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The self-lubricating mechanism of Cu–Pb bearing alloy is discussed by molecular dynamics (MD). MD friction tests are conducted on the pure Cu and Cu–Pb models. The Pb-rich secondary phases (PSPs) melt due to the frictional heat. The solid–liquid phase transition of Pb is characterized by the radial distribution function (RDF) and the potential energy. An obvious drop of motion resistance of the abrasive debris is observed in Cu–Pb alloy once the debris moves close to the soft PSP which protect the matrix from abrasion by embedding the debris and promoting the formation of a liquid lubricant film. The synchrotron radiation technology is employed to in-situ observe the phase transition of Pb, and the MD results match the experimental results well.

It is challenging to align multi-exposed images due to large illumination variations, especially in presence of saturated regions. In this paper, a novel image alignment algorithm is proposed to cope with the multi-exposed images with saturated regions. Specifically, the multi-exposed images are first normalized by using intensity mapping functions (IMFs) in consideration of saturated pixels. Then, the normalized images are coded by using the local binary pattern (LBP). Finally, the coded images are aligned by formulating an optimization problem by using a differentiable Hamming distance. Experimental results show that the proposed algorithm outperforms state-of-the-art alignment methods for multi-exposed images in terms of alignment accuracy and robustness to exposure values.

N-ary gray-level (nGL) coding strategy is an effective method for absolute phase retrieval in the fringe projection technique. However, the conventional nGL method contains many unwrapping errors at the boundaries of codewords. In addition, the number of codewords is limited in only one pattern. Consequently, this paper proposes a new gray-level coding method based on half-period coding, which can improve both these two deficiencies. Specifically, we embed every period with a 2-bit codeword, instead of a 1-bit codeword. Then, special correction and decoding methods are proposed to correct the codewords and calculate the fringe orders, respectively. The proposed method can generate n2 codewords with n gray levels in one pattern. Moreover, this method is insensitive to moderate image blurring. Various experiments demonstrate the robustness and effectiveness of the proposed strategy.

Objectives: The aim of the present work was to comparatively investigate the generation and characteristics of fretting and sliding wear debris produced by CuNiAl against 42CrMo4. Methods: Tribological tests were conducted employing a self-developed tribometer. Most experimental conditions were set the same except for the amplitudes and number of cycles. Morphological, chemical, microstructural and dimensional features of the worn area and debris were investigated using optical microscope (OM), X-ray diffraction (XRD), scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) and a laser particle sizer. Outcomes: Not only wear scar profiles but also the wear debris color, distribution and generated amount under fretting and sliding wear modes were quite different, which can be attributed to the significant difference in wear mechanisms. Particle size analysis indicates that the fretting debris has a smaller size distribution range; the biggest detected fretting and sliding wear debris sizes were 141 μm and 355 μm, respectively. Both fretting and sliding debris are mainly composed of copper and its oxides, but the former shows a higher oxidation degree.

Reducing friction and wear in contact pairs is a formidable challenge in engineering applications. In this study, the influence of different particle distribution parameters on the flow field for elastohydrodynamic lubrication (EHL) friction pairs is analyzed using a multigrid method. In particular, the effects of the particle distribution density and location on the tribological properties are examined. A general Reynolds equation for an arbitrary non-Newtonian fluid is used to account for the non-Newtonian properties in the contact area. An inclusion-EHL model is established by coupling the flow field with the elastic field of heterogeneous particles below the contact surface, which are subject to eigenstrains. The results illustrate that the distribution density of the particles causes fluctuations in the film pressure and thickness and that the spacing ratio and position of the symmetry center have serious effects on the traction force. It is also found that the traction force can be effectively reduced by using a reasonable set of particle distribution parameters.

A numerical solution for line contact elastohydrodynamic lubrication (EHL) occurring on the rough surface of heterogeneous materials with a group of particles is presented in this study. The film thickness disturbance caused by particles and roughness is considered into the solution system, and the film pressure between the contact gap generated by the particles and the surface roughness is obtained through a unified Reynold equation system. The inclusions buried in the matrix are made equivalent to areas with the same material as that of the matrix through Eshelby’s equivalent inclusion method and the roughness is characterized by related functions. The results present the effects of different rough topographies combined with the related parameters of the particles on the EHL performance, and the minimum film thickness distribution under different loads, running speeds, and initial viscosities are also investigated. The results show that the roughness morphology and the particles can affect the behavior of the EHL, the traction force on a square rough surface is smaller, and the soft particles have more advantages for improving the EHL performance.

