To address the coupled disturbances of inductance lag faced by the limited-angle torque motor and the high-stiffness rotary flow forces of the direct-drive servo rotary valve, a dual-model feedforward discrete integral sliding mode control strategy is proposed. To solve the issues of a long initial dead zone and steady-state high-frequency chattering in traditional pure sliding mode control, this strategy introduces a mechanical model feedforward to actively cancel the return spring and steady-state flow forces, effectively unloading elastic loads and suppressing chattering. Furthermore, to overcome the response lag limitation caused by the lack of over-drive in the single mechanical feedforward, this strategy superimposes an inverse electrical model feedforward to generate an over-drive voltage at the instant of command mutation, actively overcoming the coil inductance lag. High-fidelity comparative simulations indicate that this strategy compresses the initial dead zone to 0.6 ms and further shortens the step rise time by 38.5% to 8.0 ms compared to the single feedforward scheme. Bench tests at 7 MPa further verify the actual effectiveness of the strategy, showing a measured step rise time of approximately 8.2 ms and a steady-state tracking error converging to 0.04°.

The electro-hydraulic digital valve has the merits of good linearity and high reliability, which is the fundamental component in hydraulic digital control. To solve the problems that binary-coded valve groups require a large number of on/off valves, and that high-speed on/off valves have small flow rates and large impact, a decimal-coded electro-hydraulic digital flow valve is proposed, whose output flow rates follow a natural number sequence proportional relationship. Compared with binary-coded valve groups, given the same number of on/off valves, this valve achieves a wider flow regulation range and higher precision. Compared with high-speed on/off valves, it controls a larger flow rate with a smaller impact. The structure and working principle of the decimal-coded electro-hydraulic digital valve are first introduced, followed by the establishment of its static flow characteristic model. Combining the stepper motor model and the electromagnet dynamic model, a corresponding Simulink simulation model is constructed. Finally, the actual flow characteristics are obtained through experiments. The results show that at a supply pressure of 3 MPa, the output flow range of the designed valve is 0~19.3733 L/min, with a resolution of approximately 0.1294 L/min. The flow rate exhibits a linear relationship with the input signal with a smaller hysteresis. Under rated output, the step response time is less than 0.07 s, and the theoretical values obtained from the model agree well with the experimental values.

To address the difficulty in predicting flow-induced noise due to complex unsteady internal flow in axial piston pumps, a fluid-structure-acoustic multi-field coupling method is proposed to systematically analyze unsteady flow, housing vibration, and flow-induced noise. Firstly, the Smagorinsky large eddy turbulence model is adopted, with pistons and cylinder block set as rotating domains. The reciprocating motion of pistons is simulated using moving mesh and kinematic equations. Secondly, based on Lighthill's acoustic analogy, flow stress tensors and normal mass flow are mapped onto the acoustic mesh as acoustic sources. Vibration excitation is defined using sound pressure and the normal vector of the housing surface. A COMSOL multiphysics coupling model is then constructed. An experimental platform is built to validate the algorithm. Results show that oil flows out as a jet from the damping grooves of the valve plate. Sudden changes in pressure and velocity induce pressure pulsations, which act on the inner wall of the pump housing, excite housing vibration, and radiate flow-induced noise. The internal fluid sound source peak reaches up to 160 dB, but noise significantly attenuates through pump structure transmission, with radiated housing noise dropping to about 40 dB. Flow-induced noise exhibits wideband characteristics across the entire frequency range, and sound pressure level gradually decreases with increasing frequency. The measured total sound pressure level of housing-radiated noise is 63.79 dB, while the numerical simulation result is 53.43 dB. The close agreement validates the accuracy of the proposed method.

The semiconductor industry currently demands low breakage rates and energy efficiency for wafer handling. Bernoulli grippers are widely used due to their simple structure and contamination-free nature. However, high positive pressure during adsorption creates shear stress that damages wafers, while high air consumption leads to energy waste.The nozzle is the core component of the gripper. Its geometry and design parameters determine the pressure distribution and air consumption. We optimize the nozzle structure to achieve low breakage rates and reduced energy consumption.Numerical simulations are carried out using CFD for three nozzle shapes: rectangular, triangular, and arc. We also evaluate three nozzle heights: 0.3, 0.4 and 0.5 mm. Appropriate evaluation metrics are established to obtain curves of gripper radius versus bottom static pressure. Results indicate that the arc-shaped nozzle with a height of 0.4 mm offers the optimal performance.

The drainage system is essential for the normal operation of underwater vehicles. A bladder-type attenuator is an effective measure for reducing pipeline noise. It also improves the overall stability, reliability, and stealth performance of underwater vehicles. We use the ideal gas equation of state and the Ogden hyperelastic constitutive equation. The arbitrary Lagrangian-Eulerian (ALE) method is adopted to simulate the shapes of the rubber bladder and the fluid domain of the bladder-type attenuator under steady-state operating conditions. The noise transmission loss of the attenuator is calculated using the acoustic simulation software Actran. The results show that the ALE method effectively handles large deformations of rubber materials. It also addresses two-way fluid-structure interaction. Under steady-state operating conditions, the rubber bladder presents a trilobal-like shape. The attenuator significantly suppresses noise over a wide frequency range.

