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        <title>Frontiers in Mechanical Engineering | Vibration Systems section | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/mechanical-engineering/sections/vibration-systems</link>
        <description>RSS Feed for Vibration Systems section in the Frontiers in Mechanical Engineering journal | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-05-09T07:54:24.477+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1734239</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1734239</link>
        <title><![CDATA[Analysis of elastic characteristics of a transverse leaf spring with high-static-low-dynamic stiffness]]></title>
        <pubdate>2026-04-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhi Li</author><author>Zhouquan Li</author><author>Huawei Wu</author><author>Zhen Liu</author>
        <description><![CDATA[A variable-stiffness transverse leaf spring offers clear advantages in lightweight design, load-bearing capability, and vibration mitigation, indicating strong potential for broad application. However, the shock-vibration attenuation of conventional leaf springs is typically below 80%, which limits the ride comfort of leaf-spring suspensions under impact excitation. In this study, a high-static–low-dynamic stiffness (HSLDS) transverse leaf spring is proposed, and its elastic characteristics are investigated through numerical simulations and experimental validation. The results show that the static stiffness increases with load, reaching a maximum improvement of 35%. In contrast, the dynamic stiffness decreases with increasing excitation intensity, with a maximum reduction of 20.4%. Moreover, the vibration isolation ratio of the proposed leaf-spring suspension exceeds 90%. These findings provide a theoretical basis and practical reference for the design, analysis, and performance evaluation of transverse leaf springs with strongly nonlinear stiffness characteristics.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1774457</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1774457</link>
        <title><![CDATA[Inverse modeling and design of additively manufactured hybrid acoustic metamaterials for low-frequency absorption]]></title>
        <pubdate>2026-03-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ammar Alsheghri</author>
        <description><![CDATA[IntroductionEnvironmental noise is a growing problem with a negative impact on individuals, particularly at low frequencies. 3D printed acoustic metamaterials have emerged as possible load-bearing solutions for noise management. Several designs have been investigated in the literature to construct 3D lattices for optimized sound absorption including gyroid and honeycomb. Nevertheless, there exists a need for a framework to propose the best metamaterial design for application-focused target frequencies, in particular at low frequencies.MethodsIn this work, an inverse design framework is presented to propose an optimal hybrid metamaterial for sound absorption at low frequencies. To enhance broadband low-frequency absorption, the design space was extended to include a gyroid porous layer stacked in series with a honeycomb layer and an elastic wall. The inverse optimization then adjusts the porosities and effective thicknesses of gyroid and honeycomb layers to match a prescribed target absorption spectrum, while respecting additive manufacturing constraints.ResultsThe results of the proposed optimal hybrid design show that it achieves near unity sound absorption across the 250 – 2000Hz frequency range, with absorption coefficients exceeding 0.93 at all target frequencies. The resulting Noise Reduction Coefficient (NRC) reaches 0.95, demonstrating excellent broadband acoustic performance within practical thickness and manufacturing constraints.DiscussionThe proposed framework integrates inverse design with manufacturing-aware optimization to enable the development of high-performance, tunable acoustic metamaterials.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2026.1755274</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2026.1755274</link>
        <title><![CDATA[Horizontal vibration control of elevator car based on optimized NSGA-II algorithm]]></title>
        <pubdate>2026-02-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Liqun Wang</author><author>Runliang Zhang</author><author>Ying Gao</author>
