Search Results (223)

Accurate fault classification of electro-hydrostatic actuators (EHAs) remains challenging because multivariate fault signals contain local transient variations, inter-variable coupling, and dynamic temporal dependencies that are difficult to capture simultaneously using a single model. To address this problem, this paper proposes a multi-view temporal feature collaborative heterogeneous ensemble learning model (MTF-HEM) for EHA multivariate time series fault classification. MTF-HEM integrates a representative subsequence-guided time series forest (RSG-TSF), XGBoost, and a lightweight LSTM to extract local morphological, global statistical, and temporal dependency features, respectively. The outputs of these heterogeneous base learners are fused using a bootstrap-driven out-of-bag probability binning stacking (BOPB-stacking) strategy. The proposed method was evaluated on an AMESim-based simulated EHA plunger pump fault dataset containing one normal condition and six fault conditions. Under the present simulation setting, MTF-HEM achieved an accuracy of 99.52% and outperformed the tested deep time series classification models, ensemble models, and individual base learners. These results suggest that multi-view heterogeneous feature fusion can improve the classification of simulated EHA fault time series and provide a methodological reference for intelligent actuator fault diagnosis. However, the current validation is based on data generated from a single AMESim simulation model, and further evaluation on real EHA systems is needed to assess the practical applicability and generalizability of the proposed approach. Full article

To address the limitations of the centralized hydraulic steering system used in the first-generation heavy-duty wheeled platform developed by our team, this study proposes a fully electrified steering system based on a compact direct-drive electro-mechanical actuator (DEMA) architecture. Compared with the original hydraulic system, the proposed solution reduces the steering-system weight from approximately 150 kg to 32 kg in the single-channel configuration and 40 kg in the dual-channel configuration, while significantly improving system integration and maintainability. For the single-channel DEMA steering system, a composite control strategy combining three-loop PID control with feedforward compensation is developed to improve dynamic response and position-tracking accuracy. AMESim simulation results under a steering resistance torque of 6000 ± 500 Nm show that the system achieves an overshoot below 2%, a steady-state error below 0.1°, and a tracking error below 0.4°. To reduce motor power and thermal-management requirements, a dual-channel DEMA steering architecture is further proposed. Considering inter-channel parameter differences, a primary–secondary synchronization control strategy is developed to suppress force-fighting behavior and improve motion consistency. Simulation results demonstrate that the proposed strategy effectively reduces synchronization errors and maintains highly consistent force output between channels while preserving excellent steering accuracy and tracking performance. The proposed fully electrified steering system and synchronization control strategy provide an effective solution for improving the dynamic performance, lightweight design, and reliability of heavy-duty wheeled platforms. Full article

This paper systematically investigates the performance of data-driven algorithms for fault diagnosis in aircraft hydraulic systems. Firstly, the hydraulic system of an aircraft is modeled in AMESim software, and five typical faults are artificially injected. The pressure and flow curves from different position sensors are extracted to construct the fault diagnosis dataset. Then, a multi-level feature extraction method based on deep learning algorithms, including 1DFFCNN, stacked LSTM, and improved CNN-LSTM-Attention, is designed to identify the sensitive features of potential abnormal behaviors. Finally, we study the sensitivity of multi-source heterogeneous response data of the hydraulic system to the degradation of the hydraulic system’s state, and establish the correlation between the evolution of the hydraulic system’s working state and the multi-source heterogeneous response data, achieving the early prognostics of abnormal states of the hydraulic system. Numerical experiments demonstrate that the accuracy rate of the aircraft fault diagnosis based on the data-driven algorithm presented in this paper exceeds 98%. Full article

The underground caverns of pumped-storage power stations generally feature large inclination angles. During the bottom-up oblique excavation by hard-rock Tunnel Boring Machines (TBMs), the Anti-Back-Slip (ABS) support system is the core device ensuring safe operations. Specifically, the synchronization of the multiple hydraulic cylinders within the ABS system is a critical factor determining the stability and safety of the TBM. Therefore, this paper designs a hydraulic control system for the ABS device and proposes an adjacent cross-coupling synergistic control strategy based on adaptive backstepping. This strategy innovatively integrates an adaptive backstepping control law into the adjacent cross-coupling topology to achieve high-precision multi-cylinder control. Utilizing the AMESim-Simulink platform, high-fidelity co-simulations are conducted under both uniform and eccentric load conditions. The results demonstrate that under nominal conditions, the proposed algorithm exhibits asymptotic convergence at the mathematical level. The system maintains robust stability under dynamic excitations. When subjected to sudden asymmetric eccentric loads of 1.0–2.0 times, the system prevents tracking divergence and limits the maximum multi-cylinder synchronization error to within 1.82 mm. This research satisfies the requirements for synchronous control and provides a theoretical and engineering reference for the disturbance-rejection synergy of inclined shaft TBM support systems. Full article

