Machines, Volume 11, Issue 5 (May 2023) – 73 articles

The article describes the implementation of road driving tests with a vehicle in urban and extra-urban traffic conditions. Descriptions of the hardware and software needed for archiving the data obtained from the vehicle’s on-board diagnostic connector are presented. Then, the routes are analyzed using artificial intelligence methods. In this article, the reference of the route was defined as the trajectory of the driving process, represented by the engine rotational speed, the driving speed, and acceleration in the state space. The state space was separated into classes based on the results of the cluster analysis. In the experiment, five classes were clustered. The K-Means clustering algorithm was employed to determine the clusters in the variant without prior labelling of the classes using the teaching method and without participation of a teacher. In this way, the trajectories of the driving process in the five-state state space were determined. The article compares the signatures of routes created in urban and extra-urban driving conditions. Significant differences between the obtained results were indicated. Interesting methods of displaying the saved data are presented and the potential practical applications of the proposed method are indicated. Full article

This paper proposes a nonlinear flux linkage observer for the PMSM speed controls without motion sensors, introducing the deviation among the real stator flux linkage and an estimated stator flux linkage to suppress feedback and integral flux drift. In the position detection of an interior PMSM without a speed sensor, the traditional back EMF integration method uses a pure integrator, or LPF, to estimate the stator flux. Its inherent defects inevitably lead to inaccurate flux estimation, which directly affects the estimation of the motor mover position, resulting in the decline in motor control operation and the distortion of phase current. This paper uses an improved integrator with adaptive compensation. The projected value of the stator flux linkage has been derived from the estimated value of the rotor permanent magnetic flux linkage position angle and the algebraic model (m-model) of the stator flux linkage, along with a synchronous coordinate system. The IPMSM stator coil flux linkage obtained from the stator coil current and integral voltage models in the static coordinate system is compared to form a feedback closed-loop to suppress the integral drift, and using the cross-product approach of the actual and estimated flux linkage yields the projected value of the IPMSM rotor speed and position through a PLL. Compared with the existing motion-sensorless observers, the methodology proposed in this article is simple and exhibits better dynamic and static estimation performance. Extensive and comprehensive MATLAB computer simulation and experimental findings validate the proposed motion-sensorless control mechanism. Full article

The traffic management system holds immense importance due to its significant impact on human living standards. With the advent of advanced technologies such as natural language processing and autonomous vehicles, this study proposes a novel cooperative traffic management system based on collection auctions at an isolated unsignalized intersection, taking into account the users’ preferences for passing the intersection while being subject to their social credits. Once vehicles enter the vehicle-to-infrastructure communication zone, drivers provide the intersection control center with their bidding information, which reflects their urgency for right-of-way. According to the traffic and biding information, the vehicles’ passing sequence is optimized by the control center, in order to maximize the drivers’ average satisfaction. To demonstrate the effectiveness of the proposed system, a series of simulation experiments were conducted under varying traffic volumes. The simulation results were then compared with several other traffic control systems from the literature. It was shown that the proposed algorithm demonstrates superior performance in terms of computational time, traffic delay, and drivers’ personal satisfaction. Full article

The main goal of control theory is input tracking or system stabilization. Different feedback-computed controlled systems exist in this area, from deterministic to soft methods. Some examples of deterministic methods are Proportional (P), Proportional Integral (PI), Proportional Derivative (PD), Proportional Integral Derivative (PID), Linear Quadratic (LQ), Linear Quadratic Gaussian (LQG), State Feedback (SF), Adaptative Regulators, and others. Alternatively, Fuzzy Inference Systems (FISs) are soft-computing methods that allow using the human expertise in logic in IF–THEN rules. The fuzzy controllers map the experience of an expert in controlling the plant. Moreover, the literature shows that optimization algorithms allow the adaptation of FISs to control different processes as a black-box problem. Python is the most used programming language, which has seen the most significant growth in recent years. Using open-source libraries in Python offers numerous advantages in software development, including saving time and resources. In this paper, we describe our proposed UPAFuzzySystems library, developed as an FISs library for Python, which allows the design and implementation of fuzzy controllers with transfer-function and state-space simulations. Additionally, we show the use of the library for controlling the position of a DC motor with Mamdani, FLS, Takagi–Sugeno, fuzzy P, fuzzy PD, and fuzzy PD-I controllers. Full article

