The dynamic pressure signals of hydraulic systems have the characteristics of nonlinearity, multi-source coupling, and sensitivity to operating conditions. This results in high signal complexity and low feature discernibility, rendering traditional diagnostic methods ineffective. A deep learning diagnostic framework based on multi-sensor collaborative perception is proposed to address these issues. Multiple heterogeneous sensor signals are mapped into a multi-channel input tensor through spatial topology mapping, which preserves independent sensor features while achieving joint representation of multimodal information. A parallel convolutional architecture extracts spatiotemporal features from each channel, and an effective channel attention mechanism enhances fault-sensitive information, optimizing cross-modal features for precise classification. Experimental results show that the proposed method achieves over 95% accuracy in diagnosis of hydraulic pump leakage fault on the UCI standard hydraulic dataset. By introducing transfer learning theory, the pre trained model trained on the UCI standard hydraulic dataset is transferred to the forklift lifting hydraulic system, and the model still maintains an accuracy of 97.65%. These results confirm the model's strong generalization ability across different scenarios and provide an effective solution for fault diagnosis in complex hydraulic systems.

To reduce the overall energy consumption of hydraulic excavators and improve the energy utilization efficiency of the hydraulic system, this study proposes an energy recovery and reuse system for the potential energy of the excavator's boom, utilizing a hydraulic winch and an accumulator. The system recovers gravitational potential energy during boom descent and reuses it to assist in boom lifting, thereby reducing the working pressure of the hydraulic system and decreasing fuel consumption. First, the working principle of the system is elaborated in detail, and a mathematical model of the energy-saving device is established. Next, the system is modeled and simulated using AMESim software. The simulation results demonstrate that the system effectively recovers the gravitational potential energy of the descending boom and assists in boom lifting, achieving an energy-saving efficiency of approximately 55.6%. Finally, an experimental bench is constructed to validate the feasibility and effectiveness of the proposed energy-saving device.

Insufficient control precision is caused by strong nonlinearity in vacuum butterfly valve pressure control systems. A dual-mode switching strategy fusing Active Disturbance Rejection Control (ADRC) and PID control is proposed. The controller utilizes an extended state observer to uniformly estimate and compensate for aggregated disturbances including gas temperature drift, sealing friction, and gas source fluctuations. A pressure error threshold triggering mechanism is designed to activate ADRC exclusively during dynamic processes for rapid overshoot suppression, while automatically switching to lightweight PID control during steady-state operation to maintain precision. Compared with conventional PID control, settling time of proposed method is significantly shortened and overshoot substantially reduced. Compared with single ADRC control, steady-state error is effectively minimized. Under flow disturbances, pressure recovery time is 67% faster than that of PID control, with a steady-state error below 25 Pa. This approach significantly enhances system response speed, precision, and robustness, fully leveraging the cost advantage of butterfly valves. And it provides a high-performance, low-cost vacuum pressure control solution for semiconductor, aerospace, and related fields.

In grain storage management, the curved surface structure of silo walls imposes stringent demands on the adhesion performance of wall-climbing robots. These robots must possess sufficient flexibility to adapt to curved surfaces while maintaining adequate rigidity to ensure stable support. We find that when a rigid suction cup is employed on walls with varying curvature, the limited deformation capacity of the suction cup body causes the sponge to adopt a “saddle-shaped” deformation during adhesion, which significantly diminishes the adhesion performance. To address this issue, we optimize the rigid suction cup structure, leading to the design of a semi-rigid suction cup with distributed rigid elements. The adhesion force experiments on various simulated substrates reveal that the rigid suction cup exhibit forces of 205.49 N, 307.56 N and 360.25 N on simulated substrates with curvature radii of 100 mm, 200 mm and 400 mm, respectively. In contrast, the semi-rigid suction cup exhibit slight fluctuations in adhesion force across different curved surfaces, yet maintain a stable overall value around 420 N. This solution achieves a significant enhancement in adhesion performance on complex curved surfaces, effectively reducing the risk of detachment during robot operation, which establishes a reliable foundation for expanding the application of wall-climbing robots in areas such as silos.

Porous graphite materials significantly influence the performance of porous restrictors, which are key components of aerostatic guideways. This study employs the compressible Darcy-Forchheimer equation to fit experimental data and determine the permeability and inertia coefficients of porous graphite with five different porosities (18%, 17%, 13%, 12%, 11%). A CFD model incorporating these coefficients is established, accurately predicting the flow velocity and pressure drop within the porous medium, with an error margin within 5%. Further analysis under various supply pressures and loading conditions reveals that restrictors made from low-permeability graphite materials exhibit superior load-bearing capacity and gas film stiffness. Specifically, under a supply pressure of 0.45 MPa, the stability of the aerostatic block is significantly enhanced. Based on this research, an experimental platform for an aerostatic guideway with an adjustable gas film thickness is constructed using low-permeability restrictors. The guideway surface straightness is verified using a Keyence laser sensor, achieving better than 2.5 μm/600 mm.

