workload to an acceptable level.

Hybrid bearing is a kind of bearing that uses ceramic materials instead of steel and other metal materials as rolling elements. It is often used to reduce (i.e., rolling or sliding) friction resistance. Although many published works have shown that hybrid bearings are more effective than ordinary bearings in reducing friction resistance, improving service life, and reducing the occurrence of bearing failure, many few works have been focused on the tribological properties of hybrid bearings only under sliding friction conditions. Therefore, it is crucial to understand the tribological behavior of the bearing materials to evaluate the sliding tribological process. In this paper, the tribological properties of silicon nitride-bearing steel friction pair (Si₃N₄-GCr15 pair) and bearing steel-bearing steel friction pair (GCr15-GCr15 pair) under oil lubrication were experimentally studied. An optical three-dimensional (3D) reconstruction method was used to investigate the microscopic and 3D morphologies of the friction pairs during the wear evolution process. The results show that the changing trends of the micrograph, 3D topography, friction coefficient, and surface roughness are consistent. A wear failure evaluation model was built based on the data extracted from the worn surface morphology. The model indicated that the friction performance of the Si₃N₄-GCr15 pair is better than that of the GCr15-GCr15 pair. The mechanism of friction performance of different friction pairs under lubrication conditions is studied, which provides good reference for the design of subsequent hybrid bearings.