Energy-resolved HAXPES is proposed here as a method to analyze boundary layer formation on rough frictional surfaces, in which the vertical OLAP boundary layer structure containing organic components is non-destructively analyzed. In addition, HAXPES analysis was performed with high incident X-ray energies to obtain information about the entire boundary layer, and to distinguish the organic and inorganic layers for calculating the effective thickness of each. The results revealed that the vertical structure of the OLAP boundary layer consists of a surface layer of organic molecules, including esters and phosphates, and an inorganic iron phosphate layer at the substrate interface, with each component exhibiting a vertical concentration gradient. Furthermore, the effective thickness of the organic layer formed under the present sliding conditions was estimated to be about 50 to 80 nm, which became thicker and exhibited lower friction at increased running-in times, and is greater than the inorganic layer thickness of 10 to 15 nm. It is reasonable to attribute the observed low-friction and velocity-dependent properties to the thicker organic layer that preferentially supports the load during friction, demonstrating that this method is useful for determining the effects of boundary layers on tribological properties.

For circulation support in patients with heart disease, a miniaturized implantable ventricular assist device (VAD) is required. However, several issues such as hemolysis and miniaturization need to be addressed. The objective of this study is to develop a passive levitation system for an impeller with a large gap without active control. The large gap prevents blood damage, and passive levitation contributes to the miniaturization of the VAD. In this study, a new passive levitation system utilizing thrust and magnetic force is proposed. The thrust generated by the rotation of the impeller changes depending on the interaction between the housing geometry and impeller position, even with a large gap. Considering this characteristic, the impeller was levitated by balancing the magnetic force generated by the permanent magnets and the thrust in the axial direction. The movements in the radial and angular directions are passively supported by the restoring force and torque generated by the permanent magnets. The thrust was calculated using computational fluid dynamics, and the pump was designed such that the thrust changes according to the axial displacement of the impeller. The magnetic force generated by the permanent magnets was calculated using finite-element method 3D magnetic field analysis. In addition, the required current density flowing into the coil to rotate the impeller is calculated. The levitation of the impeller was confirmed by combining the results of the analyses. The results show that the motor torque should be improved. In conclusion, this study demonstrates the feasibility of a novel levitation system for implantable miniaturized VADs.

This paper proposed a sampled-data polydyne as feedforward input for a high-speed and high-precision positioning control system that does not excite specified mechanical resonant modes. The polydyne curve is an optimal cam profile that does not generate residual vibrations due to the follower's resonant mode. Research papers have reported applications of polydyne curve to feedforward control, and they have been formulated in continuous-time domain. However, when the frequency of vibration to be suppressed is high and the sampling frequency is relatively low, the reference trajectory for feedforward control should be generated in discrete-time domain. The author rederived the polydyne curve from the response of a 1-DOF vibration system driven by an input force defined as a continuous-time polynomial. After that, the sampled-data polydyne was derived in the same way and formulated in discrete-time domain. For suppressing one resonant mode, the order of polynomial must be seventh or higher, and eleventh or higher order is necessary for suppressing two modes. Simulations of seek control in a hard drive was performed to demonstrate the proposed feedforward input using sampled-data polydyne suppressed the residual vibration of control object. The simulation results were compared with the conventional method using sampled-data polynomial. Seventh- and eleventh-order polydynes were compared with the seventh-order sampled-data polynomial. In case of even-order polynomial, on the other hand, the eighth- and twelfth-order polydynes were compared with the sixth-order polynomial. In both cases, it is confirmed that the sampled-data polydyne suppressed the residual vibrations substantially and improved the tracking error after seek motion. Furthermore, it was confirmed that the apparent damping ratio of closed-loop system should be used in generating sampled-data polydyne instead of the mechanical one.

Uniaxial tensile tests were conducted to investigate the hot tensile deformation behavior of 6061 aluminum alloy under various temperatures and strain rates. Fields−Backofen equation was employed to establish the constitutive model of 6061 aluminum alloy, which was used to construct the finite element model for multi-bosses formed by plate forging process at elevated temperature. In the combination of numerical simulations and experimental tests including micro-hardness and electron back-scattered diffraction (EBSD) examination, the influence of two main process parameters, namely deformation temperature and counter-punch force, on the boss deformation and microscopic characteristics of multi-bosses formed at elevated temperature was discussed. The results show that the constitutive equation adopted is adequate to predict the deformation behavior in the plate forging process. While a higher temperature can improve the formability due to the reduction of plastic deformation resistance, a higher counter-punch load is favorable to increase the boss height and risk of fracture around the punch radius at the same time. In addition, it is favorable to promote recrystallization and fabricate the cylindrical component with a more homogeneous microstructure at a higher deformation temperature. From a comprehensive consideration, the 623 K is taken as the optimized deformation temperature for the selected 6061 aluminum alloy.

