Modern vehicles rely on a multitude of sensors and cameras to both understand the environment around them and assist the driver in different situations. Lane detection is an overall process as it can be used in safety systems such as the lane departure warning system (LDWS). Lane detection may be used in steering assist systems, especially useful at night in the absence of light sources. Although developing such a system can be done simply by using global positioning system (GPS) maps, it is dependent on an internet connection or GPS signal, elements that may be absent in some locations. Because of this, such systems should also rely on computer vision algorithms. In this paper, we improve upon an existing lane detection method, by changing two distinct features, which in turn leads to better optimization and false lane marker rejection. We propose using a probabilistic Hough transform, instead of a regular one, as well as using a parallelogram region of interest (ROI), instead of a trapezoidal one. By using these two methods we obtain an increase in overall runtime of approximately 30%, as well as an increase in accuracy of up to 3%, compared to the original method. Full article

The grinding wheel topography influences the cutting performance and thus the economic efficiency of a grinding process. In contrary to conventional grinding wheels, super abrasive grinding wheels should undergo an additional sharpening process after the initial profiling process to obtain a suitable microstructure of the grinding wheel. Due to the lack of scientific knowledge, the sharpening process is mostly performed manually in industrial practice. A CNC-controlled sharpening process can not only improve the reproducibility of grinding processes but also decrease the secondary processing time and thereby increase the economic efficiency significantly. To optimize the sharpening process, experimental investigations were carried out to identify the significant sharpening parameters influencing the grinding wheel topography. The sharpening block width l_Sb, the grain size of the sharpening block d_kSb and the area-related material removal in sharpening V’’_Sb were identified as the most significant parameters. Additional experiments were performed to further quantify the influence of the significant sharpening parameters. Based on that, a process model was developed to predict the required sharpening parameters for certain target topographies. By using the process model, constant work results and improved process reliability can be obtained. Full article

There have been many reports of damage to wind turbine blades caused by lightning strikes in Japan. In some of these cases, the blades struck by lightning continue to rotate, causing more serious secondary damage. To prevent such accidents, it is a requirement that a lightning detection system is installed on the wind turbine in areas where winter lightning occurs in Japan. This immediately stops the wind turbine if the system detects a lightning strike. Normally, these wind turbines are restarted after confirming soundness of the blade through visual inspection. However, it is often difficult to confirm the soundness of the blade visually for reasons such as bad weather. This process prolongs the time taken to restart, and it is one of the causes that reduces the availability of the wind turbines. In this research, we constructed a damage detection model for wind turbine blades using machine learning based on SCADA system data and, thereby, considered whether the technology automatically confirms the soundness of wind turbine blades. Full article

This paper proposes a model-based two-degree-of-freedom (2DOF) speed control for a medium voltage (MV) variable speed drive (VSD) connected to a centrifugal compressor (CC) train. Torsional mode excitations in the drive shaft due to converter switching behaviour are considered. An effective description of the harmonics transfer is proposed. The tuning strategy aims to optimize the tracking behaviour of the step and ramp command, taking care of critical speed excitations. The stability of the closed-loop dynamics against time delay and drive parameter variations are studied by means of Nyquist diagrams and time-domain simulations. A descriptive method for the process damping behaviour is proposed. The control strategy is evaluated through simulations as well as an experimental setup, based on a hardware in the loop (HIL) in a master–slave configuration. Full article

A switched reluctance motor has a very simple structure which becomes its key signature and leads to various advantages. However, because of its double saliency and switching principle, the motor is also known to have a relatively high torque ripple, and this hinders its use as a high-performance drive. In this paper, a method to reduce torque ripple while maintaining average torque is introduced. Two elements are used to achieve this, namely, a non-uniform air-gap on the rotor-pole face and one hole in each non-uniform region, which maintains the saturation level of the air-gap. This approach preserves the mechanical simplicity of the motor and is easy to implement. Simulations and experiments were performed to verify the effectiveness of the proposed design. Full article

Underactuated robotic grippers have the advantage of lower cost, simpler control, and higher safety over the fully actuated grippers. In this study, an underactuated robotic finger is presented. The design issues that should be considered for stable grasping are discussed in detail. This robotic finger is applied to design a two-fingered underactuated gripper. Firstly, a new three-DOF linkage-driven robotic finger that combines a five-bar mechanism and a double parallelogram is presented. This special architecture allows us to put all of the required actuators into the palm. By adding a torsion spring and a mechanical stopper at a passive joint, this underactuated finger mechanism can be used to perform parallel grasping, shape-adaptive grasping, and environmental contact-based grasp. Secondly, the dynamic model of this robotic finger is developed to investigate how to select an appropriate torsion spring. The dynamic simulation is performed with a multi-body dynamic simulator to verify our proposed approach. Moreover, static grasp models of both two-point and three-point contact grasps are investigated. Finally, different types of grasping modes are verified experimentally with a two-fingered underactuated robotic gripper. Full article

From an aerodynamic point of view, the electric turbocharger for the air supply of an automotive fuel cell faces difficult requirements: it must not only control the pressure level of the fuel cell, but it also has to operate with very high efficiency over a wide range. This paper explores features for the compressor and the turbine of an existing electric turbocharger, which are intended to meet the specific requirements of a fuel cell in an experimentally validated numerical study. Adjustable diffuser or nozzle vanes in the compressor and turbine achieve wider operating ranges but compromise efficiency, especially because of the necessary gaps between vanes and end walls. For the turbine, there are additional efficiency losses since the pivoting of the nozzle vanes leads to incidence and thus to flow separation at the leading edge of the nozzle vanes and the rotor blades. An increase in the mass flow and a slight efficiency improvement of the turbine with the low solidity nozzle vanes counteracts these losses. For the compressor, a reduction in the diffuser height and its influence over the operating range and power consumption yields an increase in surge margin as well as in maximum efficiency. Full article