To solve the flow mismatch problem caused by unequal effective areas of the two chambers in single-rod hydraulic cylinders and overcome the low power density limitation of pure electric cylinders, we present a hybrid drive scheme combining hydraulic rotation and mechanical linear conversion. A hydraulic motor replaces the servo motor to drive the ball screw and actuate the piston rod. The proposed actuator has advantages of symmetric control, small chamber volume, variable displacement and high power-to-weight ratio. A simulation model of the valve-controlled hydraulic rotary-mechanical linear actuator system is established. A test platform with an experimental prototype is built to verify the feasibility of the actuator. The position closed-loop control strategy integrated with velocity feedforward control is adopted to investigate the control characteristics of the actuator mechanism. The results show that the valve-controlled actuator system with the velocity feedforward position closed-loop control strategy has good position control performance, with a maximum displacement error of approximately 0.606 mm relative to the set value.

Hydraulic motors are widely used in high-end manufacturing, engineering machinery, marine and military industries. The slipper pair between connecting rod slipper and crankshaft serves as the key load-bearing friction pair of crank-connecting rod type low-speed high-torque hydraulic motors, which critically affects the working performance and operational efficiency of the motors. Under high-pressure load conditions, the deformation of the connecting rod slipper further deteriorates the oil film performance of the slipper pair. We establish a mechanical mathematical model of the connecting rod slipper structure, and adopt the structural finite element analysis method to explore the influence of hydrostatic support parameters on the structural deformation of the connecting rod slipper. The results show that the maximum deformation of the slipper bottom surface is 0.014 mm under normal parameter conditions. Tilting exerts the most significant effect on the deformation of the slipper surface, with the maximum deformation increased by 42.85%. When the diameter of the damping hole increases from 0.5 mm to 0.9 mm, the maximum deformation of the slipper surface decreases by 38.89%. The increase of oil chamber area can restrain the deformation of the slipper surface. This research provides a theoretical basis for structural design and performance optimization of the slipper pair in hydraulic motors.

When an aircraft operates at high altitude and low temperature, ice may accrete on the engine nacelle lip skin. To ensure flight safety, a hot air anti-icing system is usually installed. As a key component of this system, the air butterfly valve provides stable outlet pressure for engine anti-icing. However, conventional mechanical servo structures often lead to poor outlet pressure stability, which may cause anti-icing failure or energy waste. Therefore, analyzing the outlet pressure stability of the air butterfly valve is necessary. In this study, a mathematical model of the pressure regulating system is first established to identify the main parameters affecting outlet pressure. Flow field simulations are then conducted to obtain the relationship between butterfly plate torque and inlet pressure. Finally, an AMESim simulation model is built to investigate the influence of structural parameters on outlet pressure stability. Results show that control valve spring stiffness, pilot valve orifice diameter, and butterfly plate load torque significantly affect outlet pressure. Optimizing these parameters can effectively reduce outlet pressure fluctuations and improve outlet pressure stability and is important for enhancing anti-icing system reliability and ensuring flight safety.

To suppress the main-circuit pressure pulsation and speed fluctuation of the variable-displacement motor of a wave energy hydraulic power take-off system, and to reduce the throttling loss caused by traditional valve control, a pressure-speed coordinated control method based on a hydraulic transformer is proposed. The proposed method uses a hydraulic transformer composed of a variable-displacement pump and a fixed-displacement motor as the pressure-flow conversion stage to replace the throttling pressure regulation stage of the traditional proportional flow valve. By regulating the displacement of the variable-displacement pump, the output flow of the hydraulic transformer is matched with the load demand, while the displacement regulation of the variable-displacement motor is used to improve the inlet pressure response, so that the hydraulic power take-off system can maintain relatively stable main-circuit pressure and output speed when wave height and period vary. Based on co-simulation with Simulink and AMESim, models of a valve-controlled throttling speed-regulation hydraulic power take-off system and a hydraulic power take-off system using the proposed constant-pressure and constant-speed control method based on a hydraulic transformer are established, and comparative simulations are carried out under varying wave conditions such as wave height reduction and period shortening. The results show that, compared with the traditional valve-controlled throttling speed-regulation system, the hydraulic power take-off system using the proposed constant-pressure and constant-speed control method based on a hydraulic transformer improves speed stability, reduces main-circuit pressure fluctuation, and exhibits faster response characteristics under sudden wave condition changes, providing a new approach for energy-saving optimization of wave energy hydraulic power take-off systems.

