Ni60-WC coatings with different WC contents on the bucket tooth substrates were pre- pared using laser cladding technology. Their abrasive wear properties were assessed using the dry sand rubber wheel test system. The substrate and the hard-facing layer were tested for comparison. The results showed that the hardness of the Ni60-WC coatings increased with the increase in WC content. The wear resistance of the bucket tooth substrate was greatly improved by hard-facing and laser cladding Ni60-WC coatings. The wear rate of the hard-facing layer was reduced to 1/6 of that of the tooth substrate. The wear rate of the laser cladding coatings with 20–40 wt.% WC was similar to that of the hard-facing layer. It is worth mentioning that the wear rate of the coatings with 60–80 wt.% WC was only 1/4 of that of the hard-facing layer. Micro-cutting with surface plastic deformation was the main wear mechanism of the substrate to form narrow and deep furrows. The wear mechanism of the hard-facing layer was mainly plastic deformation with a wide groove, and the surface cracks promoted the removal of the material. The removal of the binder phase caused by micro-cutting was the main wear mechanism of the laser cladding Ni60-WC coatings. However, the hard phase of WC hinders micro-cutting and plastic deformation, which improves the wear resistance of the coating.

In compound fault diagnosis of rolling bearings, traditional single-modal analysis and existing multimodal fusion methods suffer from issues including insufficient cross-modal interaction, limited adaptive weighting capability, and poor discriminability in the feature space, which leads to ambiguous decoupling of compound fault features. Which leads to ambiguous decoupling of compound fault features. For this purpose, this paper proposes a decoupling method for compound faults of rolling bearings based on multimodal bidirectional cross-attention fusion and contrastive learning. First, an autoencoder extracts temporal features from vibration signals, while adaptive rectangular convolution dynamically captures multi-scale spatial features of time-frequency images. Secondly, a bidirectional cross-attention mechanism is constructed to achieve cross-modal semantic alignment through signal-to-image and image-to-signal dual guidance. Furthermore, a dynamic gating mechanism is introduced, which generates adaptive fusion weights based on the characteristics of the samples. It dynamically adjusts contribution ratio of each modality to avoid information masking. Finally, orthogonal subspace projection maps multimodal features into independent fault subspaces. When combined with contrastive learning, this approach enhances both intra-class compactness and inter-class separability, forming clear decoupling boundaries for precise fault decoupling. Experiments on PU and lab datasets show that the proposed method achieves average decoupling accuracies of 99.36% and 98.76% under various conditions. Ablation studies further confirm the synergistic effectiveness of bidirectional cross-attention, dynamic gating, and contrastive learning, offering an industrially viable approach for decoupling compound faults in rolling bearings.

Bearing is the core component of high‐speed rotating machinery. However, the lubricating oil plays an important role in reducing the temperature and the collision between components. It can improve the performance of the bearing under high‐speed rotation. Therefore, based on the theory of oil‐air two‐phase flow, this paper establishes a numerical analysis flow‐heat model of ball bearing under different oil supply. At the same time, the vibration is calculated. The influence of internal oil‐air field and thermal characteristics on vibration is analyzed. The results show that the volume of oil is not uniformly distributed in the bearing chamber. The oil gradually decreases from the outer ring to the inner ring. It is mainly concentrated on the oil‐air inlet. With the increasing of oil supply speed, the temperature of the bearing decreases firstly and then increases, and there is an optimal oil supply speed. The inner ring vibration velocity is basically similar to the temperature trend. Meanwhile, the lowest temperature is mainly concentrated near the oil‐air inlet. The maximum error between simulation results and experimental results is 11.37%. Finally, the reliability of the simulation analysis is verified by the temperature and vibration experiment. It provides some theoretical support for the optimization of oil‐air lubrication parameters of angular contact ball bearings.

Ore processing equipment is constantly subjected to impacts from various types of ore. However, the impact force characteristics generated by ore particles of different masses have not been thoroughly studied, which has hindered the design and monitoring of such equipment. This paper presents an experimental study on the dynamic impact characteristics of iron ore particles under free–fall conditions. The research focuses on understanding the mechanical behavior of ore particles of varying sizes and weights when colliding with metallic components, particularly crushers, which are critical in the ore processing industry. A modified Split Hopkinson Pressure Bar apparatus was utilized to measure the impact forces, durations, and deformation patterns during collisions. Two types of fired iron ore pellets were collected from industrial plants and sorted into different mass ranges for testing. The pellets were dropped from a height of 1 m to impact a steel rod, and the resulting impact forces were recorded using strain gauges. Additionally, finite element simulations were conducted to validate the experimental methodology. The results revealed significant variations in impact force, duration, and deformation patterns, influenced by particle mass and impact position. The maximum recorded impact force was approximately 7500 N, indicating the high energy involved in these collisions. Impact durations ranged from 0.05 to 0.11 milliseconds, emphasizing the rapid nature of the interactions. The deformation patterns were consistent across all particles, supporting the applicability of Hertz’s contact theory.This study offers valuable insights into the dynamic impact characteristics of iron ore particles, which are essential for optimizing the design and performance of mining machinery.

The air film thickness is an important parameter of an air cushion belt conveyor, which directly affects the compressed air supply power and operating resistance of the system. Therefore, it is important to calculate the bottom thickness of the gas film accurately in the design stage. A calculation method for the thickness of a conveyor air cushion was derived based on the mathematical model of the air cushion flow field for a multi row uniformly distributed air cushion structure. Meanwhile, the algorithm was validated based on a Fluent 3D flow field numerical simulation and experiments. Through verification, it was found that due to the algorithm’s assumption that the increase in the gas flow rate only existed at the axis of the gas hole, there was a sudden change in the calculation results of the gas flow rate at the axis of the gas hole. The sudden change in the gas flow rate had caused the calculation results of the air cushion thickness to experience abrupt and discontinuous changes. Furthermore, the calculation method for air cushion thickness was revised based on the verification results. Compared with the experimental test results, the average error of the calculation results of the algorithm proposed in this paper was 14.27%.