Machinery - Repository of the Faculty of Mechanical Engineering, University of Belgrade
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The influence of dwell time on the collected data during linear displacement measurements of machine tools
No full textDuring linear displacement measurement of CNC machine tools (MT) with laser interferometer the optical components are moved along the measured axis. At the selected measurement points of the axis the optics stops and data collection is performed. At the beginning of the stopping cycle, because
of the inertion of the optics and the MT structure, vibrations occure, which spoils the collected data. To minimize the dwell time, the time needed to wait at the measurement point, the number of the collected position data needs to be minimized. In this work through an example is represented the
influence of the number of collected data on the measurement values during linear displacement measurements of machine tools.Editor of chief: Assistant Professor Dejan Branković, PhD
Executive editor: Milivoj Stipanović, Bs
A review paper: Influence of welding defects to structural integrity of welded joints
No full textThis paper presents a review of the most notable cases involving welded joint defects and their
influence on structural performance. It examines examples where imperfections such as undercuts,
incomplete penetration, lack of fusion, and so on, have compromised the integrity of welded
structures. By analyzing these cases, the paper highlights how such defects contribute to stress
concentration, reduced load-bearing capacity, and, in severe instances, failure. The review
underscores the critical importance of identifying and mitigating these flaws to ensure the safety and reliability of constructions like bridges, buildings, and industrial frameworks
Modeling of fracture toughness size effect in ductile-to-brittle transition temperature region: features and demonstration
No full textThe significant scatter observed in experimental fracture toughness data, a characteristic feature of all ferritic steels within the ductile-to-brittle transition (DBT) temperature region, necessitated the incorporation of statistical methods for data processing. Owing to the inherent stochasticity of the fracture process, the application of fracture mechanics concepts in the characterization of the DBT phenomenon has remained a challenging endeavor over the past 50 years. Various models have been developed based on a statistical approach to data processing to capture the salient features of this phenomenon; however, all exhibit certain limitations due to the intrinsic complexity of the problem. Nevertheless, these models have provided a robust foundation for the continued development of novel approaches in the
characterization of DBT. This paper presents a comparative analysis of two such novel models.
These models incorporate size effects and utilize scaling of geometrically similar CT
specimens, aiming to predict fracture toughness. A common feature of both proposed models
by the authors in this study is the application of Weakest Link Statistics. Particularly, after the
presentation of both models methods, the EURO fracture toughness dataset for 22NiMoCr37
reactor steel is employed, and experimental data obtained at a temperature of -60 °C is
selected to demonstrate the accuracy of the estimates. The fracture toughness metric used is
the critical value of the stress intensity factor employed in the master curve (more precisely,
KJc). The obtained predictions show good agreement with the experimental results,
considering the inherent scatter nature of the experimental data. The presented methods are
mainly criticized regarding their application domain and their predictive capability for fracture
toughness. One important remark to emphasize is that the estimate of the KJc cumulative
distribution function, obtained by extrapolation using the novel two-step scaling method, is
sensitive to the statistical size of the input datasets
Quality Tools Application in Examining Discomfort Issues at Mining Machinery Operators’ Workplaces
No full textThe significance of evaluating human factors issues encountered at mining machinery
operation greatly exceeds the amount of available research, given that accidents
in mining operations continue to be a recurring concern. This study included
97 Serbian mining machinery operators, who answered the questionnaire which
examines injuries and discomfort issues at mining machinery operators’ workplaces.