With commercial application of 5G networks, many researchers have started paying attention to real-time control in 5G networks. This paper focuses on dual auto guided vehicles collaborative transport scenarios and designs a formation control system in current commercial 5G networks. Firstly, the structure of the 5G network researched in this paper is introduced. Then the round-trip time of 5G networks is measured and analyzed. The result shows that although the 5G round-trip time has randomness, it is mainly concentrated in 19 ± 3 ms, and the jitter mainly in 0 ± 3 ms. The Kalman filter is applied to estimate the transmission delay and experiment result shows the effectiveness of the estimation. Furthermore, the total delay including transmission delay and execution delay in control system is discussed. After establishing the AGV kinematic and formation model, complete control system based on compensation method is proposed. Finally, an experiment is carried out. Compared to the result without formation control, maximum distance error is reduced by 82.61% on average, while maximum angle error 45.91% on average. The result shows the effectiveness of the control system in formation maintaining in 5G network. Full article

Recently, the number of vehicles equipped with the Lane Keeping Assistance System (LKAS) is increasing. Therefore, safety evaluation to validate the LKAS has become more important. However, the actual vehicle test for safety evaluation has disadvantages such as the need for professional manpower, the use of expensive equipment, and environmental constraints. Therefore, we attempted to solve this problem using the dual cameras system with only inexpensive and accessible cameras. The optimal position of the dual cameras, image and focal length correction, and lane detection methods proposed in previous studies were used, and a theoretical equation for calculating the distance from the front wheel of the vehicle to the driving lane was proposed. For the actual vehicle testing, LKAS safety evaluation scenarios proposed in previous studies were used. According to the test results, the maximum error was 0.17 m, which indicated the reliability of the method because all errors in the tested scenarios exhibited similar trends and values. Therefore, through the use of the proposed theoretical equations in conjunction with inexpensive cameras, it is possible to reduce time, cost, and environmental problems in the development, vehicle application, and safety evaluation of LKAS components. Full article

Precision machining (e.g., fine grinding, polishing) induced residual stress is very small and often not constant across the wafer and it is difficult to be directly obtained by stress testing equipment or Stoney equation. The residual stress could be obtained theoretically based on the principle of superposition in which the entire wafer deformation is taken as the sum of all deformations induced by the residual stresses of different positions on the wafer surface. However, the solved residual stress is affected greatly by deformation measurement errors and fluctuates greatly across the wafer surface. To solve the problem, a regularization method with continuity constraints was proposed in this study. The mechanisms for the discontinuity of the residual stress distribution and the sensitivity of calculation results to the measurement errors were studied. The influences of the number of subareas of the silicon wafer were investigated and the continuity constraint term was constructed based on the positional relationship of different subareas. Stable and continuous residual stress distribution was successfully obtained after using the proposed regularization method. The method may also be applied to estimate the residual stress from surface deformation for thin substrate plates of other materials. Full article

Nowadays, traffic congestion has become a significant challenge in urban areas and densely populated cities. Real-time traffic signal control is an effective method to reduce traffic jams. This paper proposes a particle swarm optimisation with linearly decreasing weight (LDW-PSO) to tackle the signal intersection control problem, where a finite-interval model and an objective function are built to minimise spoilage time. The performance was evaluated in real-time simulation imitating a crowded intersection in Dalian city (in China) via the SUMO traffic simulator. The simulation results showed that the LDW-PSO outperformed the classical algorithms in this research, where queue length can be reduced by up to 20.4% and average waiting time can be reduced by up to 17.9%. Full article

The conceptualization and framework of smart factories have been intensively studied in previous studies, and the extension to various business areas has been suggested as a future research direction. This paper proposes a method for extending the smart factory concept in the ship building phase to the ship servicing phase through actual examples. In order to expand the study, we identified the differences between manufacturing and maintenance. We proposed a smart transformation procedure, framework, and architecture of a smart maintenance factory. The transformation was a large-scale operation for the entire factory beyond simply applying a single process or specific technology. The transformations were presented through a vessel maintenance depot case and the effects of improvements were discussed. Full article

With its standardized and unified interface, the quick-change fixture is an important part for maintaining high efficiency without compensation of precision in the metal-turning process because it can conveniently realize high-precision repeated clamping and multi-station conversion without complex positioning and adjustment steps. However, the existing quick-change fixture products and related research cannot fully meet the needs of repeatability and applicability raised from ultra-precision, single-point diamond turning with ultra-high accuracy and ultra-small depth of cut. In this paper, we develop a quick-change fixture for ultra-precision diamond turning, in which the end-toothed disc acts as the positioning element. Specifically, the main parameters of two key components of the end-toothed disc and slotted disc spring are calculated analytically to ensure the positioning accuracy of the designed fixture used in the rotation condition, which is further ensured by controlling the machining tolerance of the tooth profile of the end-toothed disc. Additionally, finite element simulations are performed to investigate the static and modal states of the quick-change fixture, which demonstrate a maximum deformation of about 0.9 μm and a minimum natural frequency of 5655.9 Hz for the designed fixture. Two high-precision sensors are used to detect the radial jump and end run-out values after repeated clamping actions, which are employed to verify the repetitive positioning accuracy of the fixture. Subsequent finite-element simulation of the clamping of small-diameter copper bar, as well as the diamond turning experiment, jointly demonstrate that the designed fixture can achieve a precision of 1 μm. Current work provides an effective quick-change fixture to reduce the deformation of a weak-stiffness workpiece caused by clamping deformation in ultra-precision diamond cutting. Full article