        <description><![CDATA[IntroductionHigh-speed elevators face significant challenges in horizontal vibration control, primarily due to guideway unevenness and dynamic load variations, which conventional passive damping technologies struggle to address effectively. This study aims to develop an intelligent control approach to overcome these limitations and enhance ride comfort and system reliability.MethodsAn integrated control strategy was proposed, combining an Improved Nondominated Sorting Genetic Algorithm II (NSGA-II) with a Variable-Domain Fuzzy Proportional-Integral-Derivative (PID) controller. A closed-loop “sensing‐prediction-control” system was constructed utilizing a 3-7-2 network structure, a Back-Propagation Neural Network prediction model, an Adaptive Cross-Variance Operator, and a Dynamic Congestion Threshold Optimized NSGA‐II.ResultsExperimental validation under 6 m/s conditions demonstrated significant performance improvements. The horizontal vibration acceleration was reduced by 57% to 18.7 mg, displacement decreased by 60% to 0.070 mm, and the low-frequency energy attenuation rate increased by 12.5%–30.3%, outperforming traditional Explicit Model Predictive Control. The method exhibited optimal robustness in extreme condition tests, with a stable load adaptability index close to 1. The strategy achieved a multi-objective coordination degree of 0.92, reduced energy consumption by approximately 25%, decreased control hardware complexity to eight components, and extended the mean time between failures to 1,200 h.DiscussionThe proposed integrated control strategy provides an innovative and effective solution for horizontal vibration suppression in high-speed elevators. The results confirm significant enhancements in system stability, reliability, and energy efficiency. This approach holds substantial engineering value for improving ride quality and equipment longevity. Future work could explore its adaptation to ultra-high-speed scenarios and broader applications in vertical transportation systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1688598</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1688598</link>
        <title><![CDATA[Composite fault diagnosis of rolling bearings based on EMD-AADPCI vibration images]]></title>
        <pubdate>2026-01-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Qiongyan Shi</author><author>Fengbo Yang</author>
        <description><![CDATA[IntroductionBearing fault detection and prevention are crucial. However, traditional diagnostic methods generally suffer from insufficient accuracy when dealing with complex bearing faults. Therefore, developing new methods that can effectively characterize complex fault features and achieve high-precision diagnosis has significant theoretical and engineering value.MethodsThis study proposes a vibration image generation method based on Empirical Mode Decomposition-Adaptive Angle Distribution Polar Image (EMD-AADPCI) and constructs a hybrid diagnostic model combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). First, the vibration signal is processed by Empirical Mode Decomposition, and the designed adaptive angle distribution mechanism dynamically allocates polar coordinate angles according to the local features of the intrinsic mode functions, converting the signal into a two-dimensional vibration image containing rich fault information. Subsequently, a CNN-LSTM hybrid model is constructed. CNN extracts spatial and deep features from the image, and LSTM captures the temporal dependencies between features, ultimately achieving accurate classification of complex bearing faults.ResultsExperiments show that the proposed method significantly outperforms traditional methods. In terms of feature representation, the vibration images generated by EMD-AADPCI achieved a 20.25% improvement in fault classification accuracy compared to the comparative method MIC-SPCI (reaching 93.00%). The constructed CNN-LSTM model achieved a training accuracy of 94.88% with a loss rate as low as 1.43%. In the composite fault diagnosis task, the model achieved a classification accuracy of 98.00%. After 10 repeated experiments, the model achieved average accuracy, recall, and F1 score of 98.13%, 98.72%, and 98.33% for different composite fault diagnoses, respectively. Even in a low signal-to-noise ratio environment with strong noise interference (-4 dB), the model maintained a diagnostic accuracy of over 97%, demonstrating good robustness.DiscussionThe proposed EMD-AADPCI method can more effectively preserve and highlight fault-related information, while the CNN-LSTM hybrid model fully leverages the advantages of spatial feature extraction and time series modeling. Experimental results show that this method has extremely high accuracy and anti-interference ability in bearing composite fault diagnosis. This provides an effective and innovative solution for intelligent diagnosis and preventive maintenance of complex faults in bearings and other rotating machinery, and has good prospects for widespread application.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1712049</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1712049</link>
        <title><![CDATA[A cable tension measurement method for transmission lines based on micro-vibration broadband phase motion magnification and deep learning]]></title>
        <pubdate>2026-01-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Huang Zhiming</author><author>Wang Shuo</author><author>Wen Hongbing</author><author>Li Zixin</author>
