Fanglong Yin

Bio: Fanglong Yin is an academic researcher from Beijing University of Technology. The author has contributed to research in topics: Tribology & Seawater. The author has an hindex of 7, co-authored 27 publications receiving 154 citations.

Research on fluid-structure interaction for piston/cylinder tribopair of seawater hydraulic axial piston pump in deep-sea environment

Abstract: Seawater hydraulic axial piston pump (SHAPP) is a critical power component in underwater operating systems. A parameterized elasto-hydrodynamic (EHD) lubrication model of the piston/cylinder tribopair in the SHAPP is originally established, which considers the elasto-hydrodynamic behavior, viscosity temperature effect and deep-sea environmental pressure. The deformation of piston bush, bearing mechanism and energy loss characteristics of the water film under different operating conditions are discussed. The results show that the deformation of piston bush made of polyetheretherketone (PEEK) is in micron-scale under water film and deep-sea pressure, which could increase the leakage and viscous friction power loss of piston/cylinder tribopair. In deep-sea environment, the leakage and viscous friction power loss calculated by EHD are always greater than those calculated by hydrodynamic (HD), and increase with the increase of working pressure, shaft speed, gap size, sea depth and piston bush thickness. Besides, the increase of sea surface temperature could increase the leakage and decrease the viscous friction power loss of the piston/cylinder tribopair, respectively. Finally, design instructions to optimize the piston/cylinder tribopair are presented, therefore the proposed methodology can be used as a designing tool for SHAPP.

Optimization and performance analysis of magnetorheological fluid damper considering different piston configurations

Abstract: This article presents the design and multi-physics coupling analysis of a shear-valve-mode magnetorheological fluid damper with different piston configurations. The finite element model is built to...

Numerical and experimental study of cavitation performance in sea water hydraulic axial piston pump

Abstract: Cavitation is one of the important elements influencing the performance of sea water hydraulic axial piston pump. To understand the working performance of sea water hydraulic axial piston pump unde...

Numerical and experimental investigation on torque characteristics of seawater hydraulic axial piston motor for underwater tool system

Abstract: Seawater hydraulic axial piston motor is an important and elemental component in underwater tool system. The torque characteristics for a swash-plate-type seawater hydraulic axial piston motor is investigated, and an integrated torque model for the motor with symmetrical pre-compression angles has been developed, which consists of a torque sub-model and a dynamic pressure sub-model. Numerical simulations have been carried out to examine the effects of (a) pre-compression angle, (b) relief-groove obliquity, (c) motor speed, (d) piston chamber dead volume, (e) friction on the dynamic pressure and the output torque characteristics. The results indicate that the pre-compression angle, the friction coefficient, and the clearance between cylinder bore/piston have significant impact on the torque characteristics. The test verification has been undertaken with a five piston water hydraulic motor. This research contributes to the mechanism of output-torque fluctuation in a swash-plate-type seawater hydraulic axial piston motor, as well as the investigation of the torque transition phenomenon owing to the pre-compression angle. The research has laid the foundation for the development and improvement of the seawater hydraulic axial piston motor in underwater tool system.

Research on the sliding bearing pair of water hydraulic axial piston pump

Abstract: Sliding bearing pair is one of the important friction pairs within water hydraulic axial piston pump, which can result in significant influences on the pump’s performance Generally, owing to the characteristics of low viscosity and poor lubrication of water, the sliding bearing will operate under condition of dry or mixed lubrication, leading to a severe adhesives wear and material softening In order to investigate the flow field of the sliding bearing in hydrodynamic condition, the effects of the water film pressure distribution, load carrying capacity changing with radial clearance and width–radius ratio of the sliding bearing pair have been simulated through MATLAB And a suitable material combination of the sliding bearing pair was selected though a custom-manufactured friction and wear test rig Based on the theoretical and experimental studies, an appropriate structure of the sliding bearing within water hydraulic axial piston pump was designed The loading experiments for the developed water hydr

Noise prediction of axial piston pump based on different valve materials using a modified artificial neural network model

Abstract: In this paper, an alternative method to predict the noise of a submersible Axial Piston Pump (APP) for different valve seat materials is presented. The proposed method is composed of an Artificial Neural Network (ANN) model trained using experimental data and integrated with a hybrid algorithm consists of Cat Swarm Optimization (CSO) and Firefly Algorithm (FA) algorithms. The hybrid CSFA algorithm is used as a subroutine in the ANN model to estimate the ANN weights. The FA is used as local operator to improve the exploitation ability of CSO. The obtained results prove the excellence of the proposed method in predicting the noise of APP considering four different valve seat materials (Polytetrafluoroethylene (PTFE), Polyetheretherketone (PEEK), Aliphatic polyamides (NYLON), and stainless steel (316 L)), five speed levels, and six system pressures. Moreover, the effects of different mechanical properties of the valve seat materials as well as operating conditions (speed and system pressure) have been investigated.