The bearing temperature forecasting provide can provide early detection of the gearbox operating status of wind turbines. To achieve high precision and reliable performance in bearing temperature forecasting, a novel hybrid model is proposed in the paper, which is composed of three phases. Firstly, the variational mode decomposition (VMD) method is employed to decompose raw bearing temperature data into several sub-series with different frequencies. Then, the SAE-GMDH method is utilized as the predictor in the subseries. The stacked autoencoder (SAE) is for the low-latitude features of raw data, while the group method of data handling (GMDH) is applied for the sub-series forecasting. Finally, the imperialist competitive algorithm (ICA) optimizes the weights for subseries and combines them to achieve the final forecasting results. By analytical investigation and comparing the final prediction results in all experiments, it can be summarized that (1) the proposed model has achieved excellent prediction outcome by integrating optimization algorithms with predictors; (2) the experiment results proved that the proposed model outperformed other selective models, with higher accuracies in all datasets, including three state-of-the-art models. Full article

This paper addresses the problem of instance-level 6DoF pose estimation from a single RGBD image in an indoor scene. Many recent works have shown that a two-stage network, which first detects the keypoints and then regresses the keypoints for 6d pose estimation, achieves remarkable performance. However, the previous methods concern little about channel-wise attention and the keypoints are not selected by comprehensive use of RGBD information, which limits the performance of the network. To enhance RGB feature representation ability, a modular Split-Attention block that enables attention across feature-map groups is proposed. In addition, by combining the Oriented FAST and Rotated BRIEF (ORB) keypoints and the Farthest Point Sample (FPS) algorithm, a simple but effective keypoint selection method named ORB-FPS is presented to avoid the keypoints appear on the non-salient regions. The proposed algorithm is tested on the Linemod and the YCB-Video dataset, the experimental results demonstrate that our method outperforms the current approaches, achieves ADD(S) accuracy of 94.5% on the Linemod dataset and 91.4% on the YCB-Video dataset. Full article

Climate changes and the lack of running water across vast territories require the massive use of pumping systems, often powered by solar energy sources. In this context, simple drives with high-efficiency motors can be expected to take hold. It is important to emphasise that simplicity does not necessarily lie in the control algorithm itself, but in the absence of complex manual calibration. These characteristics are met by synchronous reluctance motors provided that the calibration of the current loops is made autonomous. The goal of the present research was the development of a current control algorithm for reluctance synchronous motors that does not require an explicit model of the motor, and that self-calibrates in the first moments of operation without the supervision of a human expert. The results, both simulated and experimental, confirm this ability. The proposed algorithm adapts itself to different motor types, without the need for any initial calibration. The proposed technique is fully within the paradigm of smarter electrical drives, which, similarly to today’s smartphones, offer advanced performance by making any technological complexity transparent to the user. Full article

The reinforcement learning control of an underground loader was investigated in a simulated environment by using a multi-agent deep neural network approach. At the start of each loading cycle, one agent selects the dig position from a depth camera image of a pile of fragmented rock. A second agent is responsible for continuous control of the vehicle, with the goal of filling the bucket at the selected loading point while avoiding collisions, getting stuck, or losing ground traction. This relies on motion and force sensors, as well as on a camera and lidar. Using a soft actor–critic algorithm, the agents learn policies for efficient bucket filling over many subsequent loading cycles, with a clear ability to adapt to the changing environment. The best results—on average, 75% of the max capacity—were obtained when including a penalty for energy usage in the reward. Full article

Three-phase induction motors (IMs) are the main workhorse in industry due to their many advantages as compared to other types of industrial motors. However, the efficiency and lifetime of IMs can be considerably affected by some operating conditions, in particular those related to unbalanced supply voltages (USV), which is quite a common condition in industrial plants. Therefore, early detection and a precise severity estimation of the USV for all working conditions can prevent major breakdowns and increase reliability and safety of industrial facilities. This paper proposes a reliable method allowing for a precise and online detection of the USV condition, by monitoring a pertinent indicator calculated using the voltage symmetrical components. The effectiveness of the proposed method is validated experimentally for several different working conditions, and a comparison with other indicators available in the literature is also performed. Full article

Real-time monitoring of the cutting force in the machining process is critical for improving machining accuracy, optimizing the machining process, and optimizing tool lifetime; however, the dynamometers are too expensive to be widely used by machine tool users. Therefore, this paper presents a simple and cheap apparatus—a smart tool holder—to measure the cutting force of turning tools in the finishing turning. The apparatus does not change the structure of the turning tool. It consists of a tool holder and a piezoresistive force sensor foil, and transmits the signal through Bluetooth wireless communication. Instead of dealing with the circuit hardware, this paper uses the Artificial Neural Network (ANN) model to successfully calibrate the warm-up shift problem of the piezoresistive force sensor. Such a software method is simple, and considerably cheaper than the hardware method. For the force measurement capability of the smart tool holder, the cross-interference between orthogonal forces are very small and thus can be ignored. The force reading of the smart tool holder possesses high repeatability for the same turning parameters and high accuracy within the experiment groups. The authors apply the smart tool holder to cut the low carbon steel S15C, and to determine its specific cutting force in fine turning. The resulting fine turning force model agrees very well with the measurement. Its mean absolute deviation is 3.87% and its standard deviation is 1.55%, which reveals that the accuracy and precision of the smart tool holder and the fine turning force model are both good. Full article

Stretchable, skin-interfaced, and wearable strain sensors have risen in recent years due to their wide-ranging potential applications in health-monitoring devices, human motion detection, and soft robots. High aspect ratio (AR) silver nanowires (AgNWs) have shown great potential in the flexible and stretchable strain sensors due to the high conductivity and flexibility of AgNW conductive networks. Hence, this work aims to fabricate highly stretchable, sensitive, and linear kirigami strain sensors with high AR AgNWs. The AgNW synthesis parameters and process windows have been identified by Taguchi’s design of experiment and analysis. Long AgNWs with a high AR of 1556 have been grown at optimized synthesis parameters using the one-pot modified polyol method. Kirigami sensors were fabricated via full encapsulation of AgNWs with Ecoflex silicon rubber. Kirigami-patterned strain sensors with long AgNWs show high stretchability, moderate sensitivity, excellent linearity (R² = 0.99) up to 70% strain and can promptly detect finger movement without obvious hysteresis. Full article