Weld shape and track precise identification is one of the key problems for automatic welding technology. In this paper, a weld track identification method based on illumination correction and center point extraction is proposed to extract welds with different shapes and non-uniform illumination. Firstly, an image pre-processing algorithm based on illumination correction is designed to eliminate the lighting influence. Secondly, an image extraction algorithm based on iterative threshold segmentation and morphological processing is proposed to obtain a continuous weld binary image. Thirdly, sub-pixel center point extraction algorithm and least-square based polynomial fitting is used to obtain the center fitting curve of welding seam. Experimental results show that the proposed method can realize accurate recognition of welding seam track under different illumination conditions effectively. The recognition error for welding seams with different typical shapes is within 4 pixels, and the average fitting error is less than 1.8 pixels. The welding seam identification and fitting method shows great application potential in the field of automatic assembling and robotic welding.

Considering the effects of vertical vibration displacement and horizontal vibration displacement of work rolls, a CNN-BN-LSTM dynamic rolling force prediction model based on the combination of one-dimensional convolutional neural network (1D-CNN), Batch Normalization (BN) and Long Short-Term Memory Network (LSTM) is proposed, and the model is optimized by Adam optimization algorithm for different parameters by designing independent adaptive learning rates. The model firstly uses CNN to extract data features effectively, secondly uses BN algorithm to improve the training speed, suppress gradient disappearance and reduce overfitting, and finally uses LSTM to extract data signals of time series to construct the dynamic rolling force prediction model. The proposed model is calculated by collecting PDA (process data acquisition) production data, vibration signals of horizontal and vertical vibrations of work rolls from the second finisher (F2) of a hot tandem rolling mill. The results show that the prediction accuracy of CNN-BN-LSTM is 90.68% and is higher than that of the Pei-Hua Hu model and CNN model, which verifies that the CNN-BN-LSTM model has strong generalization ability, fast training speed and high prediction accuracy. The relationship between process parameters and vibration is quantitatively analyzed based on the CNN-BN-LSTM model. The results show that reducing the rolling speed, reducing the entrance thickness and increasing the exit thickness can improve the stability of the rolling process.

In this study, we characterized the lubrication properties of two different hierarchical patterns comprising micro- and nanogrooves. The friction coefficient distribution was measured using a convex lens—the friction coefficients were found to periodically undulate along the scan lines with a period equal to the unit pattern. The variation of friction coefficient was more apparent in the case of the Type L pattern with the low boundary bands. For the Type H pattern with the high boundary bands, the undulation in the friction coefficient became clearer at higher sliding speeds, and concurrently, its average friction coefficient decreased with the higher sliding speed. Numerical calculations revealed that oil films formed more easily on Type H patterns than on Type L ones. When pause durations were included in Type H friction tests, the kinetic friction coefficient decreased when the lens slid parallel to the micro/nanogrooves, whereas it was not affected during orthogonal friction.

Gear vibration fault signals are non-stationary and nonlinear, so it is very difficult to accurately extract the fault characteristics for diagnosis. As symplectic geometry mode decomposition (SGMD) has shown excellent decomposition performance and noise robustness in signal processing. A novel gear fault diagnosis method, that is, SGMD-CNN, is proposed combined SGMD with a convolutional neural network (CNN). The noise of the gear vibration fault signal is reduced through the use of SGMD method, and several symplectic geometry components (SGC) are screened out according to the kurtosis value respectively. The reconstructed signal based on the selected SGCs is used as the input of the convolutional neural network. The ability of the convolutional neural network to learn features and classification is used to realize intelligent fault diagnosis of gear. The proposed SGMD-CNN is verified by the gear fault data. Based on the same convolution neural network model, the accuracy of the established SGMD-CNN model is 100%. It is about 32% higher than the accuracy of the simple CNN model and about 16% higher than the accuracy of the EMD-CNN model. The results show that the method is effective in classifying and identifying different types of gear failures.

Planetary roller screw mechanism (PRSM) is a novel high-performance linear transmission device. The non-uniformity of load distribution over PRSM threads is a vital problem severely affecting its load-carrying capacity and service performance. This work aims to develop a PRSM load distribution improvement approach with good manufacturability and general applicability. A roller taper modification method for load distribution optimization is proposed based on the deformation compatibility and force equilibrium, then the roller grinding experiment is carried out. Finally, the effects of external load and thread number on load sharing optimization are analyzed to examine the applicability. The results show that the maximum reduction in load sharing coefficient reaches 31.4% after roller taper modification under the case studied. The taper modification of roller threads could be rapidly implemented by only adjusting the roller grinding angle. The roller grinding experiment results agree well with the theoretical values, and the maximum error is no more than 2 μm. As the external load and thread number change, the improvement approach still works well. The proposed method has been verified by comparisons with finite element simulations and available references. This work can provide theoretical guidance for the optimal design of PRSM and has good engineering application prospects.