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This paper aims to propose a deep learning model that can be used to expand the number of samples. In the process of manufacturing and assembling electronic components on the printed circuit board in the surface mount technology production line, it is relatively easy to collect non-defective samples, but it is difficult to collect defective samples within a certain period of time. Therefore, the number of non-defective components is much greater than the number of defective components. In the process of training the defect detection method of electronic components based on deep learning, a large number of defective and non-defective samples need to be input at the same time.

To obtain enough electronic components samples required for training, a method based on the generative adversarial network (GAN) to generate training samples is proposed, and then the generated samples and real samples are used to train the convolutional neural networks (CNN) together to obtain the best detection results.

The experimental results show that the defect recognition method using GAN and CNN can not only expand the sample images of the electronic components required for the training model but also accurately classify the defect types.

To solve the problem of unbalanced sample types in component inspection, a GAN-based method is proposed to generate different types of training component samples and then the generated samples and real samples are used to train the CNN together to obtain the best detection results.

Hydrostatic thrust bearing is a key component of the vertical CNC machining equipment, and often results in friction failure under the working condition of high speed and heavy load. The lubricating oil film becomes thin or breaks because of high speed and heavy load and it affects the high precision and stable operation of the vertical CNC machining equipment; hence, it is an effective way of avoiding friction failure for achieving the oil film shape prediction

For the hydrostatic thrust bearing with double rectangular cavities, researchers solve the deformation of the friction pairs in hydrostatic bearing by using the computation of hydrodynamics, elasticity theory, finite element method and fluid-thermal-mechanical coupled method. The deformation includes heat deformation and elasticity deformation, the shape of gap oil film is got according to the deformation of the friction pairs in hydrostatic bearing, and gets the shape of gap oil film, and determines the influencing factors and laws of the oil film shape, and achieves the prediction of oil film shape, and ascertains the mechanism of friction failure. An experimental verification is carried out.

Results show that the deformation of the rotational workbench is upturned along its radial direction under the working condition of high speed and heavy load. However, the deformation of the base is downturned along its radial direction and the deformation law of the gap oil film along the radius direction is estimated; the outer diameter is close but the inner diameter is divergent wedge.

The conclusion can provide a theoretical basis for the oil film control of hydrostatic thrust bearing and improve the stability of vertical CNC machining equipment.

The purpose of this paper is to study thermal-fluid-solid coupling deformation and friction failure mechanism of bearing friction pairs under the working conditions of high speed and heavy load.

The deformation is simulated based on thermal-fluid-solid coupling method, its deformation distribution law is revealed and the relationships of deformation of friction pairs, rotational speed and bearing weight are obtained.

The results prove that the oil film temperature rises sharply, the lubricating oil viscosity decreases rapidly, the film thickness becomes thinner, the deformation increases, the whole deformation is uneven and the boundary lubrication or dry friction are caused with the increase in rotational speed and bearing load.

The conclusions provide theoretical method for deformation solution and friction failure mechanism of hydrostatic thrust bearing.

This paper aims to describe a theoretical and experimental research concerning influence of recess shape on comprehensive lubrication performance of high speed and heavy load hydrostatic thrust bearing with a constant flow.

The lubrication performance of a hydrostatic thrust bearing with different recess shape under the working conditions of high speed and heavy load has been simulated by using computational fluid dynamics and finite volume method.

It is found that the comprehensive lubrication performance of a hydrostatic thrust bearing with circular recess is optimal. The results demonstrate that recess shape has a great influence on the lubrication performance of the hydrostatic thrust bearing.

The simulation results indicate that to get an improved performance from a hydrostatic thrust bearing with constant flow, a proper selection of the recess shape is essential.

Prior investigations concerning misalignment resulting from journal deformation typically relied on predefined misaligned angles. Nevertheless, scant attention has been devoted to the determination of these misaligned angles. Furthermore, existing studies commonly treat the journal as rigid under such circumstances. Therefore, the present study aims to introduce a framework for determining misaligned angles and to compare outcomes between rigid and flexible journal configurations.