Thermal error is one of the main sources of machining error of machine tools. Being a key component of the machine tool, the spindle will generate a lot of heat in the machining process and thereby result in a thermal error of itself. Real-time measurement of thermal error will interrupt the machining process. Therefore, this paper presents a machine learning model to estimate the thermal error of the spindle from its feature temperature points. The authors adopt random forests and Gaussian process regression to model the thermal error of the spindle and Pearson correlation coefficients to select the feature temperature points. The result shows that random forests collocating with Pearson correlation coefficients is an efficient and accurate method for the thermal error modeling of the spindle. Its accuracy reaches to 90.49% based on only four feature temperature points—two points at the bearings and two points at the inner housing—and the spindle speed. If the accuracy requirement is not very onerous, one can select just the temperature points of the bearings, because the installation of temperature sensors at these positions is acceptable for the spindle or machine tool manufacture, while the other positions may interfere with the cooling pipeline of the spindle. Full article

Attitude estimation is a basic task for most spacecraft missions in aerospace engineering and many Kalman type attitude estimators have been applied to the guidance and navigation of spacecraft systems. By building the attitude dynamics on matrix Lie groups, the invariant Kalman filter (IKF) was developed according to the invariance properties of symmetry groups. However, the Gaussian noise assumption of Kalman theory may be violated when a spacecraft maneuvers severely and the process noise might be heavy-tailed, which is prone to degrade IKF’s performance for attitude estimation. To address the attitude estimation problem with heavy-tailed process noise, this paper proposes a hierarchical Gaussian state-space model for invariant Kalman filtering: The probability density function of state prediction is defined based on student’s t distribution, while the conjugate prior distributions of the scale matrix and degrees of freedom (dofs) parameter are respectively formulated as the inverse Wishart and Gamma distribution. For the constructed hierarchical Gaussian attitude estimation state-space model, the Lie groups rotation matrix of spacecraft attitude is inferred together with the scale matrix and dof parameter using the variational Bayesian iteration. Numerical simulation results illustrate that the proposed approach can significantly improve the filtering robustness of invariant Kalman filter for Lie groups spacecraft attitude estimation problems with heavy-tailed process uncertainty. Full article

Spiral bevel gears are known for their smooth operation and high load carrying capability; therefore, they are an important part of many transmission systems that are designed for high speed and high load applications. Due to high contact ratio and complex vibration signal, their fault detection is really challenging even in the case of serious defects. Therefore, spiral bevel gears have rarely been used as benchmarking for gears’ fault diagnosis. In this research study, Artificial Intelligence (AI) techniques have been used for fault detection and fault severity level identification of spiral bevel gears under different operating conditions. Although AI techniques have gained much success in this field, it is mostly assumed that the operating conditions under which the trained AI model is deployed for fault diagnosis are same compared to those under which the AI model was trained. If they differ, the performance of AI model may degrade significantly. In order to overcome this limitation, in this research study, an effort has been made to find few robust features that show minimal change due to changing operating conditions; however, they are fault discriminating. Artificial neural network (ANN) and K-nearest neighbors (KNN) are used as classifiers and both models are trained and tested by using the selected robust features for fault detection and severity assessment of spiral bevel gears under different operating conditions. A performance comparison between both classifiers is also carried out. Full article

With the rapid development of modern manufacturing processes, ultra-precision structured freeform surfaces are being widely explored for components with special surface functioning. Measurement of the 3D surface form of structured specular objects remains a challenge because of the complexity of the surface form. Benefiting from a high dynamic range and large measuring area, phase measurement deflectometry (PMD) exhibits great potential in the inspection of the specular surfaces. However, the PMD is insensitive to object height, which leads to the PMD only being used for smooth specular surface measurement. Direct phase measurement deflectometry (DPMD) has been introduced to measure structured specular surfaces, but the surface form measurement resolution and accuracy are limited. This paper presents a method named stereo-DPMD for measuring structured specular objects by introducing a stereo deflectometor into DPMD, so that it combines the advantages of slope integration of the stereo deflectometry and discontinuous height measurement from DPMD. The measured object is separated into individual continuous regions, so the surface form of each region can be recovered precisely by slope integration. Then, the relative positions between different regions are evaluated by DPMD system to reconstruct the final 3D shape of the object. Experimental results show that the structured specular surfaces can be measured accurately by the proposed stereo-DPMD method. Full article

In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is exploited. First, using set-membership identification techniques, we formulate the controller design problem through a model-matching scheme, i.e., designing a controller such that the closed-loop behaviour matches that of a given reference model. The problem is then reformulated as to derive a controller that corresponds to the minimum variation bounding its parameters. Finally, a convex relaxation approach is proposed to solve the formulated controller design problem by means of linear programming. The effectiveness of the proposed scheme is demonstrated by means of two simulation examples. Full article

The precision spool valve is the core component of the electro-hydraulic servo control system, and its performance has an important influence on the flight control of aviation and aerospace products. The non-uniform surface topography error causes a non-uniform mating gap field inside the spool valve, which causes oil leakage and leads to deterioration of the spool valve performance. However, the current oil leakage calculation method only considers the influence of size errors, which is not comprehensive. Thus, how to characterize the mating behavior of the spool valve and its effect on oil leakage with consideration of surface topography errors is the key to evaluating the performance of the spool valve. This paper proposes a new way of analyzing the mating performance of precision spool valves, which considers the surface topography errors based on digital twin technology. Firstly, a general framework for the analysis of mating performance of precision spool valve based on a digital twin is proposed. Then, key technologies of assembly interface geometry modeling, matching behavior modeling and performance analysis are studied. Finally, a quantitative correlation between the mating parameters and the oil leakage of the precision spool valve is revealed. The method is tested on a practical case. This proposed method can provide theoretical support for the accurate prediction and evaluation of the mating performance of the precision spool valve. Full article

