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Unmanned Aerial Vehicle (UAV) inspection has gradually replaced manual inspection of transmission tower, which produces many images. While it is laborious and time-consuming to manually analyze these images, there are also challenges in automatically detecting small-size defective components such as bolts in transmission tower images, due to problems including complex background, small size, and many similar objects of bolts. In this paper, by virtue of multi-scale features and context information, we propose a deep neural network named Camp-Net (Context Information and Multi-Scale Pyramid Network) to identify bolts defect in transmission tower images. First, multi-scale feature fusion combines deep features and shallow features in convolutional networks to detect small-size bolts. Second, context information fusion puts the information around bolts into the detection network to remove the disturbance of complex background and similar objects. An image dataset containing defective bolts and normal bolts is constructed for model training and testing. Experimental results show that bolts with loose pins and bolts without pins among fittings in transmission tower can be accurately identified with the proposed model. The Average Precision (AP) of defective bolts detection of this model can be 11.4% higher than that of the commonly used high performance model, Faster R-CNN. [ABSTRACT FROM AUTHOR]

Modeling of the structural behavior of the housing of an electromagnetic railgun is usually carried out without considering the electromagnetic origin of the forces; the magnetic pressure acting on the rails is assumed to act at the rail surfaces only. This approximation proves to be a great challenge, as moving pressure profiles at speeds of a railgun projectile are very rare in purely mechanical investigations. In the past, we have published several papers on the structural mechanics of railgun housings characterized by discrete supports. We could show that the displacement of rail surfaces at the position of the armature can reach amplitudes that are not negligible. In fact, in the case of metal brush armatures, the increase in distance between the rail surfaces of only tenths of a millimeter can make the difference between the solid contact and arcing to increase. We also matched our findings to experimental data that were, however, so far only gained in static tests. In this paper, we analyze the foundations of our mechanical modeling using electromagnetic calculations. We calculate a 3-D distribution of the $J \times B$ volume force density in the rails and use them as input for our structural mechanics model. A second point to be addressed concerns the parts made from conducting materials, such as our discrete supports made from steel bolts, which are situated in rapidly changing magnetic fields during the experiments. Again, the influence on our structural mechanics modeling is discussed. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of a magnetic lead screw (MLS) equipped with skewed arc magnets. Skewed arc magnets are adopted to approximate the helical ones, because the latter is hard to realize. Although similar method had been proposed in the previous literature, discussion about the parameters of the skewed arc magnets was insufficient and little attention was paid to the gear ratio of the resultant MLS. In this paper, the principle of approximation by skewed arc magnets is proposed and discussed, and the performance of the MLS with skewed arc magnets is evaluated and compared with the ideal MLS in terms of thrust force, torque, and gear ratio. It is highlighted that the gear ratio is the fundamental indicator of the MLS’s performance, besides the thrust force and torque. It is shown that the gear ratio of MLS is mainly affected by the reference angle and the arc angle of skewed arc magnets, and optimal values for the two angles are obtained. In addition, the effects of the magnet magnetization on thrust force and torque are analyzed. Finally, dovetail budge and groove are introduced between the adjacent magnet segments for simpler fabrication. [ABSTRACT FROM AUTHOR]

This paper introduces a batch fabrication method to manufacture Micro-Electro-Mechanical System (MEMS) platforms for 3D integration of sensors spatially-distributed on a 2D plane. In the heart of the concept is a foldable MEMS structure with polymer hinges which is used to support and guide the assembly of the discrete planar sensors by means of folding them into a 3D shape, like origami, providing controlled distribution of sensors in space. Flexible hinges carrying the electrical interconnects are a critical structural element of the platform and material selection study for those is the main focus of this paper. We analyzed different materials for flexible hinges fabrication, including photo-definable polyimide and parylene-C. Three approaches for sensor integration are presented: 1) co-fabrication; 2) sensor drop-in; and 3) transfer bonding. The prototypes of structures with different flexible hinge materials were fabricated and evaluated based on their mechanical flexibility, chemical compatibility, and material outgassing. Parylene-C exhibited similar or better performances compared to polyimide, demonstrating in each of the experiments a higher degree of thermal flexibility up to 350 °C, a superior chemical resistance against hydrofluoric acid, and 2.9 times lower outgassing. [2020-0301] [ABSTRACT FROM AUTHOR]

Hyperspectral imagery (HSI) has shown promising results in real-world applications. However, the technological evolution of optical sensors poses two main challenges in HSI classification: 1) the spectral band is usually redundant and noisy and 2) HSI with millions of pixels has become increasingly common in real-world applications. Motivated by the recent success of hybrid huberized support vector machines (HHSVMs), which inherit the benefits of both lasso and ridge regression, this paper first investigates the advantages of HHSVM for HSI applications. Unfortunately, the existing HHSVM solvers suffer from prohibitive computational costs on large-scale data sets. To solve this problem, this paper proposes simple and effective stochastic HHSVM algorithms for HSI classification. In the stochastic settings, we show that with a probability of at least $1-\varrho $ , our algorithms find an $\epsilon $ -accurate solution using $\tilde {O}({1}/{\lambda _{2}\epsilon })$ iterations. Since the convergence rate of our algorithms does not depend on the size of the training set, our algorithms are suitable for handling large-scale problems. We demonstrate the superiority of our algorithms by conducting experiments on large-scale binary and multiclass classification problems, comparing to the state-of-the-art HHSVM solvers. Finally, we apply our algorithms to real HSI classification and achieve promising results. [ABSTRACT FROM AUTHOR]