Magnetic fluid seals with large diameter are prone to deformation in the environment with a wide temperature range, resulting in a decrease of its maximum working pressure, which means a decline in its pressure resistance performance. In this research, a pressure resistance formula for magnetic fluid seals with the consideration of temperature effects is derived, and the saturation magnetization of magnetic fluids at different temperatures are measured and the simulation analysis of temperature-structure-magnetic field coupling on magnetic fluid seals with large diameter in a wide temperature range is conducted to address the above problems. The structural deformation of the seal at the temperature range of -60~+80 ℃ is analyzed. Furthermore, the magnetic field distribution after the seal deformation is analyzed and the theoretical pressure resistance values of magnetic fluid seals at different temperatures are calculated.Thereby, the reason for changes of pressure resistance of magnetic fluid seals is clarified, which provides a new design method for magnetic fluid rotary seals with large diameter in a wide temperature range. The sealing experiments verify that the magnetic fluid seals designed using this method meet the sealing design requirements.

In order to provide a simulation model for the excitation current and an integrated testing method for the main steam isolation quick-closing solenoid valve in current nuclear power plants, a mathematical model of mass-spring-damping system for solenoid valve core is first established. The excitation current characteristics of the solenoid valve are then simulated and analyzed. Furthermore, based on the current characteristics principle of the solenoid valve and the LabVIEW measurement and control platform, an integrated testing device is designed. This device is used to test the excitation current characteristics of the main steam isolation quick-closing solenoid valve. The test results show that the difference compared to the motion simulation results does not exceed 15%, indicating the rationality of the hardware and software design of the testing device. This testing method has been applied to the detection of quick-closing solenoid valve for main steam isolation valve of the “Hualong One” reactor unit at unit 5 of the Fuqing Nuclear Power Plant, where multiple practical tests have been carried out. The results meet the expectations, providing data and theoretical support for operation and maintenance of the solenoid valve.

Aimed at the problems of low static accuracy and limited dynamic performance of pump control unit, a fuzzy PID pressure stability control method based on load prediction feedforward compensation is proposed to improve the pressure control capability of the pump control unit. Firstly, mathematical models for the servo motor and fixed displacement pump in the pump control unit are established. Secondly, a load prediction algorithm based on long short-term memory neural network is designed, and we train the model, optimize the hyperparameter setting, calculate the evaluation index and carry out simulation verification. Furthermore, the proposed fuzzy PID control method based on load prediction feedforward compensation is analyzed through simulations. Finally, experimental studies validate the control method's effectiveness. The load prediction model achieves high prediction accuracy confirmed by evaluation metrics. With the use of the load prediction results as feedforward signal input compensation, the error between output pressure and expected pressure under two signal responses is reduced by 72.2% and 71.1% respectively compared with that of traditional PID controllers, enabling high-precision pressure stability control in the pump control unit.

Deflector jet servo valve fault signals are limited and easily affected by noise under complex conditions, resulting in difficult feature extraction. This paper presents a fault diagnosis method combining starfish optimization algorithm-based variational mode decomposition, temporal convolutional network, and a self-attention bidirectional gated recurrent unit network. The starfish optimization algorithm selects variational mode decomposition parameters to improve decomposition accuracy and robustness. Main features are extracted from key intrinsic mode functions based on minimum envelope entropy. These features are entered into a temporal convolutional network and a self-attention-based bidirectional gated recurrent unit network to enhance fault classification. A fault simulation platform and dataset are built, with experiments under typical fault conditions. Results show that the fault recognition accuracy of the method achieves 97.33%, demonstrating strong robustness and high diagnostic performance.

The local temperature of the swash plate increases close to the tempering temperature of the material under the swash plate axial pistion pump slipper pair working condition of high speed and large load. As a result, the residual austenite phase transformation causes the material surface expansion, the formation of static pressure support oil film, the surface hardness and durability decrease and other problems. Based on the premise of improving the friction and wear performance of the axial piston pump friction pair under high speed operation. A comparative analysis between the substitute material and the finished sample through composition analysis, high temperature treatment, friction and wear experiments is conducted. The results show that the average surface hardness of B material is increased by 17.7% compared with the original finished material at room temperature. After being stored at 400 ℃ for 10 h, the surface hardness of B material can still remain above 700 HV, the average maximum surface deformation of no more than 1 μm on the surface, and the average wear is reduced by 5.9% compared to the finished sample. The possibility of substitute material selection for swash plate axial piston pump under high speed operation is verified, which provides a reference for the follow-up research on material selection of swash plate axial piston pump.