Mathematical models have been widely used in the study of rotating machines. Their application in dynamics has eased further research since they can avoid time-consuming and exorbitant experimental processes to simulate different faults. The earlier vibration-based machine-learning (VML) model for fault diagnosis in rotating machines was developed by optimising the vibration-based parameters from experimental data on a rig. Therefore, a mathematical model based on the finite-element (FE) method is created for the experimental rig, to simulate several rotor-related faults. The generated vibration responses in the FE model are then used to validate the earlier developed fault diagnosis model and the optimised parameters. The obtained results suggest the correctness of the selected parameters to characterise the dynamics of the machine to identify faults. These promising results provide the possibility of implementing the VML model in real industrial systems. Full article

Powered Assistive Devices (PADs) have been proposed to enable repetitive, user-oriented gait rehabilitation. They may include torque controllers that typically require reference joint torque trajectories to determine the most suitable level of assistance. However, a robust approach able to automatically estimate user-oriented reference joint torque trajectories, namely ankle torque, while considering the effects of varying walking speed, body mass, and height on the gait dynamics, is needed. This study evaluates the accuracy and generalization ability of two Deep Learning (DL) regressors (Long-Short Term Memory and Convolutional Neural Network (CNN)) to generate user-oriented reference ankle torque trajectories by innovatively customizing them according to the walking speed (ranging from 1.0 to 4.0 km/h) and users’ body height and mass (ranging from 1.51 to 1.83 m and 52.0 to 83.7 kg, respectively). Furthermore, this study hypothesizes that DL regressors can estimate joint torque without resourcing electromyography signals. CNN was the most robust algorithm (Normalized Root Mean Square Error: 0.70 ± 0.06; Spearman Correlation: 0.89 ± 0.03; Coefficient of Determination: 0.91 ± 0.03). No statistically significant differences were found in CNN accuracy (p-value > 0.05) whether electromyography signals are included as inputs or not, enabling a less obtrusive and accurate setup for torque estimation. Full article

This paper presents the analytical calculation of the heat transfer coefficient of a complex housing shape of a Totally Enclosed Fan-Cooled (TEFC) industrial machine when it works below 20% of its nominal speed or close to stall. Therefore, passive cooling is dominant, and most of the heat is extracted by the combination of natural convection and radiation phenomena. Under these conditions, the area-based composite approach was used for the development of the analytical calculation method. A test rig using a TEFC Synchronous Reluctance Motor (SynRM) was constructed, and the collected experimental data was used to validate the proposed analytical method successfully. Full article

This paper presents a framework for the motion planning and control of redundant manipulators with the added task of collision avoidance. The algorithms that were previously studied and tested by the authors for planar cases are here extended to full mobility redundant manipulators operating in a three-dimensional workspace. The control strategy consists of a combination of off-line path planning algorithms with on-line motion control. The path planning algorithm is used to generate trajectories able to avoid fixed obstacles detected before the robot starts to move; this is based on the potential fields method combined with a smoothing interpolation that exploits Bézier curves. The on-line motion control is designed to compensate for the motion of the obstacles and to avoid collisions along the kinematic chain of the manipulator; this is realized using a velocity control law based on the null space method for redundancy control. Furthermore, an additional term of the control law is introduced which takes into account the speed of the obstacles, as well as their position. In order to test the algorithms, a set of simulations are presented: the redundant collaborative robot KUKA LBR iiwa is controlled in different cases, where fixed or dynamic obstacles interfere with its motion. The simulated data show that the proposed method for the smoothing of the trajectory can give a reduction of the angular accelerations of the motors of the order of $90\%$, with an increase of less than $15\%$ of the calculation time. Furthermore, the dependence of the on-line control law on the speed of the obstacle can lead to reductions in the maximum speed and acceleration of the joints of approximately $50\%$ and $80\%$, respectively, without significantly increasing the computational effort that is compatible for transferability to a real system. Full article

As an essential perceptual device, the tactile sensor can efficiently improve robot intelligence by providing contact force perception to develop algorithms based on contact force feedback. However, current tactile grasping technology lacks high-performance sensors and high-precision grasping prediction models, which limits its broad application. Herein, an intelligent robot grasping system that combines a highly sensitive tactile sensor array was constructed. A dataset that can reflect the grasping contact force of various objects was set up by multiple grasping operation feedback from a tactile sensor array. The stability state of each grasping operation was also recorded. On this basis, grasp stability prediction models with good performance in grasp state judgment were proposed. By feeding training data into different machine learning algorithms and comparing the judgment results, the best grasp prediction model for different scenes can be obtained. The model was validated to be efficient, and the judgment accuracy was over 98% in grasp stability prediction with limited training data. Further, experiments prove that the real-time contact force input based on the feedback of the tactile sensor array can periodically control robots to realize stable grasping according to the real-time grasping state of the prediction model. Full article

The study provides a solution to a dimensional synthesis problem for a hexapod-type reconfigurable parallel mechanism, which can change its configuration to realize different trajectories of its output link while having a single drive. The work presents an original procedure to find the dimensions of some mechanism’s links and their initial configuration to reproduce these trajectories. After describing the mechanism, the paper examines kinematic relations representing the basis for the subsequent synthesis algorithm. Next, the obtained expressions are extended and provide a system of equations to be solved. The structure of this equation system allows it to be solved effectively by numerical methods, which is demonstrated with an example. The proposed algorithm of dimensional synthesis does not require solving the optimization problems, in contrast to the familiar methods of dimensional synthesis of parallel mechanisms. Further, the suggested approach to the synthesis problem allows finding solution in a fast and computationally efficient manner. Full article

