The operational status of hydraulic valves is critical for system safety and stability. However, traditional feature extraction methods for 1-D data often struggle to effectively capture key features in complex signals, and the incompleteness of interpreting data from single channel, it is challenging to achieve accurate fault diagnosis. This paper proposes a novel fault diagnosis method, named GFF-CGRU, which is based on guided filtering and multi-branch spatiotemporal feature fusion. Specifically, GASF is utilized to transform vibration signals from sensors into 2-D images that facilitate fault discrimination. Subsequently, a guided filter fusion GASF (GFF-GAF) method is applied to achieve multi-sensor information fusion. A multi-branch parallel network architecture is then constructed. One branch employs 2D-CNN with attention module CBAM to extract the fused image features, while the other two branches utilize GRU to extract features from the original time-series signal. Finally, the spatiotemporal features are fused for fault classification. The proposed method was validated using hydraulic valves data from different engineering applications. It achieved diagnostic accuracies of 96.63% and 98.44%, respectively, significantly outperforming other models. The method proposed in this study demonstrates certain reference value in the field fault diagnosis of hydraulic valves.

Ocean resources are abundant and crucial, and it is necessary to monitor them for utilizing these resources. However, the monitoring devices are usually scattered across the sea and far from land, facing challenges of power supply and short battery life. Integrating solar cell (SC) with triboelectric nanogenerators (TENGs) presents a viable solution to supply power, with TENGs compensating for the limitations of solar cells at night and during rainy days. Here we report a cost-effective method for fabricating a high transparent and hydrophobic PDMS/Ag NWs/PFA film (PAP film). The dual-electrode TENG based on PAP film achieves an open-circuit voltage of 1100 V, a short-circuit current of 4 mu A and a transfer charge of 263 nC. Additionally, A dropletbased generator (DEG) based on PAP film was developed and integrated with a solar cell encapsulated, forming a hybrid energy harvesting device for capturing rain, wave, and solar energy. The encapsulated solar cell enhances its output energy by 17% compared to the unencapsulated solar cell. In combined wave and solar stimulation, the device can charge a 33 mu F capacitor to 3 V in 10 s, at the same time, the hybrid energy harvesting system successfully drives a small electronic meter in succession. indicating multi-energy integration and providing new insights for harvesting clean energy in natural environments.

To accurately grasp the transient characteristics of complex gas–liquid flow in axial piston pump, an experimental test system was established for the characteristics of two-phase flow induced vibration in pump. The two-phase flow fluctuation characteristics and its excitation mechanism of pump casing inner wall under different operating conditions were investigated based on a comprehensive computational fluid dynamics model and we are validated by experimental setup. This model elucidates the underlying mechanisms of performance degradation in axial piston pumps by quantitatively linking key operational parameters (pressure and speed) to fluid excitation forces and power loss. It further identifies flow separation and turbulent vortices as the primary sources of suction pressure loss. A variable-density topology optimization method is proposed to redesign the shape of the pump’s suction passage, aiming to minimize pressure loss. This design reduces flow separation and turbulent vortices in the two-phase flow at the suction port, thereby mitigating the fluid excitation force. Results demonstrate that under identical inlet gas–liquid conditions, the optimized suction port achieves a significant reduction in fluid pressure loss. The peak vibration acceleration of the pump is decliend by 20–100 m/s2. These findings validate the effectiveness of the proposed method in enhancing hydraulic stability and alleviating gas-induced vibration.

Axial piston pumps typically operate under high-pressure and high-speed conditions, making them prone to cavitation, particularly in the piston chambers and grooves of the valve plate. When cavitation bubbles are carried into the high-pressure region by the oil flow, their collapse generates intense pressure pulsations and fluid excitation forces, which significantly affect the working stability of the pump. To study the cavitation characteristics of the axial piston pump, a computational fluid dynamics (CFD) model is developed in this paper, taking into account key flow characteristics. Meanwhile, a cavitation visualization test rig is presented to validate the effectiveness of the simulation model. By investigating the gas-phase volume fraction and jet flow velocity at different locations within the pump, generation mechanisms and dynamic characteristics of cavitation in the piston chambers, grooves, and slippers under various operating conditions are systematically revealed under various operating conditions. Moreover, comparative studies are conducted to examine the evolution of cavitation behavior under different pressures and rotational speeds. The findings elucidate the significant influences of these parameters on cavitation dynamics in axial piston pumps. This work provides a theoretical basis for developing effective strategies to suppress cavitation and enhance pump reliability.