There are problems of unstable control accuracy and imperfect matching of various types of equipment in current proportional control valve drivers, which cannot meet the flexibility, rapidly and localization requirements of modern electro-hydraulic control systems a digital-analog hybrid proportional control valve driver based on the GD32F450ZKT6 control chip is developed. The designed driver integrates a main control module circuit, power amplification circuit, ADC sampling circuit, and CAN/USB communication circuits, thereby enabling the realization of multiple command signal inputs, host computer parameter configuration, and output precision control functions. A test platform is further established to conduct the performance of the hybrid proportional control valve driver. The results show that the developed driver achieves an output accuracy of less than 2% under diverse signal command inputs, incorporates comprehensive control parameter configuration capabilities, and effectively satisfies the electro-hydraulic control requirements across multiple operational scenarios.

This study addresses control challenges in mold demolding systems under nonlinear and time-varying load conditions. A tracking differential fuzzy PID compound control strategy is proposed to enhance system performance by integrating tracking differentiator technology with fuzzy PID control. The strategy features rapid error signal tracking and dynamic self-tuning of PID parameters. The co-simulation experiments combining AMESim and Simulink validate the proposed method. The results demonstrate significant improvements over conventional PID and fuzzy PID controllers: reduced response lag and steady-state error, enhanced tracking precision under high-frequency noise and superior disturbance rejection against unknown large-load interference. The control strategy maintains stable performance in complex operating environments while achieving faster dynamic response. These findings provide theoretical support for high-precision hydraulic servo control in mold demolding systems, particularly in scenarios requiring robust adaptability to nonlinear disturbances. The proposed method offers a practical solution for optimizing industrial mold demolding processes with time-varying dynamics.

Slipper wear is a common failure in piston pumps. Aimed at the failures of the flow rate decrease and excessive vibration of the pump caused by slipper wear in the fuel piston pump of a certain type of aero-engine, a comprehensive failure diagnosis method is proposed within the framework of multiple disciplines including dynamics, tribology, fluid lubrication, and structural strength. The calculation and simulation of the oil film thickness, structural strength, and pv value of the slipper of this type of fuel piston pump under multiple operating conditions are carried out, and the associated mechanism between each operating condition and the wear failure is analyzed. The research results show that the structural strength of the slipper of the fuel piston pump meets the requirements within the full operating condition range, and the oil film characteristics are favorable when the rotational speed is below 4500 r/min. However, when the rotational speed of the fuel piston pump gradually increases, the proportion of the axial inertial force and centrifugal force acting on the slipper pair in the contribution to the pressing force gradually increases. When the rotational speed increases to 5000 r/min, the supporting force cannot effectively compensate for the external pressing force, resulting in the rupture of the hydrostatic oil film of the slipper pair. The slipper and the swash plate change from the fluid lubrication state to the boundary lubrication state or the direct contact state. Moreover, the pv value of the material of the slipper pair is in an over-limit state under the high rotational speed operating condition, which ultimately leads to wear failure.

In order to enhance the linear regulation capability of solenoid high-speed switching valves and achieve precise control of brake fluid flow, an influence factor characterizing the radial force on axial force of valve core is proposed. The numerical simulation of the internal flow field in the apply valve is carried out, additionally, it is found that the existing structure of valve seat and spool significantly affects brake fluid jet characteristics under Coanda Effect, coupled with asymmetric outlet geometry. These factors collectively increase the vortex probability and instability of flow field in the throttling region, which inducing substantial radial force during the opening and closing cycles. Structure optimization is implemented by reducing the spool spherical throttle ineffective area, implementing of variable-cone-angle surfaces on the valve seat and incorporating symmetrical supplementary outlet ports to improve flow field symmetry. The results show that the flow field of throttle area in new structure is more stable, the radial force on the spool is 0.1 N or less, which is with the opposite direction of the bias and is conducive to self-alignment of the spool. Finally, the new structure effectively weakening the radial force's impact on the linear regulation, reliability and life of the solenoid valve.

Shear thickening fluid is a kind of intelligent material, and when applying the shear thickening fluid to the damper, we obtain the shear thickening fluid damper. Based on the reason that shear thickening fluid damper will be subjected to huge resistance due to the existence of velocity gradient when the fluid flows through small pores or gaps, the shear thickening fluid damper plays a key role in energy absorption and shock absorption. Through the way of Fluent simulation, the shear thickening fluid which is made of 20% mass fraction of nano-silica-polyethylene glycol solution is used as the working medium of the shear thickening fluid damper, and the flow of the shear thickening fluid in the damping holes is used to simulate the working process of the damper, and then draw the force-displacement hysteresis curves at different frequencies. The energy produced by the resistance force during the working process of the shear thickening fluid damper is calculated according to the results of the hysteresis curve to analyze the energy absorption effect. From the results, it is known that under the condition of the low-frequency working environment (f≤2 Hz), the force-displacement curve shows a good characteristic of symmetry, and the energy consumed in the retraction process of the damper is almost equal to that in the process of extension. But with the increase of frequency (f>2 Hz), the symmetric characteristic of the force-displacement curve becomes worse, and the energy consumed in the retraction process of the damper and the extension process are quite different.