Point clouds represent an important way for robots to perceive their environments, and can be acquired by mobile robots with LiDAR sensors or underwater robots with sonar sensors. Hence, real-time semantic segmentation of point clouds with onboard edge devices is essential for robots to apprehend their surroundings. In this paper, we propose an onboard point cloud semantic segmentation system for robotic platforms to overcome the conflict between attaining high accuracy of segmentation results and the limited available computational resources of onboard devices. Our system takes raw a sequence of point clouds as inputs, and outputs semantic segmentation results for each frame as well as a reconstructed semantic map of the environment. At the core of our system is the transformer-based hierarchical feature extraction module and fusion module. The two modules are implemented with sparse tensor technologies to speed up inference. The predictions are accumulated according to Bayes rules to generate a global semantic map. Experimental results on the SemanticKITTI dataset show that our system achieves +2.2% mIoU and 18× speed improvements compared with SOTA methods. Our system is able to process 2.2 M points per second on Jetson AGX Xavier (NVIDIA, Santa Clara, USA), demonstrating its applicability to various robotic platforms. Full article

The value of the motion resistance is one of the important characteristics that determines the technical and operational properties of the vehicle, in particular its fuel economy under operating conditions. This article summarizes the approaches to determining the rolling resistance of a wheeled vehicle in straight motion, which is a separate case from curved motion. The value of this parameter is one of the vehicle components of the motion resistance along a curved path. The regularities of changes in the motion resistance of a two-axle wheeled vehicle along a curvilinear trajectory are determined based on the determination of the motion resistance of individual wheels, which considers resistance to rectilinear motion and additional resistance along a curved path caused by the twisting and lateral displacement of the wheel disc relative to the tire patch. Analytical dependences of changes in the motion resistance along a curvilinear trajectory of two-axle vehicles with the design features of transmission, placement of tires, and their characteristics were obtained. It was found that reducing the radius of curvature of the trajectory to the minimum turning radius increases the motion resistance coefficient for the investigated vehicles by 1.68−2.04 times in relation to the rolling resistance coefficient in straight motion. Full article

The crack breathing model and crack identification method for rotors using nonlinearity induced by cracks are studied in this work. Firstly, the finite element method is utilized to model a rotor–bearing system with a response-dependent breathing crack to obtain the numerical data for crack identification. During the modelling, an improved breathing crack model is proposed, focused on the unreasonable assumption about crack closure line in the original crack closure line position (CCLP) model. Compared with the original model, the improved breathing model can reflect the nonlinear behavior of cracks better. Secondly, based on the established model, super-harmonic features at 1/3 and 1/2 of the critical rotating speeds under different crack locations and crack depths are extracted for crack identification. Additionally, the super-harmonic features from two measurement points are used as inputs into an artificial neural network with a Levenberg–Marquardt back-propagation algorithm, corresponding crack positions and depths as outputs. The robustness of the method is tested by examining the identification results under different levels of noise. The results show that the proposed crack identification method is efficient for simultaneous identification of crack depth and position in operating rotors. Full article

Robot-guided inkjet printing technology offers a new way for the digital and additive deposition of low-viscous inks to be made directly onto arbitrary surfaces and, thus, enables the production of individualized printed electronics on large-scale objects. When compared to conventional flatbed printing, the distance between the nozzle plate and the object’s surface varies and needs to be considered in order to match the accuracy requirements needed for the positioning of single drops. Knowledge about applicable distance limits and the influence of tunable print parameters is crucial for improving the print process and results. This study discusses the sources of errors in the inkjet printing process onto 3D objects and presents extensive results about position accuracy in relation to jetting distance for different parameter sets of functional inks, drop volumes, and piezo voltages. Additionally, an efficient novel method was applied to determine the drop position accuracy of inkjet droplets in relation to the jetting distance. The method relies on cylinder geometry for the object and an inkjet head that is guided by a six-axis robot manipulator along the cylinder’s axis. For the determination of drop placement accuracy, the position of single dots on the surface was compared to a model which considered the cylinder radii, drop velocity, and the movement speed of the guided inkjet printhead. The method and the extensive research results can be utilized for the prediction of achievable drop placement accuracy and the prior definition of distance limits. Full article