This paper deals with equivalent 2-D finite-element (FE) models of permanent magnet lead screw (PMLS), to accurately predict the thrust force. Due to the helical-shape permanent magnets (PMs), the magnetic fields of PMLS are typically 3-D and non-symmetric. However, the PMLS is approximately symmetric in some cases and an equivalent 2-D axis-symmetric FE model is developed instead of 3-D models. The problem lies in that no evaluation about the accuracy and applicability of the 2-D axis-symmetric FE model was offered in previous literature. In this paper, the 2-D axis-symmetric FE model is derived based on the concept of equivalent current sheets of PMs. The limitations of the existing 2-D axis-symmetric FE model are clarified, and a novel equivalent 2-D torque FE model is then proposed to predict thrust force with the gear ratio when the 2-D axis-symmetric FE model is not appropriate. It is shown that the choice of equivalent 2-D FE model depends on the lead angle of PMLS, 2-D axis-symmetric FE model is applicable in the range of (0°, 15°), and 2-D torque FE model is preferred in the range of (65°, 90°). [ABSTRACT FROM AUTHOR]

With the remarkable recent progress on learning deep generative models, it becomes increasingly interesting to develop models for controllable image synthesis from reconfigurable structured inputs. This paper focuses on a recently emerged task, layout-to-image, whose goal is to learn generative models for synthesizing photo-realistic images from a spatial layout (i.e., object bounding boxes configured in an image lattice) and its style codes (i.e., structural and appearance variations encoded by latent vectors). This paper first proposes an intuitive paradigm for the task, layout-to-mask-to-image, which learns to unfold object masks in a weakly-supervised way based on an input layout and object style codes. The layout-to-mask component deeply interacts with layers in the generator network to bridge the gap between an input layout and synthesized images. Then, this paper presents a method built on Generative Adversarial Networks (GANs) for the proposed layout-to-mask-to-image synthesis with layout and style control at both image and object levels. The controllability is realized by a proposed novel Instance-Sensitive and Layout-Aware Normalization (ISLA-Norm) scheme. A layout semi-supervised version of the proposed method is further developed without sacrificing performance. In experiments, the proposed method is tested in the COCO-Stuff dataset and the Visual Genome dataset with state-of-the-art performance obtained. [ABSTRACT FROM AUTHOR]

Fasteners are an important part of railway security. The application of computer vision and image processing on fastener detection has become a research hot spot. However, most of the researches have focused on the missing and damage detection of fasteners up to now. In this paper, a method based on image processing is proposed to locate the center of the hexagon nut in the railway fastener. The precise position of the hexagon nut can be used for the automatic replacement of the nut, which is of great significance for the automatic railway construction and maintenance. The locating method proposed in this paper can be divided into two steps. First, the improved Canny detector which combines surrounding suppression and iterative excitation is used to extract the contours of the fastener. Then, a multifeature hierarchical locating (MHL) algorithm is proposed, which integrates the circle contour of the gasket and the hexagon features of the nut. The experimental results show that the improved Canny detector suppresses noises effectively and highlights the contours of fastener. The MHL algorithm in the next step improves the locating accuracy remarkably while guaranteeing the robustness meantime. [ABSTRACT FROM AUTHOR]

The objective of this paper is to advance the state of the art of aggressive space mapping (ASM) by demonstrating how, for resonant structures, and microwave filters in particular, an ASM-based optimization procedure may converge to the desired target performance in just one step. This behavior is first justified in physical terms, using the electromagnetic cavity perturbation theory, and is then investigated numerically. Several practical filter design demonstrations are also presented. This paper is concluded with a conceptual definition of Space Alignment in the context of ASM. [ABSTRACT FROM AUTHOR]

In this paper, a real-time railway fastener detection system using a high-speed laser range finder camera is presented. First, an extensive analysis of various methods based on pixel-wise and histogram similarities are conducted on a specific railway route. Then, a fusing stage is introduced which combines least correlated approaches also considering the performance upgrade after fusing. Then, the resulting method is tested on a larger database collected from a different railway route. After observing repeated successes, the method is implemented on NI LabVIEW and run real-time with a high-speed 3-D camera placed under a railway carriage designed for railway quality inspection. [ABSTRACT FROM PUBLISHER]

This paper is an investigation in the performance of two types of magnetic screws (MSs). The first is the magnet to magnet and consists of permanent magnet (PM) nut and PM screw and the second is a magnet to reluctance and consists of PM nut and a double-start reluctance screw. It is argued that for cost sensitive and long stoke applications, a magnet-to-reluctance MS may be the preferred option. It is also shown that capacitor discharge magnetization techniques can be employed for imprinting helical magnetization distributions on cylindrical PMs, significantly reducing the complexity and facilitating the practical realization of MS systems. [ABSTRACT FROM AUTHOR]

