Search Results (2,765)

Automotive driving simulators are widely used in driving schools and training centers, where they help students acquire the necessary skills without risk to life and health. This paper presents modern research in the field of creating a model and a real prototype of an automotive driving simulator based on the Gough–Stewart platform. This investigation presents optimized geometric parameters using the PSO algorithm. Virtual prototypes of the robotic platform were created by MSC Adams. In turn, this made it possible to conduct the simulation of kinematic and dynamic parameters. They represent operating conditions when exposed to workloads. This paper shows a prototype of an automotive driving simulator and special equipment with an integrated system of virtual 3D models of real terrain. Full article

This experimental study aimed to validate the integration of a gravitational loop heat pipe (GLHP) with respect to a gas fireplace insert. The GLHP was utilized to enhance the efficiency of the fireplace by preheating the combustion air with waste heat from flue gases. The experiment involved monitoring key parameters such as vapor and condensate temperatures and absolute pressure within the LHP. The results demonstrated that a filling volume of 0.1 L of water in the LHP allowed for successful operation, while exceeding 0.2 L resulted in flooding and decreased system efficiency. Challenges related to vapor production and condensate return were identified, suggesting the need for further research and design improvements. The experimental verification confirmed the feasibility of implementing the gravitational LHP in a gas fireplace insert and emphasized the importance of optimizing vapor production and condensate return mechanisms. This study contributes to the advancement of thermal management strategies and provides valuable insights for enhancing the design and performance of such systems. Full article

One of the key parameters in the analysis of some motorcycle accident dynamics is the motorcycle’s deceleration during engine braking without applying the brakes. Since this issue lies far beyond what is usually of most interest—the critical states of movement—it is only sporadically addressed in the literature; however, these rare cases can be of fundamental importance. In our research, the results of engine-braking deceleration are presented for 26 motorcycles that were in gear with the throttle back. The tests were carried out at an initial speed of 140 km/h (if this was not possible, then from the maximum speed for a given gear) to the speed at which the motorcycle reached a constant speed or when engine operation became unstable. For all motorcycles and all gears, deceleration vs. speed and speed vs. time were plotted. Regression lines were determined, and their equations are provided, along with ±σ and ±2σ limit lines. Engine-braking deceleration was shown to be inversely proportional to both motorcycle speed (higher speed—lower deceleration) and gear number (higher gear—lower deceleration). Moreover, engine-braking deceleration at the top gear of the various motorcycles tested (i.e., 5th or 6th) was found to be close to each other. The data provided are of crucial importance from the motorcycle longitudinal dynamics and vehicle accident analysis standpoints. Full article

Pulse–width modulated inverters are commonly used to control electrical drives, generating a common mode voltage and current with high–frequency components that excite the parasitic capacitances within electric machines, such as permanent magnet synchronous machines or induction machines. This results in different types of bearing currents that can shorten the service life of electric machines. One significant type of inverter–induced bearing currents are high–frequency circulating bearing currents. In this context, this work employs finite element analysis and time-domain simulations to determine the common mode current and circulating bearing current for various permanent magnet synchronous machine designs based on the traction machines of commercial electric vehicles with a focus on the stator. The results suggest that the ratio between the circulating bearing current and common mode current is much smaller in permanent magnet synchronous machines for traction applications than previously established in conventional induction machines, with values below 10% for all analyzed designs. A further increase in the robustness of such electric machines to the detrimental effects caused by the inverter supply could be achieved by reducing the parasitic winding–to–stator capacitance or by increasing the stator endwinding leakage inductance. Full article

In recent years, there has been growing attention from the scientific community regarding the environmental impact of commercial goods, pushing companies to adopt life cycle assessment strategies to improve their environmental profile. Only few studies have examined the environmental burdens of electric motors, specifically for stationary applications such as oil and gas plants, transmission organs, operating machines, or other industrial utilization. For this purpose, this paper presents a comprehensive and detailed evaluation of the environmental sustainability of an asynchronous electric motor used for stationary applications. The motor under examination moves a stand-by hydraulic pump used in a compression plant to lubricate the bearings of centrifugal machines. The principles dictated by ISO 14040 are implemented, and a cradle-to-gate analysis is performed. This article reports in detail the inventory hypothesis and the steps that led to modeling the assessed electric motor. The results are presented for all impact categories provided by the ReCiPe methodology. Additionally, a breakdown of the eco-indicators at the single component level is proposed, focusing on the impact of raw material extraction phases and subsequent technological processes. The last section highlights which components contribute predominantly, both from a materials and processes perspective, and the environmental hotspots in the modeled supply chain are identified. Full article