This paper shows the results obtained from the study on the variables that have the greatest influence on the decision to replace three-phase induction motors, without a defined efficiency class and installed in industrial applications, with IE3 efficiency class induction motors. The work has been carried out on motors with a nominal power of 1.5 kW due to the availability of laboratory tests that have allowed us to accurately quantify the selected study variables. According to IEC 60034-30, between 0.75 kW and 4 kW is the greatest potential for energy savings in electric motors installed within the industrial sector. The tests carried out have made it possible to assess different operating conditions of the motor: direct power supply from the grid, electronic power supply using scalar control, and electronic power supply using direct torque control. The study has focused on three aspects: energy evaluation, assessing the savings potential; economic evaluation, based on indicators such as Payback Period and Net Present Value; environmental assessment, quantifying the impact indicators proposed by the Methodology for Ecodesign of Energy-related Products (MEErP). A sensitivity analysis has been carried out to quantify, through ratios, different operating points from those directly analyzed in the article. Full article

Since the stagnation point is subject to straining motion, this 3D experiment is an effort to simulate the stagnation plane, which applies to studying the particle erosion in rotary machine blades, such as wind turbines, gas turbines, and compressors. Wind turbine blade erosion, caused by particles such as sand, ice, insects, raindrops, and snowflakes, can significantly impact turbine efficiency, as with other rotary machines. Previous research has indicated that flow geometry and gravity can influence particle dynamics statistics. The current study’s laboratory experiment simulates the airfoil’s stagnation plane to investigate how floating particles cause erosion. The experiment involves seeding tracers and inertial particles in a strained turbulent flow with specific turbulent intensity, strain rate, and the presence of gravity. It is conducted on initially homogeneous turbulence undergoing a sudden axisymmetric expansion. The flow was generated in $100<R{e}_{\lambda }<160$. The Lagrangian particle tracking technique based on the 4-frame best estimate method was employed to measure the velocity field. The obtained results are with two different mean strain rates and Reynolds–Taylor microscales in the presence of gravity, which has not been considered in most numerical studies in a particle-laden turbulent flow. It provides a transparent window to investigate how particles of different sizes with distinct strain rates flow and their relationship to the turbulence intensity affects the erosion. Two most important issues are observed in the presence of gravity: Increasing the turbulence intensity from $R{e}_{\lambda }=100$ to 160 led to a 10–23% increase in the erosion ratio, depending on the particle type and the flow strain rate. Likewise, a doubled mean strain rate of the flow (caused by deformation/shear flow) resulted in a 3–10% increase in erosion, depending on the particle type and Reynolds number. Moreover, the influence of gravity could potentially play a significant role in this observation. Full article

For lower limb rehabilitation robots, different patients or patients in different rehabilitation stages have different motion abilities, and the parameters of the traditional impedance control model are fixed and cannot achieve the best active suppleness training effect. In this paper, an active training control method based on the spring damping model (SDM) and the fuzzy adaptive adjustment of its parameters is proposed. The SDM offsets the target trajectory according to the patient interaction force to obtain a new desired trajectory, creating a controllable impedance environment for the patient. Fuzzy rules are established using coefficients reflecting the patient’s motion ability to adaptively adjust the stiffness and damping coefficients of the SDM. The virtual human–machine force interaction environment is changed to achieve the adaptive adjustment of the resistance training difficulty on the motion ability. The adaptive impedance control method proposed in this paper has achieved the expected goal through experimental verification, which can greatly mobilize the active participation of patients and help improve the rehabilitation effect of patients. Full article

Near-infrared (NIR) spectroscopy is a widely used technique for determining the composition of textile fibers. This paper analyzes the possibility of using low-cost portable NIR sensors based on InGaAs PIN photodiode array detectors to acquire the NIR spectra of textile samples. The NIR spectra are then processed by applying a sequential application of multivariate statistical methods (principal component analysis, canonical variate analysis, and the k-nearest neighbor classifier) to classify the textile samples based on their composition. This paper tries to solve a real problem faced by a knitwear manufacturer, which arose because different pieces of the same garment were made with “identical” acrylic yarns from two suppliers. The sweaters had a composition of 50% acrylic, 45% wool, and 5% viscose. The problem occurred after the garments were dyed, where different shades were observed due to the different origins of the acrylic yarns. This is a challenging real-world problem for two reasons. First, there is the need to differentiate between acrylic yarns of different origins, which experts say cannot be visually distinguished before garments are dyed. Second, measurements are made in the field using portable NIR sensors rather than in a controlled laboratory using sophisticated and expensive benchtop NIR spectrometers. The experimental results obtained with the portable sensors achieved a classification accuracy of 95%, slightly lower than the 100% obtained with the high-performance laboratory benchtop NIR spectrometer. The results presented in this paper show that portable NIR sensors combined with appropriate multivariate statistical classification methods can be effectively used for on-site textile quality control. Full article