In order to reduce the power losses in construction machinery, a novel variable displacement opposed piston pump is proposed. The pump adds a piston on the basis of the traditional single-plunger pump, and the two pistons are arranged symmetrically, which not only attenuates the pressure fluctuation and eliminates the unbalance force of the single-plunger pump, but also realises variable displacement by adjusting the phase difference of the pistons. An AMESim model of the pump is developed and calibrated via equivalent modeling. The lag time of the distribution valve of this pump is compared with that of the traditional piston pump, and it is found that the lag time is relatively less, but there still exists a lag phenomenon, which led to a decrease in the performance of the pump, so the influence of different parameters of the inlet valve on the lag time of the distribution valve is comparatively analysed and the parameters are optimized using the orthogonal method. The results show that: the inlet valve parameters all have a greater impact on the inlet valve closing lag time, which is manifested as with the increase of spring stiffness, spring preload, spool diameter, respectively, the closing lag time is decreased by 10.9, 10.72, 1.73 ms, and is increased by 5.7 ms with the increase of spool mass; after parameter normalisation, the closing lag time of the outlet valve is decreased by 61.6%, 84.1%, and 8.9% with the increase of spring stiffness, spring preload, and spool diameter, respectively, with the increase of spool mass increasing by 37.1%. After orthogonal optimisation, the lag time of the outlet valve closure of the simulation model is decreased by 81.43%, which effectively reduces the return loss and improves the performance of the pump.

The disc spring hydraulic mechanism is a key equipment in the power system, and its performance directly impacts the reliability of the system. Dynamic characteristic analysis of its key components aims to enhance operational stability. The mechanism's structural composition and operational principles are analysed firstly. Subsequently, Fluent-based simulations investigate the pressure variation characteristics in both rodless and rod cavities of the working cylinder piston. These simulations reveal the intrinsic correlation between piston velocity and pressure fluctuations. Further research focuses on gas pressure dynamics in the arc-extinguishing chamber during circuit-breaking operations, employing pressure cloud diagrams to analyse the spatial-temporal pressure distribution patterns in both the disc spring hydraulic mechanism and the arc-extinguishing chamber. Experimental validation confirms the accuracy of this dynamic analyses, establishes a theoretical foundation for optimizing mechanism design and improving operational stability.

Due to the fact that electro-hydraulic servo systems are often affected by internal and external disturbances, and internal parameters change due to mechanical structure wear, the traditional control strategies are no longer sufficient to meet the control performance requirements. Therefore, a filter-based adaptive asymptotic tracking control method with guaranteed performance is proposed. Firstly, a mathematical model of the electro-hydraulic servo system is established, which is transformed into a strict feedback form space state expression by defining state variables. Then, the controller design and stability analysis are carried out. A novel error transformation is designed and combined with a barrier function to achieve the prescribe performance constraints on the tracking error. In the controller design, a single-parameter adaptive method is adopted to estimate the unknown parameters. Meanwhile, to avoid the continuous differentiation of the virtual controller, a nonlinear filter is introduced. Finally, by using the Lyapunov stability theorem and Barbalat's lemma, it is proved that the system can achieve asymptotic tracking, and the tracking error is limited within the prescribe performance function range. All signals of the closed-loop system are semi-globally uniformly bounded. The effectiveness of the control strategy is verified through simulation and compared with traditional PID and backstepping control strategies. The research results show that the rise time is increased by 82.8% and 80.3% respectively, the adjustment time is decreased by 88.9% and 91.4% respectively, and there is no obvious overshoot with a relatively small tracking error.

A new configuration of plate pilot pressure control for two-stage flow distribution hydrostatic-balanced high-pressure radial piston motor is proposed to address the problems of the large lateral forces on the piston pair lead to large transmission shocks at start/stop moments, serious leakage of the flow distribution and piston gap and low volumetric efficiency of traditional radial piston motors under high-pressure working conditions. This new model adopts composite pistons assemblies and pilot pressure control two-stage flow distribution method to achieve high-pressure power oil circuit sealing and high-efficiency flow distribution. In addition, the hydraulic floating support structure is adopted for the pilot stage flow distributor to compensate for mechanical wear and improve the reliability of long-time continuous operation. Based on AMESim, the dynamic simulation model of the whole motor is established. The thesis analyzes the correspondence between motion of single piston and its distribution valve, the influence of diameter of damping hole of distribution valve, the working pressure and main stage supply flow rate on the volumetric efficiency of the motor, and also analyzes the output characteristics of the motor with different transmission structures. The simulation results show that the motor has a volumetric efficiency of 89.74% at high pressure of 35 MPa. The pulsation rate of the output speed is reduced by 60% compared with that of the crankshaft linkage motor. It also has good low-speed stability and wide load adaptability. The results show a theoretical basis for the design and optimization of the high-pressure hydrostatic balance radial piston motor prototype is provided.