The traditional estimation methods of space targets pose are based on artificial features to match the transformation relationship between the image and the object model. With the explosion of deep learning technology, the approach based on deep neural networks (DNN) has significantly improved the performance of pose estimation. However, the current methods still have problems such as complex calculation, low accuracy, and poor real-time performance. Therefore, a new pose estimation algorithm is proposed in this paper. Firstly, the mask image of the target is obtained by the instance segmentation algorithm, and its point cloud image is obtained based on a depth map combined with camera parameters. Finally, the correlation among points is established to realize the prediction of pose based on multi-modal feature fusion. Experimental results in the YCB-Video dataset show that the proposed algorithm can recognize complex images at a speed of about 24 images per second with an accuracy of more than 80%. In conclusion, the proposed algorithm can realize fast pose estimation for complex stacked objects and has strong stability for different objects.

Object detection and segmentation can improve the accuracy of image recognition, but traditional methods can only extract the shallow information of the target, so the performance of algorithms is subject to many limitations. With the development of neural network technology, semantic segmentation algorithms based on deep learning can obtain the category information of each pixel. However, the algorithm cannot effectively distinguish each object of the same category, so YOLOMask, an instance segmentation algorithm based on complementary fusion network, is proposed in this paper. Experimental results on public data sets COCO2017 show that the proposed fusion network can accurately obtain the category and location information of each instance and has good real-time performance.

In this research, a novel vortex generator (VG) is presented. The experimental and numerical investigations were carried out to study the micro thermal-hydraulic performance in a heated tube. The numerical results showed that the fluid in the core flow region and the near-wall region was fully mixed because of the longitudinal vortices created by the vortex generators. In addition, the experimental results showed that the heat transfer coefficient (h) decreased with the increasing pitch ratio (PR) value, while the friction coefficient exhibited the opposite trend. With the increasing ration angle (RA) numbers, the h values decreased while the f numbers increased. In addition, the maximum and minimum values of the fraction ratio were 1.66 and 4.27, while these values of the Nusselt number ratio were 1.24 and 1.83. The maximum thermal enhancement factor (TEF) was 1.21 when PR = 0.5, RA = 0° and Re = 9090. The heat transfer enhancement mechanism of the vortex generator is explained from the microscopic point of view.

Pin-on-disc experiments are conducted to investigate the tribological performance of untextured and textured brass surfaces with TiN coatings under oil lubrication. The surface texture is designed as a dimple pattern with different diameters and depths for the transverse surfaces of brass pins. After texturing, a TiN coating is deposited through pulsed-bias arc ion plating in a pure N2 atmosphere using a Ti target. Three dimple diameters are used, namely 130 μm, 150 μm, and 170 μm, along with three dimple depths, namely 15 μm, 40 μm, and 60 μm. The TiN coating is around 5 μm thick. Friction tests are conducted under different rotation speeds and loads, and the interfacial adhesion is assessed via a scratch test. Compared to the untextured surface, the textured one offers improved tribological behavior in mixed lubrication because the dimples generate hydrodynamic lift. To reduce friction in the case of higher speed and lower load, the optimum texture parameters are a diameter of 150 μm and a depth of 40 μm.

A series of experiments is conducted to investigate the hydrodynamic lubricant characteristics of partial surface textured specimens. The specimens are fabricated with partial surface texture. Two dimple shapes are adopted: circular and elliptic. Four kinds of texture arrangements of elliptic dimples are designed. During each test, different rotating speeds and gaps between the tested specimen and the geometric probe are set to explain the relationship between the operation condition and load-carrying capacity. We found that the load-carrying capacity is strongly affected by the operation condition, i.e. by both speed and gap. The surface textured specimens generate large hydrodynamic lift force compared with the untextured specimen. In addition, the texture arrangements exhibit a significant impact on the lubrication property.

A robot can identify the position of a target and complete a grasping based on the hand–eye calibration algorithm, through which the relationship between the robot coordinate system and the camera coordinate system can be established. The accuracy of the hand–eye calibration algorithm affects the real-time performance of the visual servo system and the robot manipulation. The traditional calibration technique is based on a perfect mathematical model AX = XB, in which the X represents the relationship of (A) the camera coordinate system and (B) the robot coordinate system. The traditional solution to the transformation matrix has a certain extent of limitation and instability. To solve this problem, an optimized neural-network-based hand–eye calibration method was developed to establish a non-linear relationship between robotic coordinates and pixel coordinates that can compensate for the nonlinear distortion of the camera lens. The learning process of the hand–eye calibration model can be interpreted as B=fA, which is the coordinate transformation relationship trained by the neural network. An accurate hand–eye calibration model can finally be obtained by continuously optimizing the network structure and parameters via training. Finally, the accuracy and stability of the method were verified by experiments on a robot grasping system.

