No abstract

To improve the performance of vehicle suspension, this paper proposes a semi-active vehicle suspension with a magnetorheological fluid (MRF) damper. We designed an optimized fuzzy skyhook controller with grey wolf optimizer (GWO) algorithm base on a new neuro-inverse model of the MRF damper. Because the inverse model of the MRF damper is difficult to establish directly, the Elman neural network was applied. The novelty of this study is the application of the new inverse model for semi-active vibration control and optimization of the semi-active suspension control method. The calculation results showed that the new inverse model can accurately calculate the required control current. The fuzzy skyhook control method optimized by the grey wolf optimizer (GWO) algorithm was established based on the inverse model to control the suspension vibration. The simulation results showed that the optimized fuzzy skyhook control method can simultaneously reduce the amplitude of vertical acceleration, suspension deflection, and tire dynamic load.

Engine knock limits the thermal efficiency improvement of spark-ignition (SI) engines. Thus, the extract research of the knock characteristics has a great significance for the development of gasoline engines. The research proposes a novel knock detection and diagnosis method in SI engines using the CEIITD (Complementary Ensemble Improved Intrinsic timescale decomposition) and Bi-spectrum algorithm. The CEIITD algorithm is used to extract the knock characteristics. The results show that the CEIITD algorithm can effectively and clearly extract the knock shock characteristics (including light knock) through the vibration signals. A Bi-spectrum analysis can further distinguish between the light knock signal and normal combustion signal. The Bi-spectrum results also show that knock characteristic has a strong non-Gaussian property. At last, the Band pass filter and Improved ITD method were employed to identify the knock characteristics from these cylinder block vibration signals. The comparison result shows that the CEIITD method proposed in this paper is more suitable to detect the knock characteristic.

The addition of CaF2@SiO2 and SiC whiskers to ceramic tools can improve their flexural strength and fracture toughness, reduce surface damage, and improve their cutting performance. The cutting experiments showed that under the same cutting conditions, the surface roughness of the workpiece processed with the Al2O3/TiC/SiC/CaF2@SiO2 (ATSC10) tool was significantly lower than that of the workpiece processed with the Al2O3/TiC/ SiC (ATS) tool. Additionally, the main cutting force and cutting temperature when cutting with the ATSC10 tool were lower by 30 and 31.7%, respectively. These results were attributed to the precipitation of CaF2 from the nanocoated particles during cutting and the formation of a uniform and continuous lubricating film on the surface of the tool. The wear on the front surface of the ATS tool was mainly adhesive, and that on the back tool surface was mainly abrasive. For ATSC10, the main forms of wear on the tool front surface were adhesive and abrasive, whereas the main form of wear on the tool back surface was abrasive with slight adhesive wear. The addition of nano-coated particles and whiskers improved the mechanical properties of the cutting tool while maintaining good cutting performance.

The path planning algorithm of unmanned construction machinery is studied, and the potential field ant colony algorithm is improved to be applied in the field of unmanned construction machinery. Firstly, the raster map modeling was optimized to eliminate the trap grid in the map. At the beginning of algorithm iteration, the heuristic information of artificial potential field method was added and the global pheromone updating model was improve the convergence speed of the algorithm. In addition, the weight coefficient of potential field force and local pheromone updating model were introduced to enhance the development of raster map in the later iteration of ant colony algorithm and reduce the influence of heuristic information of potential field force. Finally, the selection range of parameters such as optimal pheromone heuristic factor and ant colony number is determined by simulation, and it is verified that the algorithm is better than the basic ant colony algorithm.