To address the issue of insufficient adjustability of low-frequency dynamic characteristics in heavy-duty special vehicle mount systems, this study proposes a magnetorheological fluid mount with controllable multi-inertial channel combined squeezing mode. A multi-channel magnetorheological fluid damper is developed, and experimental methods are employed to validate the switching effect of controllable flow channels. An aggregate parameter model for the magnetorheological fluid mount with controllable multi-inertial channel combined squeezing mode and a model of magnetorheological fluid mount system for 1/4 heavy-duty special vehicle are established. Finally, dynamic characteristics and vibration isolation performance are investigated based on these models. The results demonstrate that by the application of large current on different inertial channels, the peaks and peak frequencies of dynamic stiffness and hysteresis angle in the magnetorheological fluid mount become adjustable within 0~50 Hz. Additionally, under squeezing mode operation, the mount exhibits high-stiffness and high-damping characteristics at low frequencies.

Designing airfoils with biomimetic leading-edge structures offers an effective approach to concurrently improve aerodynamic and noise reduction performance. Five biomimetic airfoils with wavy leading-edge characterized by different combinations of amplitude and wavelength are designed using the NACA0012 airfoil as a baseline. Numerical simulations employing the SST k-ω and large eddy simulation methods are performed to analyze their aerodynamic performance and flow noise. The results indicate that increasing the wavelength significantly improves aerodynamic performance, with the lift-drag ratio enhanced by up to 21.8%. Increasing the amplitude strengthens flow control at the leading edge, resulting in a more uniform pressure distribution and delayed flow separation. The biomimetic structure reduces the angle of attack corresponding to the maximum lift-drag ratio and improves aerodynamic performance at high angles of attack. The biomimetic airfoils demonstrate notable noise reduction in the mid-to-high frequency range. Under small angles of attack, both tonal and broadband noises are suppressed. A reduction in sound pressure level is observed across all studied angles, peaking at 14 dB at an angle of attack of 3°.

This thesis proposes design approach of a biomimetic soft telescopic in-pipe robot that addresses the poor environmental adaptability and the insufficient active steering capability in current systems. The robot integrates flexible air chambers and pneumatic artificial muscles to construct a support-extension composite motion structure inspired by earthworm locomotion, adopting a multi-muscle coordinated actuation strategy and a continuous multi-segment locomotion method. The design includes both forward and inverse kinematic models, with system behavior verified through MATLAB simulations. An experimental platform enables performance tests in inclined and curved pipelines. The robot achieves an average crawling speed of 3.25 mm/s in a 30° inclined pipe and performs active steering in a 135° curved pipe, demonstrating strong adaptability and effective motion performance.

By designing different anti-friction lubricating structures and comparing the oil film characteristics, the influence of different anti-friction lubricating structures on the servo hydraulic cylinder to overcome the radial load and reduce the friction is studied, the best shape structure of anti-friction lubricating structure is obtained, and tests are verified. Based on the rectangular structure of anti-friction lubricating, I-shaped structure and trapezoidal structure are proposed. The pressure distribution and bearing capacity characteristic curves of different anti-friction lubricating structures are obtained by theoretical analysis and flow field simulation. The anti-friction lubricating structure of trapezoidal structure can provide more bearing capacity, and the temperature rise of oil film is smaller. The anti-friction lubricating structure can effectively overcome the radial load on the piston rod and reduce the friction of the servo hydraulic cylinder. The results show that the oil film characteristics of different anti-friction lubricating structures are different, which can effectively overcome the partial load, greatly reduce the friction of the servo hydraulic cylinder, and improve the control precision and service life of the servo hydraulic cylinder.

We design a purely soft-structured gripper and analyze the bending performance of its finger section. The gripper features a series of gas-driven elliptical cavities. A stepped cavity structure incorporates three parallel air channels for the fingertip, middle finger segment and finger root, respectively. The palm adopts an arc-triangle shape. The gripper is made of hyperelastic material Ecoflex 00-30 silicone rubber and polydimethylsiloxane, and its model uses the Yeoh constitutive model derived from uniaxial tensile theory. Building on this, we develop models for a single airbag, a single cavity group's bending and the bending deformation prediction of the entire multi-channel fully flexible gripper. Inputting the finger's structural parameters into the mathematical model yields the geometric relationship of its bending curve. The comparison of these analytical results with simulation data verifies the model's accuracy and practicality. Finally, analyzing the finger's bending performance allows us to determine optimal gripper performance parameters. Key factors include cavity structure type/number, finger width, cavity gap length and the bottom strain-limiting layer. This provides valuable research data and a reference for soft actuator development.

