Maintenance, Reliability and Condition Monitoring
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Establishing the natural frequency of oscillations of a continuous system with a concentrated mass in aviation and manufacturing engineering
Full text linkThe uneven transportation of products in the working bodies (trays) of one-mass vibrating conveyors with inertial exciters prompted the conduct of a study aimed at establishing the natural frequency of oscillations of a continuous system, namely, a long-dimensional body with distributed parameters in the form of a beam with a rigidly fixed concentrated mass. Using the Krylov-Duncan functions, the differential equation of movement of the beam was solved, taking into account the concentrated mass and the boundary conditions at its ends. The system of equations made it possible to analytically establish the natural frequency of such a continuous system. This approach was tested to establish the natural oscillation frequency of a glider, demonstrating its versatility for use in various industries. An analysis of the obtained results was carried out, and conclusions were drawn
Vibration and noise performance analysis and optimal design of V-rotor in permanent magnet synchronous motor: a new strategy for high efficiency and low noise
Full text linkInterior Permanent magnet synchronous motors (IPMSMs) have become the preferred powertrain solution for electric vehicles due to their exceptional performance characteristics. However, the high-frequency electromagnetic noise generated during motor operation poses a significant challenge to occupant comfort within the vehicle. This study provides a comprehensive analysis of the electromagnetic forces, modal characteristics, and vibration noise for a 12-pole, 36-slot IPMSM, incorporating theoretical and simulation-based approaches as well as modal tests. By innovatively combining orthogonal experimental design with nonparametric regression techniques, a response surface model is developed to accurately characterize and optimize the radial electromagnetic force harmonics of the motor. The optimization results reveal a significant 37.7 % reduction in the motor’s surface vibration velocity and an 8.5 % decrease in peak noise levels, successfully meeting the engineering objectives for vibration and noise attenuation. This study not only contributes to the advancement of noise control technologies in electric vehicle power systems but also provides novel insights and methodologies for motor design, offering significant practical value and engineering relevance
Coupling dynamics modeling and vibration characteristics analysis of TBM main drive system under complex tunnelling conditions
Full text linkIn order to ensure the reliable operation of TBM excavation process, it is particularly important to analyze the vibration characteristics in complex surrounding rock environments. The coupling dynamics model of the TBM main drive system proposed in this article considers the structural characteristics of distributed support and multi-source inputs, as well as nonlinear internal excitations such as bearing dynamic stiffness, gear meshing error, and tooth side clearance, which can more accurately calculate the dynamic characteristics of the main drive system. Based on the TBM scale test-bed, the modeling method and the vibration response of the main components were compared and verified. Based on the coupled dynamic model of the main driving system, the vibration characteristics of the driving system were analyzed under different excavation penetrations and different proportions of soft and hard surrounding rocks. The analysis results show that during the process of penetration from 5 mm to 6 mm, the average vibration increase speed is the highest, reaching 0.1493 g/mm. As the proportion of soft surrounding rock increases, the lateral unbalanced load and torque of the cutterhead significantly increase. Meanwhile, as the proportion of soft surrounding rock increases, the corresponding rate of load increase significantly increases. Within the range where the proportion of soft surrounding rock increases from 21 % to 35 %, its lateral overturning vibration RMS value increases by 13.08 %. Within the range where the proportion of soft surrounding rock increases from 35 % to 50 %, its lateral overturning vibration RMS value increases by 32.18 %. This can easily cause safety accidents such as the fracture of key load-bearing components of the system during the excavation process
Complex fault diagnosis in wind turbine bearings: a hybrid approach combining the improved feature mode decomposition and convolutional neural networks
Full text linkThe complex noise interference and diverse fault-induced signals in vibration data from wind turbine equipment pose significant challenges for bearing fault diagnosis, including cumbersome methodologies, prolonged processing times, and compromised accuracy. To address these limitations, this study proposes a novel composite fault diagnosis framework that integrates Feature Mode Decomposition (FMD), Fast Spectral Kurtosis (FSK), and Convolutional Neural Network (CNN). While conventional Empirical Mode Decomposition (EMD) exhibits limited noise robustness and struggles to extract subtle fault signatures in composite failure scenarios, our approach employs FMD to decompose fault-related intrinsic mode functions (IMFs)and further filters the IMF components using fast spectral cliffs with enhanced feature separability. Subsequently, the Short-Time Fourier Transform (STFT) is applied to derive time-frequency representations, followed by Fast Spectral Kurtosis analysis to identify optimal demodulation bands for non-stationary signals. The energy spectrum of denoised signals is converted into grayscale images, serving as input to a tailored CNN architecture for hierarchical feature learning. Experimental validation demonstrates that this hybrid methodology achieves a fault recognition accuracy of 98 % under compound fault conditions, outperforming conventional EMD-based approaches in terms of noise immunity and diagnostic precision. Comparative analysis reveals an 8 % improvement in detection reliability over standalone deep learning models, particularly in low signal-to-noise ratio (SNR) environments. The proposed framework offers a robust solution for multi-fault identification in industrial Bearing machinery, demonstrating superior generalization capability across varying operational conditions
Analysis and synthesis of a controllable crank-slider mechanism with parallel springs for frame saws