The continuous rotating valve plate piston pump (CRVPPP) can efficiently drive actuators such as hydraulic cylinders or hydraulic motors to generate excitation motion. This CRVPPP-driven excitation system can avoid the throttling losses associated with servo-valve-controlled excitation systems. However, this excitation system exhibits an asymmetric excitation phenomenon during actual operation. Through theoretical analysis and experimental research on the mechanical characteristics of the valve plate pair in the CRVPPP, it was found that the asymmetric excitation originates from the annular grooves of the fixed valve plate alternating between oil suction and discharge states. This alternation subjects the rotating valve plate to an overturning moment, which in turn causes a periodic variation in the end-face clearance of the valve plate. Targeting the asymmetric and nonlinear leakage characteristics of the CRVPPP, an adaptive neural network module was established based on the Amesim-Matlab/Simulink co-simulation framework. This module incorporates the mapping from the rotational speeds of the rotating valve plate and cylinder block to the equivalent leakage opening of the distribution grooves. By training with experimental data, the CRVPPP- driven excitation system model was formulated. Experimental results show that the established model achieves a correlation coefficient of 0.99786 on the training set, indicating its excellent fitting accuracy. Furthermore, the mean squared error on the test set is within 0.04 mm², demonstrating the model’s good generalization ability. It can reproduce the dynamic characteristics of the CRVPPP-driven excitation system with high precision, thereby laying a solid modeling foundation for the characteristic analysis, structural optimization, and high-precision control of such excitation systems. Full article

The electro-hydraulic track tensioning system of a tracked vehicle directly affects track engagement stability, vibration response, and energy utilization efficiency under complex terrain and time-varying loads. Accurate and robust control is therefore of great engineering significance. This paper focuses on an electro-hydraulic tensioning system with a composite actuation structure consisting of a proportional main valve and two 2/2 on–off valves and proposes a learning-enhanced nonlinear model predictive control (L-NMPC) method. Residual learning, adaptive weight/constraint scheduling, and execution-layer mode coordination are integrated into a unified predictive control framework. The study is carried out on a strongly coupled Simulink–AMESim–RecurDyn co-simulation model and an LF1352 prototype-vehicle test platform. Comparative evaluations are conducted under steady step-and-ramp tracking, random rough terrain, sudden steering/braking pulses, supply-pressure limitation, and parameter drift/sudden-change conditions. The evaluation indices include track-tension tracking error, peak overshoot, settling time, energy consumption, and stability under parameter mismatch. Compared with conventional nonlinear model predictive control (NMPC), the proposed L-NMPC reduces the root-mean-square error of track tension by 42–58%, decreases peak overshoot by 30–40%, shortens settling time by 25–35%, and achieves a 12–17% reduction in energy consumption at the simulation level. Under ±20% parameter perturbation, the fluctuation in track tension can be constrained within ±1.1 kN. The simulation and real-vehicle results remain consistent in terms of the dominant dynamic trends and performance ranking. This study provides a verifiable implementation path for model–data-fusion control of strongly coupled electro-hydraulic actuation systems and offers an engineering reference for intelligent, energy-efficient, and highly reliable control of tracked-vehicle chassis systems. Full article

In order to control an electro-hydrostatic actuator (EHS), as is well known in the literature, it is possible either to modify the speed and direction of rotation of the electric motor or to vary the displacement of the hydraulic pump. In a previous paper, the advantages and disadvantages of each solution were highlighted. Varying only the motor speed leads to demanding operating conditions for the electric motor, whereas varying only the hydraulic pump displacement results in continuous energy consumption that becomes excessive during long-duration flights. Combined solutions for controlling an EHS can also be found in the literature, but they generally require highly sophisticated control algorithms. In this paper, a solution is proposed in which the electric motor is switched off when the EHS remains in an idle condition for long periods of time. In this way, the large amount of energy consumed during idle operation is eliminated, while preserving the improved dynamic performance associated with the variable-displacement pump configuration. Full article