In this paper, a set of partial differential equations considering the dynamic effects of the coiled tubing (CT) is established based on the bending theory of slender beams considering the axial loads. The analytical solution of sinusoidal deformation with the time term is obtained. The critical load of coiled tubing during sinusoidal buckling and the change of half-wave number during sinusoidal post-buckling are studied through the introduction of the necessary conditions, solution and the separation constant. The contact force of coiled tubing with sinusoidal post-buckling on the horizontal well wall is analyzed. The results show that the critical load for sinusoidal buckling of fixed-size CT is related to the section angular acceleration coefficient. The half-wave number produced by the sinusoidal post-buckling bending of the CT gradually decreases during compression. The contact force of the deformed CT to the borehole wall is related to the compression speed of the CT. By introducing the dynamic term and the separation constant, this research model can provide a theoretical basis for studying the transformation of the CT from sinusoidal buckling to helical buckling. Full article

With the development of intelligent tires, the tire pressure monitoring system (TPMS) has become a standard safety feature in cars. However, the existing TPMS has limited ability to monitor tire pressure in real time due to the passive power supply device’s low power output. This work presents a conceptual design for a novel energy harvester for TPMS (NEH-TPMS) based on a mechanical structure to recover energy. The motion of the mechanical structure is driven by the deformation of the tire in contact with the ground. The energy is recovered and released by a spiral spring to accomplish the functions of power generation and charging. Mathematical models are created based on the NEH-TPMS’s movements. The simulation results indicate that the NEH-TPMS’s power generation capacity is greater than that of existing energy harvesters and can satisfy the TPMS’s power supply requirements. This work uses finite element analysis and hierarchical analysis to optimize the shape of the NEH-TPMS. The parameters of the spiral spring are optimized using simulated annealing and genetic algorithms. NEH-TPMS has been enhanced to provide greater energy storage capacity. Finally, a prototype was built to verify the structure’s feasibility. The experimental results are consistent with the simulated results. This NEH-TPMS offers an efficient means of enhancing the power generation efficiency of the passive power supply device for TPMS. Full article

The surface accuracy of a multistep rotary shaft is very important in manufacturing and the assembly process of the high-speed motorized spindle of CNC machine tools, which is closely related to the machined dimensional variation induced by the turning process. This paper attempts to enhance a comprehensive understanding of the impact of different locating-error sources and machine toolpaths on the machined dimensional variation for multistep rotary parts of the high-speed motorized spindle in the turning process. A modeling method and a compensation strategy of dimensional variation are introduced in this paper and based on the relationship definition between the error sources and the machined surface using the differential motion vector and stream-of-variation methods. Validation experiments were conducted to verify the proposed model. Additionally, the relationship between locating errors and dimensional variation was investigated with varied case studies, providing a theoretical methodology for the prediction and characterization of the expected dimensional variations of the surface machined with the given conditions. Full article

The mounting increase in the technological complexity of modern engineering systems requires compound uncertainty quantification, from a quantitative and qualitative perspective. This paper presents a Compound Uncertainty Quantification and Aggregation (CUQA) framework to determine compound outputs along with a determination of the greatest uncertainty contribution via global sensitivity analysis. This was validated in two case studies: a bespoke heat exchanger test rig and a simulated turbofan engine. The results demonstrated the effective measurement of compound uncertainty and the individual impact on system reliability. Further work will derive methods to predict uncertainty in-service and the incorporation of the framework with more complex case studies. Full article