The internal leakage of a hydraulic cylinder is an inevitable hydraulic system failure that seriously affects the working efficiency of the hydraulic system. Therefore, it is very important to accurately identify and predict leakage data in the hydraulic cylinder. In this paper, a model is proposed to simulate a small internal leakage of hydraulic cylinders, to convert the amount of leakage of hydraulic oil into strain signals through high-precision strain gauges and to train the collected strain signals using various neural networks to form a computational model and obtain prediction results from the model. The neural networks applied in this paper are convolutional neural networks, BP neural networks, T-S neural networks and Elman neural networks. The predicted results of the neural network are compared with the actual leakage amount. The results show that the prediction accuracy of the above four kinds of neural networks are all above 90%, of which the convolutional neural network is the most accurate. This research provides scientific and technical support for measuring and predicting small leaks.

Dexterous manipulation of the robot is an important part of realizing intelligence, but manipulators can only perform simple tasks such as sorting and packing in a structured environment. In view of the existing problem, this paper presents a state-of-the-art survey on an intelligent robot with the capability of autonomous deciding and learning. The paper first reviews the main achievements and research of the robot, which were mainly based on the breakthrough of automatic control and hardware in mechanics. With the evolution of artificial intelligence, many pieces of research have made further progresses in adaptive and robust control. The survey reveals that the latest research in deep learning and reinforcement learning has paved the way for highly complex tasks to be performed by robots. Furthermore, deep reinforcement learning, imitation learning, and transfer learning in robot control are discussed in detail. Finally, major achievements based on these methods are summarized and analyzed thoroughly, and future research challenges are proposed.

Feature point detection is the basis of computer vision, and the detection methods with geometric invariance and illumination invariance are the key and difficult problem in the field of feature detection. This paper proposes an illumination-invariant feature point detection method based on neighborhood information. The method can be summarized into two steps. Firstly, the feature points are divided into eight types according to the number of connected neighbors. Secondly, each type of feature points is classified again according to the position distribution of neighboring pixels. The theoretical deduction proves that the proposed method has lower computational complexity than other methods. The experimental results indicate that, when the photometric variation of the two images is very large, the feature-based detection methods are usually inferior, while the learning-based detection methods performs better. However, our method performs better than the learning-based detection method in terms of the number of feature points, the number of matching points, and the repeatability rate stability. The experimental results demonstrate that the proposed method has the best illumination robustness among state-of-the-art feature detection methods.

Laser stripe vision sensors have limited application when the whole surface of an object has to be measured; therefore, a galvanometric laser scanner is presented using a one-mirror galvanometer element as its mechanical device to drive the light stripe to sweep along the object. A flexible plane-constraint together with a look-up table calibration algorithm by viewing a planar calibration target from unknown orientations is presented to calibrate the proposed galvanometric laser scanner. The plane-constraint method generates a larger number of control points by imposing a plane constraint on the control points. Compared with the invariance of double cross-ratio, the plane-constraint-based calibration method generates the same number of control points without error propagation. Contrast experiments are conducted to verify the efficiency and accuracy of the proposed calibration method.

Appreciable friction and serious wear are common challenges in the operation of advanced manufacturing equipment, and friction pairs may be susceptible to damage even with oil lubrication when point contact exists. In this study, a type of particle-reinforced composite material is introduced for one of the components of a heavy-load contact pair, and the performance improvement of elastohydrodynamic lubrication (EHL) is analyzed considering the rheological properties of non-Newtonian fluids. The Ree–Eyring EHL model is used considering the surface of the particle-reinforced composite, in which the film thickness includes the particle-induced elastic deformation. The problem of inclusions with different eigenstrains is solved by using Galerkin vectors. The influences of particle properties, size, burial depth, and interparticle distance on point-contact EHL are investigated. Furthermore, using several cases, the structural parameters of the particles in the composites are optimized, and an appropriate parameter range is obtained with the goal of reducing friction. Finally, the results for the EHL traction coefficient demonstrate that appropriate particle properties, size, burial depth, and interparticle distance can effectively reduce the traction coefficient in heavy-load contact.

The poor operating conditions of fluid lubrication equipment during the start-up process are due to the resistance of the high-viscosity lubricating liquid. Moreover, the excessive reduction in fluid viscosity due to the elevated temperature resulting from power consumption during prolonged operation is not conducive to the generation of dynamic pressure. In this study, we examine the effect of energy accumulation and boundary slip on the laminar flow of a liquid between a pair of rotating plates. The experiments are conducted using a rotary rheometer, with polymethyl methacrylate (PMMA) as the thermal insulation material and polytetrafluoroethylene (PTFE) as the slip drag reduction material, and a three-dimensional simulation model is established. This model is derived by combining the energy equation including the slip length and the heat conduction equation. Thus, the temperature changes over time are predicted by this model, and the model accuracy is verified by experiments. The results reveal the following points: 1) boundary slips function as a drag reduction mechanism for short-time continuous operation; 2) under prolonged operation, the slip reduces the extent of the oil viscosity decrease and clear control of the elevated temperature by the boundary slip is observed.