The bearing forces are considered as an external load leading to journal deformation. This deformation is calculated using the finite element method. The pressure distribution producing the bearing force is solved using the finite difference method. The mesh grids in the finite element and finite difference methods are matched for coupling calculation. By iteration, the pressure distribution of the lubricant film at the equilibrium position is determined.

Results show that the deformation-induced misalignment has a significant influence on the performance of the bearing when the journal flexibility is taken into account. The parametric study reveals that the misalignment relies on system parameters such as bearing length-diameter ratio and static load.

The investigation of this work provides a quantification method of misalignment of hydrodynamic bearings considering the elastic deformation of the journal, which assists in the design of bearing in a rotor-bearing system.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0337/

Rotational speed and load-carrying capacity are two mutual coupling factors which affect high precision and stable operation of a hydrostatic thrust bearing. The purpose of this paper is to study reasonable matching relationship between the rotational speed and the load-carrying capacity.

A mathematical model of relationship between the rotational speed and the load-carrying capacity of the hydrostatic bearing with double-rectangle recess is set up on the basis of the tribology theory and the lubrication theory, and the load and rotational speed characteristics of an oil film temperature field and a pressure field in the hydrostatic bearing are analyzed, reasonable matching relationship between the rotational speed and the load-carrying capacity is deduced and a verification experiment is conducted.

By increasing the rotational speed, the oil film temperature increases, the average pressure decreases and the load-carrying capacity decreases. By increasing the load-carrying capacity, the oil film temperature and the average pressure increases and the rotational speed decreases; corresponding certain reasonable matching values are available.

The load-carrying capacity can be increased and the rotational speed improved by means of reducing the friction area of the oil recess by using low-viscosity lubricating oil and adding more oil film clearance; but, the stiffness of the hydrostatic bearing decreases.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This paper aims to discuss that a WC/Co-Cr alloy coating was applied to the surface of H13 steel by laser cladding.

The oxidation behavior of the WC/Co-Cr alloy coating at 600°C was investigated by comparing it with the performance of the steel substrate to better understand the thermal stability of H13 steel.

The results showed that the WC/Co-Cr alloy coating exhibited better high-temperature oxidation resistance and thermal stability than did uncoated H13 steel. The coated H13 steel had a lower mass gain rate and higher microhardness than did the substrate after different oxidation times.

The WC/Co-Cr alloy coating was composed of e-Co, CW3, Co6W6C, Cr23C6 and Cr7C3; this mixture offered good thermal stability and better high-temperature oxidation resistance.

The purpose of this paper is to solve the tracking problem for free-floating space manipulators (FFSMs) in task space with parameter uncertainties and external disturbance.

In this paper, the novel cerebellar model articulation controller (CMAC) is designed with the feedback controller. More precisely, the parameter uncertainties in the FFSM are considered for achieving the robustness.

By using the dynamically equivalent model, the CMAC can be designed and trained with the desired performance, such that the prescribed trajectory can be followed accordingly. The simulation results are presented for illustrating the validity of the derived results.

Based on the designed CMAC, the tracking error would be approaching zero by choosing appropriate quantization level in CMAC and the corresponding learning rules can be tuned online.

This study aims to investigate the specific difficulties involved in implementing electronic recordkeeping for anti-corruption investigations in Nigeria. It recognises the importance of technological advancements in such investigations and the need for efficient, internationally recognised services, especially in a country where manual processes are prevalent.

This study uses a qualitative, exploratory case study approach. Data were gathered through interviews with 15 anti-corruption investigators in Nigeria in the year 2020 and analysed using thematic analysis.

This study identified two main challenges: resistance to adopting technological change and indifference towards information technology.

This study highlights the transformative potential of technology, specifically cloud computing and forensic technology, in an investigative context. By intentionally integrating technology, existing deficiencies can be addressed, investigative processes can be streamlined and a culture of accountability can be cultivated. It contributes to ongoing discussions and emphasises the capacity of technology to drive significant transformation in the pursuit of integrity and justice.