This paper reports on mechanical design, optimization, and experimental testing of a novel piezo-actuated elliptical vibration-assisted cutting (EVC) system constructed by flexure hinges. The stroke and natural frequency were analyzed based on the theoretical modeling. An enhanced central composite design was chosen as the design of experiments methodology to reduce the modeling error, and a nondominated sorted genetic algorithm-II (NSGA-II) was adopted for structure optimization. The optimized EVC generator was manufactured and experimentally tested to investigate practical properties of the proposed EVC system. It shows that the stroke of input end can reach to 30 μ m with a motion resolution of 10 nm, and the first natural frequency can reach to 2600 Hz without considering the manufacturing error. Besides, a relatively small cross-axis coupling ratio (within 0.21%) can be effectively obtained. The developed EVC system is advantageous not only to being equipped with machine tools with various configurations, but also to easily achieving arbitrary vibrations in three-dimensional space through two actuators, which is especially important for the generation of complex structured surfaces. With this paper, it is of great significance to promote industrial application of EVC techniques. [ABSTRACT FROM AUTHOR]

This paper presents a new type electromagnetic lead screw (EMLS) intended for wave energy application. Similar to the mechanical lead screw, this electromagnetic version can transfer slow linear motion to high-rotational motion, offering gearing effects. Compared with the existing pure magnetic lead screw (MLS) employing permanent magnets only, the new EMLS proposed uses dc current to provide the required helical-shape magnetic field, offering a much simpler, robust structure compared with the MLS. The working principle and the performances of this EMLS are analyzed in this paper. Comparison with PM-type lead screw is given. In addition to this, the theoretical analysis to support the use of a 2-D finite element model to analyze the 3-D magnetic-type lead screw is given, which has not been well covered in the existing literature. [ABSTRACT FROM AUTHOR]

This paper proposes a mechatronic suspension system with capabilities of energy regeneration and semi-active control [i.e., skyhook (SK)], incorporated into the mechanism. The system overcomes the trade-off between energy consumption and ride handling/comfort in a semi-active/active suspension system. Central to the concept is the development of a switched-mode rectifier (SMR) capable of providing either a positive or negative damping ratio by controlling the electric current to alternate between regenerative and motoring modes. Using the implemented circuit, a regenerative SK control strategy is utilized to provide a continuous variable damping force that significantly improves the vibration isolation. Simulation results are presented to demonstrate power flow in both regenerating and motoring modes by utilizing a current controller. Furthermore, experimental results are presented highlighting performance of the regenerative suspension prototype in terms of power regeneration, sprung mass absolute acceleration, and relative displacement. In addition, both theoretical and experimental power conversion efficiencies in various segments of the mechatronic suspension are analyzed and reported. [ABSTRACT FROM PUBLISHER]

A novel substrateless power amplifier module realized by ridge gap waveguide (RGW) technology is proposed in Ka-band. Up to our knowledge, this is the first time that an active device is directly integrated with an RGW structure. No substrate is used in the RF section of the implemented power amplifier and the whole structure is made by machining a piece of metal. The amplifier was made of two pieces and was easily assembled without needing a precise contact between the two sections. The cavity resonance of the amplifier is suppressed using a pining structure. The fabricated amplifier module is self-packaged and does not need any packaging. It is shown that the simulated and measured results are in good agreement. This paper shows the capability of RGW technology for implementing the whole RF frontend in microwave- and millimeter-wave systems. [ABSTRACT FROM PUBLISHER]

This paper proposes a weighted large margin nearest center (WLMNC) distance-based human depth recovery method for tele-immersive video interaction systems with limited bandwidth consumption. In the remote stage, the proposed method highly compresses the depth data of the remote human into skeletal block structures by learning the WLMNC distance, which is equivalent to downsampling the human depth map at $64{\times}$ the sampling rate. In the local stage, the method first recovers a rough human depth map based on a WLMNC distance augmented clustering approach and then obtains a fine depth map based on a rough depth-guided autoregressive model to preserve the depth discontinuities and suppress texture copy artifacts. The proposed WLMNC distance is learned by the large margin clustering problem with a weighted hinge loss to balance the clustering accuracy and depth recovery accuracy and is verified to be able to preserve depth discontinuities between skeletal block structures with occlusion. A theoretical analysis is conducted to verify the effectiveness of using the weighted hinge loss. Furthermore, a novel data set containing various types of human postures with self-occlusion is built to benchmark the human depth recovery methods. The quantitative comparison with the state-of-the-art depth recovery methods on the introduced benchmark data set demonstrates the effectiveness of the proposed method for human depth recovery with such a high upsampling rate. [ABSTRACT FROM AUTHOR]

Controlled force–torque exertion by a small-scaled free-flying space robot will be potentially required for future on-orbit assembly missions. This paper presents a hybrid controller to achieve the desired end-effector motion and contact forces required for driving a screw into a floating target. Attitude of the spacecraft base is controlled simultaneously. Postcapture control to stabilize the entire system is also addressed in this paper. Simulation results have demonstrated the effectiveness of the proposed control laws. [ABSTRACT FROM AUTHOR]

The objective of this paper is to use electromagnetic-based computer-aided design (CAD) tools to investigate the maximum tuning range of channel filters, typically used in satellite payloads. Both circular and rectangular waveguide technologies are investigated. The results of the investigation show that single-mode rectangular waveguide implementations offer substantially wider tuning range, as opposed to classical dual-mode circular waveguide implementations. In addition to simulations, measurements are also presented indicating very good agreement with theory, thereby fully validating the CAD procedure. [ABSTRACT FROM PUBLISHER]