Addressing the issue of the unstable output and low accuracy issues of single-rod hydraulic cylinders under heavy load, high stiffness, and dynamic disturbances, a nonlinear model of the hydraulic system is established based on the analysis of force-bearing process and structural characteristics. Then an adaptive control method based on an asymmetric barrier Lyapunov function is proposed to performance steady tracking under output force constraints. The controller integrates adaptive parameter, extended state observer, and dynamic surface control and handles the system's parameter uncertainties, unknown states estimation and time-varying disturbances, and complexity explosion caused by high-order derivatives. The output force boundaries are constrained by the constructed asymmetric barrier Lyapunov function. Lyapunov-based analysis proves the system's asymptotic stability. Co-simulation verifys control effectiveness. The results show that the proposed method can accurately estimate and compensate for uncertainties, ensure the output remains within safe boundaries during loading while achieving high-precision actuator's position tracking.

Due to strong nonlinearity, complex multivariable coupling and difficulty in real-time state observation, pneumatic soft robotic arms pose significant challenges for dynamic control. To address these issues, this study proposes a real-time motion control method integrating visual localization and neural network modeling. A vision system is constructed using YOLOv8 object detection and semi-global stereo matching to generate sequential datasets. A long short-term memory network is then employed to model the dynamic relationship between chamber pressure and end-effector position. The results show that compared to neural networks trained on discrete data, the long short-term memory model significantly reduces the mean absolute error in three-channel pressure prediction from approximately 1.65 kPa to 0.44 kPa. Further experiments demonstrate that the proposed method achieves average mean absolute error of 1.503, 1.506, 2.825 mm along the three spatial axes, validating the effectiveness of the vision-based sequential neural network control strategy in dynamic trajectory tracking of soft robotic arms.

Addressing the issues of inadequate resistance to eccentric loads, low synchronization accuracy, limited control points and complex operation in derrick rectification equipment, an electro-hydraulic rectification system for mega-derricks is designed. This system employs a centralized control and multi-point drive architecture, utilizing a servo motor to power a radial piston pump as the oil source, using high-speed on/off valves for control and 12 high-pressure hydraulic cylinders are employed to synchronously lift the derrick legs. A dynamic master-slave multi-point synchronous control method with selection capability is proposed, which replaces closed-loop control with switch control, enabling high-precision synchronous control under heavy eccentric load conditions, regardless of the number of control points. We develop an electro-hydraulic rectification equipment for mega-derricks and conduct bench tests and field operations. The synchronous position error among multiple hydraulic cylinders is less than 0.3 mm, facilitating one-click alignment and significantly enhancing the efficiency, safety and automation level of large-scale derrick alignment tasks.

Dynamic seals in hydraulic slide valves play a crucial role in reducing oil leakage. However, their sealing performance is significantly influenced by environmental temperature, medium temperature and oil pressure, which alter the seal clearance during operation. A finite element analysis model is developed to analyze the combined sealing structures commonly used in slide valves. The model is used to evaluate the effects of varying environmental and medium temperatures, as well as pressure conditions on the clearance and friction behavior of dynamic seals. Based on the Stribeck curve, a mathematical expression describing the relationship between seal clearance and the friction coefficient is introduced. Experimental validation confirmed the accuracy of the theoretical model. The results indicate that the gap between the fluoroplastic sealing ring and the valve sleeve decreases with increasing temperature, accompanied by a corresponding change in the dynamic friction coefficient. Furthermore, both the theoretical analysis and experimental data reveal that the friction force of the dynamic clearance seal increases with temperature.

Aiming at the nonlinear control of multiple hydraulic joint system of hydraulic quadruped robot, an interactive force control strategy for floating base operation by force control is proposed. The control strategy transforms the basic motion, robot end motion, leg motion, interaction force control, joint constraint and friction cone constraint into a quadratic programming optimization problem, and the task priority is adjusted by the weight matrix. The robot task is decomposed under the position constraint to solve the conflict between the interactive force control and the optimal control based on the dynamic model, to realize the coordinated motion and force control of the robot end. Finally, the effectiveness of the proposed control strategy is verified by simulation and experiment, which shows that the hydraulic quadruped robot can perform large load operation during interactive operation and can control the appropriate contact force.

To diagnose internal leakage in hydraulic cylinders, a method based on a two-set-valued identification algorithm is proposed. This method detects faults by analyzing pressure signal variations under both normal and leakage conditions. Fifteen time-domain features are extracted from pressure signals in the rod chamber and piston chamber. Principal component analysis is applied to reduce these features to three principal components per chamber. A mathematical model integrating the six principal components from both chambers is established. The two-set-valued identification algorithm is employed to estimate model parameters for establishing internal leakage diagnosis algorithm. Experimental validation using AMESim simulation data confirms the method's feasibility and accuracy in diagnosing internal leakage, providing a theoretical basis for hydraulic cylinder fault detection.