In order to address the challenges posed by the high wear and frequent failure of hydraulic multi-way valve components, as well as the difficulty in extracting deep hide fault features and achieving high fault diagnosis accuracy, a fault diagnosis method based on a combination of convolutional neural network and bidirectional long and short-term memory network (CNN-BiLSTM) is proposed. This method takes into account the concealment of hydraulic multi-way valve components and aims to improve the accuracy of fault diagnosis. The method utilizes a combination of CNN-BiLSTM to extract both spatial and temporal features from pressure signal input. These features are then fused with information and run through a classifier for classification. To evaluate the effectiveness of the proposed method, a simulation model of a hydraulic multi-way valve is developed using AMESim software. Additionally, multiple sets of wear fault data are constructed to test the accuracy and reliability of the model. Based on simulation data, the proposed method has an accuracy rate of 96.96% for diagnosing faults in hydraulic multi-way valves. The proposed method exhibits higher stability and reliability compared to other artificial intelligence algorithms, with a commendable diagnosis accuracy.

Venous valve geometric structure significantly influences thrombotic flow regime. The fluid region near the thrombus (Peri-thrombotic Area) is an important physical space for thrombus evolution, and establishing a computational fluid dynamics (CFD) numerical model for analysis in this region is important. However, it is how the venous valve geometric structure affects mechanical indices in the Peri-thrombotic Area that has not been fully investigated. In this study, we focus on the Peri-thrombotic Area, propose a bio-hydrodynamic model in which the venous valve is treated as a hyperelastic material, the thrombus as a porous medium, the blood as a Carreau fluid. We further employ numerical analysis to compare the influence of different venous valve geometric structures on flow regime under fluid-solid interaction. Abnormalities in valve length and curve are common geometric variations in valve structure, and these abnormalities affect the flow regime and mechanical indices of the Peri-thrombotic Area. The results showed that the maximum pressure difference reaches 54.9% as the valve length changed, and the maximum flow rate difference reached 61.1% as the curvature shifted. Heterogeneity in the valve geometric structure leads to alterations in the length and constriction degree of the narrow channel between the valve leaflets, consequently causing abnormalities in mechanical indices in the Peri-thrombotic Area. This study demonstrates that considering valve structure can predict the mechanical state in the Peri-thrombotic Area, which provides assistance for the treatment of venous thrombosis and other venous diseases.

The excitation frequency of traditional electro-hydraulic fatigue test systems is primarily limited by the frequency response of the servo valve. The relatively low frequency response of the servo valve makes it difficult to achieve high-frequency excitation, even when sacrificing part of the amplitude. To address this issue, an innovative two-stage high-flow, high-speed directional valve configuration is proposed and integrated into the electro-hydraulic fatigue test system. This design aims to increase the excitation frequency, enhance the amplitude of the output characteristics, and the fatigue test cycle time is reduced. A nonlinear mathematical model of the high-frequency fatigue test system was developed, and a corresponding simulation model was constructed. A prototype experimental system was built to verify the accuracy of the simulation model and analyze the output characteristics. The effects of different operating frequencies and oil supply pressures on the dynamic characteristics of the high-frequency fatigue test system were subsequently analyzed by the simulation model. The results show that the proposed new two-stage high-speed high-flow directional valve can realize 400 Hz high-frequency output, compared with the traditional two-stage valve has a certain frequency enhancement, and the output dynamic characteristics are negatively correlated with the operating frequency and positively correlated with the oil supply pressure. Both experiment and simulation show that two-stage, high-speed, high-flow directional valves and their fatigue test systems provide excellent high-frequency dynamic performance, and the output characteristics can be changed by the operating frequency and oil supply pressure. For future use in fatigue test systems, high-frequency excitation of 400 Hz can be realized, which increases the output frequency by nearly 50

As the most critical friction pair in high-pressure plunger pumps, the plunger pair significantly influences both the volumetric and mechanical efficiency of the pump. During actual operation, the relative position and orientation between the plunger and plunger sleeve are in constant flux. Moreover, factors such as the large diameter of the plunger, high working pressure, and low medium viscosity contribute to the complexity of gap flow, complicating the evaluation of the sealing efficiency of the plunger pump. Therefore, this article develops a fluid-structure interaction (FSI) simulation model of the plunger pair and investigates the flow characteristics of the clearance under various eccentric postures, as well as the corresponding variations. A large-scale experimental platform was constructed to test the sealing performance of the plunger pair gap. Using a custom eccentricity testing device, the changes in attitude and leakage characteristics during the movement of the plunger pair were elucidated, thereby validating the accuracy of the simulation model. The findings of this study provide a foundation and technical support for the design and application of gap seals in reciprocating piston pumps.