        <description><![CDATA[IntroductionCable components are widely used in transmission lines, and their tension values and variations are critical factors affecting the intrinsic safety of these lines. Thus, tension monitoring becomes a priority during both construction and operational maintenance. Traditional cable tension measurement methods suffer from limitations such as low accuracy, stringent environmental requirements, and difficulties in live-line monitoring, resulting in a lack of universality for application in transmission lines.MethodsThis paper utilizes visual image technology and Broadband Phase Motion Magnification to amplify the micro-vibration amplitude and enhance the vibration images of transmission line cable- type components under environmental excitation. Furthermore, this study develops a combined segmentation algorithm using the U-Net network architecture and level set loss entropy to accurately capture the centroid motion trajectory of cables, thereby precisely extracting the vibration displacement time series. Finally, spectrum analysis is applied to invert the self-vibration characteristic parameters of the components and establish a tension calculation model.ResultsExperimental verification shows that the proposed method can precisely capture the micro-vibration signals induced by environmental excitation. The tension calculation results, when compared to standard sensor data, have a deviation of no more than 8%.DiscussionThis method successfully establishes a non-contact, high-precision measurement system for cable-type components, providing a new technical pathway for intelligent monitoring during the construction and maintenance of transmission lines.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1631584</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1631584</link>
        <title><![CDATA[Study on dynamics and vibration response of shield cutterhead in composite strata based on Hertz contact]]></title>
        <pubdate>2025-08-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Huanle Xu</author><author>Junfei Fan</author><author>Zhenyu Qian</author><author>Changyun Yang</author><author>Xilong Zhou</author>
        <description><![CDATA[The shield cutterhead experiences eccentric loads when excavating through composite strata, leading to potential deviation of the cutterhead. This study examines the static response, modal characteristics, and vibration response of a shield cutterhead in composite strata, utilizing Hertz contact theory. The cutterhead-rock interaction is equivalently modeled as mechanical spring constraints, with contact stiffness derived from elastic contact theory for disc cutter-rock contact. The static and dynamic responses of the cutterhead under maximum thrust and rock-breaking load are analyzed using finite element simulations. Results show that moderately weathered limestone induces larger displacements compared to hard rock. Modal analysis reveals that the natural frequencies increase with rock modulus, with composite strata exhibiting intermediate values compared to the soft and hard rock. Vibration responses under rock-breaking load demonstrate rotational symmetry in uniform strata but asymmetry in composite strata, where the displacement of the upper half exceeds the lower half due to stiffness contrast. This work provides a theoretical framework for optimizing cutterhead design and tunneling parameters in heterogeneous strata.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1591815</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1591815</link>
        <title><![CDATA[Fault diagnosis algorithm based on multi-channel neighbor feature convolutional network]]></title>
        <pubdate>2025-04-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Huang Xiao</author><author>Hanqing Jian</author>
        <description><![CDATA[IntroductionThe health status of bearings is an essential prerequisite to ensure the safe and stable operation of vehicles. However, the negative impact of covariate shifts among data channels on diagnostic accuracy is an issue that is often overlooked in data-driven algorithms based on multi-channel data. Therefore, extracting the most representative features from multi-channel data is key to achieving highprecision fault diagnosis.MethodsTo address this issue, this paper proposes a fault diagnosis algorithm based on a multi-channel neighbor feature convolutional network. First, to mitigate the covariate shift problem in the data, inverted mel-scale frequency cepstral coefficients are introduced to obtain domain-invariant features with high recognition accuracy. Furthermore, to fully leverage multichannel data and extract more discriminative features, we design a multi-channel adjacent feature convolutional module. This module employs sparse mapping to extract local neighboring features while preserving global constraint characteristics.Result and discussionExperiments are carried out on Xi’an Jiaotong University and Case Western Reserve University data. The results show that the proposed method can achieve high performance and high precision fault diagnosis.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1560986</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1560986</link>
        <title><![CDATA[Vibrational analysis of faulty deep-groove ball bearing under radial load]]></title>