Under high-frequency commutation conditions, the Single-Piston Two-Dimensional Electro-Hydraulic Pump suffers from severe reverse flow and pressure pulsation, which limit its volumetric efficiency and operational stability. To address this issue, this study proposes a surrogate-assisted multi-objective optimization framework for the pump distribution structure. First, a dynamic model is established to analyze the influence of triangular damping groove geometry on flow and pressure characteristics, and four key parameters are selected as design variables. Then, sample data generated from AMESim simulations are used to train a Genetic Algorithm-optimized Backpropagation neural network surrogate model. Finally, the surrogate model is integrated with NSGA-II to minimize the peak reverse flow and pressure pulsation amplitude simultaneously. The results show that the GA-BP model predicts reverse flow and pressure pulsation with mean relative errors of 2.72% and 2.99%, respectively. Compared with the initial design, the optimized structure reduces the peak reverse flow by 27.6% and decreases the pressure pulsation amplitude from 0.78 MPa to 0.41 MPa. These results indicate that, within the parameter ranges and operating conditions considered in this study, the proposed framework provides an effective tool for the coordinated optimization of damping groove parameters for the Single-Piston Two-Dimensional Electro-Hydraulic Pump. Full article

This study addresses the high-precision position control problem of pilot-operated proportional directional valves under dead-zone nonlinearity. A fuzzy PID-based position control strategy optimized by the dung beetle optimizer (DBO-FPID) is proposed to alleviate switching lag and accuracy degradation caused by dead-zone effects. First, a refined nonlinear model combining theoretical analysis and AMESim simulation is established to quantitatively characterize the dead-zone evolution mechanism of the valve system, and the dead-zone range of the directional valve is identified as ±34.5% of the duty cycle. On this basis, a multiphysics co-simulation model is developed to analyze the static and dynamic characteristics of the pilot valve and the main spool. Then, the DBO algorithm is introduced to optimize the key parameters of the fuzzy PID controller by minimizing an objective function based on the integral of time-weighted absolute error (ITAE), thereby improving the controller’s compensation capability for dead-zone nonlinearity. Simulation results show that, compared with DBO-PID, the proposed DBO-FPID control strategy reduces the rise time by 54.4%. During triangular and sinusoidal position tracking, the dead-zone residence time is reduced by 47.5% and 44.8%, respectively, while the mean absolute error remains below 0.2 mm. Experiments further validate the effectiveness of the proposed control strategy for high-precision position control of the pilot-operated proportional directional valve. Full article

Hydraulic rock drill exhibits outstanding attributes of high power and high frequency, but there are some issues including unclear mechanisms governing impact dynamic behaviors and inaccurate evaluation of impact performance. In this study, a dynamic test platform for the hydraulic rock drill was established by employing the terminal velocity method, utilizing a high-frequency non-contact laser displacement sensor to precisely capture the transient kinematics of the impact piston. The quantitative results indicate that as the input pressure rises from 10 MPa to 23 MPa, the impact frequency increases from 50 Hz to 76.9 Hz, and the impact energy increases from 89.9 J to 275 J. A hydraulic rock drill AMESim simulation model incorporating the impact system, collision medium and buffer system was developed and validated. This reveals the operating mechanism of impact piston driven by the equivalent pressure difference between the front and rear chambers. And the stroke reversal interval governs the duration between the deceleration onset and collision of the impact piston. As a result, both excessively large and small stroke reversal intervals will lower the impact power. The 12 mm stroke reversal interval has been identified as the optimal setting for maximizing impact power, at which the impact power reaches 17,561.3 W, which presents an increase of 4.70% and 3.12% compared to the intervals of 7 mm and 17 mm, respectively. This study contributes a reliable theoretical basis and direct data support to the performance evaluation and optimized design of hydraulic shock systems. Full article

The design process of complex systems, such as hybrid aircraft, consists of several stages that depend on each other. The product is virtually validated by simulations in various disciplines. Each of these stages and simulation disciplines is carried out by different experts and they can choose from different tools in their field. The models created during this process are highly interdependent but are typically managed independently by each team. In this paper the first implementation of an open digital platform (ODP) is presented to provide a common data backbone for models from various tools and enable traceability across domains. An open data schema is used to ensure an open interface for the platform. This is implemented with SysML v2. In a proof of concept, two tools from different domains, simulation process and data management (SPDM) and product lifecycle management (PLM) using Teamcenter^® Simulation software and model-based design (MBD) using Simcenter™ Amesim™ software, are connected through this open standard. Full article