Aiming at solving the problem of dual resource constrained flexible job shop scheduling problem (DRCFJSP) with differences in operating time between operators, an artificial intelligence (AI)-based DRCFJSP optimization model is developed in this paper. This model introduces the differences between the loading and unloading operation time of workers before and after the process. Subsequently, the quantum genetic algorithm (QGA) is used as the carrier; the process is coded through quantum coding; and the niche technology is used to initialize the population, adaptive rotation angle, and quantum mutation strategy to improve the efficiency of the QGA and avoid premature convergence. Lastly, through the Kacem standard calculation example and the reliability analysis of the factory workshop processing process example, performance evaluation is conducted to show that the improved QGA has good convergence and does not fall into premature ability, the improved QGA can solve the problem of reasonable deployment of machines and personnel in the workshop, and the proposed method is more effective for the DRCFJSP than some existing methods. The findings can provide a good theoretical basis for actual production and application. Full article

Power skiving is a new gear cutting process that has been recognized to provide a step change in the production rate achieved in the machining of high-precision internal and external involute gears. The process is based on a continuous generating meshing between the workgear and the cutting tool. Understanding of the loads applied in the cutting tool, and therefore some of the sources of tool wear, have not been thoroughly understood. This paper presents a novel model that is able to predict with high accuracy the cutting forces in the power skiving process. The model is based on a solid modelling simulation algorithm that produces high-fidelity solid bodies that are used for the calculations. The results of the model have been experimentally validated. A series of process maps are also produced to assist in the identification of the optimal machining parameters. Full article

This paper addresses the design of a novel mechatronic device for saffron harvesting. The main proposed challenge consists of proposing a new paradigm for semi-automatic harvesting of saffron flowers. The proposed novel solution is designed for being easily portable with user-friendly and cost-oriented features and with a fully electric battery-powered actuation. A preliminary concept design has been proposed as based on a specific novel cam mechanism in combination with an elastic spring for fulfilling the detachment of the flowers from their stems. Numerical calculations and simulations have been carried out to complete the full design of a proof-of-concept prototype. Preliminary experimental tests have been carried out to demonstrate the engineering feasibility and effectiveness of the proposed design solutions, whose concept has been submitted for patenting. Full article

In this article, technology for producing wire and rod solder from 52In-48Sn alloy has been developed and investigated in the conditions of small-scale production. The use of direct extrusion of wire and rods instead of traditional technology for producing solder, which includes pressing, rolling and drawing, can significantly reduce the fleet of required equipment. Using only a melting furnace and a hydraulic press, solder wires and rods can be produced in various sizes. Shortening the production cycle allows you to quickly fulfill small orders and be competitive in sales. This article develops a mathematical model of direct extrusion, which allows you to calculate the extrusion ratio, extrusion speed and pressing force. The results of modeling the process of extrusion of wire Ø2.00 mm and rods Ø8.0 mm made of 52In-48Sn alloy are presented. The temperature of the solder and the tool is simulated in software QForm based on the finite element method. Experimental results of manufacturing Ø2.0 mm solder wire and Ø8.0 mm rods are presented. The microstructure of the direct extruded solder is a eutectic of phases γ and β. Energy-dispersive X-ray spectroscopy (EDS) mapping of the 52In-48Sn alloy showed that the solder obtained by direct extrusion has a uniform distribution of structural phases. The developed technology can be used in the manufacture of wires and rods from other low-melting alloys. Full article

This paper discusses the author-developed novel method for the detection of buried metal objects that combines two basic subsurface sensing methods: one based on changes in the electromagnetic field parameters as induced by the inner or surficial impedance of the medium when affected by a propagating magnetic field; and one based on changes in the input impedance of the receiver as induced by the electromagnetic properties of the probed medium. The proposed method utilizes three instrumentation channels: two primary channels come from the ferrite magnetic antenna (the receiver), where the first channel is used to measure the current voltage amplitude of the active input signal component, while the second channel measures the current voltage amplitude of the reactive input signal component; an additional (secondary) channel comes from the emitting frame antenna (the transmitter) to measure the current amplitude of the exciting current. This data redundancy proves to significantly improve the reliability and accuracy of detecting buried metal objects. Implementation of the computational procedures for the proposed method helped to detect and identify buried objects by their specific electrical conductance and magnetic permeability, while also locating them depth-wise. The research team has designed an induction probe that contains two mutually orthogonal antennas (a frame transmitter and ferrite receiver); the authors herein propose a metal detector design that implements the proposed induction sensing method. Experimental research proved the developed combined method for searching for buried metal objects efficient and well-performing. Full article

The present paper deals with the optimization of the three components of cutting forces and the Material Removal Rate (MRR) in the turning of AISI 5140 steel. The Harmonic Artificial Bee Colony Algorithm (H-ABC), which is an improved nature-inspired method, was compared with the Harmonic Bee Algorithm (HBA) and popular methods such as Taguchi’s S/N ratio and the Response Surface Methodology (RSM) in order to achieve the optimum parameters in machining applications. The experiments were performed under dry cutting conditions using three cutting speeds, three feed rates, and two depths of cuts. Quadratic regression equations were identified as the objective function for HBA to represent the relationship between the cutting parameters and responses, i.e., the cutting forces and MRR. According to the results, the RSM (72.1%) and H-ABC (64%) algorithms provide better composite desirability compared to the other techniques, namely Taguchi (43.4%) and HBA (47.2%). While the optimum parameters found by the H-ABC algorithm are better when considering cutting forces, RSM has a higher success rate for MRR. It is worth remarking that H-ABC provides an effective solution in comparison with the frequently used methods, which is promising for the optimization of the parameters in the turning of new-generation materials in the industry. There is a contradictory situation in maximizing the MRR and minimizing the cutting power simultaneously, because the affecting parameters have a reverse effect on these two response parameters. Comparing different types of methods provides a perspective in the selection of the optimum parameter design for industrial applications of the turning processes. This study stands as the first paper representing the comparative optimization approach for cutting forces and MRR. Full article