        <pubdate>2025-04-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kiran More</author><author>Pranoti Honawadajkar</author><author>Sachin Kandharkar</author><author>Bharat Tidke</author><author>Rahul B. Pawar</author><author>Mangesh Shende</author><author>Rajesh Kherde</author><author>Ganesh Kawade</author><author>Sachin Patil</author>
        <description><![CDATA[IntroductionDeep-groove ball bearings are widely used in industrial applications due to their ability to support radial and axial loads simultaneously. However, prolonged operation under harsh conditions can lead to localized defects such as inner race, outer race, or rolling element faults. These defects often manifest as distinct vibration patterns, which can be detected and analyzed to diagnose bearing health. This study focuses on the vibrational analysis of faulty deep-groove ball bearings under radial load, aiming to establish a correlation between fault characteristics and vibration signatures.MethodsA specialized test rig evaluates the vibration responses of deep-groove ball bearings under controlled conditions, capturing data in both time and frequency domains for comprehensive analysis. Vibration signals from healthy and defective bearings are analyzed to ensure precision and reliability. The study identifies characteristic fault frequencies and harmonics caused by localized defects on the inner or outer race, comparing simulated and experimental data. This approach provides insights into how defect types and load conditions influence bearing vibration signatures.ResultsThe evaluation of single and multiple defects shows higher velocity amplitudes for multiple defects. Time-domain analysis reveals that a single inner race defect under a 5 kg radial load has a velocity amplitude of 2.00 mm/s, while two defects on the inner race under the same load result in a slightly lower amplitude of 1.88 mm/s.DiscussionThe experimental findings closely match the simulation results, showing a strong correlation between the two methods. Further analysis using orbit analysis is conducted to examine the behavior of deep-groove ball bearings under similar conditions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1553759</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1553759</link>
        <title><![CDATA[Experimental implementation of algebraic identifier for unbalance parameters in a rotor-bearing system]]></title>
        <pubdate>2025-03-31T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jesús U. Quiroz-Bautista</author><author>Manuel Arias-Montiel</author><author>José G. Mendoza-Larios</author><author>Luis Vázquez-Sánchez</author>
        <description><![CDATA[This article presents experimental results on the algebraic identification of the magnitude and phase angle of unbalance in a rotor-bearing system in a Jeffcott configuration. The algebraic identifier is designed based on a simplified mathematical model of the system and it uses only the measurement of the lateral vibration amplitude of the rotor. The proposed algebraic identifier is first validated by numerical simulation. For experimental implementation, a SpectraQuest Machinery Fault and Rotor Dynamics Simulator is used. The designed identifier is evaluated in two scenarios. In the first, the rotor-bearing system is balanced using the traditional coefficients of influence method, after which a known unbalance is induced and compared with the identified magnitude and phase values. In the second case, the unbalance magnitude and phase values obtained by the algebraic identifier from an unknown original unbalanced configuration are used to balance the rotor-bearing system. The vibration amplitude reduction is quantified to evaluate the identified values. The main contribution of this work is the discussion of practical aspects that cannot be appreciated in simulation, but must be considered in the experimental implementation of the algebraic identification method, as they can limit the performance of the designed identifiers.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1536603</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1536603</link>
        <title><![CDATA[Experimental investigation of vibrational signal in a fault induced Francis runner]]></title>
        <pubdate>2025-03-25T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Prajwal Sapkota</author><author>Subarna Paudel</author><author>Ravi Poudel</author><author>Sailesh Chitrakar</author><author>Hari Prasad Neopane</author><author>Bhola Thapa</author>