Historically, mining operations have faced numerous challenges, including safety hazards, inefficiencies, and environmental concerns. However, recent advances in robotics, automation, and artificial intelligence have presented opportunities for the mining industry. The ROBOMINERS project, a Horizon 2020 European Union initiative, aims to revolutionize the mining ecosystem by implementing disruptive robotic concepts. One such concept is resilience, which involves enabling mining robots to reconfigure morphologically during operation. This article presents the development of a modular robotic system that focuses on modularity and self-assembly to provide insight into developing a highly adaptable and compact solution for future mining robots. The robotic system is composed of a set of highly configurable modular robotic platforms that can be reconfigured with other robotic modules or submodules to form more complex systems to perform different tasks. Several module configurations are presented, and different locomotion experiments were carried out to test the ability of the modules to navigate unstructured environments. The modules exhibited great maneuverability in unstructured terrain and demonstrated self-assembly and reconfiguration capabilities during operation. This is a foundational step towards the long-term goal of developing compact autonomous agents capable of self-assembly and mining task execution. Full article

Moving on paths or trails present in natural environments makes autonomous navigation of unmanned ground vehicles (UGV) simpler and safer. In this sense, aerial photographs provide a lot of information of wide areas that can be employed to detect paths for UGV usage. This paper proposes the extraction of paths from a geo-referenced satellite image centered at the current UGV position. Its pixels are individually classified as being part of a path or not using a convolutional neural network (CNN) which has been trained using synthetic data. Then, successive distant waypoints inside the detected paths are generated to achieve a given goal. This processing has been successfully tested on the Andabata mobile robot, which follows the list of waypoints in a reactive way based on a three-dimensional (3D) light detection and ranging (LiDAR) sensor. Full article

Quality products are a main focus for manufacturers. Product users only determine a product to be a quality product if it performs in operation to the user’s perceived standard. Product manufactures need to take a product lifecycle quality (PLQ) perspective of quality and not simply focus on manufacturing quality control, which is more accurately specification control. Manufacturing is the key phase where products take their physical form. There are increasing costs and decreasing risks of different physical quality strategies. The information provided using digital twins and virtual testing promises to be both low risk and cost and has the potential to predict what the customer will experience in operation by testing products passively with data and actively with simulation to destruction. Digital Twin Certified (DTC) is proposed as the methodology for accomplishing this. DTC will be especially important for the adoption of additive manufacturing. Full article

The online monitoring and prediction of tool wear are important to maintain the stability of machining processes. In most cases, the tool wear condition can be evaluated by signals such as force, sound, vibration, and temperature, which are often processed via Fourier-transform based methods, typically, the short-time Fourier transform (STFT). However, the fixed-width window function in STFT has many limitations. In this paper, a novel tool wear monitoring method based on variational mode decomposition (VMD) and Hilbert–Huang transformation (HHT) were developed to monitor the wear of carbide tools in machining stainless steel. In this method, the intrinsic mode function (IMF) was used as the fitness function, and the (K alpha) parameter sets for VMD were optimized by the gray wolf optimization (GWO). The results show that the characteristic frequency in the GWO-VMD-HHT method is more significant with no aliasing compared with the EMD-HHT method, and an obvious characteristic frequency shift phenomenon is present. By utilizing the energy value of IMF₃ as the feature to classify the wear state of the cutting tool, the increase of energy reached 85.48% when 260–315 milling passes were in severe wear state. GWO, which can accurately find the best parameters for VMD, not only solves the problem that the Entropy Function is not suitable for force signals, but also provides reference for the selection of parameters of VMD. Full article

In this work, thick deposits of pure titanium (Ti), with a thickness of around 15 mm, were additively manufactured using high-pressure cold spraying. Nitrogen was employed as the process gas. Subsequently, the deposits were subjected to hot isostatic pressing (HIP). The HIP-treated Ti deposits were analyzed for their metallurgical and mechanical characteristics with the aim of exploring the viability of using cold spraying for the additive manufacturing of Ti components. Moreover, high-temperature cyclic oxidation testing was also performed on the HIP-treated Ti deposit to understand its stability at high temperatures. SEM/EDS showed a dense structure with marginal porosity for the HIP-treated Ti deposits, without any oxide formation, which was further confirmed via XRD analysis. An average microhardness of 214 HV was measured for the HIP-treated Ti deposits, which is close to that of the commercially available bulk titanium (202 HV). The high-temperature oxidation studies revealed that the cold-sprayed HIP-treated Ti has very good oxidation resistance, which could be attributed to the formation of protective titanium dioxide in its oxide scale. Full article

Gripper finger design is a complex process that requires a lot of experience, time, and effort. For this reason, automating this design process is an important area of research that has the potential to improve the efficiency and effectiveness of robotic systems. The current approaches are aimed at the automated design of monolithic gripper fingers, which have to be manufactured additively or by machining. This paper describes a novel approach for the automated design of gripper fingers. The motivation for this work stems from the increasing demand for flexible, adaptable handling systems in various industries in response to the increasing individualization of products as well as the increasing volatility in the markets. Based on the CAD data of the handling objects, the most suitable configuration of gripper fingers can be determined from the existing modules of a construction kit for the respective handling object, which can significantly reduce the provisioning time for new gripper fingers. It can be shown that gripper fingers can be effectively configured for a variety of objects and two different grippers, increasing flexibility in industrial handling processes. Full article