An air compressor is the core component of the air supply system of a hydrogen fuel cell, which demands high efficiency and reliable stability in a wide operation region. In this work, a centrifugal air compressor for a hydrogen fuel cell is first designed and then measured experimentally. Furthermore, a test rig for assessing the aerodynamic performance of the centrifugal air compressor is established, which includes a pipeline, gas flowmeter, flow regulating valve, pressure transmitter, centrifugal compressor, controller, DC power supply and computer. Then, the orthogonal method is employed to conduct the aerodynamic performance optimization. Four optimization parameters—including blade number, blade angle at the inlet, blade angle at the outlet and wrap angle—are set with three levels. Nine compressor individuals are designed according to the orthogonal method, and then numerical simulation is implemented to confirm the aerodynamic performance and flow pattern. Results show that the blade number has the greatest influence on the compressor’s performance, and the blade angle at inlet is also very important. The optimal performance of the compressor improves compared to that of the baseline compressor; the efficiencies of the baseline compressor and optimal compressor are 81.3% and 83.8%, respectively, improving by 2.5%. The frequency domain of pressure fluctuation in the centrifugal compressor is related to the stator-rotor interaction. The peak value of pressure fluctuation amplitude occurs at the rotation frequency of 833 Hz and its harmonic frequency. In comparison with the baseline compressor, the pressure fluctuation amplitude of the optimal compressor is obviously reduced, especially near the volute tongue. Full article

Navigating in a perpetually changing world can provide the basis for numerous challenging autonomous robotic applications. With a view to long-term autonomy, visual place recognition (vPR) systems should be able to robustly operate under extreme appearance changes in their environment. Typically, the utilized data representations are heavily influenced by those changes, negatively affecting the vPR performance. In this article, we propose a sequence-based technique that decouples such changes from the similarity estimation procedure. This is achieved by remapping the sequential representation data into the distance-space domain, i.e., a domain in which we solely consider the distances between image instances, and subsequently normalize them. In such a way, perturbations related to different environmental conditions and embedded into the original representation vectors are avoided, therefore the scene recognition efficacy is enhanced. We evaluate our framework under multiple different instances, with results indicating a significant performance improvement over other approaches. Full article

The marine engine is a complex-structured multidisciplinary system that operates in a harsh environment involving high temperatures and pressures and gas/fluid/solid interactions. Many malfunctions and faults can occur to the marine engine and efficient condition monitoring is critical to ensure the expected performance. In this paper, a marine engine test rig is established and its process data are recorded, including various temperatures and pressures. Two data-driven models, i.e., principal component analysis and the sparse autoencoder, and a physics-based model are applied to the marine engine for two classic faults, i.e., lubrication oil filter blocking and cylinder leakage. Comparative studies and discussions are conducted regarding their performance in terms of anomaly detection and fault isolation. The data points collected for the filter blocking fault are generally two times higher than the fault thresholds set by the data-driven models. In the physics-based model, it is observed that the lubrication oil pressure falls from the predicted 3.2–3.8 bar to around 2.3 bar. For the cylinder leakage fault, the fault test data are nearly four times higher than the thresholds in the data-driven models. The exhaust gas temperature of the leaked cylinder falls from an estimated 150–200 °C to about 100 °C. The transferability and interpretability of these models are finally discussed. The findings of the present study offer insights into the two types of models and can provide guidance for the effective condition monitoring of marine engines. Full article

As musculoskeletal modeling improves, the possibilities of calculating more diverse parameters or performing specific motion analyses increase. However, customization might require a different approach that is not offered by the original software or it requires complex knowledge. Patient lift motion was analyzed in Plug-in-Gait (PiG) marker-set-based kinematic model in Rhino Grasshopper for the range of motion calculation of arms. The model was compared with the biomechanics of body (BoB) 10.5 software kinematic model. For the analyzed model, RMSE evaluated as a percentage of the amplitude varied from 9.17% to 32.44%. The data showed actively accurate results except for a few values that were defined as moderately accurate. All data sets showed strong correlation with the reference model. The tested model was confirmed, since it showed significant data correlation with relative accurate values and was evaluated as suitable for further development and analysis before being put to practical use. Full article

Assistive devices can significantly improve caregivers’ ability to help disabled people with their daily activities. Existing assistive devices are not fully capable of safe transfer and are still in their early stages of development. In this research, a body-transfer system is designed and developed to ensure that the posture and body angle of the person in the sagittal plane remains unaltered while transferring from bed to wheelchair and vice versa. Two independently controlled conveyor belts (2-DOF) mounted on the indigenously developed bed are employed to transfer the disabled person using a sliding approach. Additionally, a wheelchair with conveyor belts that are fully automated is used to carry and transfer the user to and from the wheelchair. Furthermore, an integrated control architecture has been developed for safely operating the entire body-transfer system (from an indigenously developed bed and wheelchair). Finally, an experimental assessment of the body-transfer system’s performance has been conducted. The experimental findings demonstrate that the system can transfer up to 120 kg of body weight while the user’s posture remains unaltered in the sagittal plane. Users perceive a reduction in wrist and shoulder pain index using the body-transfer system. The system has great potential for relocating disabled persons safely while reducing the load on caregivers. Full article