Inaccurate precharge pressure is the fundamental reason of poor pressure ripple attenuation performance of a pressurized gas bladder-type hydraulic noise attenuator (bladder attenuator). To tackle this issue, this paper proposed changing the initial volume of the bladder ( V a0 ) through charging and discharging the bladder for improving the attenuation performance of the bladder attenuator (APBA). Consequently, a mathematical model is established to investigate APBA when the bladder is charged and discharged. The results are shown as follows. Firstly, the APBA can be improved obviously when V a0 is greater than 6.2 × 10 −5 m 3 . Secondly, if the system pressure is smaller than the air pressure within the bladder, the bladder attenuator will lose its attenuation performance completely. Finally, the response time of the pneumatic system should be greater than 0.01 s when the bladder is charged, and less than 0.08 s when the bladder is discharged, which can avoid the poor APBA.

The deep-sea submersible is an essential piece of equipment for deep-sea development, serving as a crucial tool for conducting exploration and operations in the deep ocean. As the core component of the hydraulic system, the plunger pump is vital for ensuring the smooth lifting and lowering of the submersible. The plunger pair, which constitutes the most significant friction pair in plunger pumps, plays a pivotal role in determining both the service life and volumetric efficiency of the pump through its friction, lubrication, and sealing performance. This article proposes a flow model for the plunger pair in eccentric and inclined positions, considering its various orientations and placements. It elucidates the deformation and leakage characteristics of the plunger pair under different configurations, including various postures, material properties, and design parameters. The findings not only provide a theoretical foundation for the design of reciprocating seals and the evaluation of sealing performance but also contribute to the broader field of parameter design and performance assessment for other types of gap seals.

The pressure ripple attenuation performance (PRAP) of a pressurised bladder-type hydraulic noise attenuator (bladder attenuator) is investigated in this study based on mathematical model using the transfer matrix method and equations of state for an ideal gas and liquid. Transmission loss (TL) was selected as the metric for evaluating the PRAP of the bladder attenuator. The study investigated the impact of the ratio of the precharge gas pressure to the system pressure, bulk modulus and kinematic viscosity of the hydraulic oil, and structural dimensions of the perforated tube on the PRAP. The key findings are summarised as follows: First, the applicability of the mathematical model was validated using previously published methods and experimental data. Second, the ratio of the precharge gas pressure to the system pressure emerged as a crucial factor influencing the PRAP, particularly when the precharge gas pressure was lower than the system pressure. Finally, the bulk modulus and kinematic viscosity of the hydraulic oil demonstrated minimal effects on the PRAP, whereas increasing the inner radius and number of through-holes in the perforated tube was found to effectively enhance the PRAP.

As an important part of the hydraulic system, hydraulic oil pollution will seriously affect the performance and the lifetime of the hydraulic component. Therefore, the pollution of hydraulic oil is crucial to the lifetime of the hydraulic component. In this study, an assessment model with internal leakage flow as a parameter is proposed. A Life assessment hydraulic test system is built. The test is conducted using hydraulic fluids containing test dust. It evaluates the effect of the contaminated fluid on the degradation of the internal leakage performance and reduction of lifetime. The results show that the internal leakage flow of the hydraulic directional valve, classified under ISO 4406 cleanliness level 21/19/17, increased from 6 ml to 68 ml following a test lasting 120 h. It verifies the lifetime based on the internal leakage flow is described by a logarithmic function. The hydraulic directional valve has a pressure loss of 0.8 MPa higher in port A than in port B at an operating pressure of 15 MPa. This paper provides a reference for further study on the effect of wear due to internal leakage failure on lifetime and improvement of service life of hydraulic directional valves.

Recently, transfer learning (TL) has been widely investigated to tackle the cross-domain fault diagnosis issue in machinery, and most research works follow the same assumption that the diagnosis domain shares the same fault categories. However, due to the randomness and complexity of mechanical faults, the new fault modes usually occur unexpectedly in the actual scenarios. The emergence of new faults also presents severe challenges to TL. In response to these challenges, a three-stage cross-domain intelligent fault diagnosis method is presented in this article. First, partial domain alignment is achieved based on an improved target weighted mechanism, and an outlier identifier is constructed to automatically separate the new fault classes. Then, an unsupervised learning model with silhouette coefficients is built to determine the number of new fault categories. Finally, the simulation signals are further adopted to distinguish the specific fault categories. Sufficient experiments on axial piston pump and public bearing datasets validate that the proposed method can predict a number of new fault categories and identify specific fault categories. The results indicate that the proposed method outperforms the other methods and has promising practical applications in fault diagnosis with multiple new faults.

Axial piston pump is the primary energy component of a hydraulic system, and evaluating its status is essential for guaranteeing secure functioning. The performance deterioration process in axial piston pump exhibits multistage and nonlinear characteristics. To solve these problems, this study introduces a method for online degradation modelling and the life prediction of axial piston pump based on a data-driven and failure physics fusion. Firstly, a feature fusion strategy is proposed to fuse different types of information and create an health index with trend prediction. Secondly, a degradation model for the rapid degradation stage was constructed based on data-driven and failure physics methods. Finally, the experimental data were used to continuously update the parameters of the built degradation model through an unscented Kalman filter, and the defect lifetime was predicted based on the model after updating the parameters. The proposed approach was compared with both a purely data-driven approach and a fusion method that lacks degradation stage identification and relies solely on parameter updates. The results indicate that life prediction errors were smaller than those of the comparative methods and that the comprehensive scores exceeded those of the comparative methods, thus demonstrating the effectiveness of the proposed method.