Full text linkFrame saws suffer from large unbalanced inertia forces, limiting operating speed and requiring heavy construction. This study aims to overcome these limitations by synthesizing a dynamically balanced main drive mechanism using a novel approach based on prescribed motion laws. The methodology involves proposing a crank-slider mechanism featuring a cam-actuated variable-length crank. The mechanism configuration with parallel spring is analyzed allowing for balancing inertia forces, achieved using a prescribed cosine slider motion law. For the considered configuration, the required variable crank length function (cam profile) and associated mechanism parameters (connecting rod length, spring stiffness) are analytically synthesized. The results of the carried-out numerical modeling demonstrate successful synthesis of a near-circular cam profile and very low pressure angles for the case studied. These findings show that synthesizing the saw drive kinematics based on force balancing requirements can theoretically eliminate inertial loads, offering the potential for higher speeds of saw frames and reduced loads. The synthesized near-circular cam profile suggests a pathway towards simpler manufacturing. The implications of successfully implementing such dynamically balanced frame saw mechanisms are potentially transformative for the sawmilling industry. Eliminating the primary inertial forces removes the major obstacle to increasing operating speeds. This could allow frame saws to operate closer to the optimal cutting speeds for wood (e.g., 40-50 m/s), leading to significant gains in productivity
Design and verification of a new type of hydraulic vibration isolator for high-speed train floors
Full text linkWith the development of high-speed trains, the requirements for noise, vibration, and comfort are becoming increasingly stringent. The train body floor, as one of the main pathways for vibration transmission, is crucial to be treated for vibration reduction and noise attenuation. This paper, in response to this demand, has developed a new type of floor vibration isolator specifically for high-speed trains. Through finite element simulation analysis and experimental verification, it has been proven that this vibration isolator can effectively reduce the vibration of the train body floor and significantly enhance the NVH (Noise, Vibration, and Harshness) performance of the train
Reinforcement of the embankment with reinforced concrete piles in the transition zone from the railway embankment to the bridge
Full text linkThe article presents the design of the transition section to be used in different conditions in the region of junction of roadbed and the bridge, establishment and reasons of vertical shifts under the action of vibro-dynamic forces which appear when trains are driven along transition section. Likewise, in the sections of the foundation of the roadbed and the bridge, the types and types of a variety of defects caused by this fact, such as when the pressure of the weight of constant and temporary forces dropped on the rolling stock passes the active pressure of the ground (Ea), which acts on the support of the bridge shore at the point of the passage, are provided. In order to minimize the active effort at the junction formed by soil, reinforce and make the junction location defect-free, reinforced concrete piles are driven into the embankment to act as bases of junction location between the roadbed of the railway and the bridge location and a formula of computing the spacing of the piles has been contributed taking into consideration outer influences
Evaluation and modeling of airborne dust pollution in the Kamchik railway tunnel during train movements
Full text linkThis paper presents the results of a study on airborne dust pollution in the Kamchik Railway Tunnel caused by train movements. Field measurements were carried out to determine the concentrations of suspended particulate matter (PM10, PM2.5, PM1), as well as air temperature, pressure, and humidity in different sections of the tunnel – near the portals and in its central part. It was established that during train passages, the level of dust concentration increases by 6-10 times compared to background values, exceeding sanitary and hygienic standards. The main sources of dust generation were identified as frictional interactions between wheels and rails, braking processes, and the transportation of bulk materials. To reduce dust concentrations, engineering solutions are proposed, including the implementation of automatic water-based dust suppression systems, enhanced tunnel ventilation, and the use of hydrophobic surface coatings. The obtained results can be used to optimize ventilation modes and improve the operational safety of the Kamchik Railway Tunnel
Maintenance, repair, and overhaul of robotic systems
Full text linkThis paper not only explores the fundamental aspects of but also brings new ideas for maintenance, repair, and overhaul (MRO) operations of robotic systems (RS). This synthesis is based on the limited scholarly research in this area and on information gathered from comprehensive web searches and analysis of corporate websites so that the results reflect the current views of RS developers and operators. The paper describes several crucial areas concerning RS MRO: maintenance of robotic systems, challenges and best practices for RS MRO, predictive maintenance variables and key performance indicators, data analytics, software solutions for RS MRO, and logistics/supply chain approach that should be considered. These insights provide not only a comprehensive understanding of the current state of RS MRO but also describe trends and suggestions for the future of RS MRO, emphasizing the novelty of the proposed research conducted. Key trends that organizations will need to address include the use of artificial intelligence (AI) models and the increasing importance of RS MRO logistics and supply chain management
Multi-parameter inversion of concrete face rockfill dam using wild horse optimizer and optimal polynomial chaos kriging
Full text linkStructural parameter inversion is essential for monitoring and assessing the risks of concrete face rockfill dams. Current parameter inversion techniques are, however, often overly complex, computationally demanding, and inefficient, especially when the dam is simulated with a 3D nonlinear finite element method. This study proposes a novel approach combining the Wild Horse Optimizer with Optimal Polynomial Chaos Kriging (WHO_OPCK) to tackle these issues. The method benefits from the low computational cost of optimal polynomial chaos kriging and the fast convergence of the wild horse optimizer. By incorporating statistical uncertainty in input parameters, the method successfully inverts four key constitutive parameters φ, Kb, K, and Rf based on displacement data from a complex dam. The approach proves practical and cost-effective in real engineering applications and has culminated in the development of specialized software that streamlines this structural parameter inversion process. Sensitivity analysis using Sobol’ indices further highlights the importance of each parameter at a low computational cost. The study highlights two key advantages of WHO_OPCK: (i) Unlike traditional methods that struggle with complex dams, WHO_OPCK significantly reduces computational costs and handles parameter determination efficiently. (ii) Compared to other surrogate model combinations with WHO, the proposed WHO_OPCK method offers superior accuracy and efficiency. This method establishes a solid foundation for multi-parameter inversion in concrete face rockfill dams