This study focuses on the thermodynamic performance analysis of the solar organic Rankine cycle (SORC) that uses solar radiation over a moderate temperature range. A compound parabolic collector (CPC) was adjusted to collect solar radiation because of its long-lasting nature and featured low concentration ratios, which are favorable for moderate temperature applications. A thermal storage tank was fixed to preserve the solar energy and ensure the system’s continuous performance during unfavorable weather. However, water was used as the heat transfer fluid and R245fa was used as the working fluid in this system. The performance in both the hottest and coldest months was analyzed using the average hourly profile in MATLAB using weather data from Riyadh, Saudi Arabia. Variations in the tank temperature during the charging and discharging modes were found. The hourly based thermal efficiency and net power output for both configurations were also compared. The results show that at 17:00, when the cycle was about to shut down, the thermal efficiency was 12.79% and the network output was 16 kW in July, whereas in January, the efficiency was ~12.80% and the net power output was 15.54 kW. Full article

Aerostatic bearing slideways have been increasingly applied in the precision engineering industry and other high-tech sectors over the last two decades or so, due to their considerable advantages over mechanical slideways in terms of high motion accuracy, high speeds, low friction, and environment-friendly operations. However, new challenges in air bearings design and analysis have been occurring and often imposed along the journeys. An industrial-feasible approach for the design and development of aerostatic bearing slideways as standard engineering products is essential and much needed particularly for addressing their rapid demands in diverse precision engineering sectors, and better applications and services in a continuous sustainable manner. This paper presents the multiscale modelling and analysis-based approach for design and development of the aerostatic bearing slideways and its digital twin. The multiscale modelling and analysis and the associated simulation development can be the kernel of the digital twin, which cover the mechanical design, direct drive and control, dynamics tuning of the slideway, and their entire mechatronic system integration. Using this approach and implementation, the performance of an aerostatic bearing slideway can be predicted and assessed in the process. The implementation perspectives for the sideway digital twin are presented and discussed in steps. The digital simulations and digital twin system can be fundamentally important for continuously improving the design and development of aerostatic bearing slideways, and their applications and services in the context of industry 4.0 and beyond. Full article

High quality, highly efficient finishing processes are required for finishing difficult-to-machine materials. Magnetic abrasive finishing (MAF) process is a finishing method that can obtain a high accuracy surface using fine magnetic particles and abrasive particles, but has poor finishing efficiency. On the contrary, fixed abrasive polishing (FAP) is a polishing process can obtain high material removal efficiency but often cannot provide a high-quality surface at the nano-scale. Therefore, this work proposes a new finishing process, which combines the magnetic abrasive finishing process and the fixed abrasive polishing process (MAF-FAP). To verify the proposed methodology, a finishing device was developed and finishing experiments on alumina ceramic plates were performed. Furthermore, the mechanism of the MAF-FAP process was investigated. In addition, the influence of process parameters on finishing characteristics is discussed. According to the experimental results, this process can achieve high-efficiency finishing of brittle hard materials (alumina ceramics) and can obtain nano-scale surfaces. The surface roughness of the alumina ceramic plate is improved from 202.11 nm Ra to 3.67 nm Ra within 30 min. Full article

The article is devoted to cybersecurity risk assessment of the dynamic device-to-device networks of a smart city. Analysis of the modern security threats at the IoT/IIoT, VANET, and WSN inter-device infrastructures demonstrates that the main concern is a set of network security threats targeted at the functional sustainability of smart urban infrastructure, the most common use case of smart networks. As a result of our study, systematization of the existing cybersecurity risk assessment methods has been provided. Expert-based risk assessment and active human participation cannot be provided for the huge, complex, and permanently changing digital environment of the smart city. The methods of scenario analysis and functional analysis are specific to industrial risk management and are hardly adaptable to solving cybersecurity tasks. The statistical risk evaluation methods force us to collect statistical data for the calculation of the security indicators for the self-organizing networks, and the accuracy of this method depends on the number of calculating iterations. In our work, we have proposed a new approach for cybersecurity risk management based on object typing, data mining, and quantitative risk assessment for the smart city infrastructure. The experimental study has shown us that the artificial neural network allows us to automatically, unambiguously, and reasonably assess the cyber risk for various object types in the dynamic digital infrastructures of the smart city. Full article

The article deals with the optimal control of the positional electric drive of the stator element of a segment-type wind turbine. The calculation options charts current in the assumption of the minimum energy consumption and the implementation of line chart current using the phenomenon of capacitor discharge. The analysis of the implementation is expressed in a jump-like change in current and a triangular graph of the speed change. This article deals with small capacity synchronous wind turbine generators with a segment type stator. These units have the possibility of intentionally changing the air gap between the rotor and stator. This allows: (1) Reduce the starting torque on the rotor shaft, which will allow the rotor to pick up at low wind speeds. (2) Equivalent to change of air gap in this case is change of excitation of synchronous generators. Thus, the purpose of the article is to consider a method of excitation of generators in a segmented design, by controlling the gap with the electric drive, while providing control should be carried out with minimal losses. Full article

Since centrifugal pumps consume a mammoth amount of energy in various industrial applications, their design and optimization are highly relevant to saving maximum energy and increasing the system’s efficiency. In the current investigation, a centrifugal pump has been designed and optimized. The study has been carried out for the specific application of transportation of slurry at a flow rate of 120 m³/hr to a head of 20 m. For the optimization process, a multi-objective genetic algorithm (MOGA) and response surface methodology (RSM) have been employed. The process is based on the mean line design of the pump. It utilizes six geometric parameters as design variables, i.e., number of vanes, inlet beta shroud, exit beta shroud, hub inlet blade draft, Rake angle, and the impeller’s rotational speed. The objective functions employed are pump power, hydraulic efficiency, volumetric efficiency, and pump efficiency. In this reference, five different software packages, i.e., ANSYS Vista, ANSYS DesignModeler, response surface optimization software, and ANSYS CFX, were coupled to achieve the optimized design of the pump geometry. Characteristic maps were generated using simulations conducted for 45 points. Additionally, erosion rate was predicted using 3-D numerical simulations under various conditions. Finally, the transient behavior of the pump, being the highlight of the study, was evaluated. Results suggest that the maximum fluctuation in the local pressure and stresses on the cases correspond to a phase angle of 0°–30° of the casing that in turn corresponds to the maximum erosion rates in the region. Full article