Subgrade bears both the impacts of the high-speed train and the weight of superstructures. Its stability affects the line smoothness directly, but it is very hard to simulate its working condition, and the in situ testing method is inadequate. The article presents a railway roadbed in situ testing device, and it proposes an excitation hydraulic cylinder system to output static and dynamic pressure simultaneously in order to simulate the force of the train. The dynamic following performance is quite poor without control algorithm, so the robust control block is adopted to improve the following performance of the excitation system under different frequencies and waveforms. In addition, considering the effects of the external disturbances, simulation is carried out with a certain intensity of noise to test the effectiveness of the control scheme. The simulation results show that the robust control algorithm makes the excitation system achieving much better following performance.

According to the hydraulic principle diagram of the subgrade test device, the dynamic pressure cylinder electrohydraulic servo pressure system math model and AMESim simulation model are established. The system is divided into two parts of the dynamic pressure cylinder displacement subsystem and the dynamic pressure cylinder output pressure subsystem. On this basis, a RBF neural network backstepping sliding mode adaptive control algorithm is designed: using the double sliding mode structure, the two RBF neural networks are used to approximate the uncertainties in the two subsystems, provide design methods of RBF sliding mode adaptive controller of the dynamic pressure cylinder displacement subsystem and RBF backstepping sliding mode adaptive controller of the dynamic pressure cylinder output pressure subsystem, and give the two RBF neural network weight vector adaptive laws, and the stability of the algorithm is proved. Finally, the algorithm is applied to the dynamic pressure cylinder electrohydraulic servo pressure system AMESim model; simulation results show that this algorithm can not only effectively estimate the system uncertainties, but also achieve accurate tracking of the target variables and have a simpler structure, better control performance, and better robust performance than the backstepping sliding mode adaptive control (BSAC).

The problem of shaft axial motion which significantly affects the lubrication performance has been a common phenomenon in journal bearing systems. The existing work involved in the solution of shaft axial motion is also very rare. In this study, we choose to examine the flow between sliding pair in which regard we present a unique heterogeneous surface consisting of a slip zone and a no-slip zone. The results reveal the following points: 1) By appropriately arranging the slip zone to change the angle between the borderline and the moving direction of the upper plate, it is possible to control the direction of the lateral traction in which the liquid film acts on the upper plate. 2) Exponent of the power function of the borderline and aspect ratio of the computational domain are large or small are not conducive to increasing the effect of lateral traction. For the object of this study, the final results of the optimization are shown that the lateral traction can account for 20% of the resistance.

Droplet generation process can directly affect process regulation and output performance of electrohydrodynamic jet (E-jet) printing in fabricating micro-to-nano scale functional structures. This paper proposes a numerical simulation model for whole process of droplet generation of E-jet printing based on the Taylor-Melcher leaky-dielectric model. The whole process of droplet generation is successfully simulated in one whole cycle, including Taylor cone generation, jet onset, jet break, and jet retraction. The feasibility and accuracy of the numerical simulation model is validated by a 30G stainless nozzle with inner diameter ~160 μm by E-jet printing experiments. Comparing numerical simulations and experimental results, period, velocity magnitude, four steps in an injection cycle, and shape of jet in each step are in good agreement. Further simulations are performed to reveal three design constraints against applied voltage, flow rate, and nozzle diameter, respectively. The established cone-jet numerical simulation model paves the way to investigate influences of process parameters and guide design of printheads for E-jet printing system with high performance in the future.

The Auto Anti-Deviation Drilling System (AADDS) is a high-performance, highly automated vertical drilling hydraulic guide control system. This article takes its power extraction device - driving bearing for the study object, analyzed the single-plunger pump's principle, established the mathematical model of hydraulic guide system, applied Matlab/Simulink to simulate the pump outlet flow under different contour curve of the driving bearing. The results show the oval-shaped bearing is of high efficiency under lower drilling speed, and its performance is better than that of original eccentric-shaped and clover-shaped.

Nowadays, the electro-hydraulic valves are widely used in industrial manufacture for their low-cost and accuracy. Aiming at electro-hydraulic proportional position system, a model of the system is established in Simulink. The system is simulated respectively as the situation of without PID controller, with the PID controller turned by critical ratio method and SRO optimize module. The results show that: the position control system with electro-hydraulic proportional valve is of good static and dynamic characteristics, and meets the requirements of industrial production fairly, and it also indicates the usage of computer automation optimization technology can design the control system with good performance in a short time and can improve the design efficiency.