Descriptive statistics was conducted followed by quality tools: Pareto (ABC), Ishikawa,
and control charts were performed. ABC analysis found that 41.7% of operators
complained to back pain, mostly due to poor working conditions. Back pain is
caused by repetitive movements, poor anthropometric adjustments, lack of training,
environmental factors, and vibrations, according to the Ishikawa diagram. The
attribute control chart shows that no points exceed the lower and upper limits. Thus,
examined processes are controlled. A future research avenue is further data collection
and expansion of the sample size, as well as the application of other quality tools.no. 451-03-65/2024-03/20010
EVALUATING THE STRUCTURAL INTEGRITY OF NOVEL DECKHOUSES ON TANKER SHIPS UNDER EXTREME CONDITIONS
No full textThis paper assesses the structural integrity of atypical superstructures mounted on the decks of two sister sea-going tankers under extreme load conditions. Namely, each tanker features a pair of deckhouses which are welded onto the existing deck structure girders, exposing them directly to harsh environmental loads. These deckhouses, designed as ‘ad hoc’ solutions resembling land-based structures with similar applications, serve as storage for ballast water treatment systems, added due to insufficient internal technical space within the existing ship structure. Given the lack of fully developed regulations for assessing the structural integrity of novel and atypical ship structures, classification rules typically require a direct structural assessment to ensure their structural integrity. Therefore, this study uses the finite element method to analyse extreme design load scenarios faced by these structures, including seawater loads from waves, wind loads, accelerations due to ship motions, and static loads from the structures’ and internal equipment weights. Besides identifying critical areas, the findings reveal that the initially proposed deckhouse structures failed to meet the criteria for certain scantling arrangements and demonstrate how variations in scantlings affect the overall structural response. Based on these insights, general recommendations for modifying the deckhouse structure are proposed.Contract No. 451-03-137/2025-03/20010
Reliability Evaluation and Optimization of System with Fractional-Order Damping and Negative Stiffness Device
No full textAbstract
Research on reliability control for enhancing power systems under random loads holds significant and undeniable importance in maintaining system stability, performance, and safety. The primary challenge lies in determining the reliability index while optimizing system parameters. To effectively address this challenge, we developed a novel intelligent algorithm and conducted an optimal reliability assessment for a Negative Stiffness Device (NSD) seismic isolation structure incorporating fractional-order damping. This algorithm combines the Gaussian Radial Basis Function Neural Network (GRBFNN) with the Particle Swarm Optimization (PSO) algorithm. It takes the reliability function with unknown parameters as the objective function, while using the Backward Kolmogorov (BK) equation, which governs the reliability function and is accompanied by boundary and initial conditions, as the constraint condition. During the operation of this algorithm, the neural network is employed to solve the BK equation, thereby deriving the fitness function in each iteration of the PSO algorithm. Then the PSO algorithm is utilized to obtain the optimal parameters. The unique advantage of this algorithm is its ability to simultaneously achieve the optimization of implicit objectives and the solution of time-dependent BK equations.To evaluate the performance of the proposed algorithm, this study compared it with the algorithm combines the GRBFNN with Genetic Algorithm (GA-GRBFNN)across multiple dimensions, including performance and operational efficiency. The effectiveness of the proposed algorithm has been validated through numerical comparisons and Monte Carlo simulations. The control strategy presented in this paper provides a solid theoretical foundation for improving the reliability performance of mechanical engineering systems and demonstrates significant potential for practical applications
Enhanced wave attenuation through inertial amplification in periodic beam-rigid body structure
No full textWe address the fundamental challenge of achieving low-frequency wave attenuation in periodic structures without increasing system mass -a critical limitation in current design of metastructures. Traditionally, low-frequency attenuation has been achieved through the use of local resonators, which can be tuned to a specific low-frequency range by increasing their mass. To overcome this trade-off, we investigate the influence of two inertial amplifiers with distinct configurations: one with auxiliary masses connected to both beam and main mass and another with auxiliary masses suspended between the main mass and a fixed support. The transfer matrix method, combined with the spectral element method, is employed to analyze how design parameters influence the dispersion properties of each system. Our findings show that purposeful structural design of these inertial amplifiers can lead to as much as 50% broader attenuation bands across both high and low-frequency ranges. We also demonstrate near-coupling phenomena between local resonance and Bragg scattering mechanisms, which result in an ultra-wide low-frequency band gap. This study provides a method for robust wave control in periodic structures made of elastic and rigid segments such as buildings and bridges, particularly for low-frequency, lightweight acoustic and seismic isolatio
Vision-Based Robot System for Object Manipulation
No full textThe paper presents a robotic system for object manipulation based on information obtained from a camera. The developed system enables the differentiation of four classes of objects with regular geometric shapes. To achieve that, a semantic segmentation model was trained using a set of images of objects in different positions. An algorithm for objects’ position and orientation determination was developed so objects can be placed in arbitrary positions and orientations within the camera’s field of view. The developed algorithms ensure the necessary information for automatic robot programming for moving the objects to desired poses. To prove the proposed concept on the 4-axis SCARA robot equipped with a vacuum gripper for object grasping, a camera calibration procedure was per-formed and necessary coordinate transformations were obtained. The verification of the developed system was conducted through several experiments. The experiments showed good reliability of the trained model for objects’ classification and accurate positioning of the robot end-effector above the objects.contract No. 451-03-137/2025-03/20010
Self-tuning intelligent PID controller for robot manipulators
No full textThis article tackles the problem of tuning model-free intelligent PID controllers for nonlinear systems such as robot manipulators. Based on the ultra-local model formulation, intelligent PD position control parameters are tuned for each discrete time step. The Particle Swarm Optimization (PSO) is used to tune control parameters based on chosen objective function. Finally, the performance of the proposed tuning approach is verified through simulation and comparative analysis.No. 451-03-137/2025-03/200105 from 04.02.202