        <description><![CDATA[Hydro turbines are prone to failure and the detection of fault in turbine is essential to ensure the reliability of power plant. This study investigates vibrational signals in a fault-induced Francis turbine using an experimental test setup to identify the trends that could be helpful in diagnosis of turbine faults. By analyzing the vibrational signal, the study aims to correlate the turbine's dynamic behavior. Faults in the turbine have been introduced by adding masses to the blades, and the experimental tests are conducted under two different conditions: dry and wet testing conditions for both normal and faulty turbine blades. The turbine's operating condition is determined with the help of pressure, flow, and RPM sensors. The turbine's speed is varied using a variable frequency drive. For the acquisition of vibration signals, the NI-LabVIEW system is employed along with a uniaxial vibration sensor located at the turbine bearing. The obtained vibration data are analyzed using the Fast Fourier Transform (FFT) algorithm and wavelet transform algorithm to identify frequency-domain characteristics. While studying and comparing the fundamental frequency of the turbine shaft, it is found that turbine faults can either increase or decrease the amplitude of the resonant peak frequency of the system, but the amplitude at other frequencies remains almost unaffected.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1495704</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1495704</link>
        <title><![CDATA[Experimental study on hydrodynamic characteristics of a taut moored floating box]]></title>
        <pubdate>2025-03-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Qiaoling Ji</author><author>Xiuru Jia</author><author>Yan Xu</author><author>Yu Cheng</author><author>Guowei Zhang</author><author>Zhenyu Li</author>
        <description><![CDATA[To investigate the hydrodynamic capabilities of the floating breakwater with a taut mooring system, a two-dimensional physical modelling experiment was performed to investigate the hydrodynamic characteristics of the hydrodynamic pressure on the front surface of the floating box, mooring line tension and transmission coefficient under regular waves, considering factors such as mooring angle, mooring line pre-tension and relative width. The results show that, with the increase of the mooring angle, the hydrodynamic pressure on the floating box first increases and then decreases, the mooring line tension first increases and then decreases slightly, and the transmission coefficient obviously decreases. As the mooring line pre-tension increases, the hydrodynamic pressure and the mooring line tension increase, and the transmission coefficient first decreases and then increases. As the relative width increases, the hydrodynamic pressure, mooring line tension and transmission coefficient all show a decreasing trend. The results can provide a reference for the design and safety assessment of taut moored single pontoon floating breakwater.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2025.1547120</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2025.1547120</link>
        <title><![CDATA[Multi-parameter optimizations of elastic chain catenary based on response surface methodology for high-speed railway]]></title>
        <pubdate>2025-02-27T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zongfang Zhang</author><author>Maoyou Zhang</author>
        <description><![CDATA[As train operating speeds increase, the quality of pantograph-catenary current collection deteriorates, sometimes even resulting in contact loss. To ensure stable current collection during high-speed operation, it is crucial to optimize the design parameters of the catenary system. This study employs finite element analysis and constructs a pantograph-catenary coupling model using MSC. Marc software to simulate the coupled motion between the catenary and the pantograph. During the research process, the primary technical challenge was accurately evaluating the comprehensive effects of multi-parameter variations on pantograph-catenary current collection quality. First, we independently analyzed the effects of catenary tension and linear density variations on contact pressure to clarify the mechanisms of individual parameter influences. However, recognizing that multiple parameters might change simultaneously in actual operations, we introduced the Response Surface Methodology (RSM) to deeply explore the combined effects of two parameters on current collection quality. The innovation of this study lies not only in considering the effects of individual parameters but also in systematically analyzing the impact of multi-parameter interactions using RSM. Furthermore, from the perspective of the combined effects of catenary tension and contact wire linear density, we proposed an optimized catenary design scheme for the 500 km/h high-speed train operation scenario. Specifically, by increasing the contact wire tension, reducing the messenger wire tension, and lowering the linear density of the contact wire, we can significantly improve pantograph-catenary current collection quality, thereby providing robust support for the safe and stable operation of high-speed railways. In conclusion, this study addresses key technical challenges in multi-parameter optimization and proposes a practical optimization scheme with significant application value, offering important references for the design and optimization of high-speed railway catenary systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2024.1493579</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2024.1493579</link>
        <title><![CDATA[Diagnosis and prognosis of soybean roaster failures using particle swarms]]></title>