In recent years, the application of multi material molding technology in automotive parts manufacturing has been on the rise. This technology offers the advantages of lower costs and fewer processes. Based on the structural characteristics and technical requirements of the front fixed triangle cover plate for an automobile's A-pillar, a three-color injection molding mold was designed using a "Co-injection molding + Overmolding" scheme. For the first and second colors, the mold employs the "knife-valve sealing" method for single-cavity dual-color co-injection molding. Subsequently, a counter injection molding machine is used to rotate the back-mold horizontally by 180°, and overmolding is employed to complete the third-color injection molding process. All three materials were integrated using a needle-valve hot runner system, and the feed system incorporated three distinct feed methods. The cooling system was designed with a combination of " conformal cooling + slider cooling + baffle cooling". Simulations using Moldflow software identified potential warpage risks, which were mitigated during the waterway design phase. Results showed a reduction in maximum warpage from 1.743 mm in the initial simulation to an actual measured value of 0.477 mm. Following mold trial production, all structural systems operated smoothly and reliably. The product successfully met both appearance and dimensional accuracy requirements.

The master cylinder of most pump trucks is equipped with a waterproof valve, whose purpose is to prevent water from the tank from entering the master cylinder. Once waterproof valve fails to failure, the waterproof valve at the main cylinder can only be supported by a BS seal (this seal is very easy to fail), which results in oil emulsification and pollution of the hydraulic system. Therefore, a fault diagnosis method combining a multi-sensor high-dimensional time-domain feature expansion map (MHTFEM) with an attentional convolutional capsule network (ACCN) is proposed. In this method, the raw vibration signals acquired by all sensors are first preprocessed to generate a high-dimensional feature matrix. Then the different high-dimensional feature matrices are stitched, expanded and generated into grayscale images, followed by randomly dividing the training set and the testing set. Finally, the training set is brought into the ACCN for training and the testing set is brought into the network model for fault type identification. A test bench was built to confirm the effectiveness of the method for waterproof valve fault diagnosis. This provides a method to achieve intelligent fault diagnosis of construction machinery to ensure its reliability.

Recently, the intelligent fault diagnosis models gain increasing attention due to the development of artificial intelligent and state monitoring technology. However, obtaining massive defect data in advance in the actual diagnostic environment is difficult. Constructing diagnostic models on small sample datasets will easily lead to serious over fitting problems and loss of generalization ability, which is referred to as the small sample problem in this study. The simulation model method has made some progress in addressing the small sample problem. However, establishing an effective simulation model is difficult and time-consuming. The simulation signals also have a certain deviation between the actual signals. To address the above problem, a simulation data-driven adversarial domain adaptation fault diagnosis framework was proposed, which is based on dynamic modeling and adversarial domain adaptation approach. First, a reliable and complete dynamic model is established by considering the actual operating state of the faulty part. Second, the failure geometric defects are added to the model as displacement excitation, and the vibration response of the classical fault is simulated. Finally, adversarial domain adaptation approach is utilized to extract the common features of the simulated and measured samples to identify the faults. The effectiveness of the proposed method is validated and discussed on axial piston pump dataset and other dataset. It indicates that the proposed method can effectively solve the small samples problem in different mechanical equipment.

Inspired by the working principle that there is no throttling loss (theoretically) in the fully open and fully closed states of high-speed on–off valves, a high-frequency two-dimensional rotary valve is proposed to generate fluid pulse width modulation waves to control and distribute the flow rate of the hydraulic system in an energy-saving manner. The mechanism has been designed, so the aim of this paper is to develop detailed research on the characteristics of the high-frequency two-dimensional rotary valve as a new hydraulic component. The mathematical model of the rotary valve is established, and influences of key parameters on its characteristics are analyzed. Then, the static and dynamic characteristics of the rotary valve are simulated including valve coefficients, leakage, dynamic response and efficiency. Finally, a prototype of the two-dimensional rotary valve is designed and the testing system is built, and its pressure loss characteristics and energy efficiency characteristics were tested experimentally. The experiment results show that the valve is able to reduce throttling losses and improve the overall energy efficiency in the hydraulic system compared with the traditional throttling control. It can be used as a new variable mechanism, combined with a quantitative pump, to provide a way of forming a variable or load sensitive or bidirectional variable function of the pump system.