This work aimed to design a tensile horizontal machine that performs mechanical testing for suspension clamps, transmission line accessories, and overhead conductors with the following features: the suspension clamps device will be a permanent part of the structure, requiring a minimal setup; and it will accept overhead conductor specimens with lengths of up to 12 m and also be able to perform testing for pieces that require the plate-fork fastening option. Analytical and numerical calculations are performed according to the AISC-360-16 standard and static structural module of ANSYS software, respectively, to compare results. Full article

When a two-wheeled inverted pendulum (TWIP) robot vehicle travels on slippery roads, the occurrence of wheel slip extremely threatens its postural stability owing to the loss of wheel traction. If a severe wheel slip happens between the driving wheels and contact surfaces, no control techniques can guarantee the driving performance and stability of the TWIP robots in the absence of an extra wheel slip control strategy. In this paper, a TWIP-compatible countermeasure against the wheel slip phenomena is investigated for enhancing the reliability of the vehicle and the robustness of the motion control performance on low-frictional surfaces. To this end, we propose a balancing-prioritized anti-slip control method based on the maximum transmissible torque estimation, which is activated only when a wheel slip is detected by the acceleration slip indicator utilizing accessible data from the IMU and wheel encoders. It is proved that the TWIP vehicles applying the proposed method can successfully cope with low frictional surfaces while maintaining postural stability. Finally, comparative simulations and experiments demonstrate the effectiveness and feasibility of the proposed scheme. Full article

Aiming at the operation conflict problem of multi-objective, multi-path and multi-vehicle relay during mine locomotive operation under complex geological conditions, a mine operation of locomotive modeling method based on an object-oriented stratified timed Petri net is proposed. In order to load and transport materials as object oriented, which are combined with the mine operation of locomotive rules and time constraints, stratified modeling of an underground roadway route is carried out. In addition, given token time parameters to describe the dynamic behavior of the locomotive, through the model to analyze the operation of a mine transport locomotive, the correlation matrix and accessibility tree analysis are used to study the conflict. Taking the actual operation of a locomotive in a complex mine in Guizhou as an example, the operation of locomotive behavior model was established to detect the interval and time of operation conflicts. The experimental results show that the proposed operation of locomotive modeling and conflict analysis method are effective and feasible, and have important application value to the safe operation of a mine production system. Full article

Based on data-driven and mixed models, this study proposes a fault detection method for autonomous underwater vehicle (AUV) rudder systems. The proposed method can effectively detect faults in the absence of angle feedback from the rudder. Considering the parameter uncertainty of the AUV motion model resulting from the dynamics analysis method, we present a parameter identification method based on the recurrent neural network (RNN). Prior to identification, singular value decomposition (SVD) was chosen to denoise the original sensor data as the data pretreatment step. The proposed method provides more accurate predictions than recursive least squares (RLSs) and a single RNN. In order to reduce the influence of sensor parameter errors and prediction model errors, the adaptive threshold is mentioned as a method for analyzing prediction errors. In the meantime, the results of the threshold analysis were combined with the qualitative force analysis to determine the rudder system’s fault diagnosis and location. Experiments conducted at sea demonstrate the feasibility and effectiveness of the proposed method. Full article

The reliability assessment of electric machines plays a very critical role in today’s engineering world. The reliability assessment requires a good understanding of electric motors and their root causes. Electric machines mostly fail due to mechanical problems and bearing damage is the main source of this. The bearings can be damaged by mechanical, electrical, and thermal stresses. Among all stresses, the researcher should give special attention to the electrical one, which is bearing current and shaft voltage. This review paper introduces a comprehensive study of bearing current and shaft voltage for inverter-fed electric machines. This study aims to discuss several motor failure processes, as well as the sources and definitions of bearing current and shaft voltage. The different kinds of bearing currents are addressed and the parasitic capacitances, which are the key component to describe bearing current, are determined. Several measurement approaches of bearing current will be discussed. Furthermore, modeling of bearing current will be covered together with the machine’s parasitic capacitances. Moreover, the different bearing current mitigation techniques, as described in many papers, will be thoroughly addressed. The use of rewound multiphase machines for mitigation of bearing current will be proposed and compared to a three-phase machine. Finally, various pulse width modulation techniques of multiphase systems that reduce bearing current and shaft voltage will be investigated, and the findings described in the literature will be summarized for all techniques. Full article