Due to the limitations of factors such as on-site space and economic, the sample acquisition size of certain fault type of each component is very small, and thus a fault dataset of extreme long-tail distribution is formed, which makes the traditional decoupled supervised contrastive learning model unable to conduct effective diagnosis. Therefore, an improved decoupled supervised contrastive learning model is proposed, namely contrastive distillation type equilibrium decoupled supervised contrastive learning mode. Firstly, the synthetic minority oversampling method is introduced to generate tail samples appropriately to alleviate the problem of dataset imbalance; secondly, the parameter contrastive learning is introduced to construct a double contrast mechanism to increase the contribution of the tail and the diagnosis accuracy, solving the problem of sparse feature distribution of the tail type; finally, the type balanced self-distillation is introduced to solve the problem of insufficient representation of tail features through knowledge transfer. The experimental analysis of two extreme distribution forms of measured fault samples from the hydraulic pump, the gear and the rolling bearing shows that the proposed model can effectively solve the problem of extreme long-tail distribution, with diagnostic accuracies reaching up to 90.93% and 98.61%, respectively. In addition, the accuracy of the proposed method is 40.99% higher than that of the original method, and 76.97% and 35.83% higher than those of the traditional wide parameter contrastive learning and balanced contrastive learning methods.

Airtightness testing is a crucial technical measure to ensure the specific pressure chambers sealing performance. The direct pressure testing method is widely adopted in the manufacturing of such chambers due to its simple principle and convenient operation. However, its energy consumption issues have not received sufficient attention. To address energy waste caused by direct emission of compressed air after single-use in conventional direct pressure testing, a detection gas recovery and reuse method based on recycle air tanks is proposed, aiming to design an energy-saving direct pressure testing system that integrates high-precision detection and one-click start-stop functionality. A human-machine interface is developed via programming software to achieve solenoid valve switching control and real-time pressure monitoring during testing. The results demonstrate that the gas recovery and reuse scheme significantly reduces compressed air consumption, achieving a 16.2% reduction in energy consumption per test, which provides theoretical foundations and engineering references for energy optimization in direct pressure airtightness testing.

To meet the posture adjustment requirements of the wind proof and sand fixation transverse grass grid laying machine when operating on uneven desert surfaces, we design an electro-hydraulic control posture adjustable suspension system for connecting the wind proof and sand fixation transverse grass grid laying machine to the tractor. The mechanical structure of the posture adjustable suspension is analyzed, and a kinematic model is established; a hydraulic system for posture adjustment is designed, and a valve-controlled cylinder hydraulic power element model is established; and an electro-hydraulic control system scheme is designed. A simulation model of the posture adjustable suspension of the transverse grass grid laying machine is established using AMESim software. The simulation results indicate that the electro-hydraulic control system design is feasible; the posture adjustable suspension design for the transverse grass grid laying machine is feasible.

A magnetorheological damper, known for rapid response, wide adjustment range of damping coefficient and low energy consumption, is a significant research direction in the field of vehicle engineering. By dynamically controlling the excitation current of the magnetorheological damper, we minimize the vibrations transmitted to the vehicle body, ultimately improving vehicle running smoothness. This research conducts a theoretical analysis of the hybrid-mode damping characteristics of a certain magnetorheological damper model. A multi-physics simulation model of the magnetorheological damper is developed using ANSYS to analyze the relationships among piston velocity, damping force and control current. A semi-active suspension and full-vehicle dynamics model is established, and a sliding mode control algorithm is applied in a Simulink numerical simulation to investigate the impact of control system on suspension and vehicle vibration performance. The research shows that the finite element analysis of the electromagnetic field provides a clear visualization of magnetic flux distribution, offering guidance for magnetic fluid flow path structural design. Additionally, the sliding mode control significantly enhances the performance of the semi-active suspension, effectively improving critical indicators such as vehicle body acceleration and suspension stroke. Ultimately the vibration characteristics, as well as ride smoothness and ride comfort of vehicles are significantly improved.

The problem of energy efficiency and thermal stability of underground coal mine explosion-proof vehicles under long-distance and large slope conditions has seriously restricted its unmanned development. Based on the chassis by-wire architecture, this thesis explores the thermal management strategy of unmanned development explosion-proof vehicles. A transient thermodynamic modeling method of multi physical field coupling is proposed, and the series hydraulic hybrid power system architecture based on closed loop is constructed. The architecture integrates the accumulator cooperative control and bidirectional energy conversion mechanism to improve the braking energy recovery efficiency and peak power output capacity. At the same time, a dynamic temperature boundary model based on oil flow direction identification is established to effectively overcome the time lag problem of the traditional model in transient response. Through the hardware in the loop experiment, the nonlinear relationship between the hydraulic oil temperature rise process and the system efficiency is revealed. The final test results show that the temperature prediction error of all key components such as hydraulic pump, motor and accumulator does not exceed ±3.5 ℃, and the model shows high accuracy in the prediction of system temperature level and change trend. This thesis provides a theoretical model and solution for the thermal management optimization of underground trackless auxiliary transportation equipment.