The electro-mechanical brake booster (EMBB) is a kind of mechatronic actuator, which is developed to suit the brake assist requirement of electric vehicles. In this paper, we report on the design of an EMBB system consisting of a dc motor, a two-state reduction of a gear and ball screw, a servo body, and a reaction disk. Considering the inconvenience of installation and high price of the pedal force sensor, we translate the control problem of brake power assist control to position tracking control. Meanwhile, a nonlinear control method for position tracking is presented to solve the problem of power assist braking, which is formalized as three parts: the steady-state control, feed-forward control based on reference dynamics, and state-dependent feedback control. The benefit of the nonlinear control method is that it offers a concise control law and performs well in engineering implementations. In addition, a second-order filter was designed to do the signal processing and obtain a higher-order derivative. Finally, the bench tests based on rapid control prototyping environment were designed and implemented to verify the performance of the controller. Test results show that both the position tracking performance and response time of the EMBB system performed well. [ABSTRACT FROM AUTHOR]

The performance of distance-based classifiers heavily depends on the underlying distance metric, so it is valuable to learn a suitable metric from the data. To address the problem of multimodality, it is desirable to learn local metrics. In this short paper, we define a new intuitive distance with local metrics and influential regions, and subsequently propose a novel local metric learning algorithm called LMLIR for distance-based classification. Our key intuition is to partition the metric space into influential regions and a background region, and then regulate the effectiveness of each local metric to be within the related influential regions. We learn multiple local metrics and influential regions to reduce the empirical hinge loss, and regularize the parameters on the basis of a resultant learning bound. Encouraging experimental results are obtained from various public and popular data sets. [ABSTRACT FROM AUTHOR]

Piezo-driven precision positioning platforms with large stroke are greatly demanded in both scientific research and industrial applications. Although various principles have been proposed to design piezo-driven positioning platforms, the problem of backward motion commonly exists, greatly hindering their applications. To suppress the backward motion, in this paper, an idea by generating a forward frictional force to balance the reversed frictional force was proposed. Correspondingly, a specific arc-shape flexure hinge was designed to generate the forward frictional force via its elastic recovery. To verify the feasibility of the proposed idea, a positioning platform with alterable initial gap between contact surfaces is designed by the parasitic motion principle (PMP). By measuring the output displacement under various initial gaps, a critical initial gap was identified, at which the positioning platform could output stepping displacement without backward motion. Under this critical initial gap, effects of driving voltage and frequency on the backward motion are further investigated. In addition, the natural frequency and loading capacity of the positioning platform are tested. This paper confirms that using PMP, it is feasible to design piezo-driven positioning platforms with completely suppressed backward motion, which would enhance the applications of the PMP and PMP positioning platforms. [ABSTRACT FROM AUTHOR]

Homodyne laser vibrometer plays an essential role in the precision vibration measurement, but its application is restricted when measuring subfringe vibration and targets with various reflectivities. In order to achieve the nanoscale vibration measurement and to adapt to various reflectivities, an enhanced homodyne laser vibrometer is presented in this paper. First, an active vibration mechanism (AVM) based on a flexure hinge stimulated by a piezoelectric transducer (PZT) is introduced into the reference arm, with which the parameters for nonlinear error correction can be predetermined, and thereby the measurement of vibration less than quarter wavelength is feasible. Second, an automatic gain module is employed to optimize the intensity of the interference signals, which significantly improves the adaptability to target reflectivity. The experimental results show that the laser vibrometer proposed is capable of measuring vibration with amplitude down to 2 nm and vibration with surface reflectivity down to 0.08%. [ABSTRACT FROM AUTHOR]

This paper addresses two fundamental problems: 1) learning discriminative model parameters and 2) avoiding over-fitting, which often occurs in regression-based classification tasks. We formulate these two problems in terms of relaxing both the strict binary label matrix and graph regularization term into more flexible forms so that the margins between different classes are enlarged as much as possible and the problem of over-fitting is avoided to some extent. This task is accomplished by the proposed double relaxed regression (DRR) method. The convex problem of DRR is solved efficiently with an iterative procedure. Extensive experiments on synthetic and real world image data sets demonstrate the effectiveness of the proposed method in terms of both classification accuracy and running time. [ABSTRACT FROM AUTHOR]

Support vector machines (SVM) have drawn wide attention for the last two decades due to its extensive applications, so a vast body of work has developed optimization algorithms to solve SVM with various soft-margin losses. To distinguish all, in this paper, we aim at solving an ideal soft-margin loss SVM: $L_{0/1}$ L 0 / 1 soft-margin loss SVM (dubbed as $L_{0/1}$ L 0 / 1 -SVM). Many of the existing (non)convex soft-margin losses can be viewed as one of the surrogates of the $L_{0/1}$ L 0 / 1 soft-margin loss. Despite its discrete nature, we manage to establish the optimality theory for the $L_{0/1}$ L 0 / 1 -SVM including the existence of the optimal solutions, the relationship between them and P-stationary points. These not only enable us to deliver a rigorous definition of $L_{0/1}$ L 0 / 1 support vectors but also allow us to define a working set. Integrating such a working set, a fast alternating direction method of multipliers is then proposed with its limit point being a locally optimal solution to the $L_{0/1}$ L 0 / 1 -SVM. Finally, numerical experiments demonstrate that our proposed method outperforms some leading classification solvers from SVM communities, in terms of faster computational speed and a fewer number of support vectors. The bigger the data size is, the more evident its advantage appears. [ABSTRACT FROM AUTHOR]