A circular saw blade is a commonly used tool in wood processing. The transverse vibration of the saw blade plays an important role in processing quality during cutting and affects its service life as well. In the study, the transverse vibration of the circular saw blade was investigated at the constant rotation by the simulation using ANSYS software when changing the cantilever length of the cantilever woodworking CNC circular saw machine. Meanwhile, the transverse vibration of the circular saw blade without and with load was explored by the eddy current sensors for when the detection point was differently away from the center of the circular saw blade. The time domain, probability density distribution, and power spectrum characteristics of the transverse vibration signal were analyzed, and the simulation values were compared with the actual cutting data. The results revealed that under certain conditions, the maximum transverse vibration value of the circular saw blade was the smallest in the simulation, then the middle in no-load, and the largest in actual cutting. The maximum transverse vibration value of the saw blade was increased with the extension of the cantilevered overhang, but gradually and slightly, indicating the transverse vibration was hardly affected by the change in overhang length of less than 300 mm. The finding provides the reference for the structural optimization design of cantilever CNC circular saw machines and the promotion of its application. Full article

The paper proposes an original mechanical structure of a serial-tracked robot, subject of national invention patent number RO132301, B1/2021, destinated for humanitarian demining operations: anti-personnel mine detection by using a detection device mounted on the bottom’s tracked platform, demining and clearing the land of exploded mines using a TRTTR robot structure. The dynamic model of the robot structure is determined and numerically validated. A novel approach based on the Lagrange formalism and mechanical design equations has been used in the calculus and selection of robot driving motors. The obtained results for robot translation modules are presented and analyzed. Full article

Additive manufacturing is becoming one of the most utilized tools in an increasing number of fields from Industry 4.0 concepts, engineering, and manufacturing to aerospace and medical applications. One important issue with additive-manufactured components is their orthotropic behaviour where mechanical properties are concerned. This behaviour is due to the layer-by-layer manufacturing process and is particularly hard to predict since it depends on a number of factors, including the manufacturing parameters used during the manufacturing process (speed, temperature, etc.). This study aimed to create and train an artificial neural network-based predictive model using empirical tensile strength data obtained from additive manufactured test parts using the FDM method and PLA material. The predictive model was designed to predict mechanical characteristics for different orientation axis, which were used to set the material properties for finite element analysis. Results indicate a strong correlation between predicted finite element analysis behaviour and real-world tests on additive-manufactured components. The neural network model was trained to an accuracy of ~93% for predicting the mechanical characteristics of 3D-printed PLA material. Using the predicted mechanical characteristics for defining a custom orthotropic material profile in finite element analysis, the simulated failure mode and the behaviour of a complex geometry component agreed with the real-world test. Full article

Supercritical water gasification (SCWG) of coal is a promising clean coal technology, which discards the traditional coal combustion and oxidation reaction to release carbon dioxide and other pollutants and replaces coal with a gasification reduction reaction in supercritical water to finally convert coal into a hydrogen-rich gas product with no net carbon dioxide emissions and no pollutant emissions, and thus has received much attention in recent years. However, the experimental conditions of coal to the hydrogen reactor are harsh, costly, and not easy to visualize and analyze, so numerical calculation and simulation analysis are important for the design, optimization, and industrial scaling-up of the reactor. In order to study the effect of the temperature field on the hydrogen production rate of the coal supercritical water gasification hydrogen production reactor, a numerical simulation calculation model is developed for this reactor in this paper. Comparing the experimental data in the literature, the maximum relative error of the gasification product yield per kg of coal between the two is less than 5%, which verifies the accuracy of the model built and the numerical method adopted in this paper. On this basis, the effects of supercritical water temperature and coal slurry temperature on the reactor’s gasification products and reaction rate were investigated in depth. The results show that increasing the supercritical water temperature is beneficial to improve the reactor hydrogen production efficiency, while the high coal slurry temperature is not conducive to adequate reaction, thus reducing the hydrogen production efficiency. For the laboratory coal supercritical water gasification to hydrogen reactor studied in this paper, the ideal temperature of supercritical water is 850~900 K, and the ideal temperature of coal slurry is 400–450 K. The conclusions of this paper can provide some reference for subsequent industrial scale-up studies of the reactor. Full article