        <pubdate>2024-10-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Aslain Brisco Ngnassi Djami</author><author>Ulrich Ngnassi Nguelcheu</author><author>Joseph Nkongho Anyi</author>
        <description><![CDATA[In industry, the monitoring and diagnosis of production processes are crucial issues in ensuring plant reliability, performance and quality. In particular, food processing operations, such as coffee roasting, are subject to numerous risks of failure that can impact on productivity and the quality of the final product. In this context, the main objective of this study was to develop an innovative method for the diagnosis and prognosis of failures in a coffee roasting process. The proposed method differs from standard approaches by using the particle swarm optimization (PSO) algorithm applied to the analysis of signatures of key process variables. This new approach has improved fault detection, with a recognition rate of over 90% for the main types of fault identified, such as heating problems, air obstructions or leaks. In addition to diagnostics, the method has also demonstrated its effectiveness in prognosticating the state of health of the process, with an average error on the prediction of remaining service life reduced to 15%, compared with 35% for fixed-threshold methods. This work has therefore enabled us to develop an innovative method offering superior performance to standard approaches for the diagnosis and prognosis of failures in the roasting process.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2024.1464692</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2024.1464692</link>
        <title><![CDATA[AI-driven optimization of dynamic vibration absorbers with hydraulic amplifier and mechanical inerter integration]]></title>
        <pubdate>2024-09-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ahmed Shamseldin</author><author>Mohammad A. Abido</author><author>Abdulrahman Alofi</author>
        <description><![CDATA[Dynamic vibration absorbers (DVAs) have been widely employed in vibration suppression applications for decades. While DVAs offer an effective solution, they are limited by the need for a high mass ratio between the DVA and the primary system to achieve significant vibration attenuation. To overcome this, researchers have introduced lever mechanisms, allowing for enhanced vibration suppression without increasing the mass ratio. However, levers, commonly used as amplification mechanisms, suffer from high inertia and limited amplification, particularly in larger applications. Another limitation is when DVAs are employed for energy harvesting as a secondary objective, they exhibit high sensitivity to system parameter variations, requiring extensive optimization. Various optimization techniques have been applied to DVAs for multi-objective optimization, including fixed-point theory, which is complex and requires intensive mathematical derivation, and simple metaheuristic techniques such as genetic algorithms (GA). This study proposes four novel DVAs using a hydraulic amplifier (HA) to address the limitations of traditional lever mechanisms and a mechanical inerter to improve the vibration damping. Also, multi-objective optimization was performed using particle swarm optimization (PSO) which is considered innovative in this application and compared with commonly used genetic algorithms (GA). The governing equations were derived using Newton’s second law and solved numerically with the Runge-Kutta method. An AI-based approach was utilized for HA design. The results show that integrating HA and mechanical inerters significantly enhances vibration attenuation and broadens the frequency response. Additionally, the location of the mechanical inerter is critical in reducing vibration amplitude. Also, the multi-objective PSO outperforms GA in solution diversity and quality. The proposed integration of HA in DVAs offers potential applications across various engineering fields.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2024.1426764</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2024.1426764</link>
        <title><![CDATA[Assessment of whole-body vibration and development of mitigation intervention for single-axle tractor–trailer combination]]></title>
        <pubdate>2024-09-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Rachamalla Naveen</author><author>Adarsh Kumar</author><author>Rajeev Kumar</author><author>H. L. Kushwaha</author><author>Manoj Khanna</author><author>V. Ramasubramanian</author><author>Sajja Poojith</author>