Kernel-based methods for support vector machines (SVM) have shown highly advantageous performance in various applications. However, they may incur prohibitive computational costs for large-scale sample datasets. Therefore, data reduction (reducing the number of support vectors) appears to be necessary, which gives rise to the topic of the sparse SVM. Motivated by this problem, the sparsity constrained kernel SVM optimization has been considered in this paper in order to control the number of support vectors. Based on the established optimality conditions associated with the stationary equations, a Newton-type method is developed to handle the sparsity constrained optimization. This method is found to enjoy the one-step convergence property if the starting point is chosen to be close to a local region of a stationary point, thereby leading to a super-high computational speed. Numerical comparisons with several powerful solvers demonstrate that the proposed method performs exceptionally well, particularly for large-scale datasets in terms of a much lower number of support vectors and shorter computational time. [ABSTRACT FROM AUTHOR]

This paper presents a miniature 50 mm3 inertial measurement unit (IMU) implemented using a folded microelectromechanical systems (MEMS) process. The approach is based on wafer-level fabrication of high aspect-ratio single-axis sensors interconnected by flexible hinges and folded into a 3-D configuration, like a silicon Origami [1]. Two different materials for flexible hinges have been explored, including photo-definable polyimide and parylene-C. We report, for the first time, an IMU prototype with seven operational sensors: three accelerometers, three gyroscopes, and a prototype of a reference clock. This paper concludes with the results of experimental characterization of inertial sensors demonstrating the feasibility of the proposed approach for a compact IMU. [2016-0267] [ABSTRACT FROM AUTHOR]

The virtual track train (VTT) is a new type of urban transit system with all-wheel active steering technology utilized to make the long combination vehicle run along the planned route (virtual track) like railway vehicles along physical track. This paper proposed a scalable cascade modular path following control strategy for the newly designed gantry virtual track train (G-VTT) based on preview & tracking controller, focusing on the lateral control for low-speed turning manoeuvre. The mathematical characteristics of the 2-norm was utilized to establish a local tracking objective function (LTOF) to find the optimal lateral acceleration (OLA) of the tracking point in the preview window and calculate the optimal wheel steering angle (WSA) to achieve the optimal local trajectory. Considering the lag time Td, the yaw stability and path following ability of the vehicle are contradictory in some cases, so the damping adjustment factor λ was proposed to optimize the damping characteristics and the time-delay stability factor ξ was proposed to evaluate the time-delay stability. The influence of the key parameters, preview time Tp, Td, ξ and λ, on the stability and following ability were analyzed by frequency domain analysis method, and the optimal region of ξ and λ was obtained to instruct the configuration of λ and Tp. Finally, steady-state and dynamic forward predictive models were proposed to compensate for the oscillation caused by the lag time. The effectiveness of the proposed control strategy, forward predictive models and the configuration method of λ and Tp were verified by theoretical analysis and numerical simulation. [ABSTRACT FROM AUTHOR]

In this paper, we propose a general framework termed centroid estimation with guaranteed efficiency (CEGE) for weakly supervised learning (WSL) with incomplete, inexact, and inaccurate supervision. The core of our framework is to devise an unbiased and statistically efficient risk estimator that is applicable to various weak supervision. Specifically, by decomposing the loss function (e.g., the squared loss and hinge loss) into a label-independent term and a label-dependent term, we discover that only the latter is influenced by the weak supervision and is related to the centroid of the entire dataset. Therefore, by constructing two auxiliary pseudo-labeled datasets with synthesized labels, we derive unbiased estimates of centroid based on the two auxiliary datasets, respectively. These two estimates are further linearly combined with a properly decided coefficient which makes the final combined estimate not only unbiased but also statistically efficient. This is better than some existing methods that only care about the unbiasedness of estimation but ignore the statistical efficiency. The good statistical efficiency of the derived estimator is guaranteed as we theoretically prove that it acquires the minimum variance when estimating the centroid. As a result, intensive experimental results on a large number of benchmark datasets demonstrate that our CEGE generally obtains better performance than the existing approaches related to typical WSL problems including semi-supervised learning, positive-unlabeled learning, multiple instance learning, and label noise learning. [ABSTRACT FROM AUTHOR]

This paper introduces the concept of the trans-rotary magnetic gear (TROMAG). The TROMAG is a magnetic device consisting of a rotor and a translator with an air gap in between, capable of converting linear motion to rotation, and vice versa, and doing the gearing action at the same time. Although its structure suggests that the TROMAG is simply the magnetic dual to the mechanical lead-screw, the authors show that the concept could also be derived from the elementary magnet arrays. The paper tries to establish an analogy between the TROMAG and the ordinary electrical machines with respect to the number of poles and the stack length, thus providing a deeper insight into the device operation. Three-dimensional (3-D) finite element analysis (FEA) is deployed to obtain the torque and force characteristics. Furthermore, it is shown that in addition to the permanent magnet (PM) TROMAG, developing the reluctance and the induction TROMAG is possible as well, but at a lower force density. [ABSTRACT FROM AUTHOR]