Wheel slip control is a critical aspect of vehicle safety systems, notably the antilock braking system (ABS). Designing a robust controller for the ABS faces the challenge of accommodating its strong nonlinear behavior across varying road conditions and parameters. To ensure optimal performance during braking and prevent skidding or lock-up, the ideal wheel slip value can be determined from the peak of the tire–road friction curve and maintained throughout the braking process. Among various control approaches, model predictive control (MPC) demonstrates superior performance and robustness. However, online MPC implementation encounters significant computational burdens and real-time limitations, particularly when dealing with larger problem sizes. To address these issues, this study introduces an offline robust model predictive control (RMPC) methodology. The proposed approach is based on the robust asymptotically stable invariant ellipsoid methodology, which employs linear matrix inequalities (LMIs) to calculate a collection of invariant state feedback laws associated with a sequence of nested invariant stable ellipsoids. Simulation results indicate a significant reduction in computational burden with the offline RMPC approach compared to online implementation, while effectively tracking the desired wheel slip reference values and system constraints. Moreover, the offline RMPC design aligns well with the online MPC design and verifies its effectiveness in practice. Full article

In an environment where manufacturing precision requirements are increasing, complete project plans can consist of hundreds of engineering drawings. The presentation of these drawings often varies based on personal preferences, leading to inconsistencies in format and symbols. The lack of standardization in these aspects can result in inconsistent interpretations during subsequent analysis. Therefore, proper annotation of engineering drawings is crucial as it determines product quality, subsequent inspections, and processing costs. To reduce the time and cost associated with interpreting and analyzing drawings, as well as to minimize human errors in judgment, we developed an engineering drawing recognition system. This study employs geometric dimensioning and tolerancing (GD&T) in accordance with the ASME (American Society of Mechanical Engineers) Y14.5 2018 specification to describe the language of engineering drawings. Additionally, PyTorch, OpenCV, and You Only Look Once (YOLO) are utilized for training. Existing 2D engineering drawings serve as the training data, and image segmentation is performed to identify objects such as dimensions, tolerances, functional frames, and geometric symbols in the drawings using the network model. By reading the coordinates corresponding to each object, the correct values are displayed. Real-world cases are utilized to train the model with multiple engineering drawings containing mixed features, resulting in recognition capabilities surpassing those of single-feature identification. This approach improves the recognition accuracy of deep learning models and makes engineering drawing and image recognition more practical. The recognition results are directly stored in a database, reducing product verification time and preventing errors that may occur due to manual data entry, thereby avoiding subsequent quality control issues. The accuracy rates achieved are as follows: 85% accuracy in detecting views in 2D engineering drawings, 70% accuracy in detecting annotation groups and annotations, and 80% accuracy in text and symbol recognition. Full article

The investigation in this article focuses on the rolling resistance torque and thermal inlet shear factor in tapered roller bearings (TRBs) through systematic experiments using a modular test setup. TRBs typically operate under Elastohydrodynamic Lubrication (EHL) conditions. At sufficiently high speeds, the majority of rolling friction is due to a significant shift of the pressure centre in the EHL contact. While at lower speeds, sliding friction in the roller-rib contact becomes dominant, which operates under mixed lubrication conditions. Limited literature exists on the impact of inlet shear heating on effective lubricant temperature ($T_{in\_c}$) and rolling friction in TRBs. To fill this gap, experimental measurements of the total frictional torque under axial loading at different speeds and oil temperatures are performed. With existing models for different friction contributions described in the literature, the rolling resistance due to EHL has been determined for various operating conditions. The effects of dimension-less speed (U), material (G), and load (W) parameters have also been investigated. Under fully flooded conditions, it was observed that the influence of material (G) and load (W) parameters on rolling friction is minor, while the impact of velocity (U) is significant. In the context of rolling resistance, the heating due to shear of the lubricant in the inlet zone plays a significant role. For higher rotational velocities, the estimated rotational torque reduction resulting from inlet shear heating was found to be approximately 6–8%. Full article

This paper presents a solution aimed at enhancing the accuracy of abrasive waterjet cutting (AWJC) for the processing of carbon-fiber-reinforced polymers (CFRP). Processing CFRP with high accuracy and good surface quality in a short processing time is a difficult task. One crucial problem is the occurrence of shape errors, overcuts, at the cut-in and cut-out point during the cutting process. Shape errors have the potential to create mechanical stress concentrators, which can result in structural failures and compromise the integrity and reliability of components. The primary objective of this study was to gain a comprehensive understanding of the formation mechanism underlying the shape error. The observed shape error is closely associated with both the lead-in/lead-out strategies employed and the process parameters selected. The experimental investigation focused on two commonly used strategies for CFRP cutting: lead-in/lead-out in arc and lead-in/lead-out in line. In order to minimize shape errors, this study proposed a correction method that offers a set of recommendations for selecting the appropriate lead-in/out strategy and a suitable combination of process parameters. Additionally, a mathematical model has been developed to determine the depth of the shape error. The conclusions drawn from this study have been successfully validated through industrial applications. Full article