        <description><![CDATA[IntroductionTractarization is synonymous with farm mechanization in India. Tractor-trailers are extensively used for the transportation of farm inputs and produce on and off-road, exposing drivers to excessive vibration.ObjectivesThe study was undertaken to assess tractor drivers’ vibration exposure while using trailers and to develop low-cost mitigation interventions.MethodologyThe whole-body vibrations were measured at the tractor seat during the transportation with a no, half (3715 kg soil) and full payload (5910 kg soil) trailer on two terrain conditions, namely, asphalt and farm terrains. The speeds recommended by ISO 5008-1979 of 10, 12 and 14 km/h on asphalt roads and 4, 5 and 7 km/h on farm roads, as well as actual working speeds preferred by the operator (18, 20 and 22 km/h on asphalt road and 8, 10 and 12 km/h on farm terrain), were selected for experiments. Two vibration reduction interventions, namely spring suspended single point hitch (I1) and polyurethane (PU) bush (I2), were developed and installed between the tractor and trailer. Whole-body vibration (WBV) was measured by repeating the experiments.ResultsThe maximum vibration reduction on asphalt road at 22 km/h with I1 was found as 14.3, 19.03 and 23.1%, whereas on-farm terrain at 12 km/h was found as 15.16, 22.43, and 25.56% for no, half and full payload. Similarly, with I1 + I2 interventions, the maximum total vibration reduction at 22 km/h was 16.86, 21.12 and 25.51% on asphalt roads, whereas on-farm tertian at 12 km/h was 17.07, 23.77 and 28.67%. The average value of lower health guidance caution zone (HGCZ) limits on asphalt roads increased by 1.11, 0.95 and 0.92 h and on-farm tertian 1.55, 1.14 and 0.83 h with no, half, and full payload. The average value of upper HGCZ limits on asphalt roads increased by 3.13, 3.21 and 3.68 h and on-farm tertian by 2.24, 2.94 and 3.31 h with intervention.ConclusionsThis infers that with developed interventions an operator can safely perform for a longer duration and at higher operational speeds because of the reduced vibration.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2024.1430542</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2024.1430542</link>
        <title><![CDATA[Toward compound fault diagnosis via EMAGAN and large kernel augmented few-shot learning]]></title>
        <pubdate>2024-07-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Wenchang Xu</author><author>Zhexian Zhang</author><author>Zhijun Wang</author><author>Tianao Wang</author><author>Zijian He</author><author>Shijie Dong</author>
        <description><![CDATA[Bearings are essential in machinery. Damage to them can cause financial losses and safety risks at industrial sites. Therefore, it is necessary to design an accurate diagnostic model. Although many bearing fault diagnosis methods have been proposed recently, they still cannot meet the requirements of high-accurate prediction of bearing faults. There are several challenges in this: 1) In practical settings, gathering sufficient and balanced sample data for training diagnostic network models proves challenging. 2) The damage to bearings in real industrial production sites is not singular, and compound faults are also a huge challenge for diagnostic networks. To address these issues, this study introduces a novel fault diagnosis model called EMALKNet that integrates DCGAN with Efficient Multi-Scale Attention (EMAGAN) and RepLKNet-XL, enhancing the detection and analysis of bearing faults in industrial machinery. This model employs EMAGAN to explore the underlying distribution of raw data, thereby enlarging the fault sample pool and enhancing the model’s diagnostic capabilities; The large kernel structure of RepLKNet-XL is different from the current mainstream small kernel and has stronger representation extraction ability. The proposed method has been validated on the Paderborn University dataset and the Huazhong University of Science and Technology dataset.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2024.1414626</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2024.1414626</link>
        <title><![CDATA[Optimization of tempering temperature and soaking time of SCM440 steel horn in ultrasonic-assisted metal inert gas welding]]></title>
        <pubdate>2024-06-14T00:00:00Z</pubdate>
        <category>Methods</category>
        <author>Vinh Tran-The Chung</author><author>Quynh Thi-Minh Tran</author><author>Ngoc-Ha Nguyen</author><author>Thinh Ha-Quang Ngo</author><author>Trung-Kien Le</author><author>Thanh-Hai Nguyen</author>
        <description><![CDATA[This study explores the optimization of ultrasonic horn heat treatment conditions for enhanced mechanical quality (Qm). The optimal parameters identified are a tempering temperature of 529°C and a 240-min soaking time, yielding a 1.3% experimental error. Frequency stability during welding is significantly improved, with the optimal horn exhibiting a minimal frequency variation of 64 Hz compared to 90 Hz and 82 Hz for other samples. Hardness varies with tempering temperature, reaching a peak of over 39.3 HRC at 450°C and dropping to 23.8 HRC at 650°C. Microstructural analysis reveals transformations in pearlite, spheroidization, and increased grain sizes in the optimal sample. Carbide precipitation is more pronounced in longitudinal sections and increases with higher tempering temperatures and soaking times. The presence of chromium alloying elements in SCM440 steel contributes to carbide formation. These findings underscore the critical role of heat treatment conditions in optimizing the performance of ultrasonic horns.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2024.1396170</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2024.1396170</link>