The most important components of the internal nut thread inspection process are measuring the pitch and pitch diameter value and comparing these with their respective specifications, as a test nut is considered to be abnormal when its pitch or pitch diameter does not meet specifications. This paper focuses on defects arising when the pitch diameter does not meet its specification. Because conventional contact strategies are not suited to the real-time inspection of internal thread defects, there have been a number of recent attempts to develop noncontact methods for real-time measurement. Some approaches have applied laser triangulation techniques in which reflected light is used to measure the z-axis depth on an object’s surface. Although point lasers have been shown to be highly precise in measuring pitch diameter, the optical architecture involved in these approaches is complicated and, as the laser must be scanned in a pointwise manner to derive cross-sectional measurements, the measurement process is too long to be compatible with real-time defect inspection. In this papere, an image-based method employing a line laser projector was used to develop a real-time image-based nut pitch diameter defect inspection system. The proposed method, which improves upon the conventional, widely used template-matching method for rapid defect detection, was shown to be effective through experimental validation. [ABSTRACT FROM AUTHOR]

This paper introduces a new type of reluctance-based magnetic lead screw (RBMLS) that is attractive for many potential applications. The proposed topology presents the implementation of discretized permanent magnets (PMs) and ferromagnetic semi-rings. The proposed RBMLS has PMs in only one of its movable parts, making it suitable for long-stroke applications. The proposed RBMLS is analyzed through the 2-D and 3-D finite-element method in order to test its topology and obtain the force produced per PM volume. Detailed design features are presented for the realization of a prototype. [ABSTRACT FROM AUTHOR]

This paper reports on a unique tactile microprobe based on a parallelogram kinematic made from monocrystalline silicon. This kinematic, made out of an orthogonal cascade assembly of three identical parallelograms, provides an isotropic behavior to the microprobe. Each parallelogram deflects in only one direction thanks to thin elastic silicon membrane hinges and their displacements are recognized using piezoresistors integrated into these hinges. Wide deflection ranges, isotropic behavior, and low mechanical stiffness of the new microprobe, as predicted by simulations, could be verified in experiments. The fabrication, the assembly, and the contacting of the first microprobe prototype was optimized to allow very compact integration into a Ø11 mm housing. This make it suitable for metrology research laboratories and industries equipped with conventional coordinate measurement machines and even for a variety of other 3-D force/displacement measurements. [2018-0157] [ABSTRACT FROM AUTHOR]

The estimation of the frictional and clamping forces is one of the key issues in the design and implementation of the electromechanical brake (EMB) system. In this paper, a clamping-force control algorithm is presented along with a consideration of the frictional characteristics and the estimation of the clamping force for a planetary reduction gear-type EMB. The frictional model is developed by including the frictional effect of the motor, the planetary gear, and the screw thread. Since the clamping-force estimation requires the distance of the contact gap between the pad and the disk, an initial gap-distance control algorithm that uses the gradient change of the motor torque is proposed. This paper is concluded with a discussion of the performance of the control algorithm by comparing the simulation results with the experimental results. [ABSTRACT FROM PUBLISHER]

In many real-world applications, different types of misclassification usually suffer from different costs, but the accurate cost is often hard to be determined and usually one can only get an interval-estimation like that one type of mistake is about 5 to 10 times more serious than the other type. On the other hand, there are usually abundant unlabeled data available, leading to great research effort about semi-supervised learning. It is noticeable that cost interval and unlabeled data usually appear simultaneously in practice tasks; however, there is rare study tackling them together. In this paper, we propose the cisLDM approach which is able to handle cost interval and exploit unlabeled data in a principled way. Rather than maximizing the minimum margin like traditional large margin classifiers, cisLDM tries to optimize the margin distribution on both labeled and unlabeled data when minimizing the worst-case total-cost and the mean total-cost simultaneously according to the cost interval. Experiments on a broad range of datasets and cost settings exhibit the impressive performance of cisLDM. In particular, cisLDM is able to reduce 47 percent more total-cost than standard SVM and 27 percent more total-cost than cost-sensitive semi-supervised SVM which assumes the true cost value is known in advance. [ABSTRACT FROM PUBLISHER]

Simulation of flaw detection by eddy-current testing requires the calculation of the eddy-current signal due to the presence of the flaw. In this paper, the surface integral method (SIM) is applied for the calculation of the crack signal in the workpieces composed of a conducting plate with a borehole. The adopted approach makes use of Green’s operator that takes into account the effect of the borehole, and thus, the integral formalism is restricted to the crack surface only. The truncated region eigenfunction expansion method is followed for the construction of Green’s operator. Comparisons of the computed crack signal with numerical simulations carried out using a hybrid volume integral method-SIM approach and experimental results show excellent agreement. [ABSTRACT FROM AUTHOR]