This study presents the design, thermodynamic modelling, and numerical optimisation of a medium-scale (100 kW) transcritical CO₂ air-source heat pump water heater (ASHP-WH) intended to deliver 90 °C domestic hot water under sub-zero ambient conditions. A detailed component-sizing methodology was established and implemented in AMESim 2404 using REFPROP-based property calculations, with model convergence confirmed by the mass and energy balance closure. Parametric investigations covering the discharge pressure, refrigerant charge, ambient air temperature, and water outlet temperature were conducted through 140 steady-state simulations. The results show that the system achieved a heating capacity of 100–121 kW with a coefficient of performance (COP) of 2.7–3.3 across −15 °C to +10 °C ambient conditions. The optimal discharge pressure (≈11.2 MPa) and charge inventory (10 ± 2 kg) define a broad operating window that ensures COP stability (±2%) and avoids liquid carry-over. The exergetic efficiency remained above 0.75 throughout the tested climate range. Compared with published laboratory prototypes, the proposed 100 kW module demonstrates a superior performance at harsher sub-zero boundaries, highlighting its potential for commercial hot water and industrial applications. The findings provide actionable guidelines for component sizing, charge management, and adaptive pressure control, and establish a pathway from a numerical prototype to scalable field deployment of medium-scale transcritical CO₂ systems. Full article

Wide-body dump trucks in open-pit mines frequently operate under high loads and severe road conditions, demanding superior dynamic performance from their suspension systems. Existing studies tend to focus only on the influence of individual parameters on the dynamic characteristics of hydro-pneumatic suspensions, lacking systematic analysis of parameter coupling effects and optimal parameter combinations. Taking the two-stage pressure hydro-pneumatic suspension of a wide-body dump truck as the research object, this paper theoretically analyzes its working characteristics and establishes an AMESim model under multiple excitation conditions to reveal how parameter interactions affect the dynamic performance of the suspension. With peak liquid pressure, maximum liquid pressure fluctuation, and maximum vehicle body vertical acceleration as optimization objectives, a multi-objective optimization algorithm is employed to determine the optimal suspension parameters. The results indicate that the interactive responses of damping orifice diameter and check valve diameter with respect to peak pressure and body vertical acceleration exhibit strong nonlinearity. Compared with the original parameter scheme, the optimized design reduces peak liquid pressure, maximum pressure fluctuation, and peak body vertical acceleration by 8.76%, 29.1%, and 11.7%, respectively, significantly improving vehicle ride comfort and mitigating pressure oscillations in the hydro-pneumatic suspension. The research results can provide theoretical support and engineering reference for intelligent operation and maintenance of mine heavy equipment, optimization design of suspension systems and efficient and reliable operation. Full article

Airborne electromagnetic detection systems are highly susceptible to low-frequency motion-induced noise, which significantly degrades the extraction of weak geological signals. Conventional signal processing methods alone are often insufficient to suppress mechanically induced vibration noise, resulting in signal distortion and reduced detection reliability. To address this limitation, this study proposes an active noise suppression strategy that integrates mechanical vibration isolation with advanced signal processing. A pneumatic vibration isolation platform based on a cable-driven parallel robot (CDPR) architecture is developed to achieve precise orientation correction and effective vibration isolation. The system employs kinematic modeling and a servo-controlled pneumatic cylinder driven by a proportional directional valve to enable accurate dynamic regulation. Numerical simulations conducted in the Advanced Modeling and Simulation Environment (AMESim), combined with proportional–integral–derivative (PID) control, demonstrate that piston displacement overshoot is constrained within 0.2 mm. Furthermore, targeted filtering techniques are applied to enhance signal quality. Experimental results show that the response time for continuous step input is 0.18–0.2 s, with a steady-state error below 0.3 mm, confirming robust control performance. The proposed framework provides an effective low-noise solution for airborne electromagnetic detection and can improve survey reliability in deep resource exploration. Full article

Heavy-duty forklifts possess substantial kinetic energy during braking, which is currently wasted due to a lack of recovery in conventional systems. To ensure braking safety, an electro-hydraulic–mechanical compound braking system is necessary. However, the uncoordinated distribution between regenerative and mechanical braking torque leads to braking torque fluctuations, compromising safety, comfort, and recovery efficiency. This paper constructs a parallel hydraulic hybrid power system for heavy-duty forklifts based on a four-quadrant pump/motor, enabling braking energy recovery and reuse via the pump/motor and an accumulator. A compound braking strategy based on the ideal braking force distribution and multi-sensor information fusion is proposed. The system incorporates various sensors, including pressure, speed, flow, and pedal displacement sensors, to monitor system status and driver intention in real time, providing precise data for coordinated control. Feasibility is verified through AMESim simulation and real vehicle tests. The control system based on sensor feedback maximizes braking energy recovery while ensuring braking safety and comfort, achieving a 12.2% energy-saving rate and significantly improving the vehicle’s economy and range. Full article