Accurate measurement of the speed of sound in hydraulic systems is essential for performance prediction and optimization. However, since the speed of sound is sensitive to the system state, conventional methods often fail to provide reliable measurements under varying conditions. To address these challenges, we propose a novel bidirectional progressive search algorithm for calculating the speed of sound in rigid pipelines. First, we establish a physical model of sound speed based on the pressure wave's propagation characteristics in pipelines. Next, data processing techniques are optimized, and a high-precision calculation is achieved through an improved bidirectional search algorithm. Pressure fluctuations under different operating conditions are measured using a dedicated experimental setup. We validate the accuracy of the proposed method by comparison with conventional approaches. The experimental results show that the proposed method significantly outperforms existing techniques in terms of computational accuracy across a range of conditions, with an average improvement of 4.5% in the calculated speed of sound. Notably, under a pressure of 15 MPa and in turbulent flow conditions with secondary source interference, the improvement reaches up to 7.8%. These findings demonstrate that the proposed approach can offer higher accuracy and broader applicability in dynamic hydraulic environments.

The extended supply and return pipelines of the comprehensive working face result in high-pressure loss along the hydraulic support system, and the supply strategy of the emulsion pump station is incompatible with the operation of hydraulic supports. These result in a slow dynamic response of the key actuators for hydraulic supports, which limits the automatic following speed. According to above problems, on the basis of the current intelligent integrated liquid supply system, we add a high-pressure small-displacement pump as a centralized liquid supply and pressurization system for the column lifting action. And a mathematical model of the column-pushing hydraulic cylinder for the hydraulic support group in the comprehensive working face is established. Then, an automatic following strategy for hydraulic supports with rapid fluid supply and pressurization of the lifting column is proposed. Additionally, a simulation model of the fluid supply system for a comprehensive working face, based on independent pressure compensation, is established by using AMESim. The effectiveness and superiority of the proposed automatic machine following control strategy are studied, and the fluid supply schemes of hydraulic supports under different flow conditions are compared. The research demonstrates that the proposed system and its control strategy can enhance the following speed of hydraulic supports by 30.11% and reduce the pressure-building time of the column initial support pressure by 76%. We offer a novel solution to problems such as the unsmooth flow channel of the lifting column, insufficient initial support pressure and excessive back pressure during the process of lowering the column.

As electro-hydrostatic actuator (EHA) with high order nonlinear and strong coupling characteristics, the parameters of its position sliding mode controller are difficult to adjust. Conventional swarm intelligence algorithms often fall into local optimal solutions and have poor computational efficiency. Therefore, piranha foraging optimization algorithm (PFOA) is proposed to adjust and optimize the parameters of the sliding mode controller. Therefore, on the basis of analyzing the composition principle of EHA, a mathematical model is established, and PFOA algorithm is used to adjust and optimize the sliding mode surface and approach rate parameters in the sliding mode controller. Simulation and verification work are carried out on the MATLAB/Simulink and AMESim joint platform. The simulation results show that, compared with the sliding mode PID optimized by other swarm intelligence algorithms, the sliding mode PID control optimized by PFOA algorithm has smaller steady-state error and tracking error, better robustness, and higher computational efficiency, which provides an important research idea for ensuring better control performance of EHA position sliding mode controller.

A finite time prescribed performance neural network control strategy is proposed to address the need for control strategies that balance both transient and steady-state performance in the electro-hydrostatic actuator (EHA). A nonlinear mathematical model of the EHA is established, and a barrier Lyapunov function is constructed by incorporating a finite time prescribed performance function for the tracking error. Based on the backstepping control framework, a neural network-based position tracking controller is designed. The stability and theoretical performance of the controller are rigorously proven using Lyapunov analysis. A co-simulation model is built using MATLAB and AMESim, and comparative simulations are conducted with a PI controller and a neural network controller without prescribed performance. The results demonstrate that the proposed controller achieves significantly higher tracking accuracy. Compared to the PI controller and the neural network controller without prescribed performance, it improves sinusoidal trajectory tracking accuracy by 85% and 47%, and point-to-point trajectory tracking accuracy by 85% and 55.9%, respectively. Furthermore, the tracking error converges below the predefined steady-state bound within a finite time and remains within the prescribed performance constraints throughout the operation.

The hydraulic manipulators provide high thrust/torque, making it suitable for handling heavy-payload objects. However, compared with electric drives, the hydraulic systems equip with more complex structures and respond more slowly. The hydraulic systems exhibit nonlinear characteristics, such as flow/pressure variations in servo valves and friction. Nevertheless, PID control remains the most widely used method in engineering practice. But PID performances negatively under system nonlinearities and heavy load disturbances, this study focused on the pipe-gripping manipulator and took the hydraulic nonlinearities, friction, and load disturbances into consideration. A dynamic model using the Lagrange method to describe the system response and designed two nonlinear controllers is established. A fuzzy PID controller and a fuzzy sliding-mode controller based on backstepping are designed. The simulation results showed that the latter could effectively handle system nonlinearities and heavy-load disturbances, limiting the manipulator's position error to within 1%. Additionally, the thesis adopts a saturation integral function and fuzzy sliding-mode control to mitigate the chattering problem common in sliding-mode control.