In this paper, innovative ocean wave power takeoff (PTO) system is presented to enhance the electrical energy generation from oscillating wave motions. This PTO system, mainly consisting of dual-ball screws, a gearbox with mechanical motion rectification and a permanent magnet synchronous generator (PMSG), can convert bidirectional irregular motions from a floating wave buoy into unidirectional steady generator rotations. Systematical operating principles, design, and prototyping details of the PTO system are presented and analyzed. A hydrodynamic–mechanical–electrical model of the system is established by reasonably representing power switches attached to the PMSG as an equivalent external resistance. The overall dynamics of the system are then analyzed in the frequency domain. Three power control strategies are proposed to maximize the wave power absorption by changing the equivalent external resistance. The effectiveness and relatively high-energy conversion efficiency of the PTO system have been demonstrated based on lab bench test results. The levelized cost of energy of a full-scale wave energy converter system is also calculated based on the proposed PTO system. [ABSTRACT FROM AUTHOR]

HL-2M, the satellite tokamak of ITER (International Thermonuclear Experimental Reactor), has successfully completed the first plasma experiment in December 2020 in Southwestern Institute of Physics, China National Nuclear Corporation (CNNC-SWIP). The 500 W/4.5 K helium cryogenic system used in HL-2M is mainly used to cool down the cryopumps and superconducting magnets. The refrigeration system is the heart components of the cryogenic system. The design and development of the refrigeration system witness our significant cooperation with Fullcryo Company. The refrigeration system has completed the factory commissioning and on-site installation at the end of 2019. This paper presents the performance characteristics of the main key equipment in the system. [ABSTRACT FROM AUTHOR]

Relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents for document networks, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference (RegBayes) with a regularization parameter to deal with the imbalanced link structure issue in real networks and improve the discriminative ability of learned latent representations; and 3) instead of doing variational approximation with strict mean-field assumptions, we present collapsed Gibbs sampling algorithms for the generalized relational topic models by exploring data augmentation without making restricting assumptions. Under the generic RegBayes framework, we carefully investigate two popular discriminative loss functions, namely, the logistic log-loss and the max-margin hinge loss. Experimental results on several real network datasets demonstrate the significance of these extensions on improving prediction performance. [ABSTRACT FROM AUTHOR]

This paper investigates mechanical and magnetic losses in a magnetic lead screw (MLS). The MLS converts a low-speed high-force linear motion of a translator into a high-speed low-torque rotational motion of a rotor through helically shaped magnets. Initial tests performed with a novel 17-kN demonstrator and a simplified motor model showed an efficiency of only 80% at low load; however, it was expected that the efficiency should be above 95%. For understanding and future optimization, a detailed study of the loss in the MLS is presented with the aim of identifying and segregating various loss components that was not accounted for in previous results. This is done through theoretical loss calculations and various experiments. It is concluded that the linear guide is the dominating loss component in the MLS demonstrator, whereas the losses in the axial thrust bearing is not as dominant as expected; furthermore, an efficiency above 94% was measured. [ABSTRACT FROM PUBLISHER]

Force-controllable actuators are essential for guaranteeing safety in human–robot interactions. Magnetic lead screws (MLSs) transfer force without requiring contact between parts. These devices can drive the parts with high efficiency and no frictional contact, and they are force limited when overloaded. We have developed a novel MLS that does not include spiral permanent magnets and an MLS-driven linear actuator (MLSDLA) that uses this device. This simple structure reduces the overall size of the device and improves productivity because it is constructed by a commonly used machined screw as a screw. The actuator can drive back against an external force and it moves flexibly based on the magnetic spring effect. In this paper, we propose a force estimation method for the MLSDLA that does not require separate sensors. The magnetic phase difference, as measured from the angular and linear displacements of the actuator, is used for this calculation. The estimated force is then compared against measurements recorded with a load sensor in order to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

We demonstrate a micro-electro-mechanical systems (MEMS) beam scanner capable of biaxial scanning with simultaneous focus control, for integration into a handheld confocal microscope for skin imaging. The device is based on a dual-axis gimbal structure with an integrated large-stroke deformable mirror. SU-8 polymer is used to construct both the deformable membrane as well as the torsional hinges for biaxial scanning. The 4-mm-diameter mirror can perform raster pattern scanning with a range of +/−1.5° and Lissajous scanning with a range of +/−3° (mechanical scan angle), and has a maximum deflection of $9~\mu \text{m}$ for focus control. The design, fabrication, and characterization of the opto-mechanical performance of the MEMS device are presented in this paper. [2018-0074] [ABSTRACT FROM AUTHOR]

Piezoelectric-actuator-driven nanopositioning stages, with large stroke and low crosstalk, are quite appealing for fulfilling the through-silicon via lithography etching task. The motivation of this paper is to combine the ability to enable the nanopositioning stage running in a manner of millimeter scale workspace and nanometer scale positioning accuracy. Two pairs of flexure-guided kinematic modules with high displacement amplification ratio are adopted to construct a 4-PP (P is prismatic) XY nanopositioning stage. A new decoupling design is implemented to realize the decoupling behavior between the input actuators and output compliant limbs, respectively. Kinematics modeling including output compliance, input stiffness, displacement amplification ratio modeling, and workspace determination are carried out. After a series of mechanism dimension optimizations via particle swarm optimization algorithm, the performance of the optimized mechanism is analyzed and assessed by using the ANSYS workbench. Then, a repetitive-compensated PID controller and a single-input and single-output closed-loop control strategy are designed. Finally, a series of experimental tests in terms of crosstalk test, frequency characteristic analysis, damping property analysis, dynamic hysteresis nonlinearity characterization, signal trajectory tracking, workspace determination, and Bode diagram plotting are carried out in details. It indicates that the workspace of fabricated prototype has reached to 1.035 mm $\times$ 1.035 mm, the crosstalk ratio is kept within 0.5%, and the closed-loop positioning accuracy is determined as 400 nm. [ABSTRACT FROM PUBLISHER]