A Review of High-Speed Electro-Hydrostatic Actuator Pumps in Aerospace Applications: Challenges and Solutions

Abstract: The continued development of electro-hydrostatic actuators (EHAs) in aerospace applications has put forward an increasing demand upon EHA pumps for their high power density. Besides raising the delivery pressure, increasing the rotational speed is another effective way to achieve high power density of the pump, especially when the delivery pressure is limited by the strength of materials. However, high-speed operating conditions can lead to several challenges to the pump design. This paper reviews the current challenges including the cavitation, flow and pressure ripples, tilting motion of rotating group and heat problem, associated with a high-speed rotation. In addition, potential solutions to the challenges are summarized, and their advantages and limitations are analyzed in detail. Finally, future research trends in EHA pumps are suggested. It is hoped that this review can provide a full understanding of the speed limitations for EHA pumps and offer possible solutions to overcome them.

Origin of friction and the new frictionless technology—Superlubricity: Advancements and future outlook

Abstract: Friction is a phenomenon that exists extensively in nature and industry; it has proven necessary in daily life and beneficial in energy scavenging but is also alleged to be the main cause of wear failures and energy consumption. Therefore, scientists have long worked on the origin of friction, trying in some instances to verify the possibility of achieving an absolute friction-free state, and rapid progress has been made in recent decades. In this article, we review the research on the friction mechanism and the development of a new burgeoning technique named “superlubricity”, which has been demonstrated as an attractive way to achieve ultralow friction and wear with almost no energy dissipation. It is estimated that the future application of superlubricity could result in an economic benefit of trillions of US dollars annually worldwide, as well as having great energy saving potential.

A theoretical dynamic model to study the vibration response characteristics of an axial piston pump

Abstract: A dynamic model with four masses and 19 degree of freedoms is proposed to investigate the vibration response characteristics of an axial piston pump. In the model, main parts are simplified by multiple lumped mass points connected with spring-damper elements. Experimental investigation is performed, and the discharge dynamic pressures and vibrations are measured to validate the dynamic model. Using the constructed model, influences of operating conditions (the discharge pressure, the rotational speed, and the displacement angle), and stiffness and damping coefficients between different contacting surfaces (the cylinder and valve plate, the piston and cylinder bore, and the slipper and swash plate) on the amplitude-frequency vibration responses and phase trajectory plots are analyzed. The findings showed that the vibration responses are significantly affected by the operating conditions, and are also considerably affected by the stiffness and damping coefficients. The rotational speed determines the fundamental frequency and its harmonics, and most of the harmonic vibration responses increase with increasing discharge pressure and displacement angle. The shape and the area defined by the phase trajectory are significantly changed by the operating conditions. The complex irregular motion might be changed into less irregular motion with decreasing discharge pressure, rotational speed and displacement angle.

A novel adaptive convolutional neural network for fault diagnosis of hydraulic piston pump with acoustic images

Abstract: As an essential part of hydraulic transmission systems, hydraulic piston pumps have a significant role in many state-of-the-art industries. Thus, it is important to implement accurate and effective fault diagnosis of hydraulic piston pumps. Owing to the heavy reliance of shallow machine learning models on the expertise and experience of engineers, fault diagnosis based on deep models has attracted significant attention from academia and industry. To construct a deep model with good performance, it is necessary and challenging to tune the hyperparameters (HPs). Since many existing methods focus on manual tuning and use common search algorithms, it is meaningful to explore more intelligent algorithms that can automatically optimize the HPs. In this paper, Bayesian optimization (BO) is employed for adaptive HP learning, and an improved convolutional neural network (CNN) is established for fault feature extraction and classification in a hydraulic piston pump. First, acoustic signals are transformed into time–frequency distributions by a continuous wavelet transform. Second, a preliminary CNN model is built by setting initial HPs. The range of each HP to be optimized is identified. Third, BO is employed to select the optimal combination of HPs. An improved model called CNN-BO is constructed. Finally, the diagnostic efficiency of CNN-BO is analyzed using a confusion matrix and t-distributed stochastic neighbor embedding. The classification performance of different models is compared. It is found that CNN-BO has a higher accuracy and better robustness in fault diagnosis for a hydraulic piston pump. This research will provide a basis for ensuring the reliability and safety of the hydraulic pump.