The structural parameters of the 2D valve control stage have a cross influence on the working characteristics, and unreasonable parameters may cause problems such as vibration and whistling. Firstly, a 2D valve AMESim simulation model is established to study the influence of key parameters on dynamic characteristics. Then, the transfer function is derived and the stability model is obtained based on the Routh stability criterion. Aimed at the problem of mutual constraint between response speed and stability, an adaptive non-dominated sorting genetic algorithm-II is proposed, which introduces dynamic adjustment of cross mutation probability based on individual age and improves the distribution uniformity of Pareto front through crowding penalty mechanism. We calculate the Pareto front with the goal of maximizing flow gain and amplitude margin, and finally compare the results before and after optimization. Under a system pressure of 7 MPa, the optimized 2D valve achieves a 4 ms improvement in step response speed, a 15.5 Hz increase in amplitude bandwidth, and an 11 Hz rise in phase bandwidth, providing a certain reference for the design of 2D valve structures.

Complex piping systems exhibit coupling among their components. This makes it difficult to accurately predict the flow field using empirical formulas or a single theoretical method. Traditional computational fluid dynamics methods can resolve coupled flow fields in complex piping systems, but they require long computation time and high memory consumption. We investigate a data-driven method for flow field prediction in complex piping systems based on physics-informed neural networks. A training dataset is constructed from computational fluid dynamics simulation data, and a physics-informed neural network model is trained to accelerate the solution of flow fields in complex piping systems. The model directly embeds physical constraints into the loss function, so it can be trained with only a limited amount of training data. With spatial coordinates as input, the network outputs pressure and velocity at the corresponding locations. It reconstructs the flow field with good accuracy and enables rapid and accurate prediction. The results show that, with relative errors of 1.03% for the pressure field L2 and 13.28% for the velocity field L2, the trained physics-informed neural network model reduces the computational time by 94.52% in the inference stage, significantly improving the efficiency of flow-field solution in complex piping systems.

To address the problem of inconsistent steering in narrow alleys for mining all-terrain transport vehicles, in order to enhance their handling stability and operational reliability, the structural design of the steering system and the analysis of influencing factors are carried out. The three-dimensional modeling of the steering structure is completed using SolidWorks, and finite element simulation is conducted using ANSYS to verify the structural strength and dynamic stability. The dynamic and hydraulic system simulation models are built based on Simulink and AMESim respectively, revealing the mechanical laws that uneven loading, impacts, and step loads cause continuous imbalance in the steering speeds of the left and right wheels by changing the force state of the wheels; it is also clarified that the pressure and flow of the hydraulic system have a coupled response, and the output torque of the motor is proportional to the pressure difference at the inlet and outlet of the hydraulic system. The research results provide theoretical and technical support for the optimization design of the steering system of mining all-terrain transport vehicles, and have significant engineering value for improving the efficiency of underground auxiliary transportation.

As a core component of typical soft drive systems, the pneumatic muscle actuator exhibits broad application prospects while its performance influenced by multi-physical field coupling and geometric structure. From thermodynamics and dynamics perspectives, based on the adiabatic system assumption, ideal gas state equation, geometric constraints, and mechanical equilibrium conditions, a coupled model is established to systematically investigate the working mechanism and influencing factors of pneumatic muscle actuator. The model reveals the intrinsic relationship between internal pressure changes and axial contraction motion of the pneumatic muscle actuator. An experimental device centered on an airbag-braided mesh assembly is designed. By controlling parameters such as initial diameter, initial length, airbag shape, and braided mesh structure, combined with numerical simulation, the model is validated. Results show that increasing initial diameter, extending initial length, or adopting a strip-like airbag shape significantly enhances contraction capacity and air intake, but leads to delayed response time and reduced dynamic response performance. Numerical simulation results from the theoretical model show good consistency with experimental trends and key parameters, confirming the model's validity. This provides a theoretical basis for structural optimization and engineering application of pneumatic muscle actuator.

Traditional fault diagnosis methods for rotating machinery often rely on vibration signals and ignore the correlation and complementarity among multi-source signals. To solve this problem, a multi-source fault diagnosis method based on tensor fusion and a dual-attention mechanism is proposed. Centrifugal pumps and constant-pressure variable pumps are selected as research objects. Acoustic and vibration signals are collected during operation. Continuous wavelet transform converts the original one-dimensional signals into two-dimensional time-frequency matrices. These matrices describe the time-frequency characteristics of the signals. A feature fusion framework based on tensor fusion and a dual-attention mechanism is then introduced. The time-frequency matrices of acoustic and vibration signals are organized as multi-channel tensor data. This process enhances feature correlation among multi-source signals. The dual-attention mechanism learns features from the fused samples. The spatial attention mechanism extracts local key information from the time-frequency matrices. The channel attention mechanism strengthens the correlation among features from different channels. Two experimental cases involving centrifugal pumps and constant-pressure variable pumps verify the effectiveness of the proposed method. The results show that the proposed method achieves higher fault diagnosis accuracy than existing methods. It also reduces hardware requirements and shows strong potential for engineering applications.