        <title><![CDATA[Vibration analysis of piping connected with shipboard equipment]]></title>
        <pubdate>2024-05-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Radharaman Tripathi</author><author>Tushar A. Jadhav</author><author>Mahesh K. Gaikwad</author><author>Mithul J. Naidu</author><author>Aishwarya B. Gawand</author><author>Duran Kaya</author><author>Sachin Salunkhe</author><author>Robert Cep</author><author>Emad Abouel Nasr</author>
        <description><![CDATA[The piping system connected with the shipboard equipment may be subjected to excessive vibration due to harmonic base excitation produced by hydrodynamic force imposed on the propeller blades interacting with the hull and by other sources. Vibration design aspects for shipboard pipework are often ignored, which may cause catastrophic fatigue failures and, consequently, leakage and spillage in the sea environment. Without dedicated design codes, the integrity of shipboard equipment against this environment loading can be ensured by testing as per test standard MIL-STD-167-1A (2005). However, in many cases, testing is not feasible and economically viable. Hence, this study develops an FE-based vibration analysis methodology based on MIL-STD-167-1A, which can be a valuable tool to optimize the testing requirement without compromising the integrity of these piping systems. The simulated model dynamic properties are validated with experimental modal testing and Harmonic response analysis result confirm that a mitigating solution option can be verified by a FE based vibration analysis to mitigate the vibration problem.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2024.1329345</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2024.1329345</link>
        <title><![CDATA[Efficient design of sandwich panels with cellular truss cores and large phononic band gaps using surrogate modeling and global optimization]]></title>
        <pubdate>2024-04-16T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Viviana Meruane</author><author>Ignacio Puiggros</author><author>Ruben Fernandez</author><author>Rafael O. Ruiz</author>
        <description><![CDATA[Recent advancements in additive manufacturing technologies and topology optimization techniques have catalyzed a transformative shift in the design of architected materials, enabling increasingly complex and customized configurations. This study delves into the realm of engineered cellular materials, spotlighting their capacity to modulate the propagation of mechanical waves through the strategic creation of phononic band gaps. Focusing on the design of sandwich panels with cellular truss cores, we aim to harness these band gaps to achieve pronounced wave suppression within specific frequency ranges. Our methodology combines surrogate modeling with a comprehensive global optimization strategy, employing three machine learning algorithms—k-Nearest Neighbors (kNN), Random Forest Regression (RFR), and Artificial Neural Networks (ANN)—to construct predictive models from parameterized finite element (FE) analyses. These models, once trained, are integrated with Particle Swarm Optimization (PSO) to refine the panel designs. This approach not only facilitates the discovery of optimal truss core configurations for targeted phononic band gaps but also showcases a marked increase in computational efficiency over traditional optimization methods, particularly in the context of designing for diverse target frequencies.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fmech.2024.1341466</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fmech.2024.1341466</link>
        <title><![CDATA[Automatic rolling bearings fault classification: a case study at varying speed conditions]]></title>
        <pubdate>2024-04-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Nguyen Trong Du</author><author>Pham Thanh Trung</author><author>Nguyen Huu Cuong</author><author>Nguyen Phong Dien</author>
        <description><![CDATA[Rolling bearings always operate under variable speed conditions, which poses a challenge for researchers in identifying and classifying bearing faults. In contrast to the stationary speed condition, the Fault Characteristic Frequency (FCF) under variable speed conditions exhibits a variable value that depends on the instantaneous shaft rotational speed (ISRS). The representation of the FCFs in the frequency domain reveals overlapping patterns among them. To solve the mentioned problem, a novel tool is proposed and established by mixing the two methods: The Fourier-based SynchroSqueezing transform (FSST) and Principal Component Analysis (PCA). By illustrating the envelope signal in time-frequency distribution using FSST, the FCF is highlighted in each ISRS value. Finally, this time-frequency distribution is used as input of PCA to classify rolling bearings. This method successfully diagnosed both inner race fault and outer race fault of rolling bearings.]]></description>
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