Recent smartphones increasingly employ a metal frame for a sophisticated design. However, the metal frame becomes a good coupling path for electromagnetic (EM) noise within smartphones and increases noise coupling to radio-frequency antennas located at the top and bottom sides of the smartphones. This paper proposes two novel metal frame structures with ferrite absorbing sheets or electromagnetic band gap patterns to reduce the coupling of EM noise to the antenna. Using a fabricated test board, the effects of the proposed metal frames on noise coupling suppression are experimentally validated. [ABSTRACT FROM PUBLISHER]

Using a configuration-space approach, the paper develops a 2nd-order mobility theory for rigid bodies in contact. A major component of this theory is a coordinate invariant 2nd-order mobility index for a body, B, in frictionless contact with finger bodies A/sub 1/,...A/sub k/. The index is an integer that captures the inherent mobility of B in an equilibrium grasp due to second order, or surface curvature, effects. It differentiates between grasps which are deemed equivalent by classical 1st-order theories, but are physically different. We further show that 2nd-order effects can be used to lower the effective mobility of a grasped object, and discuss implications of this result for achieving new lower bounds on the number of contacting finger bodies needed to immobilize an object. Physical interpretation and stability analysis of 2nd-order effects are taken up in the companion paper. [ABSTRACT FROM PUBLISHER]

The detection of fastener defects is an important task in railway inspection systems, and it is frequently performed to ensure the safety of train traffic. Traditional inspection is usually operated by trained workers who walk along railway lines to search for potential risks. However, the manual inspection is very slow, costly, and dangerous. This paper proposes an automatic visual inspection system for detecting partially worn and completely missing fasteners using probabilistic topic model. Specifically, our method is able to simultaneously model diverse types of fasteners with different orientations and illumination conditions using unlabeled data. To assess the damages, the test fasteners are compared with the trained models and automatically ranked into three levels based on the likelihood probability. The experimental results demonstrate the effectiveness of this method. [ABSTRACT FROM PUBLISHER]

In order to characterize the mechanical behavior of fragile resonant microelectromechanical systems (MEMS)/nanoelectromechanical systems (NEMS), nondestructive measurements are required. In this paper, a cartography of local stiffness variations on a suspended micromembrane is established for the first time, by a tuning-fork-based dynamic force sensor inside a scanning electron microscope (SEM). Experiments are conducted individually on a batch of InP membranes 200  nm thin, using a 9-degree-of-freedom (dof) nanomanipulation system, complemented with virtual reality and automation tools. Results provide stiffness values in the range of a few newton per meter, with variations in a single sample depending on the membrane models. [ABSTRACT FROM PUBLISHER]

Traditional hinge loss function-based large-scale support vector machine (SVM) algorithms tend to perform poorly in the presence of noise, especially when the model is trained incrementally. In this paper, we propose an efficient stochastic quasi-Newton method-based twin parametric SVM using the pinball loss function (termed as SQN-PTWSVM), which is efficient and more robust to the presence of noise when compared to conventional hinge loss SVM for large-scale data scenarios. To establish the theoretical convergence of the method, a modified version of SQN-PTWSVM, termed as SQN-SPTWSVM, has also been proposed. It overcomes the poor convergence issue faced by stochastic gradient twin SVM thus resulting in a faster and reliable model. In SQN-SPTWSVM, the hyperplanes obtained are stable enough to handle noise and resampling issues that occur frequently in stochastic learning scenarios, leading to better generalization ability of the classifier. The proposed method has been extended to nonlinear scenarios as well. Moreover, batch versions of the proposed algorithms have also been introduced which significantly reduce the training time and memory requirement of SQN-PTWSVM and SQN-SPTWSVM. The experimental results on several benchmark datasets and activity recognition applications have shown that the performance of our method is better than the existing classifiers in terms of speed and accuracy. [ABSTRACT FROM AUTHOR]

This paper proposes a two-element multi-input multi-output (MIMO) open-slot antenna implemented on the display ground plane of a laptop computer for eight-band long-term evolution/wireless wide-area network operations. The metal surroundings of the antennas have been well integrated as a part of the radiation structure. In the single-element open-slot antenna, the nearby hinge slot (which is bounded by two ground planes and two hinges) is relatively large as compared with the open slot itself and acts as a good radiator. In the MIMO antenna consisting of two open-slot elements, a T slot is embedded in the display ground plane and is connected to the hinge slot. The T and hinge slots when connected behave as a radiator; whereas, the T slot itself functions as an isolation element. With the isolation element, simulated isolations between the two elements of the MIMO antenna are raised from 8.3–11.2 to 15–17.1 dB in 698–960 MHz and from 12.1–21 to 15.9–26.7 dB in 1710–2690 MHz. Measured isolations with the isolation element in the desired low- and high-frequency ranges are 17.6–18.8 and 15.2–23.5 dB, respectively. Measured and simulated efficiencies for the two-element MIMO antenna with either element excited are both larger than 50% in the desired operating frequency bands. [ABSTRACT FROM AUTHOR]