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The rotary excitation valve is one of the key components for the high-frequency and high-pressure electro-hydraulic excitation system, and its dynamic characteristics directly affect the performance of the entire excitation system.In order to study the dynamic characteristics of the rotary excitation valve under the coupling effect of Fluid-Thermal-Solid multi-field. First, the flow field of the rotary excitation valve was dynamically simulated by the sliding grid method through Fluent simulation, and the simulation results were verified by the measured flow rate of the rotary excitation valve. Then, the Fluid-Thermal-Solid multi-field coupling simulation of the rotary excitation valve was performed by using ANSYS. The thermal characteristics and thermal deformation laws of the rotary excitation valve was studied when the pressure difference between inlet and outlet ΔP are 5 MPa, 10 MPa, 15 MPa and the oil temperature are 20℃, 40℃, 60℃ respectively. The research results show that the internal flow field and temperature field of the rotary vibration valve are not uniformly distributed. The temperature of fluid near the valve core and the wall of valve body is higher, and the center temperature is lower.Due to the impact of the fluid at the outlet of rotary excitation valve, a local high temperature will be generated, resulting in thermal deformation of the valve core groove and the valve body outlet port.When the pressure difference between inlet and outlet at 15 MPa, the thermal deformation is 3.789 4 μm, and the oil inlet temperature at 60℃, the thermal deformation is 7.701 7 μm. Therefore, choosing the pressure difference between inlet and outlet and oil temperature is beneficial to the operational characteristics for rotary excitation valve. The theoretical data for the structural design and optimization of the rotary excitation valve are provided.

In order to accurately diagnose the fault of submersible sewage pump, an improved Hopfield neural network（HNN） fault diagnosis method was proposed. BP neural network was used for coding operation to overcome the coding defects of HNN neural network. The connection weights of HNN neural network were optimized by particle swarm optimization（PSO） algorithm to improve the global convergence ability of the improved neural network, and the improved HNN neural network model was obtained. Based on the field experiments, the vibration signal feature vector of the submersible sewage pump under fault operation was obtained. Then the feature vector was used as sample data to train the improved neural network, and the fault types of the submersible sewage pump were diagnosed. The results show that the improved HNN neural network has better global convergence ability, and the typical fault diagnostic accuracy of the submersible sewage pump is more than 90%, which can realize the accurate diagnosis of the fault during the operation of the submersible sewage pump.

In order to reduce the flow pulsation of the inner meshing gear pump,taking PGH type involute internal gear pump as the research object,the mathematical model of flow pulsation rate and tooth profile parameters was established,and the instantaneous flow rate of gear pump outer gear ring and internal gear in different meshing relations was analyzed. Based on these,a mathematical model of gear pump optimization was established. The improved particle swarm optimization was obtained by introducing the genetic operation and mutation operation of the genetic algorithm into the particle swarm optimization algorithm,through this algorithm、the parameters of gear indexing circle pressure angle、modification coefficient、addendum coefficient and tooth number were optimized,and the gear parameters of gear pump with minimum flow pulsation rate were obtained. The simulation verification was carried out by MATLAB,and the results showed that the flow pulsation rate and the tooth shape parameters of the gear pump are nonlinear; Under the condition of satisfying the structural requirements and reasonable transmission,the flow pulsation rate of the gear pump is reduced by 7. 27%,and the flow pulsation of the internal gear pump is reduced.

In order to study the fluid flow characteristics of the key components in the hydraulic excited rotary valve, then determine the area of vortex and negative pressure to find the weak link in the structure and analyse the performance of the valve. Simulate the flow field in the rotary valve by Fluent fluid analysis software and set different opening degrees under the same boundary conditions. Studies showed that the velocity at the exit junction of the fluid in the rotary valve and the vortex degree of pressure are large at the oil groove. When the opening degree is small, the negative pressure is large, the vortex is obvious. When the opening becomes large, the negative pressure and vortex are improved. The research provides a theoretical basis for the optimisation and improvement of the rotary valve.

To determine the optimal process parameters for the preparation of a Co-based alloy cladding layer, the experimental research of laser cladding Co-based alloy was carried out based on the optimal process window and grey relational analysis methods with 42CrMo as the substrate. The analysis of variance (ANOVA) was used to explore the influence laws of laser process parameters on the forming characteristics of the cladding layer within the optimal process window range. Furthermore, the optimal process parameter combination was obtained by grey relational analysis, and the experimental verification of the optimization results was conducted. It was found that the process parameter interval determined by the optimal process window was laser power 1300–2100 W, scanning speed 6–14 mm/s, and powder feeding rate 17.90–29.84 g/min. The influence order of each process parameter was: laser power > scanning speed > powder feeding rate. The optimal process parameters of laser power 2100 W, scanning speed 6 mm/s, and powder feeding rate 17.90 g/min were obtained. The experimental verification results of optimal process parameters proved that the grey correlation grade of the optimized parameters was improved by 0.260 compared with the initial parameters and agreed well with the prediction value with an accuracy of 96%. After optimization, the cross-sectional area, the ratio of the width to height, cladding efficiency, and powder utilization rate of the cladding track increased by 4.065 mm2, 1.031, 19.032, and 70.3%, respectively, and the fluctuation ratio decreased by 60.9%. The optimal cladding track was well bonded to the substrate without cracks, holes, and evident element segregation, and included the phases of Cr3C7, CoCx, fcc-Co, and WC. [ABSTRACT FROM AUTHOR]