In aviation, using external stores under the wings is a common method of carrying payload or fuel. In some cases, the payload can be rigidly attached to the wing. However, stores must often be ejected during flight for aircraft, such as military type, which carry drop tanks and missiles. This may cause the wing to respond dynamically with increasing amplitudes, due to the impulsive load of ejection and the change of total mass. This is especially critical in aircraft with highly flexible wings, such as those with high aspect ratios. In this case, it is crucial to evaluate the wing response to store separation, which requires a suitable simulation environment that is able to support nonlinear and multidisciplinary analysis. To address such a need, this work presents the use of flexible multibody dynamics in the simulation of wing response to store separation. To demonstrate, a highly compliant wing was selected with a rigid body that was mounted on the wing to represent an external store. The time marching simulation of the wing before and after the store separation was presented to show the features and benefits of the method. Full article

Future automation systems are likely to include devices with a varying degree of autonomy, as well as advanced algorithms for perception and control. Human operators will be expected to work side by side with both collaborative robots performing assembly tasks and roaming robots that handle material transport. To maintain the flexibility provided by human operators when introducing such robots, these autonomous robots need to be intelligently coordinated, i.e., they need to be supported by an intelligent automation system. One challenge in developing intelligent automation systems is handling the large amount of possible error situations that can arise due to the volatile and sometimes unpredictable nature of the environment. Sequence Planner is a control framework that supports the development of intelligent automation systems. This paper describes Sequence Planner and tests its ability to handle errors that arise during execution of an intelligent automation system. An automation system, developed using Sequence Planner, is subjected to a number of scenarios where errors occur. The error scenarios and experimental results are presented along with a discussion of the experience gained in trying to achieve robust intelligent automation. Full article

Electric cars are typically subject to highly variable operational conditions, especially when they drive in urban environments. Consequently, the efficiency of the electric motors may degrade significantly, possibly leading to lower autonomy and higher running costs. Latest advances in power electronics and motion control have paved the way to the development of novel architectures of full electric power transmissions. In this paper, a dual-motor solution is proposed where two smaller motors are coupled via a planetary gear, in contrast to the standard configuration that uses one larger motor directly connected to the drive wheels with a fixed ratio reducer. The dual-motor architecture guarantees that both motors operate in the vicinity of their optimal working range, resulting in a higher overall energy efficiency. The technical requirements and the control strategy of the dual-motor system are selected through a parametric optimization process. Results included were obtained from extensive simulations performed over different standard driving cycles, showing that the dual-motor power transmission generally outperforms the single-motor counterpart with an average efficiency improvement of about 9% that is reached in both the power delivery and regeneration stage. Full article

In this paper, a novel nonlinear model and high-precision lifting motion control method of a hydraulic manipulator driven by a proportional valve are presented, with consideration of severe system nonlinearities, various uncertainties as well as valve backlash/deadzone input nonlinearities. To accomplish this mission, based on the independent valve orifice throttling process, a new comprehensive pressure-flow model is proposed to uniformly indicate both the backlash and deadzone effects on the flow characteristics. Furthermore, in the manipulator lifting dynamics, considering mechanism nonlinearity and utilizing a smooth LuGre friction model to describe the friction dynamics, a nonlinear state-space mathematical model of hydraulic manipulation system is then established. To suppress the adverse effects of severe nonlinearities and uncertainties in the system, a high precision adaptive robust control method is proposed via backstepping, in which a projection-type adaptive law in combination with a robust feedback term is conducted to attenuate various uncertainties and disturbances. Lyapunov stability analysis demonstrates that the proposed control scheme can acquire transient and steady-state close-loop stability, and the excellent tracking performance of the designed control law is verified by comparative simulation results. Full article

The general and constant ageing of the world population that has been observed in the last decade has led robotics researchers community to focus its aims to answer the ever-growing demand for health care, housing, care-giving, and social security. Among others, the researchers at Politecnico di Torino are developing a novel platform to enhance the performance offered by present-day issues, and to assess many others which were not even taken into consideration before they have been highlighted by the pandemic emergency currently in progress. This situation, in fact, made dramatically clear how important it is to have reliable non-human operators whom one can trust when the life of elderly or weak patients is endangered by the simple presence of other people. The platform, named Paquitop, features an innovative architecture conceived for omni-directional planar motion. The machine is designed for domestic, unstructured, and variously populated environments. Therefore, the mobile robot should be able to avoid or pass over small obstacles, passing through the capability to achieve specific person tracking tasks, and arriving to the need of operating with an high dynamic performance. Given its purpose, this work addresses the design of the suspension system which enables the platform to ensure a steady floor contact and adequate stability in every using condition. Different configurations of such system are then presented and compared through use-case simulations. Full article

Monitoring the thermal state of windings of electrical machines is a backbone for protection from unacceptable overheating. A large number of different methods and systems aim to solve this problem. This article discusses the main known methods of thermal protection of electric motors and provides their comparative analysis. This paper shows that the most promising methods are those based on control of the current active resistance of the stator winding, as its value uniquely depends on temperature. It is demonstrated that the known methods have a number of disadvantages. A new phase method for thermal protection of AC motors is proposed. The method is based on the fact that a temperature-induced change in the active and reactive components of the winding impedance causes a corresponding change in the angle between the vectors of phase voltages and currents. This allows for thermal protection by controlling the change in this angle. This article provides tabular analytical substantiation of the proposed method, which is based on the direct measurements of voltage and current and the subsequent algorithmic calculation of physical values functionally related to the sought angle. The authors develop a structural block diagram of a device that implements the proposed thermal protection method. All relevant experimental studies were carried out. In this case, a small-sized electronic thermometer with a remote digital temperature sensor connected to the USB port of a personal computer was used as a temperature meter. The results obtained confirm the functional capability and efficiency of the proposed technical solution. Full article